Household Income Survey of the Rapti and Bheri Zones, Nepal

RAP Technical Report No. 14

Regional Agribusiness Project 7250 Woodmont Avenue, Suite 200, Bethesda, Maryland 2081 4

DEVELOPMENT ALTERNATIVES, INC •• Abt Associates Inc. • Fintrac Inc. • Technical Assess­ment Systems, Inc •• DPRA Incorporated • IMCC • Land O'Lakes, Inc. • Postharvest Institute for Perishables • United Fresh Fruit and Vegetable Association • Gle Agricultural Group

Household Income Survey of the Rapti and Bheri Zones, Nepal

by

lanardan B Khatn-Chhetn

Agncultural Projects SerVIces Centre

May 1997

Prepared for the RegIOnal Agnbusmess Project (RAP), contract number AEP-0009-C-00-3057-00, wIth fundmg from the ASIa Near East Bureau of the U S Agency for InternatIOnal Development

FOREWORD

The rapId mcrease m productIon of hIgh-value cash crops m the hIlls and mountams has become an important development strategy of HIS Majesty's Government (HMG) of Nepal The Vegetables, FruIt, and Cash Crops (VFC) Project Implemented by USAID m the hIll dIstncts of the Raptl zone IS a prototype of the hIlls and mountams development strategy USAID has now agreed with HMG to extend the scope and coverage of thIS project to larger scale ImplementatIOn, desIgned to have macro Impact m the RaptI zone as well as m the three hIll dIstncts of the Bhen zone

The Agncultural Projects ServIces Centre (APROSC) was subcontracted by Development AlternatIves, Inc (DAI) to conduct a senes of studIes and analyses to serve as a baselme for the upcoming Market Access for Rural Development (MARD) and EnvIronment, Forest and Enterpnse ACtlVlty (EFEA) projects ThIS report presents results from a survey of pockets wIth mtensive actIvIty m the Rapt! zone The report also presents a random samplmg of three dIStnCtS - namely Surkhet, DaIlekh, and JaJarkot -m the Bhen zone

I would hke to express my deep appreCiatIOn to DAI for entrustmg APROSC wIth thIS Important study I would also hke to extend my deepest thanks to Drs Ken Swanberg and John Bowman, and to Bagle Sherchand for theIr valuable suggestIons, support, and backstoppmg dunng the study penod Special appreCIatIOn IS due also to Dr John Mellor of John Mellor AssocIates Inc for hIS valuable mput throughout the course of thIS study Thanks also to Dr Badn Kayastha, Teeka Pradhan, and the SIte coordmators of No-Fnlls Consultants for theIr help m SIte selectIOn and fIeld support dunng the survey

I would hke to thank Surya AdhIkan, Madhu BhattaraI, Subarna Man Shrestha, and Muran Raj KamI, along wIth theIr team members, for completmg the fIeld survey on tIme Messrs AdhIkan and BhattaraI also drafted the sectIOns on local mstItutIOns and natural resources, and fertIhzer use Thanks are also due to Raja Smgh for hIS word processmg SkIlls and to the support staff of APROSC, especIally Janak Udaya, Ananta Parajuh, Khagendra Basnyat, Kishor Gyawah, and Uma Baral, for theIr admimstratIve assIstance I would hke to thank Dr B R Dahal for partIcipatmg m fIeld supervlSlons and Dhruba Munakarmi and hIS team for data processmg

FInally, I wIsh to extend my deepest thanks to Dr Janardhan Khatn-Chhetn for hIS unstIntIng effort In coordInatmg and successfully completIng thIS study

Dr Shyam KrIshna Poudel ExecutIve DIrector (a I )

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FIELD SURVEY TEAM

Dang and Pyuthan Rukum and Jajarkot

Surya Adhikan Team Leader Madhusudan Bhattarat Team Leader

Prakash Tiwari (I) Team Member Prabhat Poudel (I) Team Member

Laxman PoudeI (I) Team Member Prakash G C (I) Team Member

Ratna Bhakta Suwal (N) Team Member Khadga Pathak (I) Team Member

Lokendra Dhakal (N) Team Member Bhan Bdr Ayer (N) Team Member

KrIshna Slmkhada (N) Team Member Sarad Slmkhada (N) Team Member

SabIn Kumar Karkt (N) Team Member Janardan Pokharel (N) Team Member

Surkhet and Dailekh Rolpa and Rukum

Subama man Shrestha Team Leader Murarl Raj KaInI Team Leader

Karunakar Sharma (I) Team Member Uttam BaJracharya (I) Team Member

Chandra Kumar Rat (I) Team Member Gopal 011 (I) Team Member

KrIshna Prasad Sharma (I) Team Member Nirmal Chhetn (I) Team Member

DJlh BhandarI (N) Team Member Pitamber Slmkhada (N) Team Member

Pandav Dahal (N) Team Member Khagendra Adhikarl (N) Team Member

Ganesh Acharya (N) Team Member Dharma Raj Dahal (N) Team Member

SUPERVISION TEAM

Dr Janardan B Khatn-Chhetn Study CoordInator

Dr Bhakta R Dahal NutntIon Consultant

Dr John Bowman DAI Project Manager

TABLE OF CONTENTS

1 1 BACKGROUND 1 2 PREVIOUS STUDIES

CHAPTER ONE INTRODUCTION

1 3 METHODOLOGY OF THE STUDY 1 3 1 DetermmatIon of Sample SIze 1 3 2 Samphng Frame 1 3 3 Reference Penod 1 3 4 SelectlOn of the InterventIOn and Control Groups 1 3 5 Sample SelectIon Procedure m RaptI 1 3.6 Sample SelectIOn Procedure m Bhen

1 4 FIELD SURVEY AND QUALITY CONTROL OF DATA 1 4 1 Data CollectIOn Tools 1 4 2 Trammg and Pretestmg of QuestlOnnatreS 1 4 3 Selection of SupervIsors and Enumerators 1 4 4 FIeld Survey and SupervISlon 1 4 5 Data Processmg and EdItmg 1 5 METHODS OF ANALYSIS

CHAPTER TWO GENERAL CHARACTERISTICS OF SAMPLE HOUSEHOLDS

2 1 DEMOGRAPHIC CHARACTERISTICS

1

1 3 3 4 4 4 5 5 7 8 8 8 8 9 9 9

13

13 2 1 1 Sample Household&, PopulatIOns, and Household Sizes 13 2 1 2 Age DIstnbutlOn and Dependency RatIo 15 2 1 3 Household Head by Gender and Mantal Status 16 2 1 4 Seasonal MIgratIOn 16 2 1 5 Household and Landholdmg Size 18 2 1 6 Literacy Rate 20

22 ACCESS TO AND TIME REQUIRED TO COLLECT BASIC HOUSEHOLD NECESSITIES 21 221 Dnnkmg Water 21 2 2 2 Fuel Wood and Fodder 22 2 2 3 Access to Telephones and Roads

2 3 LOCAL INSTITUTIONS 2 3 1 SOCial Clubs 232 Users' CommIttees 2 3 3 ConstructlOn CommIttees 2 3 4 Income-Generatmg Groups 2 3 5 Other InstitutIons

24 24 24 25 26 26 27

IV

CHAPTER THREE NATURAL RESOURCES

3 1 PUBLIC FORESTLAND AND RANGELAND 3 2 PRIV ATE FORESTS 3 3 FORESTLAND AND THE LOCAL ENVIRONMENT

3.3.1 Threats to BIOdIversIty 3.3.2 Damage from Natural DIsasters

CHAPTER FOUR LAND AND CROP PRODUCTION

41 LAND 4 1 1 Landownership 4 1 2 Land Size

4.2 CROP PRODUCTION 4 2 1 Crop Types 4 2 2 Crop Area 4 2 4 RelatIOnshIp between Crop ProductIOn and Consumption 4 2 5 EstimatIon of Crop ConsumptIOn Income ElasticIty

4.3 FERTILIZER USE 43 1 Households Reportmg FertilIzer Use 4 3 2 FertilIzer ApplIcatIOn

51 VEGETABLE CULTIVATION 5 1 1 Household PartICIpatIOn 5 1 2 Crop Area

CHAPTER FIVE VEGETABLES

5 2 RELATIONSHIP BETWEEN VEGETABLE PRODUCTION AND CONSUMPTION

5 3 ESTIMATION OF VEGETABLE CONSUMPTION INCOME ELASTICITY 5 3 1 IndIrect Method 532 Dlrect Method (RegressIOn AnalYSIS)

54 DETERMINANTS OF VEGETABLE PRODUCTION

29

29 31 33

33 33

35

35 35 37 40 40 42 45 47 50 51 52

55

55 55 58

60 62 62 64 67

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CHAPTER SIX FRUIT 69

6.1 FRUITCULTIVATION 69 6 1 1 Household PartiCIpation 69 61 2 Frmt-Beanng and Nonbeanng Trees 71

62 RELATIONSHIP BETWEEN FRUIT PRODUCTION AND CONSUMPTION 76

63 ESTIMATION OF FRUIT CONSUMPTION INCOME ELASTICITY 77 63.1 IndIrect Method 77 632 DIrect Method (RegresslOn AnalysIs) 79

6 4 DETERMINATION OF FRUIT PRODUCTION 83

CHAPTER SEVEN LIVESTOCK 85

7 1 LIVESTOCK RAISING 85 7 1 1 DIstnbutlOn of Households Rmsmg LIvestock 85 7 1 2 LIvestock Numbers and ProductlOn 87 7 1 3 Mllk ProductlOn 87

72 RELATIONSHIP BETWEEN LIVESTOCK PRODUCTION AND CONSUMPTION 89 73 ESTIMATION OF LIVESTOCK CONSUMPTION INCOME ELASTICITY 91

CHAPTER EIGHT COTTAGE INDUSTRIES 97

8 1 HOUSEHOLD INVOLVEMENT IN COTTAGE INDUSTRIES 97 82 CASH-INCOME GENERATION FROM COTTAGE INDUSTRIES 99

CHAPTER NINE ANALYSIS OF RELATIONSHIP OF INCOME SOURCES 103

91 HOUSEHOLD GROSS TOTAL INCOME 103 9 2 GROSS CASH INCOME 105 93 RELATIONSHIP OF VEGETABLE INCOME TO INCOME FROM OTHER SOURCES 107 9.4 RELATIONSHIP OF TOTAL INCOME TO INCOME FROM OTHER SOURCES 108

REFERENCES 113

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LIST OF TABLES

Page

1 1 PERCENTAGE DISTRIBUTION OF THE RAPTIIBHERI POPULATION BY AGE GROUP 6

1 2 DISTRIBUTION OF SAMPLE HOUSEHOLDS BY ALTITUDE AND WALKING DISTANCETO THE NEAREST ROAD HEAD 7

2 1 DISTRIBUTION OF SAMPLE HOUSEHOLDS, POPULATIONS, AND HOUSEHOLD SIZES, BY ALTITUDE 14

22 DISTRIBUTION OF SAMPLE HOUSEHOLDS, POPULATIONS, AND HOUSEHOLD SIZES,BY WALKING DISTANCE TO NEAREST ROAD HEAD 15

23 PERCENTAGE DISTRIBUTION OF SAMPLE POPULATIONS, BY BROAD AGE GROUP,GENDER, AND DEPENDENCY RATIO 15

24 PERCENTAGE DISTRIBUTION OF HOUSEHOLD HEADS, BY GENDER AND MARITAL STATUS 16

25 NUMBER AND PERCENTAGE DISTRIBUTION OF MIGRANTS, BY ALTITUDE 17

26 NUMBER AND PERCENTAGE DISTRIBUTION OF MIGRANTS, BY WALKING DISTANCE TO NEAREST ROAD HEAD 17

27 PERCENTAGE DISTRIBUTION OF SEASONALLY MIGRATORY HOUSEHOLD MEMBERS,BY PURPOSE AND GENDER 18

28 PERCENTAGE DISTRIBUTION OF SEASONALLY MIGRATORY HOUSEHOLD MEMBERS, BY DESTINATION AND GENDER 18

29 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS, BY FARM SIZE AND ALTITUDE 19

210 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS, BY FARM SIZE AND WALKING DISTANCETO NEAREST ROAD HEAD 19

211 LITERACY RATE, BY GENDER AND ALTITUDE 20

2 12 LITERACY RATE, BY GENDER AND WALKING DISTANCE TO NEAREST ROAD HEAD 20

213 A VERAGE TIME SPENT AND INVOLVEMENT IN FETCHING DRINKING WATER, BY GENDER AND ALTITUDE 21

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214 A VERAGE TIME SPENT AND INVOLVEMENT IN FETCHING WATER, BY GENDER AND WALKING DISTANCE TO NEAREST ROAD HEAD 22

2 15 A VERAGE TIME SPENT AND INVOLVEMENT IN FETCHING FUEL WOOD AND FODDER, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD 23

2.16 AVERAGE DISTANCE TO TELEPHONE BOOTHS AND ROAD HEADS, BY ALTITUDE AND WALKING DISTANCE 24

2 17 PERCENTAGE OF WARDS WITH SOCIAL CLUBS AND PARTICIPATION OF EXECUTIVE MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD 25

2 18 PERCENTAGE OF WARDS WITH USERS' COMMITTEES AND PARTICIPATION OF EXECUTIVE MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD 25

219 PERCENTAGE OF WARDS WITH CONSTRUCTION COMMITTEES AND PARTICIPATIO OF EXCUTIVE MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD 26

220 PERCENTAGE OF WARDS WITH INCOME-GENERATING GROUPS AND PARTICIPATION OF MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO ROAD HEAD 27

221 PERCENTAGE OF WARDS WITH OTHER INSTITUTIONS AND NUMBER OF INSTITUTIONS, BY ALTITUDE AND WALKING DISTANCE TO NEAREST ROAD HEAD 27

3 1 A VERAGE AREA COVERAGE AND CONDITION OF FORESTSIRANGELAND, BY ALTITUDE 30

32 A VERAGE AREA COVERAGE AND CONDITION OF FORESTSIRANGELAND, BY WALKING DISTANCE FROM NEAREST ROAD HEAD 31

33 AVERAGE NUMBER OF FODDER, FUEL-WOOD, AND TIMBER TREES PER HOUSEHOLD, BY ALTITUDE 32

34 AVERAGE NUMBER OF FODDER, FUEL-WOOD, AND TIMBER TREES PER HOUSEHOLD, BY DISTANCE TO THE NEAREST ROAD HEAD 32

35 AVERAGE AREA DAMAGED BY LANDSLIDES AND FLOODS, BY ALTITUDE AND WALKING DISTANCE TO NEAREST ROAD HEAD 33

4 1 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LANDOWNERSHIP, BY LAND TYPE AND ALTITUDE 36

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42 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LANDOWNERSHIP, BY LAND TYPE AND WALKING DISTANCE TO NEAREST ROAD HEAD 37

43 DISTRIBUTION OF LAND PARCELS OWNED AND CULTIVATED PER HOUSEHOLD (IN HECTARES), BY LAND TYPE AND ALTITUDE 38

44 DISTRIBUTION OF LAND PARCELS OWNED AND CULTIVATED PER HOUSEHOLD (IN HECTARES), BY LAND TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 39

45 PERCENTAGE OF HOUSEHOLDS REPORTING CROP PRODUCTION, BY CROP TYPE AND ALTITUDE 41

46 PERCENTAGE OF HOUSEHOLDS REPORTING CROP PRODUCTION, BY CROP TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 42

47 A VERAGE CROP AREA AND YIELD, BY CROP TYPE AND ALTITUDE 43

48 A VERAGE CROP AREA AND YIELD, BY CROP TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 44

49 CROP PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE 46

410 CROP PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 47

411 REGRESSION RESULTS FOR DETERMINANTS OF CROP CONSUMPTION 47

412 REGRESSION RESULTS FOR DETERMINANTS OF CROP CONSUMPTION, BY ALTITUDE 49

413 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 50

414 PERCENTAGE OF HOUSEHOLDS USING CHEMICAL FERTILIZERS, BY ALTITUDE 51

415 PERCENTAGE OF HOUSEHOLDS USING CHEMICAL FERTILIZERS, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 51

416 PER HOUSEHOLD APPLICATION OF CHEMICAL FERTILIZERS AND COMPOST, BY ALTITUDE (KG/YEAR) 52

417 PER HOUSEHOLD APPLICATION OF CHEMICAL FERTILIZERS AND COMPOST, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD (IN KGIYEAR) 53

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5 1 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS PRODUCING VEGETABLES, BY ALTITUDE 56

52 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS PRODUCING VEGETABLES, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 57

5.3 VEGETABLE CROP AREA PER HOUSEHOLD, BY ALTITUDE 58

5.4 VEGETABLE CROP AREA PER HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 60

55 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE 61

56 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 62

57 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY VALUE OF VEGETABLE PRODUCTION 63

58 INCOME ELASTICITIES OF HOUSEHOLD CONSUMPTION 63

59 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND VEGETABLE PRODUCTION 65

510 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND VEGETABLE PRODUCTION, BY ALTITUTDE 66

511 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND VEGETABLE PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 67

5 12 REGRESSION RESULTS FOR DETERMINANTS OF VEGETABLE PRODUCTION 68

61 PERCENTAGE DISTRIBUTION OF FRUIT-GROWING HOUSEHOLDS 70

62 PERCENTAGE DISTRIBUTION OF FRUIT-GROWING HOUSEHOLDS, BY FRUIT TYPE ANDW ALKING DISTANCE TO THE NEAREST ROAD HEAD BY FRUIT TYPE AND ALTITUDE 71

63 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES PER HOUSEHOLD, BY FRUIT TYPE AND ALTITUDE RAPTI 72

64 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES PER HOUSEHOLD, BY FRUIT TYPE AND ALTITUDE BHERI 73

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65 A VERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES PER HOUSEHOLD, BY FRUIT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD RAPTI 74

66 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES PER HOUSEHOLD, BY FRUIT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD BHERI 75

67 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE 76

68 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 77

69 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY VALUE OF FRUIT PRODUCTION 78

610 INCOME ELASTICITIES OF HOUSEHOLD CONSUMPTION 78

6 11 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND FRUIT PRODUCTION 80

612 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND FRUIT PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 81

613 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND FRUIT PRODUCTION, BY ALTITUDE 82

614 REGRESSION RESULTS FOR DETERMINANTS OF FRUIT PRODUCTION 83

615 REGRESSION RESULTS FOR DETERMINANTS OF FRUIT PRODUCTION, ADJUSTED FOR FRUIT CONSUMPTION 84

71 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LIVESTOCK, BY ALTITUDE 86

72 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LIVESTOCK, BY DISTANCE 86

73 NUMBER AND PRODUCTION (IN LITERS) OF LIVESTOCK PER HOUSEHOLD, BY LIVESTOCK TYPE AND ALTITUDE 88

74 NUMBER AND PRODUCTION (IN LITERS) OF LIVESTOCK PER HOUSEHOLD, BY LIVESTOCK TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 89

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75 LIVESTOCK PRODUCTION AND CONSUMPTION VALUES AND CONSUMPTION PERCENTAGE PER HOUSEHOLD, BY ALTITUDE 90

76 LIVESTOCK PRODUCTION AND CONSUMPTION VALUES AND CONSUMPTION PERCENTAGE PER HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 90

77 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND PRODUCTION OF LIVESTOCK 91

78 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND PRODUCTION OF LIVESTOCK, BY ALTITUDE 92

79 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND PRODUCTION OF LIVESTOCK, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 94

8 1 PERCENTAGE OF HOUSEHOLDS INVOLVED IN COTTAGE INDUSTRIES, BY INDUSTRY TYPE AND ALTITUDE 98

82 PERCENTAGE OF HOUSEHOLDS INVOLVED IN COTTAGE INDUSTRIES, BY INDUSTRY TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 99

83 A VERAGE VALUE OF RAW MATERIALS PURCHASED (RMP) AND INCOME EARNED (IN RUPEES) FROM THE SALE OF COTTAGE-INDUSTRY PRODUCTS, 1996, BY PRODUCT TYPE AND ALTITUDE 100

84 A VERAGE VALUE OF RAW MATERIALS PURCHASED (RMP) AND INCOME EARNED (IN RUPEES) FROM THE SALE OF COTTAGE-INDUSTRY PRODUCTS, 1996, BY PRODUCT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 101

9 1 ANNUAL GROSS TOTAL INCOME PER HOUSEHOLD AND PERCENTAGE FROM DIFFERENT SOURCES, BY ALTITUDE 103

92 ANNUAL GROSS TOTAL INCOME PER HOUSEHOLD AND PERCENTAGE FROM DIFFERENT SOURCES, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 104

93 PERCENTAGE DISTRIBUTION OF ANNUAL GROSS CASH INCOME PER HOUSEHOLD, BY SOURCE AND ALTITUDE 105

94 PERCENTAGE DISTRIBUTION OF ANNUAL GROSS CASH INCOME PER HOUSEHOLD, BY SOURCE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD 106

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95 A VERAGE VALUE OF PRODUCTION OF DIFFERENT CROPS, BY VEGETABLE INCOME QUARTILE 107

96 A VERAGE V ALUE OF PRODUCTION OF DIFFERENT CROPS BY FRUIT INCOME QUARTILE 108

97 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION 109

98 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD 110

99 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION, BY ALTITUDE 111

RAPTIIBHERI Zones TopographyNDCs BoundarylMotorable Road 11

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EXECUTIVE SUMMARY

RapId growth In the production of hIgh-value agrIcultural commodities is at the center of the hIlls and mountains strategy in HMG's AgrIcultural PerspectIve Plan (APP) Success In ImplementIng thIS high­value-commodity approach requires solutIOns to a large number of practIcal problems. USAID's Vegetables, FruIts, Cash Crops, and Ammal Products (VFCI A) Program, WhICh has been carned out III the fIve districts of the Rapti zone In Nepal, is a prototype for the APP strategy VFC/A has been implemented in a substanual number of pockets of intenSIve activity with a partIcular emphaSIS on natural resource COndItiOnS, off-season vegetables, vegetable seeds, and apples

USAID IS now moving from the VFC/A pIlot approach to large-scale Implementation desIgned to have a macro Impact on the RaptI dIStrIcts, as well as to expand Into three districts In the Bhen zone of Nepal As an element of the tranSItion, a senes of studIes has been commiSSIoned to analyze relationshIps Important to project success and to serve as a baselIne for measunng progress in a follow-up project, the Market Access for Rural Development (MARD) Project Reported here are the results from a baselIne Income survey of households among pockets of IntenSIve activity in RaptI and among a random sample In Bhen The Bhen sample populatIOn was surveyed In order to prOVIde a descnption of that zone and to serve as a base for comparIson WIth Rapt!

The Income survey was conducted for USAID by the Agncultural Projects Services Centre (APROSC), with aSSIstance from John Mellor ASSOCIates (JMA), to examine the initial, early-stage impact of the VFCI A program. The survey was conducted under a larger, RegIOnal Agnbusiness Project (RAP) InItiative known as the Nepal MId-Western Development RegIOn BaselIne Survey Activity (MWDR-BSA)

The income survey, conducted In 1996, had three main objectives:

(l) Continue support for strengthenIng InstitutIOnal capaCIty for managIng development at the dlstnct and VIllage levels,

(2) Expand and strengthen the program for managIng natural resources; and

(3) Concentrate resources on agrIcultural productIOn In both valley and hIll areas

SAMPLE PROCEDURES

The results of the Income survey descnbe the effects of agrIcultural production In pockets of Intense project actiVIty Thus, In order to conduct the survey, ItS key implementors were asked to select those pockets, to dehneate them on maps, and to hst partICIpants In the survey among those pockets That hst, now somewhat amended and updated, was sampled randomly Some bIas may eXIst toward upper­mIddle SIze farms, but It IS unhkely to be major A comprehensIve Income questionnaIre was admInIstered to households among the sample populatIOn

Because a nutntIon survey Intended to emphaSIze chIldren ages 12 to 60 months was conducted concurrently WIth the Income survey, households WIthout a chIld In that age range were dropped from the sample This resulted In an overrepresentatIOn of chIldren In that age range (12 percent), an underweightIng

XVI

of children ages 10 to 14 (12 percent), an overweighting of adults ages 20 to 34, (17 percent), and an underwelghtmg of adults ages 35 to 54 (20 percent) These bIases occurred m both the RaptI and Bhen samples and hence do not affect the comparisons (A future survey to be taken from a random sample of all households m the eIght dlstncts surveyed here will not have such a bIas)

Survey households were analyzed in general and by altItude and distance from the nearest road ill various categories, including land and crop productIOn, vegetable productIon, livestock productIOn, and cottage-industry production. In terms of the categones of altitude used, comparisons between Rapti and Bheri are most accurate for the 1 ,Ooo-to-l ,SOD-meter range. Regarding broad characteristics, that elevation range and the next hIghest (1,500 meters to 2,000 meters) are quite simIlar Thus, the mam gap in comparison occurs with the next, and hIghest, range, the above-2,000-meter category

Both the Rapti and Bheri samples show substantIal representatIon at altttudes below 1,000 meters, WhICh constItutes the fIrst altItude category used m the survey However, there are two major sources of contrast between Rapti and Bheri at this elevation FIrst, m RaptI, a large number of Tharus, an ethmc group hardly represented in the surveyed Bheri dlstncts, live m the areas surveyed below 1,000 meters The Tharus have extended famihes that are some 60 percent larger m size than the average famIly m theIr area Consequently, the Tharus have SImilarly larger farms than theIr neIghbors (They also have other cultural traits that may set them apart somewhat)

The second major source of contrast between Raptl and Bhen at elevatIons below 1,000 meters mvolves the Dang Valley, which is larger than the mIddle mountain valleys (The Dang, however, does contam a smaller, main valley m the Surkhet Dlstnct of Bhen and a number of small valleys more akm to those of the mIddle mountain valleys) For the precedmg reasons, comparIsons of the lower elevatIOns m Rapt! and Bhen must be treated cautIOusly

It is also notable that RapU's dIStrICtS have a much higher proportion of perenmally lITigated lowland than do the Bheri dIStriCtS studied That may be somewhat an effect of mtenslve development rather than purely causal Most likely, the greater prevalence of pipe lITIgation on RaptI's slopes IS the result of the high profItability of hIgh-value crops

With these caveats m mmd, there IS much of importance to be gleaned from careful comparisons across the various dIStnCtS, elevations, dIstances from roads, and, most Important, the emphasIs on hlgh­value crops exhIbited m the survey results

INCOME

The income contrasts are stnking between the pockets of mtense development m Rapti and Bheri Comparing households at elevatIOns of 1,000 to 1,500 meters (WhICh are broadly representative), gross mcome per household is twice as high in RaptI as in Bhen Although farm size is the same between the two districts at thIS elevation, farm income IS 2 6 times higher in Raptl Bhen, however, as discussed below, has a larger migrant populatIOn than Rapu and, hence, produces hIgher nonfarm mcome than Its counterpart. In RaptI, 31 percent of total income is generated by fruIt and vegetables, compared With 13 percent in Bhen In addition, the total income from frUIt and vegetables alone m RaptI IS greater than the total farm mcome from all sources m Bhen

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In RaptI, at elevatIOns of 1,500 to 2,000 meters, the average household income IS 26 percent hIgher than at the next lowest elevation (1,000 to 1,500 meters), and 36 percent of mcome IS generated by vegetables and fruIt

As noted above, households were also surveyed based on their distance from the nearest road head. At a dIstance of more than two days from the road, the contrast between RaptI and Bheri IS neglIgible At that dIstance, vegetables and frUlt constitute 14.4 percent of farm income m Rapti and 165 percent m Bheri. From these figures one can surmise that access to roads has been essential to mtensive pocket activIties in the two zones. However, the VFC/A program's largest impact relative to road access m Rapti and Bhen occurs at distances from one-half day to two days, Illustrating that it is not essential for households to have road access It may be, as discussed below, that more can be done for those VIllages WIth limIted road access, certainly, substantIal road extensIOns would be helpful

GIven the Importance of vegetables to mcome generatIon m the survey areas, the study team found It useful to dIVIde the farms mto quartIles accordmg to the farms' value of vegetable production In the lowest quartile, the average SIze farm IS about half that of the other quartiles In Rapti, from the second to the fourth quartiles, vegetable productIOn mcreases seven tImes, crop production IS hIgher by 75 percent (showmg some complementarity between vegetables and crop productIOn), and mcome IS also 75 percent hIgher FruIt productIOn, lIvestock production, and cottage-mdustry productIOn show no trend across the second to fourth quartiles m the zone

SEASONAL MIGRATION

One of the major dIfferences between RaptI and Bhen IS the former's far lower level of mIgratIOn ThIS is presumably because of the combmed effect of RaptI's higher mcomes, makmg mIgration less essential to the famIly, and the zone's greater employment opportumtIes, the result of Raptl's more mtensive farmmg and assocIated nonfarm actiVIties, whIch prOVIdes attractive employment pOSSIbIlitIes

Because migrants tend to come largely from the middle of the workmg age dIstnbution, the percentage of migrants among that group IS much hIgher than among other age groups About half the mIgrants go to India or other foreIgn destinations In Rapti, a somewhat hIgher proportIOn (15 percent of mIgrants, compared WIth 3 percent for Bhen) are employed m distnct headquarters, suggestmg some lmkages between local urban employment and farm prosperity Very few females mIgrate from either zone, most of those who do so to VISIt relatives rather than to seek employment

VEGETABLES

Vegetable productIOn is the most important thrust of the VFCI A program Its Impact has been ImpreSSIve The cropped area devoted to vegetables is nearly three tImes as great m RaptI as m Bhen Although the mtent of the VFCI A project was commercial production of vegetables and vegetable seeds, the Impact on consumption has been very large (The study team calculated consumption by subtractmg sales, plus an arbItrary constant percentage for losses, from productIOn Although thIS measure of consumptIOn is very rough, the results are stnkmg )

xviii

In the Bhen dlstncts surveyed, essentially none of the vegetables produced are sold-all are consumed at home That IS also true of Isolated areas located above 2,000 meters m Raptl, but at all other elevatiOns, about one-quarter of the vegetables grown are sold As will be seen later, this statlstlc has an Immense Impact on mcome Accordmg to the survey data, for each doubhng of the amount of vegetables produced, vegetable consumption mcreases by 90 percent

In keeping with the above, the team found the prevalence of kitchen gardens to be twice as high among households in Bheri as in Rapti Thus, it seems that the VFCI A program has had a notable effect on vegetable consumption.

Because the elasticity of consumption of vegetables shown m the study IS surpnsmgly low, it would seem that very low prices would be the major cause of the large consumption effect from vegetable production Vegetable production in the surveyed areas takes place at home, and hence entails no marketing costs In addition, a substantial proportiOn of produce IS unmarketable because of problems With quality. As a result of these factors, produce IS very cheap for home consumptiOn, and consumptiOn nses markedly

The effect of greater consumptiOn on nutntional status, discussed m another report from thiS senes, IS of course complex because of many mtervemng vanables. Whatever the fmal effect Will eventually be, however, the large mcrease m the availability and consumption of vegetables IS very beneficial for the well-being of not only people, but of the environment they inhabIt

FRUIT

Apples are the only frUIt to have received major attention m the VFC/A program MARD is expected to expand the coverage to oranges and perhaps one or two other fruit Fruit trees, of course, have a longer gestation penod than vegetables, hence the program's full impact on fruit production and consumptiOn Will be felt later than its effect on vegetable cultivatiOn At present, m the Raptl diStriCtS, young non-frult-beanng trees number about tWice as many as fruit-bearmg trees Hence, large mcreases m fruit production are yet to come.

Currently, fruit production per household IS about 2 5 times as great and consumption 3 times as great in Raptl as m Bhen The computed elastiCity of fruit consumption With respect to frUIt production approximates 1 Most apples are produced at a walkmg dIstance of one to two days from the road, and many are produced even farther away, as the frUIt is suited to hIgh elevatiOns Apples tend to fetch very low prices, and a large quantity of low-quahty pieces are available Thus, It is not surpnsmg that apple consumption IS very great among the apple-producing areas studIed

FERTILIZERS

Not surprismgly, far more fertIlIzers are used m RaptI than in the Bhen dIStriCtS surveyed No fertIhzer IS used on vegetables and frUIt m Bhen, whereas substantIal quantities are used m RaptI However, even m Rapti, lIttle or no fertilIzer IS used on fruit trees.

XIX

At low elevations, Rapti farmers use about 134 kilograms of nutrIents per hectare, while those in Bheri use only 4 kIlograms (The ratio is 47 to 2 at elevatIOns of 1,000 to 1,500 meters)

It IS not surpnsing, gIven the known complementanty between nutnents and organIc matter, that compost use IS also far heavIer in RaptI than m Bherl. At the same elevations, roughly tWIce as much compost is used in Rapti as in Bheri The lowest usage of compost in Raptl occurs at the lowest elevatIOns, where matenals for compost are most scarce, and at the highest elevations, where less fertihzer is used and output pnces are lower, and hence the rate of return to compost IS lower

It IS also notable that m Bheri, farmers use essentially no nutrients other than nitrogen m the form of urea, whereas in RaptI, farmers apply a much more balanced set of nutnents

LIVESTOCK

LIvestock receIved less attentIOn than fruit and vegetables under the VFC/A program Nonetheless, some contrasts between livestock productIOn m Rapti and Bhen may represent the mdlrect effect of the program.

The survey results reveal that the value of hvestock consumption is 30 percent hIgher m RaptI than m Bhen This IS undoubtedly partly attnbutable to RaptI's hIgher incomes, WhICh in turn greatly reflects the VFC/A program's Impact on frUlt and vegetable productIOn m the zone. In both zones, milk consumptIOn dommates livestock-product consumption

In sharp contrast to the consumption relatIOnships for fruIt and vegetables, in the case of hvestock, the elasticity of consumptIon wIth respect to total income IS a moderately hIgh 06, the elaStlCIty of consumption with respect to hvestock production, on the other hand, IS a very low 0 26 The dIfference hes m the fact that mcreased fruit and vegetable consumption is driven almost entIrely by fruIt and vegetable production, whereas hvestock consumption IS driven largely by total income Thus, an mcrease m total mcome from frUlt and vegetables is expected to dnve substantial mcreases m consumption of lIvestock products Consequently, the very poor sell their hvestock products rather than consume them at home, those with hIgher incomes can retam those products for home consumption

ConsumptIOn of lIvestock products among the study areas nses wIth an increase III elevatIOn, except among households above 2,000 meters, In whIch the substantially lower Incomes dnve consumptIon down, even though sales of hvestock products are an important source of cash Illcome

COTTAGE INDUSTRIES

Cottage-industry actIvitIes III general decline as Incomes Increase m the study areas because such actIVIties tend to proVIde low returns on labor The contributIon of cottage mdustnes to Illcome IS tWIce as hIgh among households located above 2,000 meters as m the other elevation classes, a result of the generally low mcomes, Isolated nature of the locatIons, and low returns on labor III other actIVItIes m those areas The manufacture of vanous textlles, such as radhi, Alo, and bhangra, are Important, along wIth

xx

liquor, ghee (butter), and honey productIOn Some of these occupations lend themselves to market development and increased mcomes.

DespIte the tendency for cottage-mdustry efforts to dechne as mcome nses, cottage-mdustry production per household IS 2 5 tImes as high m RaptI as m Bheri

FOREST PRODUCTS

The USAID Rapti projects have been very active m the development of commumty forestry, and that work is known to be hIghly effective Thus, it IS no surpnse that at elevations of 1,000 to 1,500 meters, there IS 4.6 tImes as much commumty forest in the RaptI pockets surveyed as in the Bhen pockets Rapti also contains many more pnvately owned trees per household than Bhen, perhaps reflecting a greater awareness of the value of trees among those m Raptl, as a result of the zone's forestry programs.

At elevations below 1,000 meters, 90 percent of forestland IS community owned, compared with only 4 percent m Bheri. However, Rapb's pocket areas contam much fewer commumty forests at hIgh elevatIOns than at low elevatIOns Similarly, m areas dIstant from roads, one-fIfth as many community forests are located more than two days from the road as m more accessible areas

HIGH·ELEV ATION POCKETS

Recent VFC/A actlVltIes have emphasized the use of temperate-Iatltude seeds m hIgh elevatIOns, and there are other efforts that could be pursued in those areas as well However, as of now, these areas are severely dIsadvantaged and, on eqmty grounds, merit special attentIOn Here, cropped area is smaller than m all other survey areas, and the average household SIze IS substantlally larger, at 7 7 persons, compared WIth 6 8 for other study locations.

By definitIOn, hIgh-elevatIOn areas are Isolated On average, the pocket actlvity VIllages at these elevatIons are 150 kilometers from a road (compared WIth the average of 40 kilometers at lower elevatIons) and 61 kIlometers from a telephone (compared WIth 8 ktlometers at lower elevatIOns) The hteracy rate among females at hIgh elevatIOns is half that among females at lower elevatIOns, and among males, 15 percent lower Only 7 percent of these households have a kItchen garden, compared WIth 75 percent of those m the RaptI htll pockets (at levels of 1,000 to 1,500 meters) In addItion, hIgh-elevatIOn households have essentially no means of lITigatIon, although the potentIal for pIpe lITigatIOn IS substanttal Farmers m these locations use essenttally no fertlhzer The above-2,OOO-meters elevatIOn IS the only one that shows a defICIt m productIOn of food relattve to consumption

Vegetable consumption among households at hIgh elevatIOns IS one-half to one-thIrd that at lower elevations Areas more than two days from the nearest road are roughly comparable to the hIghest elevatIOn areas

xxi

SOCIAL ORGANIZATIONS

By all social measures, RaptI's dlstnct pockets of activIty are far more advanced than are Bheri's In Bheri, It takes almost twice as long per tnp to fetch water as In the Raph pockets In both zones, women perform two-thIrds of the water-carryIng chores SImIlarly, in both Rapti and Bheri, women do 60 percent of the fuel and fodder carryIng.

SOCIal organIzations are 1.5 times as prevalent In RaptI as In Bhen Income-earmng organizatIOns, such as credit groups, are present in 45 percent more wards In RaptI than in Bhen Among these groups, Rapti's have 24 tImes as many members, on average, as Bhen's and 1 6 hmes as many female executIve committee members

ITEMS FOR FUTURE BASELINE SURVEYS

The pocket analyses performed In thIS study proVIde many clear comparisons for use in future basehnes. Of partIcular note are the rate of mIgratIOn, female participation In Income-earning groups, accesslbihty to telephones and roads, the amount of commumty forestland, and IrngatIon rates In the survey areas Also notable in the two zones are the levels of vegetable and frUIt productIOn, the level of Income and the proportion from various sources, lIvestock, fruIt, and vegetable consumption levels and theIr relatIOn to Income and productIOn of the respective commodItIes, and fertIlIzer use and ItS relation to compost use

1

CHAPTER ONE

INTRODUCTION

ThIS IS one of several closely related studIes conducted m 1996 m the rural areas of the RaptI and Bhen zones of Nepal The objectIves of these studIes are to (1) measure the Impact of past development efforts III the RaptI zone, wIth an emphasIs on pockets of mtensIve hIgh-value cash crop actIvItIes, (2) proVIde a baselme for future surveys measunng the Impact of actIVItIes m the RaptI and Bhen zones, (3) provIde a database for pohcy recommendatIOns to Improve the future performance of development actIVItIes m the two zones, and (4) prOVIde detaIled mformatlOn on the current status and Impact of development mterventlOns on the nutntlOnal status of the two zones' populatIOns, WIth an emphaSIS on Vltamm A

The current report IS based on a sample of households partIcipatmg m actIVItIes m the vanous pockets of the Raptl zone under the Vegetable, FruItS, Cash Crops, and Antmal Products (VPCI A) program component of USAID's RaptI Development Project (RDP) ThIS study IS further complemented by three other studIes an mtenslve nutntlOn survey and a focus-group-based study, both of whIch WIll sample the same pockets m the fIve Raptl dIstncts that are the subject of the current study, and an area-based study, whIch wIll use the same questIOnnaIres (to assess mcome and nutntlOnal status) as the current study but WIll draw randomly from a larger populatIOn from the fIve dIstncts The area-based study WIll serve not only as a basel me but also as a control for analyzmg any change that may occur m the sampled pockets

In total, SIX reports are bemg prepared (1) the current mcome study, whIch surveys those pockets WIth the most mtensIve actIVItIes, (2) the mtensIve nutntlOn study, (3) the focus-group-based study, (4) an analytIcal study, whIch WIll be compared WIth the current study and WIll be based on a randomly selected sample drawn from the entIre populatIOn of the fIve dlstncts, (5) another nutntlOn study, whIch WIll be conducted based on mformatlOn garnered from the random sample, and (6) a summary syntheSIS report, whIch WIll present the fmdmgs and recommendatIOns from the above fIve studIes

1.1 BACKGROUND

Project mterventlon for development of the RaptI zone began m the early 1980s Development actIVItIes executed under RDP's predecessor, the Raptt Integrated Rural Development Project (IRDP), also funded by USAID, were deSIgned m 1979-1980 With an mtegrated approach to bnng about economIC and SOCIal changes m remote areas of Nepal The project was Implemented m fIscal year 1981-1982 WIth two mam objectIves

(1) To mcrease the measurable aspects of the quahty of hfe, mcludmg mcome and productIon levels, for famIlIes hvmg m the RaptI zone, and

(2) To Improve the natIonal delIvery systems for agnculture, health, educatIOn, mfrastructure, resource management, and famIly plannmg

2

The evaluatIOn of IRDP, conducted m 1985, mdlcated that only 54 percent of the planned targets had been met, and that the mtegrated approach had not been fully adopted Nevertheless, the project had made sIgnIficant progress m estabhshmg support for agncultural growth and m Improvmg the forest, soIl, and water conservatIOn base m the project area Based on these achIevements, the evaluatIOn recommended that a phase II proJect, later known as the RaptI Development ProJect, be launched wIth the following objectIves

(l) Contmue support for strengthening mstitutional capacity for managmg development at the district and Village levels,

(2) Expand and strengthen the program for managmg natural resources, and

(3) Concentrate resources on agncultural productIOn m both valley and hIll areas

RDP was Implemented m July 1987 following an mtegrated techmcal and economIC appraIsal Under RDP, a consultmg fIrm called No-Fnlls Consultants (NFC) Implemented the VFC/A program m selected hIgh potentIal areas of the RaptI zone VFC/A's ObjectIves were to promote off-season vegetable productIOn, vegetable seed productIOn, fruIt productIOn, and off-farm actIvItIes a~ pIlot projects to mcrease famIly mcome and nutntIonal status

The evaluatIOn of RDP, conducted m early 1995, commended the VFC/A program for Implementmg the recommendations made m 1985 to concentrate resources m agncultural productIOn The VFC/A program not only concentrated Its efforts on agncultural productIOn, but also on cash-mcome generatIOn and on Improvmg the marketmg system to ensure the success of hIgh-value crop productIOn

The 1995 RDP reVIew noted that the success of the VFCI A program was a result of reachmg a cnHcal mass m pockets of hIgh potentIal The reVIew also reported favorably on USAID's mtentIOn to expand the project to prOVIde a macro Impact m the targeted dlstncts and to lay the groundwork for the formulatIOn of a model that could be rephcated natIOnwIde The reVIew also acknowledged the success ofRDP's Commumty Forestry Program and the potentIal for Its expansIOn mto other dlstncts m Nepal

ConsIstent WIth the 1995 reVIew, USAIDlNepal recently announced the mtentIOn to launch two new projects m the fIve dlstncts of RaptI and three dlstncts m Bhen The two projects WIll be known as the Market Access for Rural Development (MAR D) Project and the EnVIronment and Forest Enterpnse ACtIVIty (EFEA) The challenge of these projects WIll be to mtegrate successfully nutntIOnal goals mto an agnculture- and agnbusmess-dnven rural development effort The rural development effort WIll emphasIze mcome generatIOn through mostly mcreased productIOn of hIgh-value cash crops and forest products

The 1985 reVIew also pomted out that the project deSIgn formulatIOn and evaluatIOn efforts m Nepal were constramed by lack of relevant data In response, the current mcome study, as part of a senes of studIes, was deSIgned to Improve the database for analysIs of future projects m the area and to proVIde a baSIS for Improvement of these projects The studIes wIll proVIde a base, partIcularly after a few years of project ImplementatIOn, for answenng the followmg questIOns Have the mcome level and nutntIOnal status of the area's people mcreased? Has the natural resource condItIon of the project area Improved? Has the qualIty of lIfe for rural people Improved?

3

1.2 PREVIOUS STUDIES

The Agncultural Projects SerVIces Centre (APROSC) has completed several studIes smce the imtIatIOn of USAID projects m the RaptI zone These studIes mclude the Reconnaissance Study (APROSC 1977a), the PrefeasIblhty Study (APROSC 1977b), the FeasIbIhty Study (APROSC 1980a), the Household Baselme Survey (APROSC 1980b), and the Household Income Survey (APROSC 1990) Of all these studIes, only the last two were based on random samples

The 1980 Household BaselIne Survey and the 1990 Household Income Survey were based on the same methodology and mtervIews wIth the same 1,600 households The authors of both studIes attempted to calculate and compare total household mcome, but were able to report only nommal cash mcome and household expendItures Furthermore, an analysIs of the change m the ratIo of cash mcome to total household mcome between 1980 and 1990 were found to be sIgmfIcant

All of the APROSC studIes collected extensIve household-level demographIc, SOCIOeconomIC, and agncultural productIOn data, mcludmg mformatIOn on off-farm actIvItIes

1.3 METHODOLOGY OF THE STUDY

A common practIce for achIevmg the above stated objectIves IS to collect and analyze the necessary mformatIOn through a sample survey DIfferent approaches eXIst for selectmg a sample, dependmg on, among other thmgs, such factors as resource aVaIlabIlIty, survey objectIves, level of extrapolatIOn, and level of accuracy of estImate needed Appropnate random samplIng IS necessary when one needs an unbIased estImate of the sample populatIOn wIth a known probabIlIty of confIdence level and margm of error If. however, one's purpose IS to analyze the relatIOnshIp among dIfferent vanables related to a specIfIC group, and one does not reqUIre estImates of the charactenstics of the larger populatIOn, a non­random, or purposIve, samplmg procedure mIght be more appropnate

A random sample survey procedure to measure the overall mcome and nutntIOnalimpact of the VFCI A program IS expected to be mSIgmfIcant and thus deemed unnecessary because the USAID mterventIOn (especIally the VFC/A program) IS bemg Implemented m small pockets at eIther the dIstnct or zone level The Impact of the VFC/A program m pockets where It was Implemented, however, IS expected to be sIgmficant Therefore, two separate samplIng deSIgns were chosen as appropnate for meetmg the objectives of the current senes of studIes It was deCIded that the studIes would use (1) the purpOSIve samplIng method to understand the mcome and nutntIonal Impact of the VFCI A program m lImIted pocket areas, and (2) a random samplmg deSIgn to establIsh a basehne for measunng mcome and nutntIOnalimpact m new areas under the MARD and EFEA projects

More speCIfically, the current mcome study IS deSIgned to understand the mcome and nutntIOnal Impact of prevIOUS USAID mterventIOns, and to analyze relatIOnshIps wIthm successful areas of project actlVltIes so that MARD and EFEA can be deSIgned to be more effectIve ThIS study WIll also present the mcome and nutntIOnal status of selected households partIcipatmg m selected pockets of the dIfferent ecologIcal zones that are acceSSIble withm RaptI In Bhen, sample households were selected from dIfferent ecolOgical zones with varymg degrees of acceSSIbIlIty to roads The sample selectIOn was made

4

USIng the random samplIng techmque, given that, to date, USAID has not conducted an mterventlOn m Bhen

1.3.1 Determination of Sample Size

Determmmg appropnate sample SIze IS dIffIcult m all survey exerCIses because It reqmres pnor knowledge of vanabilIty in some of the Important charactenstIcs withm the study populatIOn ThIS informatIOn usually remaInS unknown until the survey IS conducted It IS Important to know the optimal size of the sample because a sample larger than reqUIred unnecessanly mcreases not only the cost and time involved In conductmg the survey, but also the degree of non-samphng error On the other hand, an madequate sample wlll not Yield estimates at the desired level of confidence and margm of error Sample Size, therefore, IS usually determmed by usmg a mix of estimates of vanance from prevIOUS studies or by usmg some proxy variables and consldenng resources, preClSlon, and tIme aVaIlablhty

For the current study, a total of 900 households was chosen as the appropnate sample Size, which was based on the mean and vanance of certam van abIes from prevIous studies on Raptl ApprOXimately two-thirds of the households were collected from Raptl and a third from Bhen

1.3.2 Sampling Frame

Smce the study area consisted of an mterventIOn (Raptl) and nonmterventlon (Bhen) areas, and multistage samphng techmques were used, the samplmg frame for the two different types of areas and the stages of samplmg were as follows

In the RaptI zone, the hst of selected Village development committees (VDCs) and mterventIOn pockets formed the first-stage samphng frame Households partlClpatmg m the VFC/ A program In the selected pockets that had at least one chlld between one and five years of age made up the samplmg frame for household selection

In Bheri, because households were selected m three stages, a hst of all the VDCs of Surkhet, Dallekh, and laJarkot formed the samphng frame for first-stage selectIOn The hst of wards m selected VDCs was used as the samphng frame for ward selectIOn, and the hst of households m the selected wards served as the samphng frame for household selectIOn

1.3.3 Reference Period

The field survey was conducted m January and February of 1996 for all of Rapt!, except for Jmabang In Rolpa Distnct, where the survey could not be conducted at that time because of pohtlcal problems The Imabang area survey was completed In Apnl For the purpose of thiS study, 1995 was conSIdered the reference penod for collectIng Information for all cases

5

1.3.4 Selection of the Intervention and Control Groups

There are two ways to measure the Impact of mterventlOn programs The first IS to measure changes m the mterventlOn area usmg time senes data from mformatIon on the pre-mterventlOn penod and post-mterventlOn penods, while accountmg for the mfluence of other factors unrelated to the mterventlOn The second way IS to collect cross-sectIonal mformatlOn from the mterventlOn area and the control area, which IS presumably unaffected by the project mterventlOn activIties In the absence of pre-mterventIon baselIne mformatlOn, the second optIon IS usually preferred, even though It IS difficult to fmd a true control area.

Determmmg a control area for our purposes can be done m two ways One way IS to survey the pockets of mfluence and diVide those mtervlewed mto those who have adopted VFC/A cultivation methods and those who have not Presumably, the adoption of VFC productIOn methods Will depend on factors such as clImate SUItabilIty as determmed by altitude, the selectIOn of adapted crop technologies, and distance from the nearest road Those m more favorable locatIOns adopt the methods more rapidly than those who are not

The second way to measure program Impact IS to Identify a control group outSide the study pockets and compare the mcome levels between the two groups In the case of the current study, It was difficult to differentiate between participants and nonparticipants (those households wlthm the mterventlOn pockets that are not even mdlrectly affected by the VFC/A proJect) Only those households on NFC's lIst of partlclpatmg households were mtervlewed, yet, m many cases, the lIst was out-of-date Consequently, the idea of selectmg some nonparticipants to form a control group from Raptl was dropped The control group instead was pulled from the three dlstncts m the Bhen zone where no prevIOus USAID project eXisted (Fortunately, a randomly selected sample from Bhen should present a better control group than a sample of nonparticipants m the mterventlOn pockets m RaptI, anyway)

The Bhen control group was selected from those households situated at the same altitude range and distance from a road as those households m RaptI The responses regardmg mcome and nutntlOn from these two groups should offer a measure of difference between the control group and the Impact group.

1.3.5 Sample Selection Procedure in Rapti

As noted above, the sample study pockets were selected from a lIst of mterventlOn areas particlpatmg m the VFC/A program Implemented by No-Fnlls Consultants These mterventlOn areas represent a good mix of areas from all different elevatIOns and distances from the nearest road head The survey team then updated NFC's hst m the field A predetermmed number of households was then selected from thiS lIst to be mterviewed Those households that dId not have at least one chIld between the ages of one and five (for purposes of measunng height and weight) were deemed unqualIfied and thus were dropped from the sample Also elimmated were those households that had no famtly members aVailable who could answer questIOns about both mcome and nutntton

Such a selectIOn process mtroduces lImitatIOns mto the study sample and renders the resultmg analYSIS a case study, for the followmg reasons

6

(1) The declSlon to survey only those households that met both the mcome and nutntlOnal survey cntena may have mtroduced an age bias m the sample wIth respect to head of household Hence, the selectlOn process may have lImIted the sample to household heads between the ages of 20 and 45 However, because of RaptI's prevmlIng extended-famIly system, m whIch normally three or even more generatIons hve m the same household, thIS age bIas may not be too senous

The Issue of age bIas can be mvestIgated by companng thIS study's sample age-sex structure with that of the 1991 census A companson of percentage dIstnbution of populatlOn between the 1991 census and the sample households shows that the sample households are higher in the under-4 age group and the 20-to-34 age group but lower m the 35-to-54 age group than those III the census data (see Table 1 1) The data confirm a biaS m some keyage groups m the sample most Importantly, the 35-to-54 age group IS under represented by approximately 20 percent, while the 20-to-34 age group IS over represented by about 17 percent ThIS analYSIS will descnbe the effects of that bias, and the random-sample analYSIS will prOVide a means for adJustmg for the bias as necessary

Although It IS not Important to thiS study of agncultural change, it seems appropnate to mentlOn that the 1O-to-14 age group is also under represented m the sample, by 12 percent The under-5 group is also under represented by 12 percent

(2) The sample pockets chosen for the survey may represent only the more successful pockets, given that they would reflect the performance of the implementor The sample, therefore, may not be a true representative of all mterventIon pockets Thus, the mformatlOn from thiS sample can only be used for analyzing relatIOnships wlthm the more successful areas of activity Companson With a random sample from RaptI and With that from Bhen will proVide a control

TABLE 1 1 PERCENTAGE DISTRIBUTION OF THE RAPTI/BHERI POPULATION BY AGE GROUP

Age Group 1991 Population 1996 Sample Survey (N=884)

Under 4 16.5% 18.5%

5-9 15.3% 15.2%

10-14 13.3% 11.7%

15-19 10.0% 95%

20-24 8.4% 9.3%

25-29 7.1% R.R%

30-::14 5.8% 6.8%

35-39 5.3% 4.7%

40-44 4.!'i% 3.5%

45-49 3.9% 2.8%

50-54 3.2% 2.6%

55+ 4.4% 4.:i%

1000% 1000%

Note Bold numbers are greater than the corresponding numbers In each group

7

1.3.6 Sample Selection Procedure in Bheri

The three dlstncts m Bhen were dIvIded mto three categones based on elevatIOn (1) less than 1,000 meters, (2) 1,000 to 2,000 meters, and (3) above 2,000 meters These categones were further dIvIded into several strata by dIstance from the nearest road head. The survey team then selected fIve VDCs from each stratum and randomly selected two wards from wlthm each VDC A predetermmed number of households was randomly selected from each ward (see Table 1 2) As wIth Rapt!, a hIgh possIbIlIty eXIsts that age bIas was mtroduced m the Bhen sample

TABLE 12 DISTRIBUTION OF SAMPLE HOUSEHOLDS BY ALTITUDE AND WALKING DISTANCE

TO THE NEAREST ROAD HEAD

Distance

Altitude < Y2 Day Y2-1 day 1-2 Days >2 Days

VDC Sample VDC Sample VDC Sample VDC Sample HH HH HH HH

< 1,OOOm Hekauh 29 Shree-gaun 23

Chaulabl 36 Satbanya 21 Ramghat 52 Bhlngn 9 BIJuwar 18

Subtotal 188

1,OOOm- Dharma- Dhana- 54 Chhlbang 41 Danda- 54 1,500m bat I 18 wang Kholagaun 41 gaun*

Phala- Pokhan- 50 Chau- 48 wang 27 kanda* ratha*

Pusakot* 48

Subtotal 45 104 178 54

1,500m- Rim 54 Badlkot 6 Llwang 6 2,000m SarpanI Okharkot 15

Garpa 27 Jlnabang 75 Budagaun 33

Subtotal 81 129 6

2,000m+ Kankn 23 Taksera 40

Syauh-wang 36

Subtotal

Raptl total 262 173 82 105 Bhen total 52 50 96 54 Total 314 233 178 159

* Denotes VDC located In Bhen

8

1.4 FIELD SURVEY AND QUALITY CONTROL OF DATA

1.4.1 Data Collection Tools

InformatiOn was collected usmg household- and ward-level questtonnaIres Household-level questIOnnaireS were semI-structured and precoded The ward-level questIOnnaireS, especIally those pertammg to natural resource conditIOns, were desIgned to complement household-level mformatIOn and to obtam commumty-level mformation Commumty-level informatIOn, such as prevaIhng pnces, norms for convertmg local measurement umts to standard umts, eXlstmg social orgamzatiOns and user groups, wage rates, forest and soIl erosion patterns, and landshde condItiOns, IS obtained more preCisely and at a lower cost from key mformants than from general households Both sets of questiOnnaires were fmahzed after mcorporatmg changes suggested by the pretest (see below)

1.4.2 Training and Pretesting of Questionnaires

All fIeld staff partICIpated m an mtensIve three-day onentatlOn and traInIng seSSiOn on Income survey methodology The tramIng and onentatiOn were held In APROSC and conducted by APROSC profeSSiOnals

Dunng trammg, questIonnaIres were analyzed and dIscussed thoroughly, and some mock IntervIews were conducted The questiOnnaIreS were then pretested In ShantInagar VDC In Dang and JhImpe VDC m Salyan, where each enumerator mtervIewed four households and each supervisor completed one ward-level questiOnnaire, obtamIng mformatiOn from key Informants The pretest was conducted dunng the fIrst week of December 1995 After pretestmg, the questIonnaIres and procedures were accordmgly and appropnately modIfIed

1.4.3 Selection of Supervisors and Enumerators

The survey team formed two teams of eIght to conduct the mcome and anthropometnc and food consumptIon (nutntiOn) surveys, both of WhICh were performed m the same households at the same time Each team consIsted of two four-member subteams, one for the Income survey and one for the nutntiOn survey Each subteam comprised a superVIsor and three enumerators

All the supervisors for the mcome survey were selected by APROSC The supervisors for the nutntIOn survey were prOVIded by the Valley Research Group, a local consultIng firm speclahzIng In nutrition and health

As the deSIgnated team leaders, the mcome survey supervisors In each team were responsible for the overall quahty and tlmehness of the surveys All the supervisors had a master's degree WIth several years of work expenence Of the enumerators, more than 50 percent were from APROSC and had a graduate degree and work expenence The rest were graduates or master's students recrUIted from outSIde APROSC

9

1.4 FIELD SURVEY AND QUALITY CONTROL OF DATA

1.4.1 Data Collection Tools

InformatlOn was collected usmg household- and ward-level questlOnnaIreS Household-level questlOnnaIreS were semI-structured and precoded The ward-level questlOnnaIreS, especIally those pertammg to natural resource condItions, were desIgned to complement household-level mformatlOn and to obtam commumty-Ievel mformatlon Commumty-Ievel mformatlon, such as prevaIhng pnces, norms for convertmg local measurement umts to standard umts, eXlstmg socIal orgamzatlOns and user groups, wage rates, forest and soll erOSlOn patterns, and landshde condItIons, IS obtamed more precIsely and at a lower cost from key mformants than from general households Both sets of questtonnaues were fmahzed after mcorporatmg changes suggested by the pretest (see below)

1.4.2 Training and Pretesting of Questionnaires

All fIeld staff partIcIpated m an mtenslve three-day onentatlOn and trammg seSSlOn on mcome survey methodology The trammg and onentatlOn were held m APROSC and conducted by APROSC professlOnals

Durmg trammg, questlOnnaIreS were analyzed and dIscussed thoroughly, and some mock mterviews were conducted The questlOnnaIreS were then pretested m Shantmagar VDC m Dang and Jhlmpe VDC m Salyan, where each enumerator mterviewed four households and each supervIsor completed one ward-level questlOnnaIre, obtammg mformatlOn from key mformants The pretest was conducted dunng the first week of December 1995 After pretestmg, the questlOnnaIreS and procedures were accordmgly and appropnately modIfIed

1.4.3 Selection of Supervisors and Enumerators

The survey team formed two teams of eIght to conduct the mcome and anthropometnc and food consumption (nutntIon) surveys, both of whIch were performed m the same households at the same time Each team consIsted of two four-member subteams, one for the mcome survey and one for the nutntlOn survey Each subteam compnsed a supervIsor and three enumerators

All the superVIsors for the mcome survey were selected by APROSC The superVIsors for the nutntIOn survey were provIded by the Valley Research Group, a local consultmg fIrm specIahzmg In

nutntIOn and health

As the deSIgnated team leaders, the mcome survey superVIsors m each team were responsIble for the overall qUalIty and tImelmess of the surveys All the supervIsors had a master's degree WIth several years of work expenence Of the enumerators, more than 50 percent were from APROSC and had a graduate degree and work expenence The rest were graduates or master's students recrUIted from outsIde APROSC

10

1.4.4 Field Survey and Supervision

The dIfferent teams mutually agreed upon the selectIOn of fIeld sItes and the number of questIOnnaireS for each team Each fIeld survey team covered two dIstncts, but the number of questIOnnaIres each team had to complete was determmed by such factors as access to sItes and geographIcal dIsperSIOn of the sample pockets

Two teams completed the aSSIgned task on schedule The other two teams, WhICh had been aSSIgned to cover Rulrnm and Rolpa, were unable to complete all interviews because of pohtical problems m these two distncts The number of mterviews that were not completed m Kankn m Rukum was small, and thus was deemed to not affect the study The mterviews planned for Jmabang m Rolpa, however, could not be dropped WIthout senous reperCUSSIOns to the overall results of the study Consequently, another team led by a semor agncultunst of APROSC was formed and sent to Jmabang m the fIrSt half of Apnl, after pohtIcal tenSIOn had subSIded The team completed 75 mterviews and returned to Kathmandu m 15 days

WhIle the teams were m the fIeld, the project coordmator and the nutntIOn consultant conducted fIeld supervISIOns three tImes at dIfferent pen ods The first supervlSlon was carned out Immediately after the departure of the teams for the fIeld, to check for and ensure conSIstency m team approach The most frequent problems centered around mIsmterpretatIOn of questIOns and confUSIOn among enumerators as a result of typographIcal errors m the questIOnnaireS These problems were dealt with by the supervlSlon team, whIch, as noted earlIer, conSIsted of members from APROSC and the Valley Research Group, representatIves from USAID's VItamm A offIce and Development AlternatIves, Inc (DAI) partICIpated at the begmnmg and end of the survey

1.4.5 Data Processing and Editing

Data edItmg was carned out at several stages of the study At the end of each day, the enumerators edIted the completed questIOnnaireS The completed questIOnnaireS were then exchanged between the enumerators to cross-check and double-check for mconsistencles and errors After thIS peer reVIew, the questIOnnaireS were further reVIewed and edIted by the superVIsors before bemg accepted The supervlSlon team then took the questIOnnaireS to the home offIce

At the home office, the questIOnnaireS were numbered sen ally and entered mto a database usmg dBASE I, a software for computenzed data management

The proJect's data entry speclahsts encountered several problems m data codmg and wntmg, despIte the field edItmg and reVIew by the enumerators and superVIsors These and other data entry problems were reCtIfIed by the responSIble enumerators, superVisors, and data enterers

1.5 METHODS OF ANALYSIS

The sample data were analyzed by means of cross-tabulatIOn, calculatIOn of averages, and multIple regreSSIOn analYSIS to examme relatIOnshIps among Important vanables Income-consumptIOn elastiCItIes were estImated for vegetables, food grams, fruit, and hvestock products

P .., '''l -r'" , r", L I L r .... , ..,... - r"', ... 1 ...

I·_,·J I..... i::'> I r-.:"", _L 1../ I J t S

LEGEtli)

Ai t I t.ude

I , Below 1020 Met.ers _ J

'M Road

EB Cl..,r r en t.. Sam~ I Q " i)Cs

* ~~S Sample . ~CS

GIS, APROSC

I-' I-'

13

CHAPTER TWO

GENERAL CHARACTERISTICS OF SAMPLE HOUSEHOLDS

ThIS chapter presents the general charactenstics of households m the sample selected from the interventIOn (RaptI) and nomnterventIOn (Bhen) areas The fIrst sectIOn of this chapter dIscusses demographic charactenstIcs of the sample at both the household and mdlVlduallevels The second sectIon deals wIth access to, and tIme reqUIred for acqumng, such baSIC household necessIties as dnnkmg water, fuel wood, and fodder The thIrd sectIOn provIdes mformatIOn on local mstItutIOns such as SOCial clubs, user's commIttees, mcommg-generatmg groups, and the lIke For companson purposes, all data are grouped by mterventIOn and nonmterventIOn areas

2.1 DEMOGRAPHIC CHARACTERISTICS

ThIS sectIon presents a general overvIew of the study sample at both the household and mdIVIdual levels and IS categonzed by elevatIOn and walkmg distance to the nearest road head DescnptIve statIstICS such as age, sex, dependency ratIOS, seasonal mIgratIOn, and hteracy status are also exammed and presented m the same categones

2.1.1 Sample Households, Populations, and Household Sizes

A household IS defmed m thIS study as a group of persons hvmg together and sharmg meals from the same kitchen m a home Thus, a household mcludes famIly members, permanent servants, relatives, and even guests hvmg together and eatmg from the same kitchen for at least SIX months pnor to the survey The total members m a household make up the household SIze

Tables 2 1 and 2 2 present dIstnbutIOns of sample households, populatIOns, and household SIzes categonzed by elevatIOn and walking dIstance to the nearest road head, respectIvely The 623 households mterviewed m RaptI contamed 5,102 mdIvlduals, whIle the 261 households mterviewed m Bhen contamed 1,781 mdIvlduals The average household SIze m RaptI was 8 2 and m Bhen, 6 9

14

TABLE 21 DISTRIBUTION OF SAMPLE HOUSEHOLDS, POPULATIONS, AND HOUSEHOLD SIZES,

BY ALTITUDE

Raptl Bhen

Household Household Altitude Household Population Size Household Population Size

< 1,000 m 135 1,608 11.9 210 1,429 68

1,000-1,500 m 183 1,273 70 51 352 70

1,500-2,000 m 216 1,533 71

2,000+m 89 688 77

Total 623 5,102 82 261 1,781 69

When companng household size based on elevatIOn, the study team found that the largest (11 9 persons per household) in the RaptI zone occurred at less than 1,000 meters, followed by those households m locatIOns above 2,000 meters (7 7 persons, see Table 2 1) The sIze of households m locatIOns m the 1,000-to-1,500-meter and 1,500-to-2,000-meter altItudes was comparable, at 7 a persons and 7 1 persons, respectIvely In Bhen, by contrast, household sIze was smaller (6 8 persons) at altItudes below 1,000 meters. Household sIze for the 1,000-to-l,500-meter elevatIOn was the same as that m RapU

The large household sIze at the less-than-l,OOO-meter elevatIOn m Raptl IS explamed by the dommance at that altitude of the Tharu ethmc commumty, whIch IS known to lIve m large extended famIlIes

When analyzmg the varIatIOn m household size by distance to the nearest road head, RaptI households closer to the road (walkmg dIstance of less than one-half day) were found to be larger (9 6 persons) than those one-half to two days away (70 and 6 8 persons, see Table 22) However, Raptl locatIOns requmng more than two days of walkmg also had relatIvely large households (7 8 persons) In Bhen, the variatIOn m household size by walkmg distance was margmal

It should be noted that the observed simllanty m dlstnbutlOn of household sIze by altItude and by road head distance for both RaptI and Bhen may have resulted from the two categones bemg pOSItIvely correlated WIth each other

15

TABLE 22 DISTRIBUTION OF SAMPLE HOUSEHOLDS, POPULATIONS, AND HOUSEHOLD SIZES,

BY WALKING DISTANCE TO NEAREST ROAD HEAD

Rapt. Bhen

Walkmg Household Household Distance Household Population Size Household Population Size

<%day 261 2,517 96 51 352 69

% -1 day 185 1,290 70 51 349 68

1-2 days 82 558 68 102 687 67

2 + days 95 737 78 57 393 69

Total 623 5,102 82 261 1,781 69

2.1.2 Age Distribution and Dependency Ratio

ThIS sample IS dIvIded Into three broad age groups (under 10, 10 to 59, and 60 and above) and by sex for both Raptl and Bhen Those m the 1O-to-59 age group are consIdered economIcally active m Nepal, conventIOnally, a workmg-age group IS defmed as bemg made up of people between the ages of 15 and 64. The ratIO of populatIOn below 10 years old to the population age 10 to 59 IS called the child dependency ratIO, and the ratIO of those above 59 to those m the economIcally active group (l0 to 59 years) IS called the aged dependency ratIO The total dependency ratIO, the ratIO of the nonworking to working-age population, IS the sum of the aged and chIld dependency ratios The percentage dIstnbutlOn of the study sample m these broad age groups and the dependency ratios are presented m Table 2 3

TABLE 2 3 PERCENTAGE DISTRIBUTION OF SAMPLE POPULATIONS, BY BROAD AGE GROUP,

GENDER, AND DEPENDENCY RATIO

Age Group Child Aged Total 60 and Dependency Dependency Dependency

Location Gender 0-9 10-59 above RatiO RatiO Ratio

Raptl Male 180 302 23 596 76 672

Female 165 309 2 1 534 68 602

Total 345 61 1 44 565 7.2 64.2

Shen Male 182 315 1 6 578 51 629

Female 172 295 20 583 68 651

Total 354 610 3.5 580 60 664

As seen m Table 2 3, the total dependency ratIO In RaptI IS 64 2, whIch IS only slIghtly lower than the 66 4 found In Bhen The total dependency ratio for males m RaptI (67 2) IS hIgher than In Bhen (62 9), but the reverse IS true for females females In Bhen appear to be carrymg a heavIer dependency burden

16

(65 1) than theIr counterparts m Rapt! (60 2) Overall, Bhen's hIgher dependency burden can be explamed by the presence of more chIldren m the Bhen sample than m the Raptl sample

2.1.3 Household Head by Gender and Marital Status

Household head IS defined in thiS study as the ultimate decision maker regarding economic activities such as crop production, acreage allocation (to crops), marketmg, pncing, and product sellIng Household heads, therefore, may not be the most semor people m the famIly, where semonty IS based on relationshIp or age

Of the 623 households mterviewed m RaptI, approxImately 5 percent of the household heads (33) were female and 95 percent (590) were male (see Table 2 4) SImIlarly, m Bhen, 65 percent (17) of the household heads were female, whIle approXImately 93 5 percent (244) were male Many of these female household heads were WIdows

TABLE 24 PERCENTAGE DISTRIBUTION OF HOUSEHOLD HEADS, BY GENDER AND MARITAL STATUS

Mantal Status

Divorced or Married Widow or Widower Separated Total

Location Gender No. % No % No. %

Raptl Male 567 961 22 37 1 02 590 Female 10 303 21 636 2 61 33 Total 577 926 43 69 3 05 623

Bheri Male 238 975 5 1 5 1 03 244 Female 17 100 17 Total 238 912 22 84 1 0.4 261

Of the male household heads, approXImately 96 percent (567) of those hvmg m RaptI were mamed, whlle of those in Bhen, approXImately 97 5 percent (238) were mamed There were very few household heads, m eIther Raptl or Bhen, who were eIther dIvorced or separated (0 5 percent and 04 percent, respectIvely)

2.1.4 Seasonal Migration

Seasonal mIgratIOn m thIS study refers to mIgratIOn by a household member, regardless of the purpose, for more than one month at a tIme durmg the reference penod If the same member left home more than once, only the longest penod away from home was recorded

Seasonal mIgratIOn appears to be almost double m Bhen (9 2 percent) as m Rapu (5 5 percent) As shown m Tables 2 5 through 2 8, for Bhen, the out-mIgratIOn occurs mostly In the plaInS and lower hIlls (11 6 percent) and from those locatIons withm less than two days walkIng dIstance from a road Table 2 8 mdicates that the mIgrants are pnmanly headIng south to more urban term towns, and over the

17

border to India, seekmg constructIon and other serVIce-type (mIhtary and clVll) Jobs As m RaptI, Bhen mIgrants are overwhelmmgly male

MigratlOn m RaptI was found to be dnven by SImIlar reasons and SImIlar destmatlOns as m Bhen (see Tables 2 7 and 2 8), although m RaptI, out-migratlOn was observed to be more rampant from the mId and hIgh hIlls than from the lower hIlls and plams (Table 2 5) In other words, migratlOn IS seen to mcrease WIth mcrease m altitude up to 2,000 meters, above 2,000 meters, It decreases

In RaptI, about half as many household members (5 5 percent) as m Bhen (9 2 percent) were observed migratmg ThIS IS thought to be attrIbutable to the hIgher partIcipatlOn of household members m the mtensive agrIcultural productlOn practIces that are prevalent m RaptI

TABLE 25 NUMBER AND PERCENTAGE DISTRIBUTION OF MIGRANTS, BY ALTITUDE

Rapti Bhen Altitude Migrants, Migrants,

Population Migrants Percentage Population Migrants Percentage

<1,000 m 1,608 41 25 352 41 11 6 1,000-1,500 m 1,273 78 60 1,429 123 86 1,500-2,000 m 1,533 123 80 2,000+m 688 37 54

Total 5,102 279 55 1,781 164 92

TABLE 2 6 NUMBER AND PERCENTAGE DISTRIBUTION OF MIGRANTS, BY WALKING DISTANCE

TO NEAREST ROAD HEAD

Raptl Bhen

Walking Migrants, Migrants, Distance Population Migrants Percentage Population Migrants Percentage

<% day 2,517 113 45 352 41 114 % - 1 day 1,290 96 74 349 28 80 1-2 days 558 32 57 687 88 128 2 + days 737 38 5 1 393 7 1 8

Total 5,102 279 55 1,781 164 92

Reason for Migration

When out-mIgratIOn IS analyzed based on gender and reasons for migratIOn, the analYSIS shows that a hIgher percentage of males than females mIgrate out of both Raptl and Bhen As shown m Table 27, males tend to mIgrate for Jobs, whIle females mIgrate to VISIt and be WIth relatives Jobs pulhng seasonal mIgrants are mamly m constructIOn, CIvIl and mlhtary servIce, portenng, and marketmg Women are mostly attracted by constructlOn Jobs above others

18

TABLE 2 7 PERCENTAGE DISTRIBUTION OF SEASONALLY MIGRATORY HOUSEHOLD MEMBERS,

BY PURPOSE AND GENDER

Raptl Sheri

Purpose Male Female Total Male Female Total

Construction labor 31 0.2 1 7 41 o 1 21 Agnculturallabor 0.3 - 01 09 04 Portenng 1 3 - 07 -Service (CIVil, military) 1 9 - 1 0 48 o 1 24 Marketmq 08 02 05 o 1 02 02 To meet relatives 04 08 05 07 1 3 1 0 Other 1 5 04 09 34 1 1 22 Total 94 1 6 55 140 28 92

Destination of Migrants

Table 2 8 shows that an overwhelmIng proportIon of seasonal mIgrants head to IndIa and other countnes, wIth a sIzable number mOVIng to the more urban areas of the term as well More males than females cross the border Table 2 8 also IndIcates that females In both Rapt! and Bhen prefer Internal mIgratIOn, and thus seek other, more urban areas In the country

TABLE 2 8 PERCENTAGE DISTRIBUTION OF SEASONALLY MIGRATORY HOUSEHOLD MEMBERS,

BY DESTINATION AND GENDER

Raptl Shen

Destination Male Female Total Male Female Total

Dlstnct headquarters 14 05 1.0 0.6 04 05 Urban area of teral 24 05 1.4 4.0 1 1 2.7 Rural area 1.3 0.3 0.8 2.3 1 1 19 India and other countnes 4.3 0.3 23 7.7 02 41 Total 9.4 16 5.5 145 2.8 92

2.1.5 Household and Landholding Size

The sample households were dIVIded Into four groups based on the SIze of landholdIng and as prescnbed by the National Planmng CommIssIOn margInal, small, medIUm, and large These groups of farmers are also categonzed by elevatIOn and dIstance (see Tables 2 9 and 2 10)

A companson between Raptl and Bhen farmers IndIcates that margInal farm households represent a mInonty (approxImately 8 8 percent), over half of the farm households have landholdIngs larger than 0 5 hectares As shown In Table 2 9, Rapt! farmers are larger landholders than Bhen farmers In Bhen, small farm households form a majorIty (38 6 percent), while In Rapt!, 43 percent own land larger than a hectare

19

each More than 60 percent of the larger farmers m Rapt! are located at an elevatIOn lower than 1,000 meters

The hIgh dIstnbutIOn of medIUm and large landholdmgs among the sample IS not consIstent WIth the dIstnbutIOn of households wIth sImIlar landholdmgs reported m earher basehne surveys conducted by APROSC (APROSC 1980 and 1990) ThIS mdicates the hkehhood that the sample selected from the mterventton area pockets m Rapt! may be bIased toward large farms

TABLE 2 9 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS, BY FARM SIZE AND ALTITUDE

Raptl Sherr

1,000- 1,500- 1,000-1,500 2,000 2,000 <1,000 1,500

Farmer <1,000 m, m, m, % m+,% m, % m, % Category Land SIze %ofHH %HH HH HH Total HH HH Total

Marginal <02 ha 96 56 80 153 87 43 99 88

Small 02-05 ha 11 9 298 133 412 21 8 553 346 386

MedIum 051-1 ha 178 366 240 242 265 191 283 265

Large 1 ha + 607 280 547 188 430 21 3 272 261

Total 100 100 100 100 100 100 100 100

A vast maJonty of the large farms m the Raptl sample area were located withm a day's walk from the road, whereas m Bhen, the large farms were farther away from the road The Bhen sample mdicates that almost half of all the small farms were located withm a day's walk from the nearest road head, whIle m Rapt!, the reverse was true (see Table 2 10)

It should be noted that gIVen the dIfferent sample selectIOn methods applIed m Rapt! (non-random) and Bhen (random), the companson between the two sets of household dIstnbutIOn data may be meanmgful only at the sample level ThIS mformatIOn can be useful m mterpretmg results m the regreSSIOn analYSIS sectIOns presented later m thIS report

TABLE 210 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS, BY FARM SIZE AND WALKING DISTANCE

TO NEAREST ROAD HEAD

RaptJ Bherl

Land Size %-1 1-2 2 Days <% %-1 1-2 2

Category Class <% Day Day Days + Day Day Days Days+

Marginal <02 ha 104 39 74 144 43 183 92 52

Small 02-05 ha 18 1 150 284 384 552 449 330 280

Medium 051-1 ha 238 238 407 245 19 1 245 258 353

Larqe 1 ha + 477 477 235 222 21 3 123 320 31 5

Total 100 100 100 100 100 100 100 100

20

2.1.6 Literacy Rate

The hteracy rate IS defmed m thIS study as the ratIO of the number of hterate people SIX years of age or older to the total populatlOn SIX years of age or older Those mdlVlduals who were able to read and wnte m theIr mother tongue dunng the household survey were consIdered hterate

The survey teams collected information on literacy status by asking respondents whether each household member SIX years or older could read and wnte and, If so, where they had learned to do so Those household members who had reportedly passed the third grade were automatically considered hterate.

The estImated hteracy rate IS presented m Tables 2 11 and 2 12 for both Rapt! and B hen by gender, altitude, and dIstance to the nearest road

TABLE 211 LITERACY RATE, BY GENDER AND ALTITUDE

Altitude Location Gender <1,000 m 1,000-1,500 m 1,500-2,000 m 2,000 m+ Total

Raptl Male 728 756 802 683 752

Female 490 464 456 243 441

Total 61.1 605 62.9 453 594

Bhen Male 878 739 765

Female 669 339 405

Total 76.8 53.6 58.1

The lIteracy rate for the sample populatIOn m Rapt! (59 4 percent) does not dIffer that much from the rate m Bhen (58 1 percent) Both samples dIsplay SImIlar patterns m terms of gender In both Raptl and Bhen, the hteracy rate among males IS almost double that among females Compared WIth the 1991 census, these rates show that the hteracy rates for both zones have almost doubled

When analyzmg hteracy rate by altitude and dIstance, one can see from Tables 2 11 and 2 12 that the rate generally decreases WIth an mcrease m altitude and dIstance from the road

TABLE 212 LITERACY RATE, BY GENDER AND WALKING DISTANCE TO NEAREST ROAD HEAD

Location Gender d2Day 1/2-1 Day 1-2 Days 2 Days + Total

Rapti Male 71 83 8412 77 94 6899 752

Female 4619 5010 4778 2375 441

Total 59.07 66.66 54.46 4537 594

Bhen Male 8782 792 4978 6690 765

Female 6692 2301 355 5175 405

Total 7685 5099 55 53.71 581

21

2.2 ACCESS TO AND TIME REQUIRED TO COLLECT BASIC HOUSEHOLD NECESSITIES

2.2.1 Drinking Water

Few households In the sample wards are reported to have potable water pIped to theIr homes or backyards In most cases, the sources of dnnkmg water are pubhc taps, spnngs, tube wells, artesIan wells, and streams, as reported dunng the survey teams' rapId rural appraIsal (RRA) Not surpnsmgly, women do a large percentage of the hauhng and fetchmg (67 to 69 percent), even though men (16 to 17 percent) and chIldren (15 to 16 percent) also are mvolved In these actIvIties (see Table 2 13)

The dIstnbutlOn of mvolvement by gender m Bhen IS SImilar to that m Rapti The average time taken to fetch water for household use, however, IS approxImately 17 mmutes per tnp m Rapti but 31 mmutes per tnp m Bhen The length of fetchmg time mdicates that, on average, RaptI resIdents have eaSIer access to potable water than do those hvmg m Bhen

Tables 2 13 and 2 14 further mdicate that as elevatlOn and dIstance from road heads mcrease, so does the mvolvement of women and chIldren m fetchmg water ThIS IS eVIdent mostly In Bhen and up to a certam pomt In Rapti The pOSItive correlatlOn between the mvolvement of, especIally, chIldren and dIstance from the road IS thought to be attnbutable to the low school enrollment of children m remote areas, resultmg m theIr greater rate of participatlOn In household activItIes

TABLE 213 AVERAGE TIME SPENT AND INVOLVEMENT IN FETCHING DRINKING WATER,

BY GENDER AND ALTITUDE

Raptl Sheri

Average Average Fetching Percentage Involvement Fetching Percentage Involvement

Time Time (Minutes (Minutes

Altitude per Trip) Males Females Children per Trip) Males Females Children

< 1,000 m 9 17 69 14 23 18 73 9 1,000-1,500 18 17 65 18 33 15 67 18 m 1,500-2,000m 30 15 72 11 - - - ->2,000m 17 19 61 20 - - - -Average 17 17 67 16 31 16 69 15

Distance to

Road Head

<%day %-1 day

1-2 days >2 days

Average

22

TABLE 214 AVERAGE TIME SPENT AND INVOLVEMENT IN FETCHING WATER,BY GENDER

AND WALKING DISTANCE TO NEAREST ROAD HEAD

Rapti Shen

Average Involvement Average Involvement Fetchmg (Percentage) Fetchmg (Percentage)

Time Time (Minutes (Minutes per Trip) Males Females Children per Tnp) Males Females

15 14 72 14 23 18 73

27 16 72 12 60 25 60

5 13 63 24 33 17 64 19 22 60 18 2 5 75

17 17 67 16 31 16 69

2.2.2 Fuel Wood and Fodder

Children

9

15 19 20

15

A maJonty of the households ill the sampled wards reported that fuel wood and fodder are normally collected from both pnvate farms and commumty- and government-owned forests In practice, however, respondents tend to use government forests more than commumty or pnvate forests

Table 2 15 presents data on the tIme taken, per tnp, to collect fuel wood and fodder ThiS mformatlOn IS dlsaggregated by gender, elevatIOn, and distance from the nearest road head for both Raptl and Bhen The illvolvement of children m both activItIes IS also noted for all categones

Households ill both Raptl and Bhen spend, on average, at least four hours per tnp fetchmg fuel wood and fodder As Table 2 15 mdIcates, women are agam the major contnbutors to these actIVIties, regardless of the remoteness of where they lIve Women provIde approximately 59 percent of the labor for fuel wood collectIon and 58 percent for fetchmg fodder m Raptl, m Bhen, women perform 63 percent of the fuel wood collectIOn and 51 percent of the fodder collectIOn

It IS also mterestmg to note that the mvolvement of children ill fuel wood and fodder collectIOn generally mcreases with an mcrease m remoteness For example, chtldren m Rapt! contnbute as much as 22 percent of the labor m collectmg fuel wood and 17 percent of the labor m collectmg fodder at altitudes greater than 2,000 meters

23

TABLE 215 AVERAGE TIME SPENT AND INVOLVEMENT IN FETCHING FUEL WOOD AND FODDER,

BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Distance to Road Head

<1,000 1,000- 1,500- >2,000 <% % -1 1-2 >2 Zones m 1,500m 2,000m m Average Day Day Days Days Average

R@.tl

Fuel Wood

Fetching time 4 5 3 6 5 4 4 6 6 5 (hours)

Percentage Involvement • Males 23 34 31 23 27 21 39 51 23 27 • Females 65 53 59 55 59 67 54 33 55 59 • Children 12 13 10 22 14 12 7 16 22 14

Fodder

Fetching time 3 4 4 5 4 3 4 5 5 4 (hours)

Percentage Involvement • Males 28 25 39 25 29 25 41 23 25 29 • Females 60 63 50 58 58 60 52 65 58 58 • Children 12 13 11 17 13 15 7 12 17 13

Sheri

Fuel Wood Fetching time 3 5 - - 4 3 2 6 6 4 (hours) Percentage Involvement • Males 13 33 - - 26 13 22 32 45 26 • Females 82 53 - - 63 82 75 49 35 63 • Children 5 14 - - 11 5 3 19 20 11

Fodder Fetching time 5 6 - - 6 5 3 6 6 6 (hours)

Percentage Involvement • Males 38 37 - - 37 38 55 25 25 37 • Females 55 50 - - 51 55 42 55 55 51 • Children 7 13 - - 12 7 3 20 20 12

24

2.2.3 Access to Telephones and Roads

Table 2 16 shows the average distance from the sample wards to telephone booths and road heads When thiS mformatlOn IS classified by altitude and distance, access to telephone booths, on average, IS greater than to road heads

TABLE 216 AVERAGE DISTANCE TO TELEPHONE BOOTHS AND ROAD HEADS, BY ALTITUDE

AND WALKING DISTANCE

Rapt. Sheri Distance Raptl Shen to

Road Altitude Head

Accessibility to Accessibility to Accessibility to Accessibility to

Telephone Road Telephone Road Telephone Road Telephone Road Head Booth Head Booth Head Booth Head Booth (km) (km) (km) (km) (km) (km) (km) (km)

<1,000m 4 2 a 3 <Y2 day 5 3 a 3

1,000- a 40 15 39 % -1 day 6 13 12 14 1,500m

1,500- 7 13 - - 1-2 days 12 79 13 25 2,000m

>2,000m 61 150 - - >2 days 57 145 14 90

Average 19 48 12 31 Average 19 48 12 31

2.3 LOCAL INSTITUTIONS

Local 1OstitutlOns could playa crucIal role 10 the economic and social development of Raptl and Bhen by Involv1Og local people In the process DurIng the survey, the teams measured local InStitutIOnal capacity by the number of orgamzatlOns 1Ovolved In social and economic activIties and by the representatIOn of both sexes as executives members In the orgamzatlOns This assessment revealed that participatIOn of women IS very hmlted, and that 1OstltutlOnal capacity IS relatively better In lower, more accessIble elevatlOns than In remote areas Even though thiS IS eVident In both Raptl and Bhen, InstitutIOnal capacIty In Raptl IS better than In Bhen

2.3.1 Social Clubs

Of the wards sampled (50 In Raptl and 11 In Bhen), 27 percent In Raptl and 18 percent In Bhen reported having social clubs Social clubs maInly Include youths' clubs, mothers' and children's clubs, and disabled persons' clubs Unhke In Raptt, Bhen's social clubs are mostly mothers' or chIldren's clubs Given the nature of the clubs, their members are mostly female

Raptl has a diversIty of socIal clubs, with an average of seven men and two women per ward as executive club members Detmls by altitude and distance are presented In Table 2 17

25

TABLE 217 PERCENTAGE OF WARDS WITH SOCIAL CLUBS AND PARTICIPATION OF EXECUTIVE MEMBERS,

BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Raptl Bhen Distance Rapt! Bhen

%01 Average %of Average to %of Average %01 Average Wards No 01 Wards No of Road Wards No of Wards No of Having Executive Having Execulive Head Having Execulive Having Executive Clubs Members Clubs Members Clubs Members Clubs Members

Der Ward DerWard DerWard per Ward

M F M F M F M F

<1,000m 64 18 1 66 1 3 <Y2 day 38 7 1 66 1 3

1,000- 18 6 1 0 0 0 Y2 -1 day 0 0 0 0 0 0 1,500m

1,500- 0 0 0 - - - 1-2 days 25 11 0 0 0 0 2,000m

>2,000m 27 6 4 - - - >2 days 25 6 4 0 0 0

Average 27 7 2 18 1 3 Average 27 7 2 18 1 3

2.3.2 Users' Committees

Users' commIttees m the sample wards are mostly formed around subjects such as forests, drmkmg water, lITIgatIOn, roadsltraIls, and the lIke Of the sampled wards, 92 percent m Raptl and 82 percent m Bhen report havmg such commIttees (see Table 2 18) The average number of executive club members per ward m both Raptl and Bhen IS approxImately 16, of whIch 13 are men and 3 women Table 2 18 also details commIttee prevalence by elevatIOn and dIstance to the nearest road head

TABLE 218 PERCENTAGE OF WARDS WITH USERS' COMMITTEES AND PARTICIPATION OF EXECUTIVE

MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Rapti Bheri Distance Rapti Bheri %01 Average %of Average to %or Average %01 Average

Wards No of Wards No of Road Wards No 01 Wards No of HaVing a Executive HaVing a Executive Head HaVing a Executive HaVing a Executive

Committee Members Committee Members Committee Members Committee Members DerWard per Ward per Ward per Ward

M F M F M F M F

<1,000m 100 13 7 33 9 3 <Y2 day 96 15 5 33 9 3 1,000- 100 17 3 100 13 5 Y2 -1 day 85 12 3 50 9 1 1,500m 1,500- 91 12 1 - - - 1-2 days 100 22 1 100 16 9

2,000m

>2,000m 73 8 0 - - - >2 days 75 8 0 100 13 3

Average 92 13 3 82 13 3 Average 92 13 3 82 13 3

26

2.3.3 Construction Committees

ConstructIOn committees 10 Raptt and Bhen mamly focus on Issues related to dnnk10g water, ImgatIOn, roads/trails, school bUIld1Ogs, and godown construction projects Of the total sampled wards, 24 percent 10 Raptl and 18 percent 10 Bhen reported hav10g orgamzed a constructIOn committee (see Table 2 19) The average number of executive commIttee members per ward 10 Rapt! IS approximately 13, of

WhICh 12 are men and 1 a woman. For Bhen, the average number is 2 men and women each Table 219 also detaIls commIttee prevalence by elevatiOn and walk10g dIstance to the nearest road head.

TABLE 219 PERCENTAGE OF WARDS WITH CONSTRUCTION COMMITTEES AND PARTICIPATIO OF

EXCUTIVE MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Rapti Bheri Distance Rapti Bheri

%of Average %of Average to %or Average %of Average Wards No of Wards No. of Road Wards No of Wards No of

Having a Executive HaVing a Executive Head HaVing a Executive Havmga Executive Committee Members Committee Members Committee Members Committee Members

per Ward per Ward per Ward per Ward

M F M F M F M

<1,OOOm 31 9 0 0 0 0 <% day 25 11 0 0 0

1,000- 45 13 1 25 2 2 % -1 day 20 12 0 0 0 1,500m

1,500- 18 14 1 - - - 1-2 days 75 12 1 50 2 2,OOOm

>2,000m 0 0 0 - - - >2 days 8 15 1 0 0

Average 24 12 1 18 2 2 Average 24 12 1 18 2

2.3.4 Income-Generating Groups

The 1Ocome-generat1Og groups formed 10 the sample wards of RaptI and Bhen are mamly orgamzed around the products their members produce, such as vegetables, fruItS, and cash crops, serVIces they need, such as sav10gs and credit, and market10g Of the total sampled wards, all those 10 Raptt and 55 percent 10 Bhen reported hav10g orgamzed such groups (see Table 2 20) The average number of members per ward in Raptl IS approxImately 19, of which 14 are male and 5 female For Bhen, the average number IS 8, of which 5 are male and 3 female Table 2 20 also details the prevalence of 1Ocome­generat10g groups by elevatIOn and walk10g distance to the nearest road head

F

0 0

2

0

2

27

TABLE 2 20 PERCENTAGE OF WARDS WITH INCOME-GENERATING GROUPS AND PARTICIPATION OF

MEMBERS, BY GENDER, ALTITUDE, AND WALKING DISTANCE TO ROAD HEAD

Altitude Raptl Bhen Distance Raptl Bhen

%of Average %of Average to %of Average %of Average

Road Wards No of Wards No of

Head Wards No of Wards No of

Having Members Having Members Having Members Having Members Income per Ward Income per Ward Income per Ward Income per Ward

Generating M F Generating M F Generating M F Generating M Groups Groups Groups Groups

<1,000m 100 15 6 33 7 4 <Y2 day 46 15 4 33 7

1,000- 100 9 5 62 4 1 Y2 -1 day 40 23 8 50 4 1,500m

1,500- 100 23 6 - - - 1-2 days 75 9 5 25 1 2,000m

>2,000m 100 9 2 - - - >2 days 83 11 2 100 5

Avera!le 100 14 5 55 5 3 Average 100 14 5 55 5

2.3.5 Other Institutions

Other mstItutlOns are defmed as those mstItutIons provIdmg serVIces to ward reSIdents, such as schools (pnmary, lower secondary, and secondary), agncultural extensIOn offIces (agncultural serVIce centers, vetennary centers, and cooperatIves), health posts, range posts, and post offIces (Also mcluded m thIS category are government-owned telephone booths) Of the total sampled wards, 86 percent In RaptI and 64 percent In Bhen reported havIng at least one of these InstitutIOns (see Table 2 21) For both RaptI and Bhen, an average of two such mstItutlOns per ward are avaIlable to the reSIdents In or wIthm the VICInIty of the sampled wards Table 2 21 also detaIls the prevalence of other InstitutIOns by elevatIon and walkmg dIstance to the nearest road head

TABLE 2 21 PERCENTAGE OF WARDS WITH OTHER INSTITUTIONS AND NUMBER OF INSTITUTIONS,

BY ALTITUDE AND WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Raptl Bhen Raptl Shen Distance

F

4

0

3

4

3

%ofWards No of %ofWards No of to Road %ofWards No of %ofWards No of Having an Institutions Having an Institutions Head Having an Institutions Having an Institutions Institution per Ward Institution per Ward Institution per Ward Institution per Ward

(Except Ward (Except Ward {Except Ward {Except Ward Office} Office} Office} Office)

<1,000m 87 3 50 2 <Y2 day 83 3 50 2 1,000- 100 2 75 2 Y2 -1 day 90 2 100 1 1,500m 1,500- 82 2 - - 1-2 days 100 2 50 2 2,000m

>2,000m 64 2 - - >2 days 75 2 100 3

Average 86 2 64 2 Average 86 2 64 2

29

CHAPTER THREE

NA TURAL RESOURCES

The rich natural resources of Nepal continue to be preserved in the Rapt! and Bhen zones ThIS is partIcularly true m the eIght dlstncts surveyed for thIS study The fIve dlstncts m Raptl and the three distncts m Bhen together cover an area of 17,760 square kIlometers, WIth vanous clImatIc zones, bIOdiverSItIes, and natural beauty (NatIOnal Research Associates, 1994) Furthermore, these eIght dlstncts are endowed WIth several major nvers, provldmg the mhabltants WIth a perenmal source of water

ThIS chapter presents an analYSIS of the state of the natural resources m the sample areas DISCUSSIOns cover forestland, rangeland, and those resources m cntIcal condItion m the country Informatton dealmg WIth access to, and mvolvement of household members m the collectIOn of, dnnkmg water, fodder, and fuel wood IS also presented and analyzed m relatIOn to both project (RaptI) and control (Bhen) areas These data are orgamzed by altitude and by walkmg dIstance to the nearest road head

3.1 PUBLIC FORESTLAND AND RANGELAND

Based on the mformatIon collected through local mstitutIOns and from an RRA conducted WIth key mformants, the sample wards are estimated to cover an average area of approxImately 300 hectares m Rapt! and 350 hectares m Bhen In Raptt, about 24 percent of thIS area IS covered by forests and 6 percent by rangeland In Bhen, forest cover makes up about 18 percent of the land area, whIle rangeland covers 4 percent Tables 3 1 and 32 present the estimated average area covered With forests (government and commumty) and rangeland m the two zones by altitude and walkmg distance from the nearest road head The tables also present data on the condItion of thIS land

30

TABLE 31 AVERAGE AREA COVERAGE AND CONDITION OF FORESTS/RANGELAND, BY ALTITUDE

Rapt. Sheri

ForesV <1,000 1,000· 1,500· >2,000 Average <1,000 1,000· Average Rangeland m 1,500 2,000 m m 1,500

m m m

Government Forests Area (ha) 8 24 39 61 30 76 42 51 Condition (% of area)

-Good 0 57 0 45 30 0 55 33 - Moderate 81 38 100 31 57 100 45 67 - Poor 19 5 0 24 13 0 0 0

Community Forests

Area (ha) 59 46 26 9 39 3 10 8 Condition (% of area)

- Good 52 48 18 35 44 0 100 89 - Moderate 48 52 82 65 56 100 0 11 - Poor 0 0 0 0 0 0 0 0

Rangeland Area (ha) 4 7 5 61 18 0 14 11 Condition (% of area)

- Good 10 0 0 15 11 0 0 0 - Moderate 89 47 0 55 54 0 100 100 - Poor 1 53 100 30 35 0 0 0

As shown m Table 3 1, Raptl wards, on average, have almost half (30 hectares) as much government-controlled or -owned forests as Bhen wards (51 hectares) Raptl, however, has more commumty-managed and commumty-owned forests In fact, Rapu has almost five times as much commumty-managed forestland as Bhen (39 versus 8 hectares), mdlcatmg RaptI's greater degree of commumty involvement m forest management

Thus far, commumty forests appear to be managed relatively well m RaptI A vallable data indicate that of the total area under commumty management m the zone, 44 percent IS m good condition (contmually regeneratmg) and 56 percent IS m moderate conditIOn (not detenoratmg)

In Bhen, which has a higher proportIOn of government-owned forests than RaptI, commumty­managed forests are few but appear to be fairly well managed A sIgmfIcant percentage (89 percent) are m good conditIOn and are regeneratmg, whIle 11 percent are m moderate condItIOn

31

It IS Important to note that commumty Involvement In the management of Raptt's forests IS more prevalent In accessIble than In remote areas, as IS eVIdent from the negatIve correlatIOn with both altitude and dIstance from roads In contrast, government forests In Raptl Increase In acreage wIth an increase In altitude and, In general, dIstance from roads

The dIstnbutIOn of rangeland In the sampled wards shows neIther a strong correlatIOn wIth altitude nor dIstance The estImated amount ofrangeland In RaptI (18 hectares) IS hIgher than In Bhen (10 hectares), but the condItIOn of RaptI's rangeland IS worse than Bhen's

TABLE 32 AVERAGE AREA COVERAGE AND CONDITION OF FORESTS/RANGELAND,

BY WALKING DISTANCE FROM NEAREST ROAD HEAD

Raptl Bhen

Forest! <1f2 1f2 -1 1-2 >2 Average <1f2 1f2 -1 1-2 >2 Rangeland Day Day Days Days Day Day Days Days

Government Forests Area (ha) 21 17 38 56 30 76 50 9 100 Condition (% of area)

- Good 20 59 33 45 30 0 100 100 25 - Moderate 75 35 66 31 57 100 0 0 75 - Poor 5 6 1 24 13 0 0 0 0

Community Forests Area (ha) 50 46 41 9 39 3 6 12 9 Condition (% of area)

- Good 44 28 69 33 44 0 100 100 100 - Moderate 56 72 31 67 56 100 0 0 0 - Poor 0 0 0 0 0 0 0 0 0

Rangeland Area (ha) 5 7 0 56 18 0 50 0 10 Condition (% of area)

- Good 5 47 0 14 11 0 0 0 0 - Moderate 49 53 0 56 54 0 100 0 100 - Poor 46 0 0 30 35 0 0 0 0

3.2 PRIVATE FORESTS

Average

51

33 67

0

8

89 11 0

11

0 100

0

Many households In both Raptl and Bhen have dIfferent types of fuel-wood, fodder, and tImber trees grOWIng on theIr land Generally, these trees are grown In comers or on land bordenng the property The trees are eIther naturally grown or delIberately planted

32

Tables 3 3 and 3 4 present the average number of trees owned by each household In RaptJ and Bhen ThIS InfOrmatIOn IS dlsaggregated by altItude and distance from the nearest road head for both zones

TABLE 3 3 AVERAGE NUMBER OF FODDER, FUEL-WOOD, AND TIMBER TREES PER HOUSEHOLD,

BY ALTITUDE

Altitude Rapti Bheri

Fodder Fuel-Wood Timber Fodder Fuel-Wood Timber Trees Trees Trees Trees Trees Trees

Avg %of Avg %of Avg %of Avg %of Avg % of Avg %of No/HH Trees No/HH Trees No/HH Trees No/HH Trees No/HH Trees No/HH Trees

>5 >5 >5 >5 >5 > 5 Yrs Yrs Yrs Yrs Yrs Yrs

<1,OOOm 10 65 5 49 32 19 24 75 1 100 2 97 1,000- 107 52 29 31 41 85 34 62 2 82 3 67 1,500m 1,500- 85 73 15 59 9 67 - -

2,OOOm >2,OOOm 25 80 15 96 3 53 - -Average 56 68 17 61 21 57 32 64 2 85 3 72

Table 3 3 shows that households In RaptJ are generally better at takIng care of theIr fuel-wood and fodder needs than are households In Bhen, as observed from the percentage of fatrly old trees on the latter group's land ThiS IS partIcularly true for those areas In the mid hIlls, at altItudes of 1,000 to 1,500 meters, where more trees are grown pnvately per household than In any other area In the two zones This practice, however, decreases With an Increase In altitude

A vatlable data on pnvate forests Indicate that households In Rapt! have an average of 56 fodder trees, 17 fuel-wood trees, and 21 tImber trees, compared With 32 fodder trees, 2 fuel-wood trees, and 3 tImber trees In Bhen

TABLE 3 4 AVERAGE NUMBER OF FODDER, FUEL-WOOD, AND TIMBER TREES PER HOUSEHOLD,

BY DISTANCE TO THE NEAREST ROAD HEAD

Distance Rapti Bhen to Road Fodder Fuel·Wood Timber Fodder Fuel-Wood Timber Head Trees Trees Trees Trees Trees Trees

Avg %ot Avg %ot Avg %01 Avg %01 Avg %ot Avg %ot No! Trees No! Trees No! Trees No! Trees No! Trees No! Trees HH >5 HH >5 HH >5 Yrs HH >5 HH >5 HH >5

Yrs Yrs Yrs Yrs Yrs

<Yz day 36 50 14 43 18 24 24 75 1 100 2 90 Yz-1 day 90 78 12 75 11 64 17 94 1 100 4 100 1-2 days 160 53 35 26 85 88 15 93 2 95 4 56 >2 days 26 81 16 96 4 65 82 44 2 55 1 90 Average 56 68 17 61 21 57 32 64 2 85 3 72

33

3.3 FORESTLAND AND THE LOCAL ENVIRONMENT

3.3.1 Threats to Biodiversity

Because of the growmg awareness of the Importance of forests, the condItlOn of forestland m Raptl and Bhen has been Improvmg The Improvement has been tnggered mamly by mcreasmg commumty participatlOn m the management of forests As a result, forests once consIdered to have been senously detenoratmg m the past are now slowly bemg restored

As a result of the two zones' detenoratmg forest base, the blOdiversity of theIr forestland had been threatened as well Consequently, several floral and fauna specIes have become endangered The fIeld survey revealed that flora such as walnut, chanp, and several herbs are now on the local endangered speCIes Itst Also on the lIst are a number of local fauna speCIes leopards, langurs, certam kmds of deer, pheasants, and peacocks

3.3.2 Damage from Natural Disasters

Table 3 5 shows that the largest area (10 hectares) damaged by landslIdes and floods m RaptI occurs at altItudes of 1,000 to 1,500 meters, where the land IS relatIvely fragIle The reglOn WIth the smallest damage (I hectare) m Raptt lIes above 2,000 meters In Bhen, damaged areas do not vary as much between these two altItudes

The largest area (13 hectares) damaged by landslIdes and floods m Raptt IS withm one-half to one day's walkmg dIstance of the road ThIS area IS also relatIvely more fragIle compared WIth others In Bhen, the largest area (7 hectares) IS m a reglOn that IS more than two days away from the nearest road ThIS area IS larger than areas at other dIstances mamly because of the larger area of the sampled wards m thIS reglOn

The degree of landslIde and flood damage m Raptt and Bhen IS related to the nature of surroundmg rocks (whether soft or hard) and the eXIstence of forests withm the regIOns Areas WIth fragIle rocks and fewer forests are found to be relatIvely more prone to landslIdes and more suscepttble to floods Moreover, the frequency of landslIdes and floods m lower altItudes IS attnbutable to the number of landslIdes and floods upstream, m hIgher altItudes

TABLE 3 5 AVERAGE AREA DAMAGED BY LANDSLIDES AND FLOODS, BY ALTITUDE AND

WALKING DISTANCE TO NEAREST ROAD HEAD

Altitude Area Covered by Landslides Distance to Area Covered by Landslides and and Floods Cha ) Road Head Floods Cha.)

Rapti Bherl Raptl Bheri

<1,000m 5 5 <Y2 day 5 5 1 ,000-1 ,500m 10 4 Y2-1 day 13 N/A 1,500-2,00Om 2 - 1-2 days 2 4 >2,000m 1 - >2 days 3 7

Average 5 4 5 4 Note N/A signifies not available

35

CHAPTER FOUR

LAND AND CROP PRODUCTION

4.1 LAND

Land IS the major asset and means of lIvelIhood for most households m the study area Land owned by households IS broadly grouped mto fIve categones culttvated lowland, cultivated slope land, kItchen gardens, grassland, and forestland The lowlands are further dIvIded mto (a) perenmally Imgated (Imgated lowland 1), (b) seasonally Imgated (Imgated lowland 2), and (c) ramfed (nommgated) SimIlarly, slope lands are dlVlded mto (a) pIpe Imgated, (b) canal Imgated, and (c) nommgated

4.1.1 Landownership

Table 4 1 shows the rate of landownershIp by land type and altItude ApproxImately 37 percent of households that own lowland m Raptt have It perenmally Imgated, as opposed to 5 percent m Bhen Bhen's low percentage mdlcates that many of the zone's sampled areas do not have as much access to lITIgatIon mfrastructure as Rapt! does The mCIdence of a much hIgher percentage of seasonally Imgated and nommgated lowlands m Bhen than m Raptl stresses thIS pomt further

The hIghest rate of ownershIp of perenmally Imgated lowlands m Rapt! occurs at elevatIOns below 1,000 meters (78 percent), thIS rate decreases as altttude mcreases Also at elevatIOns below 1,000 meters, 31 percent of the sampled households m Raptt reported ownmg nommgated lowlands ThIs percentage also decreases as altitude mcreases

The dlstnbutIOn of slope land among households dIffers lIttle between Rapt! and Bhen In both zones, the prevalence of nommgated slope land IS hIgher than the prevalence of other types of slope land, at approxImately 76 percent m Raptt and almost 79 percent In Bhen ThIS rate mcreases WIth altItude The percentage of Imgated slope lands, whether VIa pIpes or canals, ranges from 13 to 17 percent m Rapt!, and from 13 to 15 percent m Bhen It should be noted that no households reported Imgatmg theIr slope lands above 2,000 meters

The dlstnbutIOn patterns for gardens and grasslands m Raptl and Bhen are not as SImIlar as the patterns for slope land, RaptI households appear to be more active m kItchen gardenmg and grassland mamtenance than theIr cohorts m Bhen

36

TABLE 41 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LANDOWNERSHIP,

BY LAND TYPE AND ALTITUDE

Land Rapt! Bheri Type <1,000 1,000- 1,500- 2,000 Total <1,000 1,000- Total

m 1,500 2,000 m+ m 1,500 m m m

Perennially 778 403 193 11 2 370 00 62 50 IrrlQated lowland

Seasonally 185 326 184 34 204 137 381 333 Irngated lowland

Nomrngated 31 1 78 28 00 100 824 124 261 lowland

Pipe Irrigated 1 5 127 266 00 133 00 157 126 slope land

Canal Irrigated 289 21 0 138 00 172 00 181 146 slope land

Nomrngated 267 808 927 1000 759 11 8 952 789 slope land

Kitchen gardens 252 757 477 67 452 59 267 226

Grassland 21 5 635 762 584 581 235 431 392

Forestland 156 221 229 90 19 1 20 38 34

Other 126 17 23 21 4 71 00 05 04

Table 4 2 shows the rate of landownershIp by land type and walkmg dIstance to the nearest road head ThIS rate vanes much less than the rate of ownershIp by altItude

In general m RaptI, lITIgated lowlands are more common m areas that are less than half a day's walk from the nearest road head ThIS correlates wIth elevatIOns of less than 1,000 meters The exceptIOn occurs on lowlands wlthm one to two days' dIstance from the road, whIch show a hIgher rate of lITIgatIOn (58 8 and 55 a percent) and correlate wIth locatIOns between 1,000 and 2,000 meters ThIS exceptIOn can be explamed by the presence of some VDCs, such as Chibang and Kholagaun of Rukum, at one to two days' dIstance and altItudes of 1,000 to 1,500 meters These VDCs have a sIgmflcant portIOn of theIr lowlands under perenmaliITIgatIOn

37

TABLE 4 2 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LANDOWNERSHIP,

BY LAND TYPE AND WALKING DISTANCE TO NEAREST ROAD HEAD

Land Type Raptl Shen <% %-1 1-2 >2 <% %-1 1-2 Day Day Days Days Day Day Days

Perenmally Irrigated 529 168 588 137 00 00 1 0 lowland

Seasonally Irrigated 198 146 550 42 137 490 265 lowland

Nonlrrlqated lowland 179 38 101 00 824 21 6 59

Pipe Irrigated slope land 76 341 00 00 00 00 324

Canal Irrigated slope land 262 15 1 125 00 00 177 284

NOnlrrlqated slope land 551 897 840 1000 11 8 824 1000

Kitchen gardens 464 465 838 63 59 275 00

Grassland 449 741 613 61 1 235 137 406

Forestland 11 0 281 350 105 20 39 00

Other 72 22 00 221 00 20 00

4.1.2 Land Size

>2 Days

21 1

491

158

00

00

983

737

737

105

00

Table 4 3 presents the number of parcels, land owned, and land cultivated per household, by type of land and by altttude, m Raptt and Bhen In Raptt, the average Size of owned and cultivated land among the sampled households is 1 12 hectares, but the land is scattered mto 64 plots (parcels of land), on average The average Size of uncultivated land, such as grassland and forestland, is estimated to be 0 3 hectares strewn among 1 5 parcels of land The correspondmg Size of cultivated land m Bhen is estimated to be 0 74 hectares per household, but the land is diVided, on average, mto 2 parcels The average Size of unculttvated land per household m Bhen is estimated at 0 1 hectares, dispersed, on average, mto 0 6 parcels

It should be noted that of the total land owned m Raptl, 80 percent is under cultivatiOn In Bhen, 90 percent of pnvate land is under cultivatiOn Raptt's lower figure suggests that it has a higher percentage of pnvate grassland and land under tree crop cultivatiOn per household than Bhen ThiS corroborates fmdmgs m previOUS sectiOns of thiS report Furthermore, Rapti's cultivated land compnses about 40 percent lowland and 60 percent slope land In Bhen, the proportiOn of lowland to slope land IS 25 percent to 75 percent

In RaptI, the average Size of uncultivated landholdmgs is larger at higher elevations (above 1,500 meters) than at lower elevatiOns (see Table 4 3) The same IS true m Bhen, where the average size of uncultivated land IS larger and more scattered above 1,000 meters than below

38

TABLE 4 3 DISTRIBUTION OF LAND PARCELS OWNED AND CULTIVATED PER HOUSEHOLD (IN HECTARES),

BY LAND TYPE AND ALTITUDE

Land Type Raptl Sheri <l,OOOm 1 ,000-1 ,500m l,500-2,OOOm 2,OOOm+ <l,OOOm 1 ,000-1 ,500m

No Land Land No Land Land No Land Land No Land Land Total Total

No Land Land No Land Land Par Own Cult Par Own Cult Par Own Cult Par Own Cult

Own Cult Par Own Cult Par Own Cult

Perennially 42 076 089 1 1 018 014 03 006 006 03 003 003 024 026 00 000 000 01 002 002 Irrigated lowland Seasonally 10 020 021 09 012 011 03 006 005 00 000 000 010 010 02 004 004 07 010 010 Irrigated lowland Nonlrngated 15 033 037 02 004 003 00 000 000 00 000 000 009 009 14 056 054 02 005 004 lowland Pipe 00 000 000 02 005 005 06 014 014 00 000 000 006 006 00 000 000 03 005 005 Irngated slope land Canal 1 1 015 017 03 006 006 02 004 004 00 000 000 007 007 00 000 000 03 006 006 Irngated slope land NOnlrngated 05 009 010 1 9 036 036 28 081 082 86 062 062 049 050 03 003 003 22 048 050 slope land Kitchen 03 002 002 07 007 007 05 004 004 01 000 000 004 004 01 002 002 03 001 001 Qardens Total S.6 1 5 1 S 53 09 OS 4.9 12 1.2 S9 07 07 109 112 20 06 06 42 OS OS Grassland 03 005 005 10 016 016 1 6 033 033 1 1 025 025 021 021 02 003 003 06 011 011 Forestland 02 002 002 03 005 005 05 014 014 01 002 002 007 007 00 000 000 01 000 000 Other 01 001 001 00 000 000 00 001 001 03 004 004 001 001 00 000 000 00 000 000 Total 0.6 01 01 14 02 02 21 05 05 1 5 03 03 03 03 03 <1 <1 07 01 01 All Total 92 16 19 67 1 1 1 0 70 16 16 104 1 0 10 14 14 22 07 07 4S 09 09

When companng landholdmg per household by dIstance to the nearest road head m the two zones, m Raptl, the larger landholdmgs and those that are less scattered are found m 10catlOns less than a day's walk to roads (see Table 4 4) Conversely, those that are more scattered and therefore smaller m SIze are found in locations that are more than a day's walk from the neare~t road head In Bhen, the relatlOnship of average land SIze and number of parcels to dIstance was Just the OppOSIte

Total Total Own Cult

001 001

009 009

015 014

004 004

005 004

039 041

001 001

073 074 010 010 000 000 000 000 01 01 OS OS

Land Type No Par

Perenmally 24 Irngated low land Seasonally 07 Irngated lowland Nomrngated 08 lowland Pipe 01 Irngated slope land Canal 07 Irrigated slope land Nomrngated 1 1 slope land Kltchen- 05

I Qardens Total 64 Grassland 06 Forestland 01 Other 01 Total 08 All Total 72

<%Dalf

TABLE 4 4 DISTRIBUTION OF LAND PARCELS OWNED AND CULTIVATED PER HOUSEHOLD (IN HECTARES),

BY LAND TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD

Raptl Bherl %-1 Day 1-2 Da s >2 Da~s <%Da %-1 Da 1-2 Da s

Land Land No Land Land No Land Land No Land Land No Land Land No Land Land No Land Land Own Cult Par Own Cult Par Own Cult Par Own Cult Par Own Cult Par Own Cult Par Own Cult 044 050 03 009 005 1 7 021 021 03 004 004 00 000 000 01 000 000 00 000 000

014 014 03 006 005 1 6 017 017 01 001 001 02 003 003 06 009 009 06 006 006

018 020 00 001 001 02 004 004 00 000 000 14 054 052 04 004 004 01 000 000

003 003 08 017 017 00 000 000 00 000 000 00 000 000 00 000 000 05 007 007

011 012 03 006 006 02 002 002 00 000 000 00 000 000 02 003 003 06 009 009

025 026 28 086 087 23 028 028 83 064 064 03 002 002 1 2 019 019 24 053 054

004 004 05 006 006 07 003 003 01 000 000 o 1 000 000 03 001 001 00 000 000

1.19 128 5.0 1.31 1.27 6.7 075 0.76 8.7 069 069 2.0 0.59 0.58 2.8 0.35 036 42 0.76 0.76 011 011 1 6 035 035 1 2 016 016 1 1 025 025 03 001 001 o 1 000 000 06 009 009 003 003 06 015 015 06 009 009 02 003 003 00 000 000 00 000 000 00 000 000 001 001 00 002 002 00 000 000 03 004 004 00 000 000 00 000 000 00 000 000 015 015 23 052 052 1 8 025 025 1 5 032 032 03 001 001 02 001 001 06 009 009 134 144 73 183 1 79 85 100 1 01 103 1 01 1 01 23_ ~60 058 30 036 037 48 085 086

> 2 Days No Land Par Own 05 004

1 0 006

04 002

00 000

00 000

30 061

07 002

55 0.74 1 0 008 02 001 00 000 12 009 68 083

Land Cult 004

I

006

002

000

000 •

065

002

0.78 008 001 000 009 087

IN to

40

4.2 CROP PRODUCTION

NoncommercIal food crop production is still a major actIvIty for many households m the study area, even for those mvolved in commercIal frmt, vegetable, or vegetable seed farmmg Farm households consIder cereal crop productlOn, for example, to be important m ensunng food secunty Cereal crops are relatively nsk averse, secure stable pnces, and are easlly marketable

Households in the sample areas were asked about the types of different crops they grow on their land, the amount of cultivatable land they own, and the amount of land they cultivate for cereal crops. From the answers given, the interviewers mferred that farmers had dIffIculty recalling infonnation on crop area by crop type They also had difficulty recalling production mformation, because the practice of measunng yield after harvest and before home consumptlon, paying m-kmd rent, and selhng was vlftually absent.

The dIstmction between local and improved varieties of cereal crops appears to be fuzzy among many farmers. The study team observed that farmers had different mterpretatlOns of Improved and local types of crops. Some farmers referred to the variety they had been usmg for some years as Improved, even though the crop was of the local varIety Others referred to all crops as Improved If the seeds had been purchased Consequently, the mfonnation obtamed about crop variety may be questionable, even though the team's fIeld supervisors and enumerators were made aware of farmers' perceptlOns and were tramed accordmgly

The followmg sections present mformatIon on the types of crop grown, crop areas, and YIeld, by altItude and dIstance, m Rapti and Bhen The value of crop productlOn and consumption per household, and crop consumption mcome elaStICIty are also presented The report does not include mformatlOn on crop calendars, croppmg patterns, the cost of cultlvatlOn, and so on These are covered by a separate, focus group study

4.2.1 Crop Types

The percentage of households reporting dIfferent types of crop grown, by altitude and walkmg dIstance, are presented in Table 4 5 and Table 4 6, respectively

As can be seen from the tables, potatoes appear to be one of three crops cultIvated by the largest percentage of households at nearly all altitudes and dIstances ThIS IS true m both Raptl and Bhen Improved paddy crops and local maize are the runners-up to potatoes m terms of the most favored crops among the surveyed households. Improved paddy is cultIvated by a httle more than two-thirds of the households living at elevations below 1,000 meters, and by about half the households living m the 1,000-to-l ,SOD-meter range Slmtlarly, production of local maize is most popular among households hvmg at elevations of 1,500 to 2,000 meters and at elevations above 2,000 meters

Improved wheat is one of the three most preferred crops among those hvmg at elevatlOns below 1,000 meters Simllarly, barley takes second place as the most favored crop among those hvmg at levels above 2,000 meters In Bhen, Improved wheat, improved maize, and mIllet are cultIvated by the hIghest percentage of households

41

TABLE4.S PERCENTAGE OF HOUSEHOLDS REPORTING CROP PRODUCTION,

BY CROP TYPE AND ALTITUDE

Rapti Bheri

Crop Type 1,000- 1,500- 1,000· <l,OOOm 1,500m 2,000m 2,000m+ Total <1,000m 1,500m

Improved paddy I 793 530 138 34 380 59 38

NI 96 44 1 8 00 40 431 438

Local paddy I 170 262 221 101 205 20 157

NI 30 120 60 1 1 64 529 371

Improved maize I 163 251 37 00 122 39 1 0

NI 482 350 134 79 265 667 51 9

Local maize I 52 87 235 23 122 39 1 0

NI 274 312 613 921 495 21 6 481

Improved wheat I 644 530 11 5 00 335 78 38

NI 74 268 152 90 160 706 457

Local wheat I 133 180 240 79 176 00 43

NI 44 197 475 427 293 157 457

Potatoes 763 574 724 832 704 569 448

Sugarcane 07 60 69 00 43 00 33

Cotton 89 06 00 00 2 1 00 29

Mustard 859 481 664 180 583 588 648

Barley 193 492 507 719 465 137 314

Millet 07 284 148 584 220 608 362

Soybean 44 153 148 56 114 00 14

Note 1=lrngated, N=nomrngated

Total

42

437

130

402

15

548

1 5

429

46

506

35

398

471

27

23

636

280

410

1 2

From a dIstance perspectIve, Improved paddy and improved wheat are the most prevalent crops produced at locatIons that are less than half a day's walk to the nearest road Local maize and local wheat are produced by the largest number of households at the half-to-one-day's walking dIstance At the one-to­two-days' dIstance, improved paddy and barley are the most popular chmces Those hvmg more than two days away from a road grow mostly a local variety of maize and barley

42

TABLE 4 6 PERCENTAGE OF HOUSEHOLDS REPORTING CROP PRODUCTION, BY CROP TYPE AND

WALKING DISTANCE TO THE NEAREST ROAD HEAD

Rapti Bheri

Y2 -1 1·2 1h ·1 Crop Type <1h Day Day Davs >2 Days <1h Day Day 1-2 Days >2 Days

Improved paddy I 496 162 902 32 59 20 00 123

NI 61 22 6.1 00 431 549 628 00

Local paddy I 256 195 14.6 137 20 20 1 0 544

NI 27 87 19.5 1 1 529 137 402 526

Improved maize I 141 146 14.6 00 39 20 00 1 8

NI 363 146 43.9 74 667 529 637 298

Local maize I 179 130 24 32 39 39 00 00

NI 309 638 28.1 91 6 216 333 343 860

Improved wheat I 462 195 622 1 1 78 78 1 0 53

NI 130 130 41 5 84 706 569 628 53

Local wheat I 237 189 61 84 00 00 1 0 14 a NI 164 470 11 a 463 157 314 363 754

Potatoes 660 735 61 a 842 569 510 657 1 8

Sugarcane 34 76 49 00 00 00 00 123

Cotton 46 00 1 2 00 00 39 1 0 53

Mustard 771 71 9 159 168 588 60 8 52 a 91 2

Barley 263 465 79.3 737 137 177 275 50 9

Millet 34 157 500 61 1 608 21 6 51 a 228

Note 1=lrngated, N=nonlrngated

4.2.2 Crop Area

In Rapti, the average crop area per household IS estimated to be 1 77 hectares (see Table 4 7) In Bheri, the estImated figure IS approximately 1 1 hectares In Rapti, larger holdmgs (3 13 hectares of crop area per household) are most prevalent m locatIOns below 1,000 meters, and smaller holdings (0 91 hectares) are most prevalent in locatIOns above 2,000 meters Average landholdmgs m terms of crop area per household m the 1,500-to-2,000-meter elevation range are shghtly larger than at the 1,000-to-l,500-meter level In Bhen, these estImates differ markedly. The average crop area m locatIOns below 1,000 meters IS slightly lower than the area m the 1 ,OOO-to-l,500-meter range ThIS dIvergence IS mamly because average landholding SIze m Rapti's Dang District is much hIgher than m the average hIll distnct m Bhen (such as Surkhet), and because the sample VDCs in Dang are dominant at altitudes below 1,000 meters

It should be noted that in both zones, more than one-third of the cropped areas m locations below 1,000 meters, WhICh are perennially lITIgated, are under paddy In locatIOns at other altitudes, maIze accounts for the largest share of cropped areas

In terms of distance, in RaptI, the smallest cropped area per household, 0 85 hectares, occurs at households that are more than two days' walkmg distance from a road (see Table 48) The largest cropped area, 4 17 hectares, occurs at households located wlthm one to two days of the nearest road ThIS fIgure IS high for Nepal but may be skewed by the mclusion of Chibang and Kholagaun VDCs, WhICh are located

43

one to two days from a road head. These two VDCs!pockets are used mtensively for vegetable and vegetable seed production

4.2.3 Crop Yield

As Tables 4 7 and 4 8 mdicate, other than paddy, maize, and wheat m most places, and mustard, potato, and barley m other places, crops barely compete with each other for land space, as they are produced or cropped on smaller areas

When categonzmg crops by Improved and local types, and by imgatIon status, the team observed a large vanation m yield among some crops Such VarIatIOn could be related to the small sample size m each category.

When analyzing crop yield m RaptI, rrngated improved paddy fares better than the Imgated local vanety, at 22 metric tons per hectare for the fonner and 2 1 metrIc tons per hectare for the latter (see Table 47) Compared WIth RaptI, Bhen's YIeld is much lower for both the rrngated Improved and local vanetles of paddy In Bheri, rrngated local paddy YIelds more than irrigated improved paddy, at 1 8 metrIc tons per hectare versus 1.7 metric tons per hectare

In Rapti, the yields for nonimgated maize are higher among the local varIety (1.3 metric tons per hectare) than among the improved kind (1.1 metric tons per hectare) These yields are somewhat simIlar to the YIelds for the corresponding crops m Bheri.

Paddy YIelds on nonirrigated land and maIze yields on Imgated land are erratic This fluctuation can be explamed by the very small size of the sample Wheat YIeld, too, IS relatIvely low on nommgated land m both Rapti and Bheri

TABLE 4 7 AVERAGE CROP AREA AND YIELD, BY CROP TYPE AND ALTITUDE

Rapt! Bheri

1,500-

Type Crop OOOm 1,000-1,SOOm 2,000m 2,000+m <1,000 m 1,000·1,500m

Area Yield Area Yield Area Yield Area Yield Total Total Area YIeld Area YIeld Total Total

Improved I 100 1940 028 1988 004 2737 001 1678 03 2193 002 2004 001 1611 00 16877 paddy NI 010 1353 001 1407 001 411 000 0 0 849 016 1346 013 1630 01 15746

Local paddy I 008 3104 009 2191 006 1569 003 1365 01 2055 000 490 003 2098 00 17837

NI 001 2390 002 1392 003 544 000 2200 0 1430 017 1281 008 10138 01 10660

Total paddy 1.19 040 014 004 0.43 0.35 025 0.27 Improved I 014 1158 015 758 002 1355 000 0 01 944 001 1217 000 3048 00 26890 maIze NI 033 1532 010 955 008 883 003 1467 01 1128 017 1481 020 1095 02 11706

Local maIze I 004 1951 004 1338 014 1127 000 2491 01 1563 001 2114 000 1727 00 18028

NI 016 1287 014 1293 043 1184 032 1308 03 1256 004 1079 020 1177 02 11581

Total maIze 0.68 043 067 035 0.55 023 041 0.37

Improved I 042 1645 019 1157 004 1203 000 0 02 1113 004 730 001 883 00 8527 wheat NI 005 787 008 21 007 0 002 0 01 177 023 597 016 112 02 2064

Local wheat I 007 1915 006 1047 012 702 001 942 01 1100 000 0 001 697 00 5604

NI 002 1024 006 995 016 999 012 896 01 989 003 1622 014 812 01 9703

Total wheat 056 040 039 015 040 029 032 032

Potatoes 009 5923 003 6026 013 5007 007 4917 01 5492 002 5250 002 1365 00 21244

44

Raptl Bheri

1,500-

Type Crop OOOm 1,00O·1,500m 2,OOOm 2,OOO+m <1,OOOm 1,OOO-1,500m

Area Yield Area Yield Area Yield Area Yield Total Total Area Yield Area Yield Total Total

SUQarcane 001 278 000 12867 000 6588 000 0 o 6124 000 0 000 2800 00 22529

Cotton 005 1324 000 0 000 0 000 0 0 287 000 0 000 357 00 2874

Mustard 052 487 005 467 008 389 001 517 02 452 005 724 007 493 01 5378

Barley 003 801 005 439 012 857 014 780 01 711 001 875 002 826 00 8351

Millet 000 529 002 931 003 1116 015 905 0 904 006 1168 004 834 00 8991

Soybean 001 228

Total 0.71

All Total 3.13

Cultivated I 1 6 land

NI 1 5

Uncultivated 01 land

Note 1=lrngated, N=nonlrngated 1,000 kilograms (kg)=l metric ton

001 531 001

0.17 0.38

1.39 1.58

09 1 16

09 1 12

04 05

442 000 1450 0 566 000 0 000 0 00

037 039 013 0.15 0.15

0.91 1.77 1.02 1.14 1.11

07 06 08

07 06 08

03 01 02

Potato yields range from 5 to 6 metrIc tons per hectare at all elevatIons of Rapti and Bhen, except at 1,000 to 1,500 meters in Bhen, where the yield IS only 1 4 metric tons per hectare Mustard YIeld also vanes, although mmlmally, withm the different altitudes

In RaptI, Yields from improved varieties of paddy appear to increase with altItude up to 2,000 meters, while Yields from local vaneties decrease as altItude rises The significantly higher yields of local paddy over the improved variety observed from 1,000 to 1,500 meters may have resulted from the very small sample of crop areas devoted to local paddy Similarly, the higher Yields of local paddy versus improved paddy at locatIOns less than a day's distance (see Table 4 8) could have resulted from an unrepresentatIve sample size

TABLE 4 8 AVERAGE CROP AREA AND YIELD, BY CROP TYPE AND WALKING DISTANCE

TO THE NEAREST ROAD HEAD

Rap;ti Bheri

00

<111 Day 11a·1 Day 1-2 Days >2 Days <11a Day 1h·1 Day 1-2 Days >2 Days

TvpeCrol) Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield

Improved I 052 1268 027 1979 010 2731 001 1667 100 1940 028 1988 004 2737 001 1678 Paddy NI 005 1105 001 1405 002 410 000 0 010 1353 001 1407 001 411 000 0

Local Paddy I 004 1994 009 2175 016 1568 003 1363 008 3104 009 2191 006 1569 003 1365

NI 001 1921 002 1391 008 544 000 2250 001 2390 002 1392 003 544 000 220C

Total Paddy 0.62 0.40 0.36 0.03 1.19 0.40 0.14 0.04

Improved I 007 721 014 751 005 1360 000 0 014 1158 015 758 002 1355 000 C Maize NI 017 1164 010 939 021 882 002 1466 033 1532 010 955 008 883 003 146l

Local Maize I 002 1052 004 1335 036 1127 000 2550 004 1951 004 1338 014 1127 000 2491

NI 008 730 014 1294 1 14 1184 030 1308 016 1287 014 1293 043 1184 032 1308

Total Maize 035 0.42 1.76 0.33 0.68 043 067 0.35 Improved I 022 1077 019 1153 010 1204 000 0 042 1645 019 1157 004 1203 000 j: Wheat NI 002 315 008 8 018 0 002 0 005 787 008 21 007 0 002 C

45

Rapti Bheri

<11tDay Y:a·1 Dav 1-2 Days >2 Days <11t Dav U1·1 Day 1-2 Days >2 Days

TypeCro Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield Area Yield

Local Wheat I 003 1179

NI 001 667

Total Wheat 029

Potatoes 005 4182

Sugarcane 001 129

Cotton 003 544

Mustard 027 369

Barley 002 798

Millet 000 513

Soybean 000 a Total 0.36

All Total 1.62

Cult land 1 19

Uncult land 015

Note 1=lrngated, N=nonlrngated 1,000 kilograms (kg)=1 metnc ton

006

006

039

003

000

000

005

005

002

001

0.16

1.37

1 31

054

1047 032 702 001 943 007

995 043 977 011 896 002

1.04 0.14 0.56

3997 035 2663 007 4301 009

25101 000 3073 000 a 001

1290 000 0 000 0 005

453 021 367 001 513 052

438 033 824 013 780 003

865 008 1018 014 819 000

98 004 105 000 0 001

1.01 0.34 071

4.17 0.85 3.13

075 069 06

067 032 01

4.2.4 Relationship between Crop Production and Consumption

1915 006 1047 012 702 001

1024 006 995 016 999 012

0.40 0.39 0.15

5923 003 6026 013 5007 007

278 000 12867 000 6588 000

1324 000 0 000 a 000

487 005 467 008 389 001

801 005 439 012 857 014

529 002 931 003 1116 015

228 001 531 001 442 000

017 0.38 037

139 1.58 091

04 08 08

0 01 01

By mUltiplymg the quantities of all types of crops produced by their corresponding pnces, the study team obtamed value terms for the survey area's crop productIon The team determmed crop pnces by surveying key mformants using ward-level questIOnnaIreS The values of all types of crops were then aggregated to obtam the esttmated value of productIOn per household These were then categonzed by altItude and distance m RaptI and Bhen

The team derived the value of food consumption per household by subtractmg the total mcome earned from crop sales from the total value of productIon, and reducmg the value by 2 5 percent to account for storage and other losses The resultant value was then added to the amount of income spent on purchasing gram for home consumptIOn Together, the two figures Yield the total value of food consumptIOn per household Postharvest, storage, and other losses m Nepal are estImated to be 10 15 percent of production (NFS 1996)

The average values of crop productIOn and consumptIOn by household and theIr variatIon at dIfferent altItudes and dIstances are presented m Tables 4 9 and 4 to, respectIvely The value of crop productIon mcludes all cereal and cash crops hsted m preVIOUS sectIons of thIS report

Table 4 9 shows that the value of productIOn per household IS 2 6 tImes hIgher and the value of consumptIon per household I 7 tImes hIgher m RaptI than m Bhen ThIS mdIcates that households m Bhen are consummg more than they are producing

942

896

4911

C

j:

51

780

905

145C

46

TABLE 4 9 CROP PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE

Rapti Bherl

Crop Crop Crop Consump- Cultivated Crop Consump- Cultivated

Mean Production tlon Consump- Land per Production fion Consump- Land per Altitudes CV (Rs) (Rs) tion HH (hal (Rs) (Rs) tion HH (ha)

<1,000m Mean 38,409 1,7821 46% 1.5 7,454 8,043 108% 06 CV 13 0.8 07 06

1,000- Mean 12,004 8,816 73% 09 7,184 5,993 83% 08 1,500m C.V 07 06 07 07

1,500- Mean 16,297 10,328 63% 1 2 2,000m CV 21 07

2,OOOm+ Mean 7,965 8,053 101% 07 CV 08 1 2

Total Mean 1,8637 1,1184 60% 1 1 7,237 6,418 (87%) 07 CV

Note C V=coefflclent of vanatlon

Table 4 9 also shows that both production and consumption values are highest at elevations below 1,000 meters, followed by elevations from 1,500 to 2,000 meters The values are lowest above 2,000 meters Both the productIOn and consumptIon values are directly related to such factors as household size and landholdmg size per household m each location Consumption values are lowest m RaptI at locatIOns below 1,000 meters Conversely, m Bheri, locatIOns in this elevation have the highest consumptIOn value (l08 percent), perhaps indicatmg the low value of productIOn in Bhen

It is also mteresting to note that although all the sampled hill dlstncts m general are considered food-deficit areas, only those households sampled above 2,000 meters in RaptI and below 1,000 meters in Bhen have greater consumptIOn than production values

Table 4 10 shows qUIte clearly the negative correlation between the values of productIOn and consumption and distance from the nearest road m Rapti This also holds true for Bhen, with one exceptIOn occumng at the less-than-half-a-day's distance In addition, the values of productIOn and consumptIon per household are generally higher m Rapt! than in Bhen for locatIOns across all categones of distances, except for those Bhen households located farthest from the road, where the value of productIOn and consumptIon IS highest when compared With Raptl's figures and other categones m Bhen This could be the result of higher cultIvated areas per household at thiS category of distance m Bhen than m Raptl.

47

TABLE 410 CROP PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY WALKING DISTANCE

TO THE NEAREST ROAD HEAD

Rapti Bheri

Crop Crop Crop Consump· Cultivated Crop Consump- Cultivated

Distance to Production tion Consump- Land per Production tion Consump- Land per Road Head (Rs) (Rs) tion HH (ha) (Rs) (Rs) tlon HH (ha)

<Y2 day Mean 2,4762 1,3096 528% 119 7453 6,237 837% 059 CV 1 5 09 07 07

Y2-1 day Mean 1,8602 1,1272 605% 1 31 5667 4,452 960% 035 CV 20 07 08 07

1-2 days Mean 1,0999 8,226 747% 075 6,275 4,820 853% 076 CV 06 05 06 06

>2 days Mean 8,468 8,337 984% 069 10,164 7,222 749% 074 CV 07 05 07 07

Note C V=coefflclent of vanatlon

The relationshIp between the values of crop productIOn and consumptIOn, and between other vanables, can also be exammed through regression analYSIS, WhICh is discussed in the sectIOn below

4.2.5 Estimation of Crop Consumption Income Elasticity

The value of crop consumption per household was regressed wIth the value of crop production (mcome) per household and mcome from other sources, as well as with total income from all sources, household SIze, and cropped area per household, to estImate the relationship of crop consumptIon to other variables All the variables except household size, mcludmg dependent variables, were transformed mto loganthm form m order to estImate crop consumptIon income elasticIty. The regreSSIOn results and a set of explanatory variables for RaptI and Bhen are presented m Table 4.11 Tables 4 12 and 4 13 present the regression results usmg dummy variables to examine the variatIon m mtercept ShIft and slope coefficIent, by dIstance and altItude, respectIvely

TABLE 411 REGRESSION RESULTS FOR DETERMINANTS OF CROP CONSUMPTION

Variable Rapti Sheri

HHNO - 005 ·011 **

LLiV 026 ·041**

LTCROPA 180* 142*

LTINCOM 133* 082

LCROP 398* 529*

LVEG ·089* ·030

LFRU ·015 ...

044**

(Constant) 1 994* 1672*

48

Variable

Adjusted, R2=

F-statlstlcs, F=

No of observations, N=

Crop Consumption

Consumption Elasticity with respect to Income

Note * denotes significant at 1 % level of significance, ** denotes significant at 5% level of significance, and *** denotes slgmflcant at 10% level of significance

Rapti

48

51820

376

040

Dependent variables = loganthm value of crop consumption per household

Definitions of Independent variables

• HHNO = number of persons In a household • LLiV = logarithm of value of livestock production • L TCROPA = logarithm of value of total crop area • LTINCOM = logarithm of value of total Income from all sources • LCROP = loganthm of value of crop production • L VEG = logarithm of value of vegetable production • LFRU = logarithm of value of frUit production • (Constant) = Intercept term provided by the model

Bheri

813

84617

135

053

The highly signifIcant F-value and the reasonably high value of coeffIcient of determmatIOn (R2) m all the results suggest the valIdIty of the regreSSIOn model used.

Table 4 11 reveals that the variable representing income from crop productIOn is hIghly sIgnificant, suggesting crop consumptIOn elasticity to be 0 40 for RaptI and 0 53 for Bhen It is also noted that other explanatory vanables, except the vanable representing total crop area, were found to be sIgmficant m RaptI and Bhen The crop area coefficient suggests that doublIng of total cropped area wIll increase the value of crop consumption by 18 percent in RaptI and 14 percent m Bheri SimIlarly, income from lIvestock and fruIt are signIfIcant, at 5 percent, for Bhen, but only the coeffICIent of vegetable productIOn IS sIgmficant (at the 1 % level) in Rapt!.

All the coefficients of variables representmg income from vegetables, frUIt, and lIvestock productIOn are negative, suggestIng that an increase m production reduces the consumptIOn of crop ThIS IS probably because of resource dIversion from crop production to these other actIVItIes, and also because of the pOSSIble dominatIOn of the substitutIOn effect over the mcome effect

Table 4 12 presents the regreSSIOn results addmg dummy variables to the above equatIOns for measunng shIft in intercept (constant) and changes m slope coefficients related to altitude vanatIons. Dummy varIables were mcluded only for the fust three altitude ranges Thus, coeffICIents of variable, without adjustment usmg a dummy coefficient, represent elevatIOns above 2,000 meters Table 4 12 reveals that the coefficient for household IS SIgnIficant for Bhen and mSlgnifIcant for RaptI, however, these fIgures are opposite when includmg altitude dummies in the equation. Coefficients of all other variables, except crop mcome, are about the same The crop consumptIOn elaStiCIty as denoted by the coeffICient of crop income variable IS 0.66 Both the slope and mtercept coeffICients are SIgnificantly dIfferent for the 1,000-to-l,500-meter altItude range than for the above-2,000-meter range m Rapti. In all places, the

49

dIfference was statIstIcally sigmficant. Thus, crop consumption Income elaStIcIty IS 0.38, and Intercept tests are 2 55 for altitudes at 1,000 to 1,500 meters

TABLE 412 REGRESSION RESULTS FOR DETERMINANTS OF CROP CONSUMPTION, BY ALTITUDE

Variable Rapti

HHNO - 007***

LLiV 028

LTCROPA 155*

LTINCOM 098***

LCROP 659*

LVEG - 092*

LFRU - 016

DOE1 107

DOE? 1426*

DOE, 501

SDE1 - 061

SDE? - 381*

SDE, -150

Constant) 1223*

Adjusted, R2= 508

F-statlstlcs, F= 3087

No of observations N= 3660

Note * denotes significant at 1 % level of signifiCanCe, ** denotes significant at 5% level of signifiCanCe, and *** denotes significant at 10% level of significance

Dependent varlable= logarithm value of crop consumption per household

Definitions of Independent variables

Bheri 007

- 037** 167* 039 526*

- 028

- 031 -140

069

1 829*

827

7228

1350

DOE1

DOE2 DOEa SDE, SDE2 SDEa

=

Intercept dummy variable, DOE1= 1 for less than 1,OOOm altitude and 0 otherwise Intercept dummy variable, DOE2= 1 for 1,OOO-to-1 ,500-meter altitude and 0 otherwise Intercept dummy variable, DOEa= 1 for 1 ,500-to-2,000-meter altitude and 0 otherwise Slope dummy variable, SDE1= DOE1 x LFRU

= Slope dummy variable, SDE2=DOE2 x LFRU Slope dummy variable, SDE3=DOEa x LFRU

DefInitIOns of other variables are the same as In Table 4 11

In terms of dIstance VariatIon, the crop consumptIOn mcome elastICIty IS 0 62 and the mtercept 1 28 for more than two days' walkmg dIstance from a road head For RaptI, these slope coeffICIent and mtercept terms are not statIstIcally sIgmficant for dIstances that are one-half to one day or one to two days from the road, but they are sIgmficantly dIfferent for dIstances that are less than one-half day from the road Thus, the crop consumptIOn Income elaStiCIty IS 0 33 and the intercept term 1 0 for less than half a day's dIstance All other coefficients and SIgns are conSIstent with the earlIer equatIOn

Note * **

50

TABLE 413 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Variable Raptl

HHNO - 005

LLiV 131 ***

LTCROPA 180*

LTINCOM 108***

LCROP .624*

LVEG - 091*

LFRU - 013

DOD 1 085**

DOD, 319

DOD. 473

SOD - 287**

SOD? - 108

SOD. -146

(Constant) 1277*

Adjusted, R2= 496

F-statlstlcs, F= 2944

No of observations N= 3760

denotes significant at 1 % level of significance, denotes significant at 5% level of significance; and denotes significant at 10% level of significance

Bheri 001

- 023

098***

043

750*

- 029

- 029

380

1 016*

-146

- 066

- 253*

- 043

947*

850

5956

1350

Dependent variable:::: logarithm value of crop consumption per household

DefinitIOns of Independent variables

0001

0002 DODa SDD1 SDD2 SDD3

= =

= =

Intercept dummy variable, 0001= 1 for less than % day's distance and 0 otherwise Intercept dummy variable, 0002= 1 for % to 1 day's distance and 0 otherwise Intercept dummy variable, 0003 = 1 for 1 to 2 days' distance and 0 otherwise slope dummy variable, SDD1= 0001 X LFRU slope dummy variable, SDD2= 0002 X LFRU slope dummy variable, SDDa= 0003 x LFRU

DefInItIOns of other variables are the same as in Table 4.12.

4.3 FERTILIZER USE

This sectIOn presents the dIstrIbutIOn of households usmg chemIcal fertIlIzers for major cereal crops, vegetables, and fruits. ThIS sectIOn also prOVIdes mformatIOn on the amount of total chemIcal fertIlIzers used In terms of nutrIent value and compost in Rapti and Bheri Compost use IS dIS aggregated by source

51

4.3.1 Households Reporting Fertilizer Use

Tables 4.14 and 4 15 depIct, in general, the relatively higher use of chemical fertIlIzers among households m RaptI than m Bheri Chemical fertIlIzer is mostly applIed to such cereal crops as paddy, wheat, and vegetables

When analyzmg chemIcal fertIlIzer use by altitude, those households below 1,000 meters are the hIghest users The level of applIcatIOn decreases WIth elevation

TABLE 414 PERCENTAGE OF HOUSEHOLDS USING CHEMICAL FERTILIZERS, BY ALTITUDE

Rapti Sheri

1,000- 1,500- 1,000· Crops <1,000m 1,500m 2,000m 2,OOOm+ Total <1,OOOm 1,500m Total

Paddy 615 552 125 0 339 21 6 105 127

Maize 37 164 157 23 11 4 137 124 127

Wheat 733 454 167 1 1 352 137 33 53

Veqetables 556 448 278 0 348 0 0 00

FrUit 07 0 6 34 27 0 0 00

Others 259 22 46 1 1 80 39 0 08

When informatIon on chemIcal fertilIzer use is analyzed m terms of dIstance from the nearest road head, households m locations wIthm one to two days from the road appear to be the highest users This IS applIcable to households m both RaptI and Bhen

Table 4 15 shows that a small percentage of households apply chemIcal fertIlizers on malze, more so on Improved than local varIetIes Local varIeties are cultivated using fewer fertilIzers pnmarily because local varIetIes are grown exclusively for home consumptIOn As a result, malze, even though cultIvated proportIOnately on larger areas than other crops m Raptl and Bhen, produces relatively low YIelds m both zones Very few farmers report applymg chemIcal fertilIzers on frmt trees

Crops

Paddy

Maize

Wheat

Veqetables

FrUit

Others

TABLE 4.15 PERCENTAGE OF HOUSEHOLDS USING CHEMICAL FERTILIZERS,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Raptl Bheri

<% <% Day %-1 Day 1·2 Days >2 Days Day %-1 Day 1-2 Days

443 147 829 0 214 11 8 59

305 217 259 21 125 0 255

435 239 732 1 5 125 0 69

424 255 683 32 0 0 0

07 652 0 32 0 0 0

153 435 0 21 36 0 0

>2 Days

173

0

0

0

0

0

52

4.3.2 Fertilizer Application

In thIS report, fertilIzer use is analyzed at the household level because a more detmled analysIs of fertilizer use, by crop, 10 the same areas has been conducted usmg a focus group survey approach As shown 10 Tables 4.16 and 4 17, the applIcation of chemIcal fertilIzers (prImarIly mtrogen, phosphates, and potassIUm) IS higher below 1,000 meters, the level that mcludes the term and/or the lOner valleys of the lower hIlls

In general, total chemical fertilizer application, in terms of nutrient equivalent, is 134 kilograms per household per year for areas below 1,000 meters. In contrast, usage IS only 1 6 kilograms per household per year in locations above 2,000 meters In Rapti The mverse relatIOnship between chemical fertilizer use and increased altitude is consIstent WIth the scarcity of chemical fertilizers at hIgher elevations, as well as the higher costs they entaIl through added transportation expenses.

FertIlIzer usage differs In the case of paddy Unlike paddy cultivated 10 the term, paddy In the hills IS cultIvated in small but fertIle areas, such as river basms, under mtensive management As a result, they produce a relatively hIgh yield Moreover, the use of natural fertIlizers such as compost IS relatively high 10 the lower and mId hills (at elevatIons of 1,000 to 2,000 meters) Given the avaIlabIlity of more fodder and forest leaves in the hills, households there tend to keep more hvestock than do farmers In other areas, whIch facilItates the productIon of more compost Consequently, chemIcal fertihzer usage is low at thIS altitude compared With usage In the term, but the applicatIOn of compost is almost double

TABLE 416 PER HOUSEHOLD APPLICATION OF CHEMICAL FERTILIZERS AND COMPOST,

BY ALTITUDE (KGNEAR)

Rapti Sheri

Chemical 1,000· 1,500· 1,000· Fertilizer <1,000m 1,500m 2,000m 2,000m+ Total <1,000m 1,500m

NItrogen 675 241 21 7 06 344 3 1 9 Phosphorous 434 122 263 06 222 02 022

PotassIum 1275 08 21 04 38 09 01

Total nutnents 13365 471 50.1 1.6 604 41 222

Compost Own farm 4,979 5,467 7,569 4,088 4,8249 1,999 2,975

Forest 20 311 493 185 2930 16 23

Compost Total 4,999 5,778 8,054 4,273 6,1833 2,015 2,998

Total 21

02

03

26

2,7843

21 6

2,8059

Compared WIth Rapti, the use of chemical fertilizers IS much lower in Bhen, as shown 10

Tables 4 16 and 4.17 The rate of compost applicatIon, both farm- and forest-based, however, IS also much lower in Bhen than in Rapti. ThIS can be explamed by the agrIcultural productIon practIces prevaIl 109 in Bhen, which are less Intensive than those 10 Raptl

As expected, the closer to the road a household is, the higher ItS use of chemical fertlhzers and the lower its use of compost. As shown, in Rapti, the applicatIOn of chemical nutrIents IS 73 kilograms

53

per household per year In areas wIthIn half-a-day's walk to the nearest road head This rate decreases as dIstance from the road increases Conversely, the rate of applicatIOn of compost IS lowest (4,173 kilograms) In areas closest to the road and hIghest (7,530 kilograms) In areas up to two days from the road.

TABLE 417 PER HOUSEHOLD APPLICATION OF CHEMICAL FERTILIZERS AND COMPOST,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD (IN KGIYEAR)

Chemical Raoti Bheri

Fertilizer <1h Day 1h·1 Day 1·2 Days >2 Days <1h Day 1h-1 Day 1-2 Days

Nltroqen 410 2413 39 10 34 05 290

Phosphorous 259 30 22 066 015 0 028

Potassium 710 20 09 04 01 020 003

Total nutrients 732 560 619 206 365 070 321

Compost

Own farm 4,024 4,613 7,530 4,303 2,741 2,063 2,370

Forest 149 583 0 380 16 0 28

Total 4,173 5,196 7,530 4,683 2,757 2,063 2,398

>2 Days

1002

042

005

149

4,210

34

4,244

The average dose of chemIcal nutnents apphed in Raptl and Bheri is 60 4 kilograms and 2 6 kilograms per household per year, respecttvely In Bhen, mtrogen fertlhzers, pnmarlly urea, are the most prevalent, whtle phosphorus and potassium ferttlizers are uncommon The rate of compost appltcatlon IS 6,183 kilograms per household per year in Rapti and 2,806 kilograms per household per year In Bhen ThIS indIcates that Bhen's agncultural productIOn practIces are less intensIve In nature, WIth low levels of inputs, than are Raptt's One must note, however, that the acreage devoted to productIOn, as well as the rate of productIOn of vegetables and other cash crops, IS much higher In Rapti than In Bheri

55

CHAPTER FIVE

VEGETABLES

Market-onented vegetable production has attracted attention in recent years as a powerful income­generating activ1ty Vegetables as a food category are more income elastic in terms of demand than are cereal grams Th1S IS particularly true among poor households, where vegetable consumptIOn 1S not a trad1tIOnai pract1ce. Increases m both income and consumptIOn of vegetables are beheved to have a pos1tive Impact on the nutr1tIOnai status of the famIly.

Off-season fresh vegetable productIOn and vegetable seed productIOn are mcluded m the VFCI A program Off-season vegetable production programs are mostly supported m locations close to appropnate markets or m places within at least one-half day's walking d1stance from motorable roads Vegetable seed production, on the other hand, 1S encouraged m relatively maccess1ble areas as a way to overcome the d1ff1cult1es of dealmg with transportmg bulky, low-value, or penshable products

The purpose of this chapter 1S to discuss variations m areas growmg vegetables m RaptI and Bhen in terms of the value of productIOn and the consumptIOn of vegetables on a per-household bas1s The chapter also addresses the mcome-to-consumptIOn eiastIc1tIes of vegetables.

5.1 VEGETABLE CULTIVATION

5.1.1 Household Participation

Overall, a larger number of the sampled households in Raptl than m Bhen grow vegetables Table 5 1 presents percentages of households reportmg cult1vatIon of a vanety of vegetables, by altitude for both Rapt1 and Bhen The table md1cates that rad1shes (70 2 percent), mustard leaves (56 2 percent), and ch1lIes (55 4 percent) are three of the most popular vegetables grown in Raptl In Bhen, pumpkms (54 4 percent), snake gourds (51 7 percent), and colocasIa (45 3 percent) are the three most commonly grown vegetables

56

TABLE 51 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS PRODUCING VEGETABLES, BY ALTITUDE

Vegetable/Spice Rapti Bheri

<1,000m 1 ,000~1 ,500m 1,500-2,000m 2,000m+ <1,000m 1,000-1,500m Total

Radishes 725 770 788 314 274 281 281

Onions 770 50.2 468 78 156 90 102

Mustard seed 2.2 48.0 30.8 17.9 0 242 195

Tomatoes 222 617 42.8 1.1 37.2 46.1 441

Colocasla 592 623 534 224 470 452 452

Cumin 07 54 1 8 0 0 09 0.7

COriander 43.7 480 447 1 1 235 104 129

Chilies 607 491 622 438 78 21 9 194

Peas and beans 229 431 57.1 157 156 147 152

Cabbage 71 1 262 433 56 1 9 09 1 1

Ginger 5.9 47.5 180 1 1 13.7 11 4 11 8

Garlic 688 448 444 67 196 181 183

Cauliflower 540 486 347 22 58 28 34

Mustard leaves 748 469 606 359 156 352 31 4

Pumpkins 11 1 568 532 213 509 552 544

Green vegetables 103 4.9 50 33 39 23 26

Turmeric 474 218 166 191 294 152 180

Carrots 29 05 1 8 0 0 0 00

Bottle gourds 11 8 54 37 0 58 28 34

Bnnjal 674 196 46 22 98 85 88

Okra 348 54 1.3 0 11 7 90 95

Snake gourds 51 469 69 0 431 538 51 7

Long gourds 88 87 37 0 196 11 9 134

Bitter gourds 281 480 532 22 98 361 310

Cucumbers 125 551 560 157 196 376 341

Squash 1 4 38 64 0 0 09 07

Other 29 60 74 1 1 39 57 53

Production of vegetables vanes by altItude In Rapti, at elevations below 1,000 meters, more than 70 percent of the sampled households cultlvate radlshes, mustard leaves, and omons At elevatIons of 1,000 to 1,500 meters, radishes, tomatoes, and pumpkms are most popular ChilIes, mustard leaves, and radlshes are most favored in locatlOns above 1,500 meters.

57

Bhen follows much the same variatIOn m vegetable production as Raptl. The top two vegetables among Bhen growers are pumpkms and snake gourds. A thIrd, colocasIa, IS also grown by a majority of the sampled households at elevatIOns below 1,000 meters Tomatoes are also popular, especially at elevatIOns of 1,000 to 1,500 meters

In RaptI, radishes are by far the most cultivated vegetable at all altitudes and at nearly all distances from the nearest road. Cabbage and chIlIes are the most cultIvated vegetables among those households located less than one-half day's walkmg distance from a road head (see Table 5 2) Many of those livmg WIthin one-half to one day's walking dIstance appear to prefer cultivatmg peas, beans, and colocasIa Cucumbers and snake gourds are the top two vegetables among households located withm one to two days of a road, whIle a large number of those located more than two days away prefer to cultivate chilies and colocasIa.

In Bheri, pumpkms and snake gourds are the top two vegetables grown at all dIstances from the road. Colocasia IS the thIrd most popular among those living WIthin less than half a day's dIstance from the road, while tomatoes are thIrd among households located one-half to one day away. Mustard leaves and mustard seeds rank thIrd among households living one to two days or more from the nearest road head

TABLE 5 2 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS PRODUCING VEGETABLES,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Rapti Sheri Vegetable/Spice <1h Day 1h-1 Day 1-2 Days >2 Days <1h Day 1h-1 Day 1-2 Days

Radishes 709 80 853 357 288 173 225

Omons 610 491 548 73 153 76 78

Mustard seeds 187 291 670 168 0 1 9 1 9

Tomatoes 473 340 597 1 0 365 461 41 1

Colocasla 480 616 804 252 461 384 490

Cumm 1 1 27 85 0 0 0 09

Conander 412 481 573 1 0 230 57 156

Chilies 667 491 50 41.0 9.6 76 245

Peas and beans 31.6 621 402 17.8 173 96 176

Cabbage 618 351 85 94 1 9 1 9 0

Ginger 210 286 31 1 0 137 215 29

Garlic 521 551 402 63 196 11 7 264

Cauliflower 452 335 634 73 58 1 9 49

Mustard leaves 555 610 658 40 156 294 451

Pumpkins 356 475 634 210 509 392 451

Green vegetables 72 48 61 42 39 0 1 9

Turmenc 352 151 231 189 294 78 147

Carrots 1 9 21 0 0 0 0 0

Bottle gourds 95 21 61 0 58 39 39

BnnJal 421 43 231 21 98 11 7 29

>2 Days

473

122

842

543

438

1 7

52

298

140

1 7

175

87

0

228

877

52

228

0

0

157

58

Rapti Bheri

Vegetable/Spice <% Day %-1 Day 1-2 Days >2 Days <% Day %-1 Day 1-2 Days >2 Days

Okra 203 1 0 61 0 11 7 0 186 0

Snake gourds 103 75 817 0 431 451 421 824

Long gourds 84 37 85 0 196 21 5 107 52

Bitter gourds 333 594 512 4.2 98 235 343 508

Cucumbers 268 54.0 81.7 16.8 196 215 21 5 807

Squash 53 37 2.4 0 0 0 09 1 7

Other 26 8 1 10.9 1.0 39 78 49 52

5.1.2 Crop Area

Each household, on average, dedIcates approxImately 0 16 hectares to vegetable cultivatIOn In Raptl, and about 0 06 hectares m Bhen In RaptI, most households, on average, allocate approximately 003 hectares to radIsh cultIvatIOn Table 5 3 shows that households at altItudes of 1,000 to 1,500 meters are relatively more Involved In vegetable productIOn than those at other elevatIOns, given that each household at thIS altItude dedIcates, on average, the largest area (0 23 hectares) to vegetable productIOn ThIS IS followed by those households hvmg In locatIOns below 1,000 meters, whIch IS followed by those at 1,500 to 2,000 meters Lastly, the per-household allocatIOn of productIOn area to vegetables IS smallest (004 hectares) In locatIOns above 2,000 meters In Bhen, the amount of productIon area by vegetable type varIes only margmally

In RaptI, vegetables other than radIshes that cover large cropped areas mclude pumpkms, mustard seeds, peas, and beans m locatIOns above 1,000 meters In Bhen, coiocasia IS the only vegetable crop grown at locatIOns below 1,000 meters

Although fresh vegetable productIOn IS expected to take place close to roads, the largest cropped area per household (0 35 hectares) m Rapu that IS dedIcated to vegetable productIOn occurs at locatIOns one to two days from the road ThIS IS probably attnbutable to vegetable seed productIOn, whIch IS more SUited to remote areas The smallest area (0 11 hectares) occurs at locatIOns less than one day away (see Table 5.4)

Vegetable/Spice

Radishes

Omons

Mustard seeds

Tomatoes

Colocasla

TABLE 5 3 VEGETABLE CROP AREA PER HOUSEHOLD, BY ALTITUDE

(ha)

Ra~ti Bheri

1,000- 1,500- Total 1,000-<1,000m 1,500m 2,000m 2,000m+ <1,000m 1,500m

Crop Crop Crop Crop Crop Crop Crop Area Area Area Area Area Area Area

001 007 002 000 003 0.00 000

002 001 000 000 001 000 000

000 002 000 000 001 000 002

001 001 002 000 001 000 000

000 001 001 000 001 001 000

Total

Crop Area

000

000

001

000

000

59

Rapti Bheri

1,000- 1,500- Total 1,000- Total <1,000m 1,500m 2,000m 2,000m+ <1,000m 1,500m

Crop Crop Crop Crop Crop Crop Crop Crop Vegetable/Spice Area Area Area Area Area Area Area Area

Cumin 000 000 000 a 00 000 000 000 000 Conander 000 000 000 a 00 a 00 a 00 000 000

Chilies 001 000 001 000 001 000 000 000

Peas and beans 000 002 002 001 0.02 000 001 001

CabbaQe 001 001 002 000 001 000 000 000

Ginger a 00 001 001 000 001 000 000 000

Garlic 001 000 a 00 000 000 000 000 000

Cauliflower 001 001 001 000 001 000 000 000

Mustard leaves 001 001 002 000 001 000 000 000

Pumpkins 000 002 001 000 001 000 002 002

Green vegetables 000 000 000 000 000 000 000 000

Turmeric 000 000 000 000 000 000 000 000

Carrots 000 000 000 000 000 000 a 00 000

Bottle gourds 001 000 000 000 000 000 000 000

Bnnjal 001 001 000 a 00 000 000 000 000

Okra 000 000 000 000 a 00 a 00 000 000

Snake Qourds 000 000 000 000 000 000 000 000

Long gourds 000 000 000 000 a 00 000 000 000

Bitter Qourds 001 000 001 000 000 000 000 000 Cucumbers 002 000 a 00 000 001 000 000 a 00 Squash 000 a 00 a 00 000 000 000 000 a 00

Other 000 001 000 000 000 000 000 000

Total 015 023 017 004 016 001 007 006

LocatlOns m Rapt! that are less than one-half day's walking dIstance from a road dedicate their largest area (0 01 hectares) to omons, tomatoes, and cabbage Those households withm one-half to one day's dIstance cultivate mustard leaves on 0 03 hectares, radIshes on 0 02 hectares, and peas and beans on 002 hectares. At one to two days' dIstance, radIshes (0 14 hectares), mustard seed (004 hectares), and peas and beans (004 hectares) are most popular For those hvmg beyond two days' dIstance, the largest areas are devoted to pumpkms (05 hectares), peas and beans (04 hectares), and rad1shes (01 hectares) In Bhen, colocas1a 1S the only vegetable (0 01 hectares) cultlvated two days or fewer from the road

60

TABLE 5 4 VEGETABLE CROP AREA PER HOUSEHOLD, BY WALKING DISTANCE TO THE

NEAREST ROAD HEAD (IN HECTARES)

Rapti Bheri Vegetable/Spice <V2 Day V2-1 Day 1-2 Days >2 Days <V2 Day V2-1 Day 1-2 Days

Crop Crop Crop Crop Crop Crop Crop Area Area Area Area Area Area Area

Radishes 001 0.02 0.14 0.01 000 000 000

Onions 0.01 0.00 0.03 0.00 0.00 0.00 000

Mustard seeds 000 0.00 0.04 004 000 000 000

Tomatoes 001 001 000 000 000 000 000

Colocasla 000 0.01 001 001 001 000 000

Cumin 000 000 000 000 000 000 000

COriander 000 000 000 000 000 000 000

Chilies 001 000 000 a 00 000 000 000

Peas and beans 001 002 004 004 000 000 000

Cabbage 001 001 a 00 a 00 000 000 000

Ginger 000 0.01 000 000 000 000 000

Garlic a 00 000 000 000 000 000 a 00

Cauliflower 001 000 002 000 000 000 a 00

Mustard leaves 000 003 002 000 000 a 00 000

Pumpkms 000 001 003 005 000 000 000

Green vegetables 0.00 000 000 000 000 000 000

Turmeric 000 000 0.00 000 000 000 000

Carrots 000 000 000 000 000 000 000

Bottle gourds 000 000 000 000 000 000 000

BnnJal 001 000 001 000 0.00 000 000

Okra 000 000 0.00 000 000 000 000

Snake gourds 000 000 000 000 000 000 000

Ghlraula 000 000 0.00 a 00 000 000 a 00

Bitter gourds 0.00 0.00 0.00 000 000 000 a 00

Cucumbers 001 000 0.00 0.00 000 000 000

Squash 000 000 0.00 000 000 000 000

Total 009 012 0.34 015 001 00 00

>2 Days

Crop Area

000

000

006

000

0.00

000

000

000

005

000

000

000 000 000

007 000

000

000

000

000

000

000

a 00

000

001

000

019

5.2 RELATIONSHIP BETWEEN VEGETABLE PRODUCTION AND CONSUMPTION

Vegetable production and consumption per household are measured in value terms m order to examine the relatIOnships between them. The value of a vegetable's productIOn was denved by multiplymg the productIOn level of the vegetable by its corresponding farm gate pnce Pnces were obtained from key mformants via ward-level questIOnnaireS The total value of vegetable productIon was then calculated by addmg up the values of all types of vegetables produced The value of consumptIOn was denved by subtracting the amount sold from total productIOn and then reducing the resultant fIgure

61

by 27 percent to account for storage and other losses Postharvest and other losses of vegetables In Nepal IS estimated to be approxImately 25 to 30 percent of production (WFS 1996)

Table 55 shows the mean and the coeffIcIent of vanatIOn (c v) of the value of vegetable production and consumption per household, as well as the percentage of total vegetable productIOn consumed The values of vegetable productIOn and consumption In an average household in Raptl are about 10 tImes hIgher than III the average sampled household III Bhen These values are hIghest (Rs 16,241 and Rs 6,877 per household) at altItudes of 1,000 to 1,500 meters and lowest (Rs 3,065 and Rs 2,138) above 2,000 meters

From a dIstance perspective, the values of vegetable productIOn and consumptIOn In RaptI are lowest at locations more than two days from the nearest road and hIghest at locatIOns one to two days from a road (see Table 56)

In contrast, in Bhen, the vegetable productIon and consumptIon values are hIghest (Rs 1,709 and Rs. 1,171) In areas more than two days from the road and lowest (Rs 996 and Rs 689) In areas one-half to one day from the road

TABLE 5 5 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE

Raptl Bhen

Vegetable Vegetable Vegetable Vegetable Production Consumption Production Consumption

Altitude (Rs) (Rs) Consumption (Rs) (Rs) Consumption

<1,000m Mean 10,610 5,213 49% 1,161 795 68% CV 09 1 0 1 1 1 0

1,000- Mean 16,241 6,877 42% 1,424 986 69% 1,500m CV 1 8 28 1 6 1 5

1,500- Mean 14,886 6,309 42% 2,000m CV 14 2 1

2,000m+ Mean 3,065 2,138 70% CV 1 6 1 7

Note C V = coefficient of vanatlon

The van ability (c v) of productIOn, and especIally of consumptIOn, among households Increases as value Increases Consumption as a percentage of production across dIfferent altitude ranges does not show a clear relatIOnshIp WIth altItude, but It does show an Inverse relatIOnshIp WIth the value of productIOn ThlS Inverse relationshIp IS expected because Income elastIcIty of consumptIOn decreases WIth Increase In Income after a certaIn Income threshold

62

TABLE 5 6 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Vegetable Vegetable Vegetable Vegetable Production Consumption % Production Consumption %

Distance (Rs) (Rs) Consumption (Rs) (Rs) Consumption <y:! day Mean 12,858 5,565 43% 1,161 795 68%

CV 1.6 2 1 1 1 1 1 ~ -1 day Mean 13,344 6,187 46% 996 689 69%

CV 16 22 1 1 1 2

1-2 days Mean 21,058 8,275 39% 1,479 1,033 70% CV 14 25 1 9 1 9

>2 days Mean 3,594 2,526 70% 1,709 1,171 69% CV 17 1 7 1 0 09

Note C V=coefflclent of vanatlon

5.3 ESTIMATION OF VEGETABLE CONSUMPTION INCOME ELASTICITY

5.3.1 Indirect Method

In order to calculate a rough estImate of income elaStICIty of vegetable consumption, the study team grouped all observatIOns mto four income classes consIsting of an equal number of households for both RaptI and Bheri Table 5 7 presents the disaggregated average values of vegetable consumption and production for the two zones by value of mcome (earned from vegetable productIOn) quartIle Vegetable consumption percentage IS mversely related to income earned from vegetable productIOn in both RaptI and Bherl. In Rapti, however, this diverts slightly. vegetable consumptIon there decreases as mcome from vegetable production increases up to the third mcome category. At the fourth mcome category, consumptIOn increases margmally with the rise m mcome from vegetable production ThIS dIvergence may result from the mcome effect on vegetable consumption

It should be noted that the value of vegetable consumptIOn reported m the fourth mcome category appears to be too hIgh, gIven the context of the study area. The reason for obtammg such a hIgh value may be the inherent weakness m the methodology applIed m estimating consumption In the absence of actual consumptIon data, the team assumed that the study households consumed the surplus obtamed by subtracting the value of sales and estimated loss and waste from overall vegetable production This consumption figure mcludes vegetables given to neIghbors and relatIves and, most important, those vegetables used for some unmarketable stocks of vegetable seed

63

TABLE 5 7 VEGETABLE PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD,

BY VALUE OF VEGETABLE PRODUCTION

Rapti Bheri

Value Vegetable Value ofVeg. Vegetable Value Value of Income ofVeg. Con- Consump- Income ofVeg. Veg. Quartile Number Prod. sum. tlon Quartile Number Prod. Consum. Class (Rs) ofHH (Rs) (Rs) 0/0 Class CRs} ofHH (Rs) CRs}

0-3,050 156 1377 777 564 0-375 66 177 243

3,051-6,774 156 4,821 2,555 530 376-759 65 401 549

6,775-15,115 155 9,815 4,142 424 760-1,470 65 754 1,055

15,116-34,484 156 34,608 1,5047 435 1,471-20,705 65 2,402 3,551

Total 623 12,669 5,643 45% 261 949 1,372

Any disaggregatIOn of a contmuous vanable mto equal parts by a monotOnIC rankmg IS expected to overstate the actual dIspersIOn This IS because randomly dlstnbuted overestImatIOns of the vanable tend to cluster to one side of the dlstnbutIOn, whIle underestImatIOns tend to cluster to the opposite side This IS a problem at the front and back categones, for mIddle categones, over- and underestimatIOns wIll tend to even out

Table 5 8 was denved from Table 5 7 to obtam a rough estImate of the vegetable mcome elastICity as an mitIal check agamst regreSSIOn results discussed m the followmg sectIOn Table 5 8 reveals that m RaptI, mcome from vegetable productIOn mcreases by a factor of 25 1 from the fIrst to the fourth quartile, whereas the factor for vegetable consumptIOn between the same quartIles IS only 19 3 The correspondmg figures for Bhen are only 14 6 and 13 5 However, the ratIos for the thIrd to the second quartIle for mcome and consumptIOn are 2 03 and 1 62, respectIvely, for RaptI, and 1 92 and 1 88 for Bhen

TABLE 58 INCOME ELASTICITIES OF HOUSEHOLD CONSUMPTION

Quartile across Which Elasticities Are Ratio of Ratio of Expenditure

Calculated Location Income (Value of Consump.) Implied Elasticity

Third and Second Raptl 203 162 06

Income Quartlles Shen 1 92 1 88 095 Fourth and Second Raptl 718 589 079 Income Quartlles Shen 647 599 090 Fourth and First Raptl 251 193 076 Income Quartlles Shen 146 135 091

Income elastiCity from vegetables was calculated mdlrectly from the ratIO of the thIrd and second quartIles and was found to be 0 6 for RaptI and 0 95 for Bhen SImIlarly, the mcome elastICIty calculated from the ratIos of the fourth and fIrst quartiles was found to be 0 76 for RaptI and 0 91 for Bhen

Con-sump-tion %

728

730

714

676

69%

64

5.3.2 Direct Method (Regression Analysis)

The study team regressed the value of vegetable consumptIon wIth a set of explanatory vanables, mcludmg value of vegetable productIon All the variables, except household size, were converted mto log form so that the coefficient of the income vanable could provIde, directly, the vegetable consumptIOn mcome elaStiCIty

The F-values of all the regression equatlons are highly slgnificant, and the coefflcients of determmation (R2 value) are also high, suggesting the vahdity of the model The results of estimating the relatIOnship between values of vegetable consumption and other explanatory variables for different sets of observatIOn are presented below.

Table 5 9 shows the coefficient of income from vegetables as pOSItive and hIghly sigmficant It also mdicates the vegetable consumptIOn elasticity wIth respect to mcome from vegetables, WhICh is estimated at 0.90 for Rapti and 0 94 for Bhen These elastICItIes are larger than the average elastICItIes estImated for vegetables and reported by most previous studies It should be noted, however, that the study team estImated its elastIcitIes under the assumptIon that real costs (prices) of vegetables are very low because of the amount of low-qUalIty, unmarketable product produced ConsumptIOn biases toward higher mcome resultmg from an mherent weakness m the methodology used to estImate consumptIOn could also have contributed to the team's high estimates

The coefficIents of crop income (-0.16) and livestock mcome (-0 064) are negatIve and statIstIcally sIgmficant for RaptI but negatIve and statistically mSIgmficant for Bhen (-0 011 and -0 007, respectIvely) The coeffiCIent of household size (0 015) and the mtercept (constant) term are posItive and sIgmficant for Raptl. All other variables are statIstIcally insignifIcant.

The coeffICIent of total income shows that for each lOa-percent mcrease in total mcome, vegetable consumption increases by 3 percent, however, thIS coeffiCIent IS statIstically mSIgmficant The coeffICIents of livestock and crop incomes are negatIve and sIgmficant, although the magnitude of the coeffICIents IS small. The negative sign of these coefficients probably imphes that when more resources are dIverted to these crops, vegetable productIOn decreases Because vegetable consumption is strongly correlated WIth vegetable productIon, the income effect of these crops on vegetable consumptIon becomes dommated by the substitution effect.

Regression analysis by altitude withm RaptI shows that vegetable consumption and mcome elastICIty varies from 0 880 at elevatIOns below 1,000 meters to 1 034 at elevations from 1,000 to 1,500 meters (see Table 5.10) The coeffiCIent of crop income IS both sIgnifIcant and negative from 1,000 to 1,500 meters, but not at other elevatIOns. The coeffiCIent of mcome from frUIt IS negative and mSIgnificant from 1,000 to 1,500 meters, posItIve but insigmficant from 1,500 to 2,000 meters, and pOSItIve and SIgnificant above 2,000 meters.

The dIfference between the regression results m areas below 1,000 meters and from 1,000 to 1,500 meters in Bhen was small. However, the coeffICIent of total income and the intercept are sigmficant at the latter elevatIOn, but not at the former.

In Rapti, the vegetable consumption elaStICIty is lowest, 0 88, in areas located less than one-half day's walk from the nearest road head (see Table 5 11). In all other locations m the zone, the elaStiCIty IS about lOIn Bheri, the elaStICIty varies less, from 0 90 to 0 96, among locatIOns at vanous dIstances from the road

65

TABLE 5 9 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND VEGETABLE PRODUCTION

Variable Rapti

LVEG 0902*

LTINCOME 0030

LLiV -0064**

LFRU -0025

LCROP -0163***

LTCOT 0016

LTCROPA 0041

HHNO 0015**

(Constant) 0656***

Adjusted, R2= 095

F-statlstlcs, F= 1 2*

No of observations, N= 293

Vegetable consumption 090 elasticity with respect to Income

Note * denotes significant at 1 % level of signifiCanCe, ** denotes significant at 5% level of significance, and *** denotes significant at 10% level of significance

Dependent variable = value of vegetable consumption of household

Definitions of Independent variables

LVEG LTINCOME = LLiV LFRU = LCROP LCOT LTCROPA HHNO

logarithm of value of vegetable production loganthm of total Income derived from all sources logarithm of value of livestock production and sale logarithm of value of frUit production logarithm of value of crop production logarithm of value of cottage Industry products logarithm of crop area measured In hectares household size

Bheri

0937*

0094

-0007

-0012

-0011

-0011

0022

0001

-0381*

096

3668*

1290

094

66

TABLE 510 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND VEGETABLE PRODUCTION, BY ALTITUTDE

Rapti Variable

<1,000m 1,000- 1,500-1,500m 2,000m

LVEG 0880 1034* 0994*

LTINCOME 0251** -0034 -0095

LLiV 0001 -0044 -0113

LFRU 0042 -0013 0024

LCROP 0302** -0574** -0192

LTCOT 0007 0077 -0036

LTCROPA 0010 0323** 0229

HHNO 400 -a 001 0.020

(Constant) 0441 1 793** 1.134

Adjusted R2= 073 063 056

F= 256* 20 4* 165*

N= 70 a 90 a 970

Note * denotes slgmflcant at 1 % level of slgmflcance, ** denotes slgmflcant at 5% level of slgmflcance, and *** denotes slgmflcant at 10% level of slgmflcance

DefimtIOns of variables are the same as in Table 5 9

Bheri

2,000+ <1,000m 1,000-1,500m

0979* 0957* 0940*

-0018 -0050 0122*

-0015 -0006 -0011

0048* 0023 -0013

-0037 0088 0005

0048 -0002 -0012

-0103*** 0082 -0043

0010** -a 005 0002

- 200 -a 153 -0 441*

099 098 095

391* 1628* 2621*

33 a 21 a 106 a

67

TABLE 511 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND VEGETABLE PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Variable Rapti

<~Day %-1 Day 1-2 Days >2 Days

LVEG 876* 1 014* 1 067* 992*

LTINCOME 306* - 071 -125 - 027

LLiV - 008 - 071 022 - 010

LFRU - 043 023 011 041**

LCROP - 343* - 172 -1 051 * - 030

LCOT - 013 004 - 022 022

LTCROPA 048 216 320 - 064

HHNO 001 011 012 008***

(Constant) 374 589 3812* - 113

Adjusted R2= 60 46 99 99

F= 2318* 692* 47537* 46737*

N= 83 116 55 36

Note * denotes significant at 1 % level of significance, ** denotes significant at 5% level of significance, and *** denotes significant at 10% level of significance

DefimtlOns of vanables are the same as In Table 59.

Sheri

<~Day ~-1 Day

957* 897*

- 050 071

- 006 - 033***

023 - 019

088 020

- 002 018

082 - 065

- 005 - 001

- 153 -127

98 96

162 68 *

21 20

5.4 DETERMINANTS OF VEGETABLE PRODUCTION

1-2 Days >2 Days

904* 959*

185** - 106**

050 025

- 017 - 015

-100 078

- 032 033***

031- 064**

001 004

- 383 - 041

93 99

9388* 467 *

55 29

The study team regressed the value of vegetable productlOn (Income) with a set of explanatory variables, IncludIng income from other crops, total income, household SIze, and number of seasonal mIgrants The lInear regresslOn results for Raptl and Ehen are presented In Table 5.12 The results show that In the case of Raptl, 42 percent (R2=O 42) of the vanatlon In vegetable mcome IS explamed by the set of mdependent vanables used in the equation However, the same set of independent variables could only account for 10 percent of the vanance m the case of Bhen This is probably because mcome from vegetables IS quite low m Bhen compared WIth Raptt It should also be noted that were all coeffICIents zero, mcome from vegetables would be Rs 5,474 m Raptl and Rs 969 m Bhen, as mdlcated by the mtercept term.

Most coeffICients of the explanatory vanables are significant at at least the lO-percent alpha level m the RaptI equation Of the sIgmfIcant varIables, the coeffICIent of total income IS pOSItive and SIgnIfIcant, whIle coeffICIents of other income sources (frUIt, cottage industry, and crop production) and household SIze are signifIcant but negatIve Such a relationshIp mdIcates that vegetable productIon IS competmg WIth frUIt productIon, other crop productIon, and cottage Industnes

68

The negative coeffICIent of the vanable measunng household SIze IS dIffIcult to explam, because larger household SIze generally ImplIes the greater aVaIlabIlIty of famIly labor to partIcIpate m the labor­mtensIve process of vegetable productIOn However, because labor IS not a constramt for vegetable cultIvatIOn, WhICh IS the case m bIgger households that are posItIvely correlated wIth smalllandholdmg sIze, household SIze may have a negatIve effect ThIs pomt needs further mvestIgatIon

For Bhen, all the explanatory varIables, except for total mcome denved from all sources, are InsIgmficant.

TABLE 512 REGRESSION RESULTS FOR DETERMINANTS OF VEGETABLE PRODUCTION

Variable Raptl

HHNO

SMC09

TINCOME

TCROPA

PCROPA

L1V

ICROPA

FRU

COT

PRODCROP

(Constant)

Adjusted, R2=

F-statrstlcs, F=

No of observations, N=

Note * denotes slgnrflcant at 1 % level of slgnrflcance, ** denotes slgnrflcant at 5% level of slgnrflcance, and *** denotes slgnrflcant at 10% level of slgnrflcance

-4484**

-9961

39*

-3686

2461

- 39

6789

- 38*

- 43*

- 32*

54739*

042

462

621

Dependent vanable = value of vegetable production of household

Deflnrtlons of Independent vanables VEG = value of vegetable production In Rs TINCOME = total Income denved from all sources In Rs L1V = value of livestock production and sale In Rs FRU = value of frUit productron In Rs CROP = value of crop production In Rs COT = value of cottage Industry products In Rs TCROPA = crop area measured In hectares PCROPA = paddy crop area measured In hectares ICROP = Irrigated crop area measured In hectares HHNO = household size SMC09 = number of seasonal migrants In household

Bheri

-687

-996

-03*

2937

-52203

- 00

4289

- 01

09

- 00

9692*

010

408

260

69

CHAPTER SIX

FRUIT

FrUIt farmIng for commercIal purposes IS In the early stages of development In the study area TradItIonally, fruit trees have been grown In kItchen gardens, In between crop land, and on the homestead for household consumptIOn It was very dIffICUlt to estImate the total study area covered by frUIt trees, except In places where they were grown In orchards for commercIal purposes As a result, the total area dedicated to fruIt trees IS not discussed below

This chapter presents the dIstribution of households grOWIng fruit, the number of fruIt trees per household, the percentage of frult-beanng trees by fruIt type, the value of the fruit produced, the value of the fruit consumed, and consumptIOn Income elastIcities As in prevIOUS chapters, these data are categonzed by altItude and walking dIstance to the nearest road for both RaptI and Bheri

6.1 FRUIT CULTIVATION

6.1.1 Household Participation

ClImatic vanation and altitudInal dIfferences allow fruIt to grow in a WIde range of both subtrOPICal and temperate zones In RaptI and Bhen As shown In Table 61, the study team recorded 19 dIfferent fruIt types In Rapti and 16 In Bhen Approximately 20 percent of the Rapti households plant banana plants and apple, peach, and pear trees In Bhen, about 26 percent of the sampled households produce banana plants, 22 percent produce guava trees, and 17 percent produce peach trees Approximately 5 percent of the sampled households In Bhen report prodUCIng 8 of the 16 types IdentifIed In Bhen, and 5 percent of the households In Raptl report producing 13 of the 19 types IdentIfIed In RaptI

In general, households at elevatIons below 1,000 meters and above 2,000 meters reported haVIng fewer fruit trees than households at other altItudes ThIS supports the assertion that, In general, the mId hIlls are more SUItable for frUIt cultIvatIOn than are the lower or high hIlls, even though fruIt type vanes by altitude and clImate

In Rapti, at elevatIons below 1,000 meters, less than 3 percent of households per fruit type reported planting any fruIt, except for mangoes, WhICh 13 percent of the households at that elevatIOn reported grOWIng In Bhen, at least 10 percent of households per fruIt type reported owmng at least one of seven types of fruIt trees or plants at elevatIOns below 1,000 meters Mango and guava trees were reported by more than one-fourth of sampled households hVIng at these altItudes

Fruit

Mango

Guava

Papaya

JackfrUit

Lemon

Banana

Lime

Apricot

Pear

Llchl

OranQe

Apple

Pineapple

Walnut

Peach

Melon

PomeQranate

Pomelo

Blmlro

Others

70

TABLE 61 PERCENTAGE DISTRIBUTION OF FRUIT-GROWING HOUSEHOLDS,

BY FRUIT TYPE AND ALTITUDE

Rapti Bheri

<1,OOOm 1,000- 1,500- 2,000m+ Total <1,000m 1,000· Total 1,500m 2,000m 1,500m

13.3 26.2 2.8 0.0 11 6 255 10.1 13.1

3.0 273 32 00 98 275 206 21 9

2.2 230 05 00 74 137 134 135

07 27 05 00 1 1 11 8 05 27

07 361 194 00 175 11 8 91 96

22 465 212 1 1 21 6 137 292 262

1 5 153 148 00 99 157 153 154

00 27 166 46 72 00 00 00

1 5 230 341 34 194 39 43 42

07 22 23 00 1 6 00 1 9 15

00 328 143 23 149 00 191 154

00 33 373 557 21 9 00 00 00

07 06 05 23 08 00 00 00

00 49 203 125 103 00 24 1 9

07 251 350 125 21 5 78 191 169

07 00 09 00 05 00 05 04

00 33 23 00 1 8 00 29 23

00 49 23 00 22 00 1 0 08

00 66 97 00 53 20 24 23

163 11 5 157 341 172 39 91 8 1

FruIt trees are most commonly grown at altitudes of 1,000 to 1,500 meters, followed by altItudes of 1,500 to 2,000 meters The percentage of frmt growers varies by frmt type For example, in RaptI, 46 percent of households at levels of 1,000 to 1,500 meters grow bananas, 36 percent grow lemons, and 33 percent grow oranges At the 1,500-to-2,000-meter range, 37 percent grow apples, 35 percent grow peaches, and 21 percent grow bananas Those households livmg at elevations above 2,000 meters mamly grow apples (56 percent), peaches (13 percent), and walnuts (13 percent) In Bheri, 29 percent of the sampled households hving at elevations of 1,000 to 1,500 meters grow bananas, 21 percent grow guavas, and 19 percent grow oranges.

From a dIstance perspective, m Rapti, the hIghest concentratIOn of fruit -growmg households occurs at locations that are one to two days from a road (see Table 6 2) The next largest concentratIOn of fruit growers in Raptl occurs one-half to one day from the nearest road Mango, guava, and CItrus growers are more pronounced m locations one to two days from the road than m any other location m the zone

In Bhen, guavas, bananas, and oranges are the most commonly grown fruit at locatIOns more than two days from the road ThIS is probably because frmt productIOn, especIally m Bhen, IS mfluenced by chmatic conditIOns rather than by accessIbihty to the market

71

TABLE 6.2 PERCENTAGE DISTRIBUTION OF FRUIT-GROWING HOUSEHOLDS, BY FRUIT TYPE AND

WALKING DISTANCE TO THE NEAREST ROAD HEAD

Rapti Bheri Fruit <1h day 1h -1 day 1·2 days 2 days+ <1h day 1h·1 day 1·2 days 2 days+

Manqo 11 1 4.3 427 00 255 137 78 107 Guava 57 3.2 488 00 275 216 69 439 Papaya 27 0.5 463 00 137 196 00 316 JackfrUit 04 1 1 49 00 11 8 20 00 00 Lemon 88 283 41 5 00 11 8 11 8 98 53 Banana 126 308 537 1 1 137 157 196 579 Lime 84 178 85 00 157 157 157 140 Apncot 23 184 1 2 43 00 00 00 00 Pear 84 373 329 32 39 00 78 1 8 Llchl 1 5 2.2 24 00 00 20 20 18 Orange 73 184 463 21 00 20 186 351 Apple 12 427 24 553 00 00 00 00 Pmeapple 08 05 00 21 00 00 00 00 Walnut 34 238 00 11 7 00 59 1 0 18 Peach 49 384 476 11 7 78 59 186 31 6 Melon 04 1 1 00 00 00 20 00 00 Pomegranate 08 27 49 00 00 00 00 105 Pomelo 00 2.7 110 00 00 00 00 35 Blmlro 12 11 9 98 00 20 20 29 1 8 Others 39 20 49 228

6.1.2 Fruit-Bearing and Nonbearing Trees

Tables 6 3 and 6 4 present per-household averages for number and age of frmt trees and percentage of fruIt-bearing trees, by altItude, m Raptt and Bhen, respecttvely. One can clearly see vanatton m the number of fruIt trees and frmt types and among the varIOUS altttudmal ranges

In Raptt, the hIghest number of fruit trees per household at elevations below 1,000 meters IS 26, WhICh mamly compnses mango trees At elevatIOns of 1,000 to 1,500 meters, orange trees tend to dommate fruit productIOn, wIth 4 8 trees per household In the 1,500-to-2,000-meter and above-2,000-meter categones, apple trees are the favonte, WIth 49 trees per household at the former level and 48 trees per household at the latter In Ehen, mango trees are the most popular frmt trees grown below 1,000 meters, wIth 146 trees per household, whIle orange trees take fIrst place at elevatIOns of 1,000 to 1,500 meters, wIth 3 2 trees per household

Fruits

<1yr

ManQo 032

Guava 012

Papaya 020

JackfrUit 001

Lemon 007

Lime 000

Apncot 000

Pear 001

lIchl 000

Orange 001

Apple 001

Pineapple 004

Walnut 000

Peach 001

Melon 000

Pomegranate 001

Pomelo 000

Blmlro 000

Others 001

Total 081

Banana 059 ---

72

TABLE 63 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES

PER HOUSEHOLD, BY FRUIT TYPE AND ALTITUDE RAPTI

<1,OOOm 1,OOO-1,500m 1,500·2,OOOm

No. of Trees No. of Trees No. of Trees

1-5yr 5+yr %FB <1yr 1-5yr 5+yr %FB <1yr 1-5yr 5+yr %FB <1yr

1 10 1 21 486 026 085 072 362 002 007 00 364 000

053 105 873 042 063 104 614 007 018 01 557 000

1 11 041 755 013 036 028 714 003 006 00 444 000

033 012 226 011 009 007 250 001 001 00 750 000

027 018 671 1 51 133 050 226 073 058 02 154 000

010 012 767 012 039 040 488 001 030 02 487 000

001 001 500 002 005 002 412 007 041 05 571 000

005 013 640 008 016 042 71 7 061 138 06 281 010

008 010 760 002 009 006 387 001 008 00 286 000

004 004 61 5 044 331 1 07 169 006 242 06 208 0.01

000 000 00 001 009 002 45 048 3208 161 446 3.40

003 001 600 041 009 016 289 000 000 00 714 003

000 000 00 0011 000 008 938 006 331 03 37 1 15

004 013 720 006 033 038 631 045 1 31 09 860 027

000 001 1000 000 000 000 00 071 000 00 38 000

001 009 750 002 001 010 636 001 005 00 391 000

001 001 667 003 004 005 435 000 003 00 556 000

024 036 86 066 039 021 61 005 007 01 593 000

039 022 83 425 833 2107 27 010 013 00 922 000

436 420 577 852 1656 2664 136 350 4249 203 416 497

097 323 853 758 905 325 210 059 387 09 534 000

Above 2,OOOm

No. of Trees

1-5yr 5+yr %FB

000 000 OC

000 000 OC

000 000 OC

000 000 OC

001 000 100C

000 000 OC

002 006 71 4

018 007 129

003 001 25 C

004 046 63 C

2361 2056 164

006 033 378

1 10 056 92

009 055 398

000 000 00

001 000 00

000 000 00

003 008 100

007 002 00

2556 2270 172

003 004 1429

73

TABLE 6 4 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING

TREES PER HOUSEHOLD, BY FRUIT TYPE AND ALTITUDE. BHERI

<1,OOOm 1 ,000-1 ,500m

Name of fruits and No. of trees No. of trees

other trees <1 year 1-5 years 5+year FB% <1 year 1-5years 5+year

Mango 265 841 351 1723 011 009 022

Guava 012 351 027 5578 005 033 035

P~~a 002 020 012 5294 011 011 022

JackfrUit 000 010 016 3846 001 000 001

Lemon 000 010 002 8000 008 007 016

Lime 008 002 020 10667 004 018 021

Apncot 000 000 000 000 001 000 002

Pear 000 004 000 5000 001 033 004

Llchl 000 000 002 10000 000 002 003

OranQe 000 000 000 000 065 134 1 20

AppJe 000 000 000 000 000 000 000

Pineapple 000 000 000 000 000 000 000

Walnut 000 000 000 000 000 001 010

Peach 000 002 002 2500 004 007 033

Melon 000 000 000 000 000 000 000

Pomegranate 000 000 000 000 000 001 002

Pomelo 000 000 000 000 000 000 001

Blmlro 006 000 010 8750 000 000 001

Others 000 000 004 000 046 070 068

Total 292 1239 445 1 58 326 363

Banana 229 1 71 139 1418 992 1422 134

FB%

5977

7020

7935

3333

6364

6292

6667

2250

6100

5367

000

000

81 00

51 00

000

6250

5000

5000

2857

173247

Tables 65 and 66 present per-household averages for number and age of fruIt trees and percentage of frult-beanng trees, by walkmg dIstance to the nearest road, in Rapti and Bhen, respectIvely Compared wIth the relationship between altItude and frmt type, these tables reveal a weak relatIOnship between dIstance and frmt type

74

TABLE 6 5 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES

PER HOUSEHOLD, BY FRUIT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD RAPTI

<1h day lh-1 day 1-2 days 2days+

Number of trees Number of trees Number of trees Number of trees

<1yr 1- S+yr %FB <1yr 1-Syr S+yr %FB <1yr 1-Syr S+yr %FB <1yr 1-Syr S+yr 5yr

Mango 027 0.77 087 45.9 000 007 010 468 029 1 29 077 321 000 000 000

Guava 009 0.47 077 80.1 009 019 010 528 082 080 1 70 599 000 000 000

Papaya 012 0.66 030 76.6 004 010 004 588 021 046 035 619 000 000 000

Jackfruit 004 0.20 010 25.2 001 003 000 625 013 006 004 105 000 000 000

Lemon 011 0.41 033 450 1 01 085 036 190 278 1 72 027 148 000 002 002

Lime 005 034 027 468 004 031 035 569 005 006 001 600 000 000 000

Apncot 000 0.02 007 86.3 008 051 055 535 004 002 000 200 000 002 005

Pear 001 005 020 749 074 165 066 232 007 018 062 805 012 018 006

Llchl 000 011 009 538 001 009 000 31 5 004 000 004 500 000 003 001

Orange 012 0.51 044 286 013 277 085 216 049 598 084 11 3 001 005 043

Apple 000 001 003 500 052 3727 1876 446 000 005 000 00 327 2259 1932 Pineapple 031 007 012 315 001 000 003 714 000 001 000 00 003 005 031

Walnut 001 003 005 409 005 382 044 45 000 000 000 00 1 11 103 053

Peach 004 012 013 560 049 149 108 888 011 052 072 612 026 038 053

Melon 000 000 000 00 083 000 003 37 000 000 000 00 000 000 000

PomeQranate 001 003 008 689 001 003 006 526 004 001 011 384 000 001 000

Pomelo 000 000 001 666 000 004 006 555 007 010 011 434 000 000 000

Blmlro 004 016 025 152 000 006 012 91 1 146 080 040 32 000 003 007

Others 003 032 027 392 015 037 009 205 933 1774 4649 23 000 006 002

Total 126 428 437 513 420 4965 2368 413 1593 2983 5246 87 480 2446 21 35

Banana 075 1 67 339 653 210 484 189 400 1232 1576 001 127 000 003 005

%FB

0

0

0

0

75

0

714

11 7

25

617

163

378

90

396

0

0

0 10

0 171

75

TABLE 6.6 AVERAGE NUMBER OF FRUIT TREES AND PERCENTAGE OF FRUIT-BEARING TREES

PER HOUSEHOLD, BY FRUIT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD BHERI

Name of fruit <%day %·1 day 1·2 days 2days+ trees and

No. of Trees No. of Trees No. of Trees No. of Trees other trees <1yr 1·Syr S+yr %FB <1yr 1-Syr S+yr %FB <1yr 1-Syr S+yr %FB <1yr 1·Syr S+yr

Mango 265 841 351 172 018 010 029 509 010 014 011 457 005 000 037

Guava 012 351 027 559 008 008 016 750 002 036 013 412 007 047 091

Papaya 002 020 012 1500 024 018 067 881 002 000 001 00 018 023 019

Jackfrult 000 010 016 385 000 002 004 667 003 000 000 00 000 000 000

Lemon 000 010 002 800 010 016 010 500 012 007 024 628 000 000 009

Lime 008 002 020 670 008 016 008 688 003 024 026 585 004 009 023

Apncot 000 000 000 00 000 000 000 00 002 000 004 667 000 000 000

Pear 000 004 000 500 000 002 000 1000 003 066 009 218 000 000 000

Llchl 000 000 002 1000 000 000 002 00 000 001 003 500 002 007 004

Orange 000 000 000 00 000 004 010 857 130 249 202 522 004 044 070

Apple 000 000 000 00 000 000 000 00 000 000 000 00 000 000 000

Pmeapple 000 000 000 00 000 000 000 00 000 000 000 00 000 000 000

Walnut 000 000 000 00 000 000 000 00 000 002 000 00 000 000 037

Peach 000 002 002 500 000 002 000 500 006 009 027 1095 004 007 074

Melon 000 000 000 00 000 000 000 00 000 000 020 1000 000 000 000

Pomegranate 000 000 000 00 000 000 000 00 000 000 000 00 000 000 000

Pomelo 000 000 000 00 000 000 000 00 000 000 000 00 002 004 009

Blmlro 006 000 010 875 000 000 000 00 000 001 000 2000 000 000 005

Others 000 000 004 00 000 000 000 00 000 059 005 63 168 1 51 242

Total 293 1240 446 6961 068 078 146 91 8 173 468 345 508 214 292 620

Banana 229 1 71 139 141 014 047 037 3378 089 463 206 11 9 3467 4346 091

%FB

881

690

700

00

1000

694

00

00

538

636

00

00

1000

929

00

00

600

1000

324

539

144

A relatIvely hIgh percentage of young trees and a low percentage of fruIt-bearing trees can be conSIdered a crude indIcator of a household's adoption of recent fruIt cultIVatIOn practices SImIlarly, a hIgh percentage of older frult-beanng trees can be considered a crude mdlcator of the use of tradItional cultIvation methods It should be noted, however, that the dIstrIbution of papaya trees and, espeCially, banana trees across dIfferent age groups may be Irrelevant, because the age range speCIfIed m the survey questionnaire was not partIcularly SUitable for papaya trees or, espeCIally, banana trees, gIven that the hfe cycles of these two frUit trees are much shorter than that of other fruit trees Banana trees, for mstance, bear fruit only once every two years

Another mdicatlOn of modern fruIt cultIvation techmques takmg hold IS Illustrated by the mcreasmg number of mango saplmgs bemg sold by local nursenes, and by the mterest a dozen Tharu women showed m leammg mango-tree grafting techniques m private nursenes, as the study team observed m Rapt!

At hIgher altitudes, espeCIally m locations above 2,000 meters, 56 percent of the sampled households reported owning apple trees At elevations of 1,500 to 2,000 meters, 37 percent of households mterviewed mdicated ownmg apple trees However, only 16 percent of the apple trees above 2,000 meters were reported to be beanng frUit, whIle about 45 percent of those m the 1,500-to-2,000-meter range were

76

reportedly beanng fruIt The dIfference m matunty of apple trees between these two altItudes corresponds dIrectly to the tImes at whIch the VFC/A program promoted apple cultIvatIOn m Jmabang and Taksera (Taksera IS located above 2,000 meters, whIle Jmabang IS m the mId hIlls, between 1,500 and 2,000 meters)

6.2 RELATIONSHIP BETWEEN FRUIT PRODUCTION AND CONSUMPTION

The study team converted into values the quantities of fruIt productIon It recorded dunng the study The team obtained the values by multiplymg the respectIve quantItIes of dIfferent types of fruIt by theIr correspondmg umt pnces (prices were collected from ward-level data) The team then added up the values of all fruIt types to determine the total value of fruIt productIOn m Raptl and Bhen

The team denved the value of fruit consumptIOn by subtractmg sales from total productIOn and then reducmg the result by 17 5 percent to account for storage and other losses (Postharvest and other fruit losses m Nepal are eStimated to be 15 to 20 percent of total productIOn [WFS 1996])

Tables 67 and 68 present the mean and the coeffICIent of vanatlon (c v) of the values of fruIt productIOn and consumptIOn per household m Rapt! and Bhen Table 6 7 shows these data by altItude, Table 6 8, by walkmg dIstance to the nearest road Both the fruIt productIOn and the consumptIOn values for Rapu were found to be, on average, about two and one-half times hIgher than for Bhen SImIlarly, frUlt consumptIOn as a percentage of fruIt productIOn was hIgher (73 percent) m Rapt! than m Bhen (69 percent)

TABLE 6 7 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY ALTITUDE

Raptl Shen

FrUit FrUit FrUit Fruit Altitude Prod. Con sum. Prod. Consum. Ranges MeanC.V (Rs) (Rs) Consumption (Rs) (Rs) Consumption

<1,000m Mean C V 6605 5181 78% 2455 1602 66% 38 40 37 37

1,000-1,500m Mean CV 5364 4073 76% 2427 1695 70% 35 38 39 46

1,500-2,000m Mean CV 8539 5840 68% 30 36

2,000m+ Mean C V 1408 1001 71% 51 55

Note C V=coefflclent of vanatlon

Lookmg at the vanatIOn m the values of fruIt productIOn and consumptIOn m terms of altItude, m RaptI, the values are hIghest (Rs 8,539 and Rs 5,840 per household) at elevatIOns of 1,500 to 2,000 meters, and lowest (Rs 1,408 and Rs 1,001 per household) above 2,000 meters The mtense apple productIOn m Jmabang may have contnbuted to the hIgh values at the 1,500-to-2,000-meter level

77

The team found that the coeffIcIent of variatIOn IS mversely related to the corresponding values of frUIt productIOn and consumption RaptI's coefficIent ranges from 300 percent at the 1,500-to-2,000-meter level to almost 500 percent above 2,000 meters. The patterns are similar m Bhen.

In terms of distance from the nearest road head, the highest values of frUIt production and consumptIOn m Raptl occur at locations wIthin one to two days' walkmg dIstance from the road, such as lmabang In Bheri, the VariatIOn m the values by walkmg dIstance is much smaller than m RaptI.

TABLE 6 8 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD, BY WALKING DISTANCE

TO THE NEAREST ROAD HEAD

Rapti Sheri

Fruit Fruit Fruit Fruit Distance Prod. Consum. Consum- Prod. Consum. Consump-Classes Statistics (Rs) (Rs) ption (Rs) (Rs) tion

<%day Mean C V 5476 4229 77% 2455 1602 66% 04 44 37 37

% day 1 day Mean C V 10921 7515 69% 2664 2136 81% 27 32 52 54

1-2 days Mean C V 3233 2565 79% 2344 1654 71% 1 3 1 4 40 46

2+ days Mean CV 1350 1007 75% 2322 1345 58% 52 56 08 1 1

Note C V=coefflclent of vanabon

6.3 ESTIMATION OF FRUIT CONSUMPTION INCOME ELASTICITY

6.3.1 Indirect Method

As It did for vegetable consumption (see Chapter FIve), the study team estImated the income elastiCIty of fruit consumption by grouping data mto four mcome classes conslstmg of an equal number of households for both Rapti and Bhen Table 69 presents the mean, the coeffIcients of vanatIOn (c v) of productIOn and consumption, and consumptIOn percentage, by Income, for RaptI and Bheri.

The value of fruIt productIon ranges from zero to more than Rs 200,000 m Rapti and to more than Rs 100,000 10 Bhen The average production values m the four groups range from Rs 6 to Rs 22,510 m RaptI and from Rs 5 to Rs 8,493 m Bhen In addItlOn, the percentage of consumption from total productlOn IS hIgher m RaptI (73 percent) than 10 Bhen (69 percent) The percentage of consumption decreases as production mcreases m Bhen, whIch was expected In RaptI, however, the percentage remains the same m all quarttles except the thIrd

As Table 6 9 mdicates, the relative vanability m values of frUlt production and consumption IS about 200 percent, except m the two mIddle income categones When the data for RaptI and Bhen are aggregated, the vanabIhty m the values of fruIt production and consumptIOn doubles, to approxImately 400 percent In most cases, the varIatIOn m consumptIOn IS hIgher than m productIOn

FrUit Income Class (Rs)

0-72

73-899

900-3,052

3,053-24,000 Total

78

TABLE 6 9 FRUIT PRODUCTION AND CONSUMPTION VALUES PER HOUSEHOLD,

BY VALUE OF FRUIT PRODUCTION

Raptl Bhen

Value of Fruit Value of Value of Value of FrUit Consum- Income FrUit Fruit

No of Statl- Fruit Prod Consum ptlon Class In No of Prod Consum HH sties (Rst (Rs) % Rs HH (Rst JRs) 156 Mean 588 431 73 0-65 66 52 43

CV 26 27 23 23

156 Mean 421 308 73 66-544 65 274 212 CV 05 06 05 05

156 Mean 1840 1261 68 545-1,761 65 966 695 CV 03 04 03 04

155 Mean 22510 16475 73 >1,761 65 8493 5798 CV 1 8 20 24

623 Mean 6168 4493 73 Total 261 2423 1670 CV 36 40 39 44

Note C V=coefflclent of vanatlon

Consum-ptlon

%

82

77

72

68

69

The fruIt consumptIOn mcome elastICItIes presented m Table 6 10 were denved from the mformatIOn prOVIded m Table 6 9 As shown m Table 6 10, the values of productIOn and consumption mcrease many tImes from the fIrst quartIle to the fourth quartIle, but mcrease fIve times from the second to the third The fruIt consumptIOn Income elastiCItIes calculated from the ratIo of the thIrd and second quartlles are 0 92 for Raptl and 0 90 for Bhen The elasticIties for all other quartiles are higher for Raptl than for Bhen

TABLE 610 INCOME ELASTICITIES OF HOUSEHOLD CONSUMPTION

Class across Which Ratio of Ratio of Implied Elasticities Are Calculated Location Income Expenditure Elasticity

Third and Second Raptl 437 409 092 Income Quartile Bherl 352 328 090

Fourth and Second Raptl 5344 5344 1 00 Income Quartile Bherl 3100 2735 088

Fourth and First Income Raptl 381542 382271 1 00 Quartile Bherl 164593 1361 03 083

79

6.3.2 Direct Method (Regression Analysis)

The team regressed the value of fruit consumption per household wIth mcome from fruit, mcome from other sources, household size, and crop area All vanables except household SIze were transformed into logarithm form so that the coeffIcIent of income from fruit could also serve as the fruit consumptIon income elasticIty. The regression results from estImating the relationshIp between the values of fruIt consumption and a set of explanatory variables for Rapti and Bhen are presented m Table 6 11

The highly sigmflcant F-value and the hIgh value of the coefficient of determmatIOn (adjusted R2>0 8) suggest the validIty of the regressIOn model The hIghly signifIcant coefficIent-of-mcome-from-frmt variable shows the fruIt consumptIOn income elastICIty to be 0 88 for RaptI and 0.87 for Bheri.

It should be noted that income from cottage mdustnes IS mversely related to fruIt consumption, that IS, for every 100-percent mcrease in mcome from cottage mdustrIes, the value of fruit consumption decreases by approxImately 10 percent Because fruit consumption is highly correlated WIth mcome, thIS ImplIes that cottage industry production and fruit productIon are complementary actIvItIes, especially in Rapti

The coeffiCIents of all other vanables in the equatIon modeled for RaptI and Bhen are statIstIcally msigmflcant (The variable representing mcome from cottage mdustrles m Bhen IS also statistIcally msignifIcant. )

The team examined the vanations in the relationship of frUlt consumption to the set of explanatory variables mentIOned above by dIstance (Table 6 12) and altitude (Table 6 13) usmg dummy vanables for both mtercept (constant) and slope changes Separate equatIOns were estimated for exammmg variatIon by altItude and dIstance to aVOid multI-colhneanty, as the altItude categones are pOSItively correlated with the dIstance categories.

In Table 6.12, the dummy varIable for the last category of dIstance (more than two days) was excluded because the intercept and coefficIents of the other dummy variables prOVIde the dIfference with respect to the coefficIent representing households located more than two days from the nearest road head FruIt consumptIon income elastIcIty is estImated to be 0 76 for locations more than two days away ThIS was observed to mcrease to 0 95 (0.76 + 019) for locatIOns both within one to two days' walking dIstance and within less than a day's dIstance Similarly, the coefficient for one-half to one day's dIstance increases to 0 90 (076 + 014) m the case of more than two days' dIstance

The coeffICIent of the crop area variable IS statistically SIgnificant at the 10-percent level of sIgmficance in thIS equation, which was not the case for Bheri and Rapti as a whole

80

TABLE 611 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF

CONSUMPTION AND FRUIT PRODUCTION

Variable Rapti Sheri LCOT - 101 * - 093

LCROP 024 -.022

HHHNO .005 008

LFRU 878* 872*

LTCROPA 053 063

LTINCOM 006 203

LVEG 029 - 012

SMC09 033 - 013

LLiV 013 - 016

Constant) 401 063

Adlusted, R2= 85 82

F-statlstlcs, F= 17353" 5996·

No of observations N= 271 116

Note • denotes significant at 1 % level of significance Dependent variable = logarithm of value of frUit consumption of household

Definitions of Independent variables

LCOT LCROP HHNO LFRU LTCROPA LTINCOME LVEG SMC09 LLiV

= logarithm of value of cottage Industry products = logarithm of value of crop production = household size = logarithm of value of frUit production = logarithm of crop area measured In hectares = logarithm of total Income derived from all sources = logarithm of value of vegetable production = no of seasonal migrants In the household = logarithm of value of livestock production and sale

81

TABLE 612 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND FRUIT PRODUCTION, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Variable Rapti LCOT - 073** LCROP 018 LFRU 757 LVEG 005 LLiV 016 LTCROPA 112*** LTINCOM 023 HHNO 001 SMC09 023 DOD - 603* DOD? - 567* DOD, - 594** SOD 195**

SOD? 138** SOD, 191** Constant) 725**

Adjusted, R2= 85 F-statlstlcs, F= 111 90* No of observations N= 271

Note * denotes significant at 1 % level of significance, ** denotes significant at 5% level of significance, and *** denotes significant at 10% level of significance

Dependent van able = loganthm of value of frUit consumption of household

Definitions of Independent vanable LCOT = loganthm of value of cottage Industry products LCROP = loganthm of value of crop production LFRU = loganthm of value of frUit production L VEG = loganthm of value of vegetable production LLiV = loganthm of value of livestock production and sale L TCROPA = loganthm of crop area measured In hectares L TINCOME = loganthm of total Income denved from all sources HHNO = household size SMC09 = no of seasonal migrants In the household

Bheri - 043 - 024 1 008*

023 - 011

071 074 007 009

1467* 164 191

- 388 - 011 - 022

273

87 5760*

116

0001 = Intercept dummy vanable, 0001 =1 for less than Y2 day distance and zero otherwise 0002 = Intercept dummy van able, 0002= 1 for Y2 -1 day dIstance and zero otherwIse 0003 = Intercept dummy vanable, 0003 = 1 for 1-2 days dIstance and zero otherwIse SOOI = slope dummy vanable, S001= 0001 X LFRU S002 = slope dummy vanable, S002= 0002 X LFRU S003 = slope dummy vanable, S003= 0003 X LFRU

In Table 6 13, the dummy vanables for locations above 2,000 meters were excluded so that the coeffICIents of the mtercept and the dummy vanables could proVIde the dIfferences WIth respect to the coeffICIent of dummy variables excluded from the model

The frUit consumption mcome elaStICIty IS 076 and hIghly sIgmficant The coeffICIent of the vanable measunng crop production IS sIgmficant for locatIOns above 2,000 meters m RaptI, as IS the case for RaptI as a whole The frUit consumption elaSticItIes for other locations are around 0 96 (for those below

82

2,000 meters) For households In the 1,000-to-l,500-meter and above-2,000-metercategones, the elaSticItIes are statistIcally insigmficant.

In Bhen, the fruit consumption income elaStICIty IS 0 97 and hIghly sIgnificant, but the Intercept term is statistIcally InSIgnifIcant for those households in the 1 ,000-to-1 ,500-meter range For those below 1,000 meters, the coefficient of the intercept IS 1 29 and highly sigmficant, with an elastIcity of 0 60

TABLE 613 REGRESSION RESULTS FOR RELATIONSHIP BETWEEN VALUES OF CONSUMPTION AND

FRUIT PRODUCTION, BY ALTITUDE

Variable LCOT LCROP

LFRU LVEG LLiV LTCROPA LTINCOM HHNO SMC09 DOD DOD,

0000 SDE SDE,

SDEo (Constant)

Adjusted, R2=

F-statlstlcs, F=

No of observatIons, N=

frUIt consumptIon elastICIty WIth resoect to Income

Note • denotes slgnrflcant at 1 % level of slgnrflcance and .- denotes slgnrfrcant at 5% level of slgnrflcance

Rapti - 053--

002 758-

012

023 116--

022 - 001

- 027 - 610-

- 183 - 855-

200--

055 213· 678--

86 11559-

271

076

Dependent vanable = loganthm of value of frUit consumption of household

DefinItIons of Independent vanables

Bheri - 062

- 038 022 008-

011 080 120 004

- 022 1 291-

- 362-

- 011

- 022 - 062

88 586-

116

DOE1 = Intercept dummy vanable, DOE1= 1 for less than 1,000m altitude and zero otherwIse DOE2 = Intercept dummy vanable, DOE2= 1 for (1,000-1 ,SOOm) altitude and zero otherwIse DOE3 Intercept dummy vanable, DOE3= 1 for (1 ,SOO-2,000m) altitude and zero otherwIse SDE, = Slope dummy vanable, SDE1= DOE1 x LFRU SDE2 = Slope dummy vanable, SDE2=DOE2 x LFRU SDE3 Slope dummy vanable, SDE3=DOE3 x LFRU

All other vanables are as defined above

83

6.4 DETERMINATION OF FRUIT PRODUCTION

The team regressed the value of fruIt productIOn wIth mcome from other sources, total mcome, household SIze, total crop area, and number of seasonal mIgrants m the household The lmear regressIon results, estimated separately for RaptI and Bhen, are presented m Table 6 14 The F-values for both equatIOns are hIghly sIgmficant, but the adjusted R 2 values show that m the case of RaptI, 40 percent of the total vanatIOn m mcome IS explamed by the set of explanatory vanables, whIle for Bhen, only 17 percent of the total vanatIOn m mcome IS explamed by thIS set

A value of 0 39 (Rapt!) for R2 for cross-sectIOnal data IS consIdered to be qUIte good, but an R2 of o 17 (Bhen) IS consIdered low by the same standards When, however, value of fruIt consumptIOn IS added as an explanatory varIable, the value of R2 mcreases, and the SIgn and SIgnIfIcance of the coeffIcIents of some vanables change (see Table 6 15)

TABLE 614 REGRESSION RESULTS FOR DETERMINANTS OF FRUIT PRODUCTION

Variable Rapt! HHNO - 703 34*

VEG - 40

TINCOME 39*

TCROPA 35784 SMC09 -54896

LlV - 30* CROP - 38*

COT - 43* I{Constant) 262950

Adjusted, R2= 39 F-statlstlcs, F= 5246* No of observations N= 622 Note • denotes significant at 1 % level of significance

Dependent vanable = value of frUit production per household

Definitions of Independent vanables

TINCOME LlV CROP = COT = TCROPA = PCROPA = ICROP = HHNO = SMC09 =

Total Income denved from all sources In Rs Value of livestock production and sale In Rs Value of Crop production In Rs Value of cottage Industry products In Rs Crop area measured In ha Paddy crop area measured In ha Irrigated crop area measured In ha Household size Number of seasonal migrants In household

Bheri - 062 - 038

022 008*

011 080 120 004

-48245

17 770'

260

84

TABLE 615 REGRESSION RESULTS FOR DETERMINANTS OF FRUIT PRODUCTION,

ADJUSTED FOR FRUIT CONSUMPTION

Variable Raptl HHNO - 12266-VFRUC 120-

VEG -001-

TINCOME 001*

TCROPA 3913

SMC09 30030*·

LlV - 01* CROP - 00 COT 09-

Constant) 79678

Adjusted, R2= 98 F-statlstlcs, F= 5651 84-

No of observations N= 622

Note - denotes significant at 1 % level of significance and -- denotes significant at 5% level of significance

Dependent vanable = value of frUit production per household

Definitions of Independent vanables

VFRUC = Value of frUit consumption per household

All other vanables are defined In Table 6 14

Sheri 8848 125-

005

000 -15818

20635*

00 03 04

-63638-

98 215159-

260

The coefficients of some of the variables III the case of RaptI are SIgnificant III both Tables 6 14 and 6 15, but the number of seasonal mIgrants IS statistically sIgnIfIcant only m the latter, and the coeffIcIent of crop production IS statistically significant only in the former In addition, the magnItudes of the coeffIcIents change, and the number of seasonal immIgrants and mtercepts becomes statIstIcally sIgnifIcant, when the vanable measunng the value of fruIt consumptIon is added.

85

CHAPTER SEVEN

LIVESTOCK

Ratsmg lIvestock IS an mtegral part of the farmmg system m rural areas of Nepal, mc1udmg the study area In fact, crop productlOn m the present context cannot be sustamed wIthout bemg mtegrated WIth lIvestock systems The Importance of lIvestock, therefore, IS best reflected withm the totalIty of the farmmg system rather than m a study of the lIvestock sector alone

LIvestock m Nepal provIde manure for crops, power for almost all agncultural operatlOns (such as plowmg, threshmg, and transportmg farm produce), and cash mcome, as well as meat, mIlk, and other by-products

This chapter presents the percentage dIstnbutlOn of households raIsmg lIvestock and poultry It also presents such mformatlOn as number of lIvestock and mIlk productlOn per household, value of productlOn, consumptlOn of lIvestock products, estImates of lIvestock consumptlOn, and mcome elastICIties by altitude and dIstance for RaptI and Bhen

7.1 LIVESTOCK RAISING

7.1.1 Distribution of Households Raising Livestock

Tables 7 1 and 7 2 present the dIstnbutIon of households ratsmg dIfferent types of lIvestock and poultry m Raptl and Bhen, by altItude and dIstance, respectIvely Of the lIvestock prevalent m the sample areas, the most common are bullocks, whIch are raIsed by more than 85 percent of households overall m both zones, and by at least 81 percent of households at each elevatIon and dIstance from the road For all other types of lIvestock and poultry, the percentage ratsed vanes by dIstance and altItude After bullocks, chIckens, male goats, cows, and mdkmg buffaloes are ratsed by the next hIghest percentage of households overall m the two zones

86

TABLE 71 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LIVESTOCK, BY ALTITUDE

Livestock Rapti Sheri

<1,000 1,000- 1,500- 2,000+m Total <1,OOOm 1,000-1,500m Total m 1,500m 2,000m

Male buffaloes 263 174 11 6 172 173 14 1429 142

Bullocks 835 81 4 888 897 856 86 8524 854

POnies 00 1 1 51 00 21 0 095 08

Mules 00 00 00 69 1 0 0 0 00

Male goats 295 655 879 184 587 36 5143 484

Female goats 31 8 295 433 253 342 18 2714 254

Pigs 61 7 60 186 333 263 0 238 1 9

Sheep 436 23 256 31 295 32 381 93

Milking buffaloes 421 596 530 333 498 64 7095 696

Cows 677 519 767 828 683 46 61 9 588

Chickens 81 2 820 735 747 778 50 4857 488

Ducks 188 00 98 00 75 0 0 00

Pigeons 173 98 42 1 2 83 0 1 9 1 5

Analyzmg the data by dIstance, after bullocks, mllkmg buffaloes and chIckens are rmsed by a large percentage of households withm most dIstances m Bhen, while cows are very popular among those hvmg at most dIstances m both Rapu and Bhen

TABLE 72 PERCENTAGE DISTRIBUTION OF HOUSEHOLDS REPORTING LIVESTOCK, BY DISTANCE

Rapti Shen

<%day %-1 day 1- 2 days 2+ days <%day %-1 day 1- 2 days 2+ days

Male buffaloes 158 152 277 161 164 59 98 289

Bullocks 857 814 892 903 873 863 863 808

POnies 00 60 24 00 00 00 1 0 1 9

Mules 00 00 00 65 00 00 00 00 Male goats 55 995 264 194 40 1137 284 327 Female goats 395 372 205 258 236 41 2 196 231 Pigs 452 87 00 312 00 78 1 0 00 Sheep 27 241 482 302 328 2 0 97 Milking buffaloes 324 607 940 376 673 314 804 885

Cows 757 678 313 81 7 491 863 588 423

Chickens 807 721 831 763 509 706 392 442 Ducks 97 11 5 00 00 00 00 00 00 Pigeons 139 33 96 1 1 00 20 20 1 9

87

7.1.2 Livestock Numbers and Production

The average number of bullocks per household In RaptI IS 2 7, rangIng from a high of 3 7 at elevatIOns below 1,000 meters to a low of 2 1 above 2,000 meters (see Table 73)

In Rapti, the average number of cows per household IS positively correlated with altItude, rangIng from 1.7 below 1,000 meters to 4 1 above 2,000 meters Male and female goats are also posItively correlated with altttude, but only up to levels of 1,500 to 2,000 meters Sheep are plentIful (2 0 and 1 7 per household, respectively) In two 10catIOns--below and above 1,000 meters Pigs are raised maInly at elevatIOns below 1,000 meters (1 6 per household) Poultry ammals, espeCially chIckens, are negatively correlated wIth altitude In RaptI The average number of chickens per household decreases from 9 2 below 1,000 meters to 5 2 above 2,000 meters

In Bhen, the average number per household of all poultry and lIvestock ammals, except mIlking buffaloes, IS smaller than In Rapu It should be noted that In Bhen, the average number per household of all lIvestock and poultry ammals (except sheep and chIckens) IS highest at elevatIOns of 1,000 to 1,500 meters.

When analyzIng the data based on distance to the nearest road head, the relationship between dIstance and hvestock held by each household generally remaInS unclear, except m the case of bullocks, whose average number per household decreases wIth dIstance from the road (see Table 7 4) In RaptI, the average number of mIlkIng buffaloes per household IS highest (2 2) at locatIOns wIthIn one to two days from the road and lowest (0 8) at locatIOns wIthIn less than one-half day's dIstance The average number of cows averages the hIghest (4) at locations more than two days from roads, and the lowest (06) at locatIOns wIthIn one to two days from the nearest road

In Bhen, households wIthIn all dIstances, except one to two days, have the same number (2 2) of bullocks The average number of cows, goats, and chIckens per household IS hIghest In locatIOns wIthIn one-half to one day's walk from the nearest road At thIS dIstance, however, mIlkIng buffaloes are the least plentiful (0 9 per household)

7.1.3 Milk Production

Data on annual milk production (from both buffaloes and cows) were also collected from the sampled households In Raptt and Bhen Tables 7 3 and 7 4 present InfOrmatIOn on per-household mIlk productIOn by altitude and dIstance, respectively The tables reveal that milk productIOn from both cows and buffaloes, m general, IS lower m Bhen than m Raptl The dIstnbutIOn of mIlk productIOn m Rapt!, based on altItude, mdicates that It IS hIghest (700 lIters per household) at 1,500 to 2,000 meters and lowest (250 lIters per household) above 2,000 meters For Bhen, the hIghest (322 lIters) per-household mIlk productIOn occurs below 1,000 meters Although the number of cows IS greater than the number of mIlkmg buffaloes In Rapt!, total mIlk productIOn m the zone from buffaloes IS much greater than from cows In all places except those above 2,000 meters

Livestock Type

Buffalo (male)

Bullock

Poney

Mule

Goat

Goat (female)

PIQS

Sheep

Buffalo

Cow

Chicken

Ducks

Pigeon

88

TABLE 7 3 NUMBER AND PRODUCTION (IN LITERS) OF LIVESTOCK PER HOUSEHOLD,

BY LIVESTOCK TYPE AND ALTITUDE

Raptl Bheri

<1,000m 1,000- 1,5000- 2,000m+ <1,000m 1,000-1,500m 2,000m Total Total 1,500m

No. Prod. No. Prod. No. Prod. No. Prod. No. Prod. No. Prod. No. Prod.

08 00 03 00 02 00 03 00 04 00 018 0 018 0

37 00 23 00 27 00 2 1 00 27 00 1 96 0 215 0

00 00 00 00 01 00 00 00 00 00 0 0 001 0

00 00 00 00 00 00 04 00 01 00 0 0 0 0

05 00 1 8 00 2 1 250 06 00 1 5 87 09 01 1 2 1 3

09 00 1 2 00 22 00 14 00 1 5 00 031 1 59 148 011

1 6 00 01 00 02 00 05 00 05 00 0 0 003 0

20 20 04 00 06 07 1 7 31 1 0 1 1 094 0 008 143

1 1 2544 13 3766 1 3 4102 1 2 924 1 2 321 2 1 43 2997 1 65 191

1 7 351 1 9 1278 28 2888 41 1580 25 1678 076 2204 178 325

92 156 78 283 70 37 52 138 75 150 38 024 373 02

08 26 00 00 1 7 136 00 00 08 53 0 0 0 0

1 3 00 07 00 02 01 00 00 06 00 0 0 005 0

Total Total

No Prod.

02 00

2 1 05

00 00

00 01

1 2 29

13 09

00 o 1

02 09

1 6 2258

1 6 625

37 56

00 1 6

00 00

A sIgmficant dIfference between mIlk YIeld from buffaloes and cows IS also observed by altItude The average mIlk productIOn per buffalo IS hIghest (410 hters) at 1,500 to 2,000 meters and lowest (92 hters) at locatIOns above 2,000 meters In Rapt! For Bhen, the annual mIlk productIOn per buffalo IS hIghest (300 hters) at less than 1,000 meters

SImIlarly, the annual mIlk productIOn per cow In RaptlIS hIghest (289 hters) In locatIOns at 1,500 to 2,000 meters and lowest (35 hters) In locatIOns below 1,000 meters In Bhen, the annual mIlk YIeld per cow IS hIghest (33 hters) at elevatIOns of 1,000 to 1,500 meters

In RaptI, both buffalo and cow mIlk productIOn per household IS posItIvely correlated wIth altItude, except at locatIOns above 2,000 meters At thIS elevatIOn, buffalo mIlk productIOn per household IS the lowest of all elevatIOns Cow mIlk productIOn at thIS elevatIOn, on the other hand, IS only second lowest among all elevatIOns

In terms of dIstance, In Bheri, buffalo mIlk productIOn per household IS hIghest at dIstances of less than one-half day from the nearest road, and lowest at locatIOns wIthIn one-half to one day's dIstance Cow mIlk per household IS hIghest at locatIOns WIthIn one-half to one day's dIstance and lowest at more than two days' dIstance ThIS mdicates that there IS no dIstInct relatIOnshIp between mIlk productIOn and dIstance

89

TABLE 74 NUMBER AND PRODUCTION (IN LITERS) OF LIVESTOCK PER HOUSEHOLD,

BY LIVESTOCK TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD

Rapti Sheri Livestock Type <% day %-1 day 1-2 days 2 days+ <% day %-1 day 1-2 days 2 days+

No

Buffalo (male) 05

Bullock 33 Pony 00 Mule 00 Goat 14 Goat (female) 1 5 Pigs 1 0 Sheep 1 2 Buffalo Milk 08 Cow Milk 27 Chicken 87 Ducks 04 Pigeon 1 0

Prod No Prod No Prod No Prod No. Prod No Prod

00 03 00 04 00 03 00 02 00 01 00 00 25 00 23 00 2 1 00 22 00 22 00 00 01 00 00 00 00 00 00 00 00 00 00 00 00 00 00 04 00 00 00 00 00

0 25 295 07 0 06 0 1 2 01 27 34 00 1 9 00 07 00 14 00 1 1 1 6 26 04 00 01 00 00 00 05 00 00 00 01 00 1 1 04 06 09 0 1 6 29 1 0 0 0

2053 1 5 5399 22 4674 1 3 988 1 8 2997 09 880 2394 22 151 0 06 45 40 1480 1 0 220 3 1 574

97 69 35 72 590 55 137 41 02 70 07 1 4 2 1 160 00 00 00 00 00 00 00 00 00 03 01 03 00 00 00 00 00 00 00

7.2 RELATIONSHIP BETWEEN LIVESTOCK PRODUCTION AND CONSUMPTION

No Prod No Prod

01 00 04 00 20 00 22 00 00 00 00 00 00 00 00 00 07 09 08 0 07 00 1 2 00 00 00 00 00

0 0 02 53 1 6 2720 21 1394 1 5 375 08 1 1 33 01 1 3 00 00 00 00 00 o 1 00 00 00

The value of hvestock productIOn was denved by addmg annual mcome from the sale of lIvestock and hvestock products, such as mllk from buffaloes and cows The value of hvestock consumptIOn was denved by subtractmg the sale of hvestock from the total value of lIvestock productIOn and addmg the cash spent on purchasmg hvestock and lIvestock products for consumptlOn The values of lIvestock productIon and consumptlon per household thus denved are grouped by altitude and distance m Tables 7 5 and 7 6, respectlvely

Table 75 presents the mean, the coeffIcIent of vanatlOn (c v), the values of lIvestock productlOn and consumptIon, and the percentage of consumptlOn over productIOn, by altItude The data for both Raptl and Bhen are categonzed by the same range of altItudes as m pnor tables As seen m the table, the values of hvestock productIOn and consumptIOn In Rapt! are hIgher than In Bhen by at least 30 percent The percentage of consumptIOn over productIOn IS higher In Bhen than In Rapt! because of Bhen's lower productIOn value

Table 7 5 further shows that m Raptl, both production and consumptlOn of lIvestock and lIvestock products are generally lowest In 10catlOns below 1,000 meters ProductIOn and consumptIOn m the zone Increase WIth altItude up to elevatIOns of 1,500 to 2,000 meters In Bhen, the values of productIOn and consumptIOn are hIghest m locatIons below 1,000 meters The vanatlOn In lIvestock productIOn and consumptlOn between RaptI and Bhen lS less compared wlth vegetables and fruIt

90

TABLE 7 5 LIVESTOCK PRODUCTION AND CONSUMPTION VALUES AND CONSUMPTION PERCENTAGE

PER HOUSEHOLD, BY ALTITUDE

Rapt. Bhen Altitude Range Livestock Livestock Consump. Livestock Livestock Consump.

Prod. Consump. Prod. Consump. (Rs) (Rs) (Rs) (Rs)

<1,000m Mean 8988 6957 77% 14744 12720 86% CV 1 5 1 3 38 43

1,000- Mean 9669 8439 79% 5683 4626 81% 1,500m CV 17 1 8 1 3 1 3

1,500- Mean 10608 9025 86% N/A N/A N/A 2,000m CV 1 1 12

2,000m+ Mean 9504 6339 67% N/A N/A N/A CV 2 1 1 4

Total Mean 9892 8056 82% 7454 6208 83% CV 1 6 14 35 39

Note C V=coefflclent of vanatlOn

Table 7 6 presents the mean, the coefficient of vanatlOn (c v) of productIOn and consumptIOn, the values of hvestock productIOn and consumptIOn, and the percentage of consumptIOn over productIOn, by distance It is interestmg to note that the values of productIOn and consumption are highest m locatIOns at mid-distances (one-half to one day and one to two days) m Raptl but are generally the opposite m Bhen

TABLE 7 6 LIVESTOCK PRODUCTION AND CONSUMPTION VALUES AND CONSUMPTION PERCENTAGE PER

HOUSEHOLD, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Rapti Bheri Distance Livestock Livestock Consump. Livestock Livestock Consump.

Prod. Consump. (Rs) Consump. JRs) (Rs) (Rs)

<% day Mean 8524 7253 85% 14744 12720 86% CV 1 5 1 7 38 47

%-1 day Mean 11202 9347 83% 4198 3263 78% CV 1 2 1 4 1 3 1 3

1-2 days Mean 11218 9674 86% 6146 5557 90% CV 1 6 1 7 1 1 1 1

2+ days Mean 9505 6351 67% 6184 4179 68% CV 20 1 6 1 4 1 6

Note: C V=coefflclent of vanatlOn

91

7.3 ESTIMATION OF LIVESTOCK CONSUMPTION INCOME ELASTICITY

The value of lIvestock consumptIOn per household was regressed wIth a set of mcome vanables includmg per-household mcome from lIvestock, household SIze, and cropped area per household All the vanables, except household SIze, are expressed m loganthm form so that the coeffICIent of the vanable representmg the value of lIvestock consumptIOn can also provIde the lIvestock consumptIOn elaStiCIty The regressIOn equations estimated for Raptl and Bhen are presented overall m Table 7 7, and by altItude and dIstance m Tables 78 and 79, respectively

The hIghly sIgmficant (at the 1-percent level of sIgmficance) F-values and moderately hIgh R2 values mdicate that the model used IS valId The regressIOn results show that the vanable representmg mcome from hvestock IS sIgmficant at the I-percent level III Raptl and Bhen, and that the vanable for total mcome IS sIgmficant at the same level m RaptI The vanables representmg crop area and mcome from crops are sIgmficant at the 5-percent and to-percent levels of sIgmficance, respectively, m Raptl In Bhen, however, the only statIstically sIgmficant varIable IS that representmg mcome from lIvestock In both zones, all other vanables are statIstIcally mSIgmflcant

TABLE 7 7 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND PRODUCTION OF LIVESTOCK

Variable Raptl

HHNO 001

LCOT 015

LCROP - 066"""

LLiV 261"

LTCROPA 145""

LTINCOM 597*

LFRU - 032

LVEG - 070

(Constant) 555

Adjusted, R2= 56

F-statlstlcs= 5105'

No of observations, N= 317

Note * denotes slgmficant at 1 % level of slgmflcance, ** denotes slgmficant at 5% level of slgmflcance, and *** denotes slgmflcant at to% level of slgmflcance

Dependent varlable=logarlthm of value of hvestock consumptIOn

Sheri

009

- 098

043

286"

064

212

- 074

095

1 641

60

3063'

162

92

DefmItIons of mdependent van abies:

HHNO = Household SIze LCOT = LogarIthm of value of cottage mdustry products LCROP = LogarIthm of value of crop productIOn LLIV = Loganthm of value of livestock productIOn and sale

LTCROPA = Logarithm of crop area measured In hectares LTINCOME = Loganthm of total mcome derived from all sources LFRU = Loganthm of value of fruIt productIOn LVEG = Loganthm of value of vegetable productIOn (Constant)

TABLE 7 8 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND PRODUCTION OF LIVESTOCK, BY ALTITUDE

Vanable Rapti

HHNO 008

LCOT - 001

LCROP - 037

LLiV 187*

LTCROPA - 099

LTINCOM 597*

LFRU - 042

LVEG - 088***

DOE1 - 873

DOE2 -138

DOE3 - 280

SDE1 197*

SDE2 047

SDE3 076

(Constant) 807***

Adjusted, R2= 591

F-statlstlcs= 33794

No of observations, N= 317

Note * denotes sIgmficant at 1 % level of sIgmficance, ** denotes sIgmficant at 5% level of sIgmficance, and *** denotes sIgmficant at 10% level of sIgmficance

Bheri

009

- 079

041

301*

062

162

- 055

107

294***

- 072

1669*

597

2492

161

93

Dependent vanable=loganthm of value of hvestock consumptlOn

DefImtlOns of mdependent van abIes

HHNO = Household SIze LCOT Loganthm of value of cottage mdustry products LCROP Loganthm of value of crop productlOn LLIV = Loganthm of value of hvestock productlOn and sale LTCROPA = Loganthm of crop area measured m hectares LTINCOME = Loganthm of total mcome denved from all sources LFRU = Loganthm of value of frUlt productIon LVEG = Loganthm of value of vegetable productlOn DOE! = Intercept dummy vanable, D0p = 1 for less than 1,000 meters and zero

otherwIse DOE2 = Intercept dummy vanable, DqE= 1 for 1,000 to 1,500 meters and zero

otherwIse DOE3 = Intercept dummy vanable, DQE= 1 for 1,500 to 2,000 meters and zero

otherwIse SDEJ = Slope dummy vanable, SDE!= DOE! x LFRU SDEz = Slope dummy vanable, SDE2=DOEz x LFRU SDE3 = Slope dummy vanable, SDE3=DOE3 x LFRU

The livestock consumptlOn mcome elastICItIes as represented by the coeffIcIent of ltvestock income are 0 26 for RaptI and 0 29 for Ehen Interestmgly, the coeffIcIent of the vanable representmg total mcome IS much larger for RaptI than the coeffIcIent of mcome from hvestock ThIS Imphes that a 100-percent mcrease m total mcome WIll mcrease consumptIon of hvestock m RaptI by approXImately 60 percent, m contrast to the 21-percent mcrease m hvestock consumptIon that would result from a 100-percent mcrease m total mcome m Ehen Ehen's total mcome vanable, however, IS statIstIcally mSIgmficant

The coeffICIent of mcome from crops IS small, negatIve, and sIgmficant m RaptI, suggestmg that resources for crop productIon and hvestock are competmg WIth each other The same vanable for Ehen IS statIstIcally mSlgmficant

Table 7 8 presents the regresslOn results from addmg dummy vanables m the model presented m Table 7 7 Dummy vanables were added to examme vanatlOn m relatlOnship by altItude NeIther the slope nor the mtercept (constant) dummy vanable for the category representmg altItudes above 2,000 meters IS mcluded, gIven that the estImated equatIOn by default prOVIdes those estImates The results show that hvestock consumptIOn elaStIcIty IS estImated to be 0 19 for altItudes above 2,000 meters The lIvestock mcome elastICItIes for the 1 ,OOO-to-l ,500-meter and 1 ,500-to-2,000-meter categones dIffer lIttle from the elastICIty estImated for the above-2,000-meter category The elastICIty for the category representmg altItudes below 1,000 meters IS estImated to be approxImately -0 87 and statIstIcally sIgmfIcant for RaptI In Ehen, the hvestock consumptIOn mcome elaStICIty IS estImated to be 0 29 for both categones of altItude (below 1,000 meters and 1,000 to 1,500 meters)

Exammmg regresslOn results estImated by usmg dummy varIables for VarIatlOn by walkmg distance to the nearest road, the hvestock consumptlOn mcome elastICItIes are 0 19 and 0 27 for the category representmg 10catlOns more than two days' dIstance m RaptI and Ehen, respectIvely The

94

estimated elaStiCIty for the category representmg the one-to-two-days dIstance IS statIstIcally mSIgmficant for both Raptl and Bhen However, the lIvestock consumptIOn mcome elastIcItIes for the one-half-to-one­day dIstance are -0 25 for Raptt and -0 60 for Bhen, the elastIcItIes for less than one-half-day's dIstance are -0 87 for Raptl and 0 28 for Bhen

TABLE 7.9 REGRESSION RESULTS FOR THE RELATIONSHIP BETWEEN VALUES OF CONSUMPTION

AND PRODUCTION OF LIVESTOCK, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Variable Rapti

HHNO 099

LCOT - 013

LCROP - 042

LLiV 186*

LTCROPA - 106

LTINCOM 585*

LFRU - 036

LVEG - 074

DOD, - 870*

DOD2 - 252

DOD3 - 074

SDD, 201*

SDD2 073***

SDD3 032

(Constant) 852**

Adjusted, R2= 596

F-statlstlcs= 3452

No of observations, N= 317

Note' * denotes SIgnifIcant at 1 % level of sigmficance, ** denotes sIgmficant at 5% level of sIgnifIcance, and *** denotes sIgnIfIcant at 10% level of sIgmficance

Dependent van able = loganthm of value of lIvestock consumptIOn

= = =

Household SIze Loganthm of value of cottage mdustry products Loganthm of value of crop productIOn

Bherl

013

- 012

-8704

269*

- 053

155

058

- 147

278

- 605*

220

- 050

178*

- 031

1 595*

637

2125

161

HHNO LCOT LCROP LLIV = Loganthm of value of hvestock productIOn and sale

LTCROPA LTINCOME LFRU LVEG DOD l

0002

0003

SDD l

SDD2

SDD3

= = = =

95

Loganthm of crop area measured In hectares Loganthm of total Income denved from all sources LogarIthm of value of fruIt productlOn LogarIthm of value of vegetable productlOn

= Intercept dummy varIable, 001;> = 1 for less than Yz day dIstance and zero otherWIse

= = =

Intercept dummy varIable, 0002= 1 for Y2 -1 day dIstance and zero otherwise Intercept dummy varIable, 0003 = 1 for 1-2 days dIstance and zero otherwIse Slope dummy varIable, SDD l = DOD l x LFRU

= Slope dummy vanable, SDD2= 0002 x LFRU

= Slope dummy varIable, SDD3= 0003 x LFRU

Vanable Rapti Shen

FRU - 179* - 612*

COT - 121 1446

HHNO -66736 -204157

TCROPA 164367 -5139352*

VEG - 238* - 393

TINCOME 221* 602

PRODCROP -175* - 011

(Constant) 3837740* -2802558

Adjusted, R2= 233 622

F-statlstlcs= 28000* 62162*

No of observations, N= 623 261

Vegetable consumption elastiCity with respect to Income 096

Note * denotes sIgmficant at 1 % level of sIgmficance, and ** denotes sIgmficant at 5% level of sIgmficance

Dependent vanable = value of lIvestock productlOn

HHNO LeOT LCROP LLIV LTCROPA LTINCOME LFRU LVEG

= = = = = = = =

Household SIze LogarIthm of value of cottage Industry products Loganthm of value of crop productIon Logarithm of value of hvestock productlOn and sale LogarIthm of crop area measured In hectares Loganthm of total Income denved from all sources LogarIthm of value of fruIt productIon LogarIthm of value of vegetable productlOn

97

CHAPTER EIGHT

COTTAGE INDUSTRIES

Cottage mdustnes are an Important source of nonfarm actiVIty among rural households m Nepal In thIs study, cottage mdustnes pnmanly refer to mformal, home-based production activItIes

As many as 29 dIfferent types of cottage-mdustry products are reported by at least a few households m one or more locatIOns m the survey areas Generally, most cottage-mdustry productIOn takes place dunng the agncultural slack seasons or dunng the leIsure tIme avaIlable after baSIC household needs are met Market-onented cottage-mdustry productIOns are, therefore, still very hmited

ThIS chapter presents the percentage dIstnbutIOn of households reportmg nonfarm, home-based productIOn of dIfferent Items, the amount of money mvested m purchasmg raw matenals for such productIOn, and mcome earned from the sale of cottage-mdustry products The data are presented, as in prevIOUS chapters, by altItude and dIstance for both RaptI and Ehen Fmally, the estImated values of total productIOn and consumptIOn are presented by altitude and dIstance m both zones as well

8.1 HOUSEHOLD INVOLVEMENT IN COTTAGE INDUSTRIES

Tables 8 1 and 8 2 present the percentage of households reportmg productIOn of dIfferent home­based items, by altitude and walkmg dIstance, respectively The tables mdicate that woven products such as rugs and mats, and certam home-processed foods such as ghee (butter), chana (dned radIsh shces), smh (dned fermented radIsh shces), gundruk (dned fermented vegetable leaves), and dned vegetable leaves, are the most commonly produced home-based products m both RaptI and Ehen

Ghee productIOn IS reported by more than 50 percent of the sampled households at altitudes above 1,000 meters m both RaptI and Ehen Smki and chana are reported by about 82 percent of RaptI households located below 1,000 meters Dned vegetable leaves (44 percent) are the next most popular food Item among households located below 1,000 meters m RaptI In Ehen, the productIOn of smkllchana (17 to 18 percent) IS, by contrast, much less than m Rapt! ThIS IS most hkely attnbutable to the hIgher productIOn of vegetables, such as radIshes, mustard leaves, and caulIflower, m Raptl than m Ehen

Nonfood home-based products, such as mats and rugs and bamboo and Alo products, are also produced by a good number of the sampled households m all altItudes m Raptl and Ehen

98

TABLE 81 PERCENTAGE OF HOUSEHOLDS INVOLVED IN COTTAGE INDUSTRIES, BY INDUSTRY TYPE

AND ALTITUDE

Industry Type Rapti Bherl

<1,OOOm 1 ,000-1 ,500m 1,500-2,OOOm 2,000m+ <1,OOOm 1,000-1,500m

Honey 53 51 282 129 1 9 153

Ghee 30.8 522 722 588 21 5 540

Buttermilk 255 109 258 364 39 86

Kuraunl 21 0 0 1 1 0 09

Gundruk 21 2 90 267 35 352 287

8lnkl/chana (radishes) 81 9 428 645 223 176 167

Dnedleaves 436 71 282 235 11 7 14

Masyaura/tJtaura 95 26 23 1 1 0 11

Dned fruit 1 0 0 23 0 0 0

Chuk amllo (citrus) 95 77 81 0 1 9 28

Pickles 276 45 09 0 0 09

Tama (bamboo shoots) 202 84 23 0 0 11 9

Dried ginger 0 71 0 0 0 09

Woolen cloth 2 1 0 0 35 1 9 09

Cotton cloth 1 0 06 0 1 1 0 0

Coarse cloth 1 0 0 0 0 0 0

Herbs 0 0 0 1 1 0 0

Intoxicants 361 58 23 470 0 28

Mats and related objects 670 64 258 164 745 526

Bamboo products 95 64 62 294 98 95

Nepali paper 0 0 04 0 0 0

Iron goods 0 06 0 1 1 1 9 0

Bricks 1 0 0 0 0 0 0

Leather qoods 0 0 0 0 1 9 0

Earthen pots 1 0 0 0 0 0 0 Tallonnq 1 0 0 0 0 0 04 Alo products 0 1 3 43 141 0 0

Bhangra 0 0 138 352 0 0 Radhl/pakhl 0 06 04 341 0 09

99

TABLE 8 2 PERCENTAGE OF HOUSEHOLDS INVOLVED IN COTTAGE INDUSTRIES, BY INDUSTRY TYPE AND

WALKING DISTANCE TO THE NEAREST ROAD HEAD

Industry Type Raptl Shen

<% Day %-1 Day 1-2 Days >2 Days <Y2 Day Y2-1 Day 1-2 Days >2 Days

Honey 53 232 37 153 1 9 11 7 88 31 5

Ghee 380 604 71 6 593 21 5 352 549 684

Buttermilk 336 197 24 384 39 39 137 35

Kuraum 1 7 0 0 1 1 0 0 1 9 0

Gundruk 241 228 24 54 352 41 1 362 35

Slnkl/chana (radishes) 803 565 444 274 176 196 88 280

Dned leaves 437 228 0 252 11 7 0 29 0

Masyauraltltaura 107 1 9 12 1 1 0 1 9 21 5 0

Dned frUit 08 1 9 0 0 0 0 0 0

Chuk amllo (citrus) 107 93 24 0 1 9 39 29 17

Pickles 285 1 1 0 0 0 0 1 9 0

Tama (bamboo shoots 241 27 37 0 0 0 235 1 7

Dned ginger 0 03 123 0 0 0 0 35

Woolen cloth 17 0 0 33 1 9 0 09 1 7

Cotton cloth 08 0 12 1 1 0 0 0 0

Coarse cloth 08 0 0 0 0 0 0 0

Herbs 0 0 0 1 1 0 0 0 0 Intoxicants 303 03 11 1 483 0 1 9 0 87

Mats and related objects 616 205 0 208 745 784 696 0

Bamboo products 107 65 1 2 296 98 176 107 0

Nepah~~er 0 03 0 0 0 0 0 0 Iron goods 0 0 1 2 1 1 1 9 0 0 0 Bncks 08 0 0 0 0 0 0 0

Leather goods 0 0 0 0 1 9 0 0 0 Earthen pots 08 0 0 0 0 0 0 0 Tallonnq 08 0 0 0 0 0 0 1 7

Alo products 0 27 24 153 0 0 0 0 Bhangra 0 11 2 0 329 0 0 0 0 Radhl/pakhl 0 07 0 31 8 0 0 0 35

8.2 CASH-INCOME GENERATION FROM COTTAGE INDUSTRIES

The total number of cottage mdustnes from whIch at least some households earn money at one or more altItude categones m Raptl and Bhen IS about 20 However, among these 20, only 4 m RaptI and 2 m Bhen generated more than Rs 100 m cash mcome per household last year These 6 mdustnes are mamly food based bee keepmg (honey), ghee makmg, gmger drymg, and cloth weavmg m Raptl, and bee keepmg (honey) and ghee makmg m Bhen

100

The total value of raw matenals purchased and mcome earned from the sale of all types of cottage­mdustry products were Rs 159 and Rs 1,257, respectIvely, per RaptI household m 1996 (see Table 8 3) In Bhen, however, the value of raw matenals purchased and mcome earned from product sales totaled only about Rs 54 and Rs 534 per household, respectIvely, last year, whIch IS more than 50 percent less than mRaptI

It should be noted that cottage industnes that make nonfood products such as woven cloth and Iron goods must mvest a slgmfIcant amount m certam raw matenals that other industries do not use

In Rapti, the annual income earned per household last year from the sale of cottage-mdustry products was greatest (Rs 1,835) at altItudes of 1,500 to 2,000 meters and lowest (Rs 807) above 2,000 meters In Bhen, the largest amount earned (Rs 560) occurred at elevatIOns of 1,000 to 1,500 meters

TABLE 8 3 AVERAGE VALUE OF RAW MATERIALS PURCHASED (RMP) AND INCOME EARNED

(IN RUPEES) FROM THE SALE OF COTTAGE-INDUSTRY PRODUCTS, 1996, BY PRODUCT TYPE AND ALTITUDE

Product Raptl Shen Type <1,000m 1,000- 1,500-2,000 2,000+m Total Total <1,000m 1,000- Total

1,500m 1,500m

RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP

Honey 00 00 00 129 00 9385 00 258 00 3329 00 00 00 1564 00

Ghee 00 284 1 7 3639 00 8838 00 969 05 4333 00 71 4 00 3305 00

Buttermilk 00 00 00 00 00 00 00 34 00 05 00 00 00 63 00

Slnkl/chana 00 09 00 11 1 00 00 00 00 00 35 00 00 00 48 00 (radishes)

Chuk amllo 00 1 1 03 61 00 25 00 00 01 29 00 00 00 1 5 00 (citrus)

Pickles 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00

Tama 00 00 1 6 295 00 00 00 00 05 87 00 00 00 00 00 (bamboo shoots)

Dned ginger 00 00 00 4000 00 00 00 00 00 1175 00 00 00 00 00

Woolen 00 00 00 00 00 00 00 00 00 00 00 00 03 00 02 cloth

Cotton cloth 3413 6080 1 1 546 00 00 00 00 743 1478 00 00 00 00 00

Coarse 3556 4444 00 00 00 00 00 00 770 963 00 00 00 00 00 cloth

Herbs 00 00 00 0.0 00 00 00 1 7 00 02 00 00 00 00 00

IntOXicants 00 22 00 55 00 1 2 101 1927 1 4 300 00 00 00 11 4 00

Mats and 00 47 00 1 1 06 00 00 00 02 13 00 00 00 00 00 related objects

Bamboo 00 00 00 81 00 46 00 1472 00 250 294 490 00 24 57 products

Iron goods 00 00 00 142 00 00 40 281 06 82 2353 2941 1 1 76 469

Total

Sale

1259

2798

5 1

38

1 2

00

00

00

00

00

00

00

92

00

11 5

636

101

Product Raptl Bhen Type <1,000m 1,000- 1,500-2,000 2,000+m Total Total <1,000m 1,000- Total Total

1,500m 1,500m

RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale

Leather 00 00 00 00 00 00 00 00 00 00 39 11 8 00 00 08 23 goods

Tallonng 00 89 00 00 00 46 00 00 00 35 00 00 00 357 00 287

Alo 00 00 00 00 00 00 00 230 00 33 00 00 00 29 00 23 products

Bhangra 00 00 00 00 00 00 00 214 00 31 00 00 00 00 00 00

Radhl/ 00 00 00 16 00 00 325 2671 46 386 00 00 02 00 02 00 pakhl

Total 6969 10987 47 9085 06 18352 466 8072 1593 12565 2686 4263 1 7 5595 538 5335

Table 8 4 presents raw-matenals and mcome data by dIstance from the nearest road The table mdicates that m Raptl, households located withm one-half to one day of the nearest road earned the hIghest total mcome (Rs 2,213) from the sale of cottage-mdustry products last year, those located less than one­half day away earned the lowest (Rs 601) In contrast, m Bhen, households located more than two days from the road earned the hIghest total mcome (Rs 1,638) from the sale of cottage-mdustry products last year, those at one-half to one day's dIstance earned the lowest (Rs 126)

TABLE 8 4 AVERAGE VALUE OF RAW MATERIALS PURCHASED (RMP) AND INCOME EARNED (IN RUPEES)

FROM THE SALE OF COTTAGE-INDUSTRY PRODUCTS, 1996, BY PRODUCT TYPE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD

Product Raptl Bhen Type <Y2 Day 1h-1 Day 1-2 Days >2 Days <1h Day 1h-1 Day 1-2 Days >2 Days

RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale

Honey 0 0 0 1105 0 78 0 24 0 0 0 0 0 29 0 571

Ghee 0 478 1 7 1048 0 6582 0 101 0 71 0 125 0 157 0 824

Buttermilk 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 233

Slnkl/chana 0 048 0 0 0 247 0 0 0 0 0 0 0 0 0 175 I (radishes)

Chuk amllo 0 057 03 768 0 293 0 0 0 0 0 0 o 314 0 0 I (citrus)

Tama 0 0 1 6 291 0 0 0 0 0 0 0 0 0 0 0 0 (bamboo shoots) Dried ginger 0 0 0 378 0 8842 0 0 0 0 0 0 0 0 0 0

Woolen 0 0 0 0 0 0 0 0 0 0 0 0 059 0 0 0 cloth

Cotton cloth 1766 314 0 0 24 122 0 0 0 0 0 0 0 0 0 0

Coarse 1839 230 0 0 0 0 0 0 0 0 0 0 0 0 0 0 cloth

Herbs 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0

IntOXicants 0 1 15 0 0 0 122 947 183 0 0 0 0 0 0 0 421

102

Product Rapti Sheri Type <112 Day 112-1 Day 1-2 Days >2 Days <112 Day 112-1 Day 1-2 Days >2 Days

RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP Sale RMP

Mats and 0 243 07 108 0 0 0 0 0 0 0 0 0 0 0 related objects

Bamboo 0 0 0 11 5 0 427 0 138 294 49 0 0 0 49 0 products Iron goods 0 0 0 0 0 31 71 379 26 235 294 0 0 0 0 421

Bricks 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Stone 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 objects

Leather 0 0 0 0 0 0 0 0 392 12 0 0 0 0 0 Igoods

Earthen 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 I pots

Tailoring 0 46 0 541 0 0 0 0 0 0 0 0 0 0 0

Ala 0 0 0 0 0 0 0 22 0 0 0 0 0588 0 I products

Bhangra 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0

Radhl/pakhl 0 0 0 1 62 0 0 304 250 0 0 0 0 0 0 088

Total 3605 6014 43 2213 24 1748 437 769 2686 4263 o 1255 059 174 509

When analyzmg annual sales of cottagelhome-based products by mdustry type and dIstance, the data mdlcate that in both Raptl and Bhen, ghee (butter) productIOn IS one of the higher mcome-earnmg actIvItIes m households located more than one-half day's walkmg distance from the road The prevalence of ghee makmg beyond the one-half-day dIstance perhaps ImplIes that the sellmg of fresh milk IS a preferred actIvity among households there

In RaptI, at households less than one-half day's dIstance from the road, cotton and weavmg are gammg Importance and are earnmg hIgh mcomes In Bhen, Iron goods (at less than one-half day's dIstance), bee keepmg (at more than two days' distance), and ghee makmg (at all dIstances) YIeld relatIvely hIgh amounts of mcome

Sale

0

0

281

0

0

0

0

132

0

0

0

1638

103

CHAPTER NINE ANALYSIS OF RELATIONSHIP OF INCOME SOURCES

As part of Its InveStigatIOn, the study team eStimated two types of annual household Income, gross total income and gross cash income, each of whIch is dIscussed In separate sectIOns below

The study team denved gross total Income by multIplYIng each of the total productIOn fIgures for cereal and cash crops, vegetables, fruIt, hvestock, and cottage Industnes by theIr correspondIng pnces, and totalIng the results It should be noted that In denvIng the hvestock fIgure, the team dId not account for (1) the value of meat that households consume from theIr own hvestock and poultry, and (2) the cost of productIOn of hvestock The team also deducted a certaIn amount of total productIOn In the case of crops, vegetables, and fruIt In order to allow for seed and post harvest waste and storage losses, as descnbed In prevIOUS chapters

The team's gross cash Income figures constItute the money households receIved from the sale of marketable surpluses of crops, hvestock, vegetables, fruIt, and cottage Industry and other nonfarm products

9.1 HOUSEHOLD GROSS TOTAL INCOME

Tables 9 1 and 9 2 present annual gross total Income and percentage share from dIfferent sources, by altItude and walkIng dIstance to the nearest road, respectively, In RaptI and Bhen Table 9 1 reveals that the annual gross total Income per household (Rs 63,455) In RaptI IS more than tWIce that In Bhen (Rs 30,491) The greatest contnbutors of Income are cereal and cash crops In Raptl (29 4 percent of total) and hvestock In Bhen (24 5 percent) It IS InterestIng to note that the percentage of vegetable Income to total Income (21 4 percent) In RaptI IS almost fIve times hIgher than In Bhen (45 percent)

Source

Cereal and cash crops

Livestock Vegetables FrUit Farm Income

Nonfarm Income

Total

Gross total Income

TABLE 91 ANNUAL GROSS TOTAL INCOME PER HOUSEHOLD AND

PERCENTAGE FROM DIFFERENT SOURCES, BY ALTITUDE (Rs)

Raptl

1,000· 1,500· <1,000m 1,500m 2,OOOm 2,000m+ Total <1,OOOm

474% 213% 230% 242% 294% 182%

11 1% 171% 149% 289% 155% 360%

136% 288% 242% 93% 214% 28%

82% 95% 120% 43% 97% 60%

803% 767% 742% 667% 760% 630%

197% 233% 258% 333% 240% 370%

1000% 1000% 1000% 100 0% 1000% 1000%

81,039 56,421 71,007 32,919 63,455 40,951

Bhen

1,000· 1,500m Total

256% 236%

204% 245%

51% 45%

87% 80%

597% 606%

403% 394%

1000% 1000%

27,951 30,491

104

In terms of farm versus nonfarm income, farm Income makes up three-fourths of the total gross household Income In Rapti, compared wIth about two-thIrds In Bhen

ContnbutIOns to total gross Income from dIfferent sources vary by altitude At elevatIOns below 1,000 meters, vegetables and hvestock contnbute about equally, at 136 and 11 1 percent, respectively Above 2,000 meters, however, hvestock contnbutes more than three times as much as vegetables (28 9 percent versus 9 3 percent) Income from vegetables exceeds Income from crops at elevatIOns of 1,000 to 1,500 and 1,500 to 2,000 meters, whIle income from hvestock exceeds that from crops at levels above 2,000 meters In Bheri, the share of livestock income to total mcome IS hIghest (36 0 percent) at levels below 1,000 meters, which is unusual for low altItudes

Among nonfarm actIVItIes, government and busIness serVIces contrIbute more Income than other nonfarm sources in both Rapti and Bhen

In terms of Income vanatIOn by distance to the nearest road head, annual gross total Income per household decreases as dIstance Increases, except at dIstances of one-half to one day WhIle Rapt! households earn the greatest portIOn of theIr gross total Income at thIS dIstance (Rs 74,763), Bhen households earn the lowest (Rs 23,026), ThIS vanatlOn could not be explaIned from the InfOrmatIOn avaIlable to the study team

In Rapt!, the percentage of crop Income to total Income IS hIghest at dIstances of less than one-half day (37 2 percent) and between one-half and one day (24 9 percent) from the road, whIle the percentages of vegetable Income (340 percent) and lIvestock Income (27 8 percent) are hIghest In the one-to-two-days and more-than-two-days categones, respectively In Bhen, the percentage of Income from lIvestock IS hIghest at dIstances less than one-half day from the road (36 0 percent)

TABLE 92 ANNUAL GROSS TOTAL INCOME PER HOUSEHOLD AND PERCENTAGE FROM DIFFERENT SOURCES, BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

(Rs)

Raptl Shen

Source <% Day %-1 Day 1-2 Days >2 Days <% Day %-1 Day 1-2 Days >2 Days

Cereal and cash croQs 372% 249% 178% 247% 182% 246% 192% 417%

livestock 128% 150% 181% 278% 360% 182% 188% 254%

Vegetables 196% 215% 340% 105% 28% 43% 45% 70%

FrUit 82% 146% 52% 39% 60% 116% 72% 95%

Farm Income 779% 760% 751% 669% 630% 587% 498% 836%

Nonfarm Income 221% 240% 249% 331% 370% 413% 502% 164%

Total 1000% 100 0% 1000% 1000% 1000% 100 0% 1000% 100 0%

Gross total Income 66,560 74,763 61,912 34,237 40,951 23,026 32,645 24,389

105

9.2 GROSS CASH INCOME

Tables 9 3 and 9 4 hst annual gross cash Income from dIfferent sources, by altItude and dIstance, respectively, m Raptl and Bhen In RaptI, the largest portIOn of total household mcome comes from sales of cereal and cash crops (27 1 percent), followed by sales of vegetables (16 4 percent), and salary and penSIOn from serVIces (124 percent) In Bhen, the largest contnbutors to total mcome are salary and pensIOn (26 5 percent), government serVIces (22 7 percent), and hvestock (16 1 percent).

Table 9 3 further reveals that the average annual household mcome m Raptt IS much lower at elevatIOns above 2,000 meters than at other altttudes Cereal and cash crops contnbute almost half of the total mcome at elevatIons below 1,000 meters, but vegetables and cereal and cash crops together contrIbute about half of the total mcome at 1,000 to 1,500 meters and about two-fIfths at 1,500 to 2,000 meters The mam contnbutors to total mcome at levels above 2,000 meters are salary and penSIOn (38 7 percent) and army mcome (30 7 percent)

In both of Bhen' s elevatIOn ranges, salary and penSIon contnbutes the hIghest percentage of total mcome, followed by government serVIces

TABLE 9 3 PERCENTAGE DISTRIBUTION OF ANNUAL GROSS CASH INCOME PER HOUSEHOLD,

BY SOURCE AND ALTITUDE (Rs)

Rapti Sheri

1,000- 1,500- 1,000· Source <l,OOOm 1,500m 2,000m 2,000m+ Total <l,OOOm 1,500m Total

Cereal and cash crops 447% 230% 213% 58% 271% 14% 70% 542% Vegetables 89% 253% 190% 07% 164% 03% 05% 044% FrUit 08% 14% 44% 08% 22% 22% 25% 241% livestock 76% 75% 73% 235% 88% 270% 119% 1608% Cottage industries 27% 40% 50% 38% 40% 04% 42% 317% Labor-based agriculture 17% 07% 04% 09% 09% 00% 04% 027% Construction labor 16% 21% 25% 65% 25% 83% 115% 1061% Other dally wages 03% 11% 1 1% 14% 09% 10% 19% 167% Wage labor 63% 79% 91% 127% 82% 97% 181% 1573% BUSiness 32% 59% 87% 07% 57% 70% 90% 849% Contract 00% 00% 02% 01% 01% 00% 00% 003% BUSiness/contract 32% 59% 90% 07% 58% 70% 91% 852% Interest and land rent 01% 03% 05% 05% 03% 00% 09% 062% House rent 03% 14% 13% 05% 10% 28% 01% 088% Total Interest and rent 04% 17% 18% 09% 13% 28% 10% 150% Government services 58% 73% 57% 16% 58% 291% 202% 2268% BritiSh, Indian army 03% 00% 01% 307% 27% 05% 17% 135% Other services 32% 17% 43% 05% 29% 06% 01% 026% Pension 05% 08% 01% 59% 09% 00% 27% 197% SpeCial services 00% 01% 01% 00% 01% 00% 03% 025% Salarv and oenslon 99% 99% 102% 387% 124% 302% 251% 2651%

106

Rapt! Bheri

1,000- 1,500- 1,000-Source <1,000m 1,500m 2,OOOm 2,OOOm+ Total <1,OOOm 1,500m Total

Wealth remitted by household members 32% 19% 40% 77% 35% 24% 23% 234% Land sales 24% 129% 18% 00% 49% 00% 55% 398% House yard sales 10% 04% 04% 03% 06% 01% 08% 060%

Asset sales 66% 151% 62% 80% 90% 25% 86% 692%

Other 117% 23% 118% 82% 88% 169% 163% 1647%

Total 1000% 1000% 1000% 1000% 1000% 1000% 1000% 10000% Gross cash Income 42,740 31,208 32,951 19,055 32,575 23,491 14,773 16,477

As Table 9 4 depIcts, m Raptl, cereal and cash crops contnbute more than one-thIrd of total mcome at locatIOns less than one-half day (35 2 percent) and one-half to one day (36 2 percent) from the road Simllarly, vegetables at dIstances of one to two days from the road contnbute more than one-thIrd (37 9 percent) At more than two days' dIstance, salary and penSIOn contnbutes 40 6 percent of total mcome In Bhen, salary and penSIOn contnbutes most of the total mcome at all dIstances, except those one-half to one day away, at which pomt wage labor contnbutes 33 0 percent of total income

TABLE 9.4 PERCENTAGE DISTRIBUTION OF ANNUAL GROSS CASH INCOME PER HOUSEHOLD,

BY SOURCE AND WALKING DISTANCE TO THE NEAREST ROAD HEAD (Rs)

Raptl Bheri

Source <V2 Day V2-1 Day 1-2 Days >2 Days <V2 Day V2-1 Day 1-2 Days >2 Days

Cereal and cash crops 352% 362% 79% 73% 09% 46% 24% 24% Veqetables 168% 147% 379% 08% 02% 04% 02% 02% FrUit 11% 54% 04% 08% 14% 06% 1 1% 1 1% livestock 73% 84% 88% 261% 173% 119% 45% 45% Cottage Industnes 34% 58% 39% 40% 03% 20% 07% 07% Labor-based agnculture 15% 05% 05% 10% 00% 03% 00% 00% Construction labor 23% 24% 13% 77% 53% 315% 45% 45% Other dally wages 05% 10% 15% 23% 06% 12% 11% 11% Wage labor 43% 39% 33% 110% 59% 330% 56% 56% BUSiness 64% 81% 37% 13% 45% 51% 69% 69% Contract 02% 00% 00% 01% 00% 00% 00% 00% BUSiness/contract 67% 81% 37% 14% 45% 51% 69% 69% Interest and land rent 03% 05% 02% 05% 00% 00% 08% 08% House rent 04% 22% 08% 05% 18% 00% 01% 01% Total Interest and rent 07% 27% 10% 10% 18% 00% 09% 09% Government services 73% 43% 108% 17% 187% 86% 162% 162% Bntlsh, Indian army_ 02% 01% 00% 318% 03% 00% 16% 16% Other services 50% 22% 13% 05% 04% 02% 00% 00% Pension 06% 01% 07% 66% 00% 00% 26% 26% Special services 01% 02% 00% 00% 00% 08% 02% 02% Salary and pension 131% 68% 128% 406% 194% 95% 206% 206% Wealth remitted by household members 43% 34% 00% 81% 15% 22% 15% 15%

107

Raptl Sheri

Source <% Day %-1 Day 1-2 Days >2 Days <% Day %-1 Day 1-2 Days >2 Days

Land sales 38% 21% 213% 00% 00% 31% 28%

House yard sales 07% 06% 05% 03% 01% 13% 04%

Asset sales 45% 27% 219% 03% 01% 44% 33%

Other 103% 110% 23% 108% 485% 306% 546%

Total 1000% 1000% 1000% 1000% 1000% 1000% 1000%

Gross cash Income 32,086 33,195 32,058 17,200 36,633 12,673 32,133

9.3 RELATIONSHIP OF VEGETABLE INCOME TO INCOME FROM OTHER SOURCES

28%

04%

33%

546%

1000%

32,133

Table 9 5 presents vegetable Income per household along wIth Income from other sources, total crop area, and household SIze, all grouped by vegetable Income quartIle In RaptI, the only van abIes that Increase as vegetable Income quartIle Increases are crop productIOn, vegetable productIOn, and Income from other sources Household Income from lIvestock and cottage mdustnes IS hIghest m the second Income quartile, whIle Income from fruIt productIOn IS hIghest In the thIrd quartIle

In contrast, In Bhen, mcome from lIvestock, Income from cottage Industnes, and crop area mcrease as vegetable income quartIle mcreases InterestIngly, Income from fruIt, crop production, other income, and household SIze Increase WIth quartIle untIl the hIghest quartIle, at WhICh POInt they decrease These fmdmgs may suggest that resource dIversIon occurs among dIfferent productIOn actIvIties after they reach a certam level of IntensIfIcatIOn The fmdIngs may also suggest that such a level of mtensIficatIOn appears only at the hIghest vegetable Income quartIle m Bhen, but starts from the second quartIle m Raptl

TABLE 9 5 AVERAGE VALUE OF PRODUCTION OF DIFFERENT CROPS, BY VEGETABLE INCOME QUARTILE

(Rs)

Value of Value of Value of Total Veg.lncome Veg. Livestock Cottage Crop Value of Value of Other HH Class (Rs) Production Prod. Ind. Prod. Area (ha.) FrUit Prod. Crop Prod. Income Size

Raptl

0-3,060 1,377 8,833 1,720 1 08 3,733 9,109 33,583 701

3,061-6,775 4,822 10,613 4,176 224 6,672 15,409 54,288 858

6,776-15,115 9,815 9,333 3,772 1 96 8,012 17,716 67,630 824

>15,115 34,485 10,505 2,969 241 6,279 26,926 94,952 897

Rapt! average 12,669 9,823 3,159 1 93 6,169 17,304 62,649 820

Sheri

0-373 243 3,703 391 077 507 4,831 15,874 620

374-760 549 4,814 550 1 04 2,385 6,670 25,753 670

761-1,475 1,055 5,888 709 1 06 4,795 10,552 61,448 770

>1,475 3,551 15,100 870 1 67 1,910 6,285 28,838 676

Bherl average 1,372 7,454 633 1 14 2,423 7,118 31,056 686

108

Table 9 6 shows Income from fruIt per household along wIth Income from other sources, total crop area, and household SIze, all grouped by vegetable Income quartIle Interestmgly, Income from all sources except vegetable productIOn Increases wIth an Increase 10 fruIt 1Ocome quartIle 10 both Rapt! and Bhen However, the magmtude of 10crease dIffers among the dIfferent sources and among quartIles

TABLE 9 6 AVERAGE VALUE OF PRODUCTION OF DIFFERENT CROPS BY FRUIT INCOME QUARTILE

(Rs)

Fruit Income

Class (As)

0-73

74-887

888-3,053

>3,053

Rapt! average

0-51

52-526

527-1,761

>1,761

Bhen averaQe

Value of Value of Live- Value of Crop Value of Value of Total

Fruit stock Cottage Area Veg. Crop Other Production Prod. Ind. Prod. (ha.) Prod. Prod. Income

Aapti

6 5,321 1,718 143 13,385 11,744 45,215

421 8,122 2,410 187 10,909 14,978 47,531

1,841 11,187 2,510 212 12,932 18,343 59,427

2,252 14,695 6,002 229 17,057 29,553 104,584

6,184 9,823 3,159 1 93 13,565 18,637 64,125

Bhen

5 4,798 475 108 845 5,636 24,098

274 5,477 515 090 839 6,088 24,764

957 6,552 681 088 1,393 7,839 27,776

8,493 13,029 864 13O 2,420 9,407 47,693

2,423 7,454 633 1 14 1,372 7,236 31,056

9.4 RELATIONSHIP OF TOTAL INCOME TO INCOME FROM OTHER SOURCES

HH Size

771

845

843

821

82O

645

632

672

795

686

The study team regressed total 1Ocome per household wIth percentage of contnbutIOn to total 1Ocome from productIOn of vegetables, crops, fruIt, hvestock, and cottage 1Odustnes, as well as total crop area and household SIze The results, presented In Table 97, show that all of the explanatory varIables, except proportIOn of vegetable, hvestock, and cottage-1Odustry Income to total Income, are sIgmficant for Rapti For Bhen, all vanables except household SIze and 1Ocome from vegetables are sIgmflcant The value of R2 shows that In Raptl and Bhen, respectIvely, 21 percent and 30 percent of the vanatIon In total Income IS explaIned by the explanatory vanables The F-values are sIgmficant for both zones

Table 9 7 shows that a I-percent Increase In fruIt 1Ocome to total Income WIll Increase total Income by Rs 1,136 In RaptI but only Rs 329 In Bhen Conversely, a I-hectare Increase 10 total crop area WIll add Rs 9,365 in Income In Raptl but Rs 15,692 In Bhen The vegetable coeffIcIent of the proportIOns of crop and cottage-1Odustry productIOn In both Raptl and Bhen suggests that an 10crease 10 the proportIOn of 1Ocome from cottage 10dustnes and crop productIOn WIll reduce the magmtude of total Income However, the coeffICIent of cottage 10dustry IS statistIcally InsIgnifIcant 10 Raptl

Note" * ""*

***

109

TABLE 97 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION

Variable Rapti

COTIPRO -14732

CROPIPRO -66659'

FRUIPRO 1,13617*

HHNO 2,61232'

TCROPA 9,36491'

VEGIPRO 23702

LlVIPRO -7186

(Constant) 33,53619

Adjusted, R2= 21

F-statlstlcs, F= 2391

No of observations, N= 597

denotes sIgmficant at 1 % level of sIgmfIcance,

denotes sIgmficant at 5% level of sIgmfIcance, and

denotes sIgmfIcant at 10% level of sIgmficance

Bheri

-1,48488'

-62483'

32941'"

1,07433

15,69200'

-33629

21887"

24,51361*

30

1641

251

Dependent vanable = total 1Ocome from all sources per household

Def1OItIons of 10dependent vanables

HHNO

COTIPRO

VEGIPRO

FRUIPRO

LIVIPRO

TCROPA (Constant)

= = = = = =

number of persons 10 household

proportIOn of value of cottage-1Odustry productIOn to total 1Ocome

proportIOn of value of vegetable productIOn to total 1Ocome

proportIOn of value of frUIt productIOn tototal 1Ocome

proportIOn of value of hvestock production to total 1Ocome

total crop area per household

Table 9 8 presents the results of the model dIscussed above when 10cludlllg dummy varIables for measurlllg vanatIOn by walklllg dIstance to the nearest road head The dummy vanable for the dIstance ofless than one-half day was excluded 10 the equatIOn so that the llltercept (constant) term could represent that dIstance

Table 9 8 shows no sIgmficant shIft in 10tercept between the less-than-one-half-day dIstance and the one-to-two-days dIstance The 10tercept shIfts upward from less than one-half day to one-half to one day but moves downward from less than one-half day to one to two days 10 the case of RaptI The study

110

team found no sIgmficant dIfference In Intercept between the less-than-one-half-day dIstance and the more­than-two-days dIstance

Note. * **

***

TABLE 9 8 REGRESSION RESULTS FOR DETERMINANTS OF CROP PRODUCTION,

BY WALKING DISTANCE TO THE NEAREST ROAD HEAD

Variable Rapti

COTIPRO -106 18

CROPIPRO -66531"

FRUIPRO 1,011 01'

HHNO 2,94920'

TCROPA 8,81353"

VEGIPRO 18423

LlVIPRO -6874

0002 12,38684*'

0003 30294

0004 -13,81824***

(Constant) 31,81824

Adjusted, R2= 22

F-statlstlcs, F= 1820

No of observations, N= 597

denotes sIgmfIcant at 1 % level of sIgmfIcance,

denotes sIgmficant at 5% level of sIgmfIcance, and

denotes sIgmfIcant at 10% level of sIgmfIcance

Bheri

--1,36726**

-661 50*

32793***

94936

16,26714*

-29306

207 14***

-14,60204**

-14,83270*

-8,65237

36,01583*

31

1248

251

Dependent van able = total Income from all sources per household

DefInitIons of Independent variables

HHNO

COTIPRO

VEGIPRO

FRUIPRO

LIVIPRO

TCROPA

(Constant)

DOD2

= = = = = =

=

number of persons In household

proportIOn of value of cottage-Industry productIOn to total mcome

proportIOn of value of vegetable productIOn to total mcome

proportIOn of value of frUlt productIOn to total Income

proportIOn of value of hvestock productIon to total Income

total crop area per household

mtercept dummy van able, DOD2= 1 for Y:z -1 day dIstance and zero otherwIse

= =

111

mtercept dummy vanable, DOD3 = 1 for 1-2 days dIstance and zero otherwIse.

mtercept dummy vanable, DOD 4= 1 for more than 2 days dIstance and zero otherwIse

Table 9 9 presents the regressIOn results dIscussed above when mcludmg dummy vanables for exammmg vanatIOn by altItude The dummy vanable for the less-than-l ,OOO-meters category was excluded so that the mtercept could represent that altitude range The results show that a downward shIft m mtercept occurs from less than 1,000 meters to more than 2,000 meters

TABLE 9 9 REGRESSION RESULTS FOR DETERMINANTS OF

CROP PRODUCTION, BY ALTITUDE

Variable Rapti Sheri

COTIPRO -1508 -1,25851

CROPIPRO -71037* -61396

FRUIPRO 1,05934- 37839-

HHNO 2,511 50- 94916'

TCROPA 8,484618 16,25863

VEGIPRO 16429 -23876

LlVIPRO -5297 22512'

DOE1 13,63076'

DOE2 -11,55026

DOE3 -461 65

DOE4 -24,95041'

(Constant) 45,60091' 20,10149-

Adjusted, R2= 23 31

F-statlStlcs, F= 1820 1552

No of observations, N= 597 252

Note * denotes sIgmficant at 1 % level of sIgmficance, and ** denotes sIgmficant at 5% level of sIgmficance

Dependent vanable = total mcome from all source" per household

DefmItIOns of mdependent vanables

HHNO = COTIPRO = CROPIPRO= VEGIPRO =

number of persons m household

proportIOn of value of cottage-mdustry productIOn to total mcome

proportIOn of value of crop productIOn to total mcome

proportIOn of value of vegetable productIOn to total mcome

FRUIPRO

LIVIPRO

TCROPA

(Constant)

DOE2

DOE3

DOE4

= = =

=

=

=

112

proportion of value of fruIt productIOn to total mcome

proportIOn of value of lIvestock productIon to total mcome

total crop area per household

mtercept dummy varIable, DO~ = 1 for 1,000 to 1,500 meters of altItude and zero otherWIse

intercept dummy variable, DOl; = 1 for 1,500 to 2,000 meters of altItude and zero otherWIse.

mtercept dummy varIable, DOE4= I for more than 2,000 meters of altItude and zero otherwIse.

113

REFERENCES

Agncultural Projects ServIces Centre (APROSC), 1977 ReconnaIssance Survey for Rapti Zone Rural Area Development Project Kathmandu, September

___ " 1977 PrefeasIbIhty Study for the Integrated Rural Area Development Project. Kathmandu.

___ , 1980 FeasIbIlIty Study of the Raph Integrated Rural Development Project Kathmandu

___ " 1980 Report on Rapt! Baselme Survey Kathmandu, September

___ " 1990 Household Income Survey for the Integrated Rural Area Development Project Rapt! Kathmandu.

NatIonal Research ASSOCIates, 1994 Nepal DIstnct ProfIle A DIstnct-wIde SocIO-Techno-EconomIc ProfIle along WIth a ComprehensIve NatIOnal ProfIle of Nepal EdIted by Han Bhakta Sharma and TIka Ram Subedy Kathmandu

WFS, 1996 Nepal POSItIOn Paper, delIvered at the World Food SummIt, Rome (unpublIshed document).