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1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation Cairo Conference, Egypt March 31, 2009

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Page 1: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Modeling Gender Effects of Pakistan’s Trade Liberalization

Rizwana SiddiquiPakistan Institute of Development Economics

Perspectives on Impact evaluationCairo Conference, Egypt March 31, 2009

Page 2: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Outline

Introduction

Methodology – Gender Sensitive CGE

Data - Gender Sensitive SAM

Simulation Results

Conclusion

Page 3: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Introduction

Gender Inequalities in Pakistan

women are

– Less fed – Low health status– Less educated– Less mobile– Located in low paid jobs– Wage rate is low – Market work under estimated– Household work is completely ignored– Over loaded by Work

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cont….

• Bias in Intrahousehold Allocation of Resources

• Bias in Division of Labour

Constraints Men and Women Face Differ

Page 5: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Policy Effects

Trade Liberalization and Gender Effects

– Change in structure of employment and prices

• Time Allocation

• Consumption

• Incidence of poverty- time, capability, income

Page 6: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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ObjectiveThe objective of the present study is

to measure gender dimensions of effects of Trade Liberalization in Pakistan using a comprehensive frame work that takes into account:

– Market work, household work, leisure

– Men and Women Labour

– Consumption of men and women

Measure effects using gender based poverty indicators

Page 7: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Development of Gender Aware CGE

1. Production – Integrate market and non-market sectors

2. Labour by gender

3. Rigidities

4. Consumption by Gender

5. Poverty Indicators by Gender

Page 8: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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DATAConstruction of Gender SAM

1. Traditional SAM-based on market economy

2. Integration of Market Economy and Household Economy

3. Female Participation Adjusted with new data

4. SNA Classification is used to Categorize market, household, and leisure

5. Evaluation of Non Market Work—Opportunity cost of labor

Page 9: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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AssumptionsAll activities are separable

Minimum time required for self care is 10Hours/d

Rest of the hours/d are distributed between Market, Household and Leisure activities

Households Produced Goods are consumed by Households themselves

Page 10: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Structure of SAM-1990 Market Sector (20)—Agriculture (5) , Industry ( 9)

Services ( 7)

Non Market Sectors(18)— Nine categories of households are identified with nine social reproduction sectors and nine leisure sectors

Factors of Production—Labor (8)—Grouped by Gender and education

—Capital By Sector

Households(9)—4 Urban by education level of hh and 5 Rural by Gender and then male head hh by employment status.

Page 11: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Salient Features of Gender SAM

1. It makes invisibility of women's household work visible.

2. Hidden market work: Improved female participation- female participation in the market is over 50 % instead of 12%

3. Female labour increases from 3.1 million (OLD) to about 15 million

Page 12: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Female Labour Force Participation Rate (based on

old and new data collection techniques)

0

10

20

30

40

50

1 2 3

years

FL

FP

R (

%)

Series1 Series2

Page 13: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Time Allocation between market and non market

activities Women

Urban• Market – 26.5 to 40 %• Household- 34.1 to

45.3%• Leisure- 10 to 20 %

Rural• Market-34.1 to 45.3 %• Households-35.9 to

47.3%• Leisure-10 to 20%

MenUrban • Market – 50.6 to 57.4%• Household- 2.9 to10.7

%• Leisure- about 40%

Rural• Market- 47.5 to 53.3%• Households-1.6 to

16.8%• Leisure-about 40 %

Page 14: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Time allocation by Gender in Market Economy

Male Labour in hours Female labour in hours

Sectors No-Educatio

n

Low-Educati

on

Med-Educat

ion

High-Educat

ion

NoEducati

on

LowEducati

on

Med-Educati

on

HighEducat

ion

Crop* 39.5 21.3 21.8 7.9 66.2 55.5 51.9 0.0

Live Stock

11.5 6.5 5.9 1.8 10.0 11.2 6.5 0.0

Textile 6.3 6.5 7.9 3.9 9.5 18.6 19.7 27.0

Machinery

1.8 4.3 3.4 2.0 0.0 0.0 0.0 0.5

Public Administration**

8.0 13.2 16.8 31.5 4.3 0.0 0.3 13.3

Education and Health**

1.4 2.3 4.3 13.5 1.3 0.0 0.9 26.7

Page 15: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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yHousehold Reciepts by Source and Poverty

020406080

100120140160

NoEd

ucat

ion

Low

Educ

atio

n

Med

ium

Educ

atio

n

High

Educ

atio

n

Empl

oyee

Fem

ale-

Head

edHo

useh

olds

Self-

Empl

oyed

Oth

er

Empl

oyer

Household

shar

e (%

)

Labor Capital Dividends Govt Transfers Remittances Poverty

Page 16: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Structure of Demand

• Inequality in Consumption by Region

• Rural households (70%)—Consumption 52%.

• Urban households (30%)—Consumption 48 %.

• Household and Intermediate consumption account for over 85.4% of total demand

• Exports—6.6 %

• Investment—8 %

Page 17: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Consumption by Gender

• An equation based on Working Engel Curve

• Where w is share of good i, x total expenditure, n household size, F number of adult equivalent males and number of adult equivalent females

• We calculated out lay equivalent ratio for both male and females.

• Where G = F and M

iunxFMw ii )/ln(21

n

x

xq

Gq

i

jiijG

/

/

Page 18: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Intra Households Allocation of Resources

Significant Difference - food, clothing, education and health consumption of men and women. Other commodities are like public goods which are consumed by men and women equally, i.e., housing, sanitation facilities and utilities such as water, electricity, and gas etc.

Using Following Ratio Household Consumption Disaggregated by gender

MF

Ff CC

Ca

MF

Mm CC

Ca

where af + am =1

Page 19: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Intra Households Allocation of Resources Urban

Crop-(Vegetables, and cereals) –ALL HH-W

Live stock & poultry-all hh Men

Cloth- Poor- MenRich-women

Education and Health• Poor-female• Rich-male=female

Rural

Crop and Live Stock

Men > Women

Clothing vary by type of hh

Rich – Women

Poor-Men

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CGE ModelProduction - 3

Market sectors—TwentyHouseholds Social Reproduction—Nine

Leisure—Nine

Labor by gender and by education levelMen-(4)—No education, below primary, 5-9 years,

Ed>10Women-(4)—No education, below primary, 5-9

metric, above

Consumption of MenWomen

Page 21: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Cont…

• It is assumed that non market sectors, leisure and reproduction, behaves like market sectors.

• Household consume all goods produced social reproduction and leisure

• Price of non market goods is the opportunity cost of labor used in these activities.

• Market rigidities are introduced by keeping low elasticities of substitution

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Consumption of Market and Non-Market Goods

Maximizing Stone-Geary utility function

• S.t

• Income constraint

• Time constraint

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Other Features of the MODEL• Goods with same sectoral classification are different in

qualities for domestic markets and foreign markets.

• Imports and domestically produced goods are imperfect substitutes.

• CES and CET functions describe substitution and transformation possibilities reflecting empirical realities, respectively, for the above two functions.

• Model is calibrated to SAM data using parameters estimated from SAM and econometrically estimated elasticities.

• Model is solved using GAMS software.

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Closure

CAB and Nominal exchange rate are constant and real exchange rate adjust to keep the balance.

Government consumption and Investment are kept fixed in real term for welfare and poverty analysis.

Savings equal Investment

Page 25: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Poverty and Welfare Analysis

A. Capability Poverty Indicators-

• 1. IMR—Measure satisfaction of at least 4 basic needs

• 2. LR—Education

hHEPC

hPC

base

CGCHA

IMRIMRIMRIMR

__min

min **1

)(

eHEPC

CGePC

CHA

LRLRLRLR

base

_*_*1

)max

(

max

Page 26: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Cont…

• Income Poverty—Absolute and Relative

— Absolute - FGT Indices

— Relative Women share in poor population

•Time Poverty—Absolute and Relative —Change in leisure of men and women over base

value —change in leisure of women relative to men

Welfare -- EV-based on consumption of market goods– EV-based on consumption of market and non market goods

Page 27: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Simulation: Revenue Neutral Trade Liberalization

• Tariff Reduction

• Sales tax increases

Figure 1. Custom Duties and Sales Tax as Percentage of Government Revenue

0

5

10

15

20

25

30

35

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Year

Percentages

Custom duties Sales Taxes

Page 28: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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Variation in Macro Aggregates

Sectors M/Q E/Xs

Trade Liberalization

PC PM Q D M E VA

Agriculture 3.5 1.05 -1.32 -2.45 -0.21 -0.27 1.47 3.5 -0.23

Industry 26.8 15.2 -4.01 -8.48 0.03 -1.18 3.41 4.34 -0.19

Textile 3.8 42 -2.2 -5.4 1.2 1.0 4.7 4.6 2.6

Machinery 61.5 3.5 -8 -9.5 1.2 -2.4 3.5 6 -2.1

Services 4.9 6.1 -1.8 0.66 -0.39 -0.08 -2.98 2.22 -0.19

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Factor Market Effects

Market Sectors

Female Labour Male Labour  

No Low Med High

Total

No LowMediu

m High

Total

Total Lab

Edu Edu Edu Edu Edu Edu Edu Edu

Agriculture 0.2 -1.9 -2.5 0 -1.12 0.91 -2.4 -0.66 -4.57 -0.1 -0.42

Textile 7 4.7 4.2 1.8 4.34 7.9 4.5 6.4 2.4 6.12 5.3

Chemicals -6.1 0 -9.2 -10.7 -9.21 -5.4 -8.1 -7.2 -10.2 -8.54 -8.6

Non-Metallic -6.3 0 0 0 -6.28 -5.5 -8.2 -7.7 -10.4 -6.39 -6.4

Metallic 0 0 0 0 0 -8.6 -11.2 -10.7 -13.3 -11.62 -11.7

Industry 6.24 4.65 1.72 -0.68 2.17 1.04 -1.91 -0.43 -5.64 -1.21 -0.41

Services -4 -1 -1.7 -3.5 -2.66 3.9 0.9 1.5 -1.5 -0.31 -0.54

Total 0.84 -0.99 -1.62 -2.34 -0.73 -1.2 -4.2 -2.6 -6.2 -0.4 -0.47

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Labor to Non Market Activities

HouseholdSocial Reproduction Leisure

Urban households 0.48 1.8

No-Education -1.5 -0.8

Low-Education 4 6.4

Med-Education 0.3 1.6

High-Education 3 3.9

Rural households -0.45 -1.4

Employee Male -1.6 -1.8

Female-Headed 2.8 4.8

Self-Employed -1.1 -1.4

Other -1.2 -1.5

Employer -0.8 1.2

Total -0.02 0.16

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Variation in Wage Income, Expenditure and CPI

Household

Women wage Incom

eMen Wage

Income CPI

Household Expenditu

re

Urban 2.7 1.3 -1.6 1.06

No-Education 1.3 -1.2 -1.6 -1.7

Low-Education 2.6 0.9 -1.6 3.5

Med-Education 3.0 0.5 -1.7 0.8

High-Education 4.1 4.1 -1.6 4.1

Rural 1.1 -0.3 -1.7 -0.35

Female Headed hh 0.8 -0.3 -1.7 1.6

Employee 1.5 0.0 -1.7 -1.6

Self-Employed 0.9 -0.5 -1.7 -1.5

Other 2.0 0.7 -1.8 -0.7

Employer 5.2 1.8 -1.7 1.7

Total 1.9 0.5 1.7 0.34

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Poverty and Welfare

HouseholdHead

CountPoverty

Gap SeverityWelfare

(EV)1 Welfare

(EV)2

No-Education 3.7 5.6 6.9 -0.01 -0.03

Low-Education -11.8 -11.1 -12.5 0.03 -0.03

Med-Education -1.5 -1.2 -3.6 0.01 -0.02

High-Education -14.0 -13.8 -13.3 0.03 0

Urban households -3.6 -2.6 -2.5 0.01 -0.037

Employee Male 3.0 6.2 7.7 -0.01 -0.02

Female-Headed -3.3 -5.6 -5.9 0.02 -0.05

Self-Employed 2.8 5.2 5.6 -0.01 -0.04

Other 1.7 2.2 7.1 -0.01 -0.03

Employer -3.5 -5.4 -8.3 0 0

Rural households 2.3 4.5 5.7 -0.004 -0.036

Total -0.3 1.3 2.0 0.004 -0.037

Page 33: 1 Modeling Gender Effects of Pakistan’s Trade Liberalization Rizwana Siddiqui Pakistan Institute of Development Economics Perspectives on Impact evaluation

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continued

Relative Poverty-Change in Gender Composition in Poor Household

NoED

LowED

MedED

HighED

Urban

Empee FH

S-Emp oth

Empyer Rur Pak

Men -0.11 -0.99 0.03 0 -0.08 0 0.08 -0.03 -0.07 0 0.02 -0.03

Women 0.11 0.99 -0.03 0 0.08 0 -0.08 0.03 0.07 0 -0.02 0.03

Capability Poverty Indicators    

M-IMR 0.7 -0.2 -0.06 -0.23 -0.08 0.07 -0.11 0.07 0.02 -0.1 0.04 0.01

F-IMR 0.7 -0.2 -0.06 -0.24 -0.05 0.07 -0.11 0.07 0.02 -0.1 0.05 0.03

M-LR -0.6 0.24 0.04 0.02 -0.2 -0.92 0.49 -0.3 -0.04 0.15 -0.37 -0.29

F-LR -0.92 0.95 0.17 0.08 -0.33 -3.33 1.57 -1.12 -0.1 0.59 -1.69 -1.11

Leisure—Relative Time Poverty

Men -0.7 6.4 1.7 3.8 1.87 -1.7 4.8 -1.3 -1.4 1.7 -1.49 0.15

Women -1.3 6.3 1.2 4.3 1.74 -1.9 4.8 -1.5 -1.5 0.6 -1.68 -0.09

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Conclusion• Revenue Neutral Trade Liberalization • benefit more to women by increasing

•Market Employment of unskilled worker •Wage income of women more than menHarmful as •Division of labor remains unequal and

Women becomes more time poorTrade Liberalization, Poverty and Welfare

•Head Count Ratio Reduces at the national level increases in rural, decreases in urban area

– Trade Liberalization and Welfare •Welfare improves when measured at

consumption level of market goods•Deteriorate- with reduction in consumption

of market and non market goods

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ConclusionTL and Poor

– Increase Work Load on women relative to Men– Deteriorate capabilities—FLR > MLR– Increase income poverty among women relative to men– Increase time poverty by reducing leisure time– Welfare improves - Consumption of market goods only– Welfare deteriorate - consumption of both market and

non-market goods

TL and Rich

– TL is Gender Neutral for Rich Households – Remittances neutralize negative effects of trade

liberalization– Welfare Improves with consumption of market goods– Welfare does not change with total consumption (market and non market goods)—work load increases and leisure reduces)

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Policy Implications

• Complementary Policies

• Reduce Tax on basic need

• Transfer payments

• Poverty Targeted Program

• Public Investment in Social Sector

• Migration – Remittance

• Household Responsibility must be share by men

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