ETHIOPIAN DEVELOPMENT

RESEARCH INSTITUTE

Derek Headey, Fantu Bachewe, Ibrahim Worku,

Mekdim Dereje & Alemayehu Seyoum Taffesse

IFPRI ESSP-II

“Towards what works in rural development in Ethiopia: Evidence

on the impact of investments and policies”

A conference by IFPRI-ESSP II

13 December 2013

Addis Ababa

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URBAN WAGE BEHAVIOR

AND FOOD PRICE INFLATION IN

ETHIOPIA

1) Background

2) Data and Methods

3) Results

4) Conclusion

Outline

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• Global food crises of 2007/08 and 2010/11 sparked efforts to understand the poverty impacts of high real food prices

o World Bank simulation suggested global poverty rose by 160 million people

o Subjective survey data from Gallup suggest substantial variation of impacts: (Headey 2011)

o A third approach is to deflate wages by (food) prices to proxy for disposable income

o Cointegration analyses: short and long-run adjustment of wages for changes in food prices-

1) Background

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In this paper we have two objectives:

1. To track real wages (as per Mason et al.)

2. To formally test wage adjustment (as per Lasco et al., etc)

Particularly interesting in the Ethiopian context :

1. Large population of urban poor

60% earns <$2/day and 20% unemployment rate

2. Understudied in World Bank & Gallup studies

3. Rich monthly panel data on informal or casual wages

4. Arguably one of rapid food inflation in 2008 & 2011

1) Background

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• CSA consumer price data covering

119 woredas, with 1 or more markets-from 3 respondents

The July 2001 to August 2012

• Prices on food & non-food items (more than 700 items): wages of daily laborers, and maids and guards salaries,…

Maids and guards are partly paid with food-in-kind

• Food, non-food, and general price indices specific to the poor computed to create a better wage-welfare proxy,

• The 2004/05 HICES expenditure data used to measure expenditure shares of food & non-food for the bottom 40%

2) Data and methods

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• Rural and urban areas of each region considered separately

• Weights applied on CSA price data to derive spatially disaggregated “poor person’s price indices” (PPPIs) for food, non-food and all items

• Laborer’s wages deflated by both food and total CPIs for the poor.

Deflating by total CPI appropriate for welfare interpretation,

Deflating by food prices more relevant for the poor

• Deaton & Dreze (2002)-casual labor wage series are a good poverty indicator-represent reservation wage of the poor

• We make the same argument for Ethiopia

2) Data and methods (cont.)

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• Finally, we use panel regressors to see whether wages react to food prices in the short run

• We use a panel vector error correction (PVEC) model & spatially disaggregated subsamples by town/city size & regions

• PVEC effectively separates out a long run adjustment relationship (cointegrating relationships) and short run adjustments.

• Short run adjustments more interesting as they are more welfare-relevant.

2) Data and methods (cont.)

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• The theoretical model results in a relationship:

where W, Pf, Pn, and Pc stand for wages, food, non-food, and construction materials prices and QMC construction output.

• Given all series are non-stationary we can’t use OLS

• Cointegration analysis used

where

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2) Data and methods (cont.)

( , , , ) f n c M cPW P P Q

[ ],M c

it it it it

f n c

it itZ w p p p q , k kA1 1, k k kA A

1 1 2... , and k kA A A 1( ... ).kI A A

1 1 2 2 1 ( 1) 1 it it it k it k it it itZ Z Z Z Z X t

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Region

Average nominal wages Urban Rural 2001 2005 2010 2012 Food Non-food Food Non-food

National 6.9 8.1 23.4 34.3 67% 33% 69% 31% Wages in USD 0.82 0.93 1.62 1.95 Tigray 9.0 10.0 28.2 45.8 65% 35% 72% 28% Amhara 6.0 7.6 23.7 32.1 63% 37% 66% 34% Oromiya 7.3 8.2 21.2 31.9 67% 33% 71% 29% Somali 10.7 10.7 30.7 47.8 68% 32% 70% 30% SNNP 5.7 6.6 20.3 28.7 65% 35% 67% 33% Addis Ababa 6.7 9.1 25.6 35.2 63% 37% _ _

Table 1. Regional average daily laborers’ nominal wages and expenditure shares for the lowest 40% income quintile

2) Data and methods (cont.)

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Nominal wage index

Poor persons' food CPI

Poor persons' nonfood CPI

Poor persons' total CPI

2 sharp food price spikes, but

2011 saw nonfood inflation too

Fig. 1. Price trends for the urban poor: 2001-2012

Fig. 2. Comparing food price trends for the poor and general population: 2001-2012

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Food CPI

86% and 73% growth in PPFCPI & FCPI

Over 97% increase

Table 2. National and regional trends in daily laborers' wage (2006 birr), deflated by the poor person’s food CPI: 2001-2012

Year National Tigray Amhara Oromia Somali SNNP Addis

2001 12.0 15.1 10.0 12.0 14.7 9.4 10.5

2002 11.9 14.8 9.5 11.7 15.5 9.2 10.6

2003 10.8 12.8 8.7 10.6 14.5 8.4 10.0

2004 10.8 12.6 9.3 10.2 13.9 8.3 10.7

2005 10.9 13.1 9.9 10.3 12.5 8.2 11.2

2006 10.7 11.9 10.6 9.8 12.2 8.2 11.4

2007 11.3 12.8 9.8 10.1 14.7 8.5 12.0

2008 9.8 11.6 8.8 7.8 13.4 7.0 10.0

2009 10.8 11.6 9.8 8.8 16.5 7.6 10.5

2010 12.0 13.1 10.6 9.7 17.9 9.3 11.1

2011 10.1 13.1 8.7 8.3 13.7 7.7 9.1

2012 10.5 13.1 8.6 8.2 16.2 7.4 9.2

%: 2007-08 -13.8% -9.4% -10.1% -23.0% -8.4% -17.8% -17.3%

%: 2010-11 -15.4% 0.3% -18.1% -14.4% -23.2% -17.5% -17.9%

Figure 3. Trends in real daily laborer wages deflated by the urban poor’s food and total prices indices

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Wages deflated by poor persons' food CPI

Wages deflated by poor persons' total CPI

16% decline in food-disposable income relative to total disposable income

26% decline

22% decline

• Substantial long-run adjustment of wages to food prices, but lower to non-food prices:

Wages =1.197*food CPI+0.484*non-food CPI - 0.564* CMU CPI +0.00003*t+0.424

Adjustment speed: 3.4% per month

• Difficult to put a welfare interpretation

I. It takes long time for wages to partially and fully adjust

o 48 and 86 months for wages to partially and fully adjust for one SD change in poor persons’ food CPI

o 61 and 101 months for one SD change in non-food CPI

II. Short run adjustments are small

3) Results

Variable

Full

sample

“Cities”

>=30K

Small

towns

<30K SNNP

Addis

Ababa Amhara Oromia

∆ FPIt-1 -0.029** -0.049* -0.033* -0.044 0.115 0.021 -0.058*

∆ FPIt-2 -0.029** -0.044* -0.034** -0.037 0.114 -0.023 -0.019

∆ FPIt-3 0.005 -0.012 _ -0.037 _ 0.019 0.006

∆ NFPIt-1 -0.027** -0.011 -0.035** 0.025 -0.042 -0.005 -0.0158

∆ NFPIt-2 0.004 0.012 0.006 0.035 0.0004 0.006 0.02

∆ NFPIt-3 -0.017 -0.021 _ 0.002 _ -0.015 0.017

∆ CMRUPIt-1 0.091*** 0.011 0.142*** 0.139* -0.13 0.043 0.146*

∆ CMRUPIt-2 0.101*** 0.039 0.103*** 0.092 0.148 0.07 0.0072

∆ CMRUIt-3 -0.011 0.019 _ -0.081 _ -0.038 -0.098

Table 3. Short run adjustment coefficients of panel vector error correction (PVEC), July 2001-October 2011

Main findings:

Casual workers in urban Ethiopia have been hit hard by rapid food inflation in 2008 & 2011, particularly ultra-poor:

10-26% loss of disposable income

2011-12 crisis seems worse than 2008 crisis

Short run results show scarcely any adjustment and “In the long run we are all dead”

Given households could have coping mechanisms (e.g. long work hours), these may be upper bound estimates of welfare impacts

4. Conclusions

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Policy questions:

GOE has focused on trying to directly curb food inflation through price controls & some subsidization of food.

Efforts to reduce domestic inflation are sensible,

The capacity to fully reduce inflation may be limited given higher international prices and growth scenarios

Does Ethiopia need an urban social safety net?

Many considerations here, but one option is to index cash transfers to poor person’s price index

4. Conclusions (cont.)

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Thank you!

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