1

URBAN WAGE BEHAVIOR DURING FOOD PRICE HIKES:

THE CASE OF ETHIOPIA

Derek Headey, Fantu Bachewe, Ibrahim Worku, Mekdim Dereje & Alemayehu Seyoum Taffesse

Ethiopia Strategy Support Program (ESSP),International Food Policy Research Institute (IFPRI),

Addis AbabaContact: d.headey@cgiar.org

1) Background and Objective

2) Data and Methods

3) Results

4) Conclusion

Outline

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• The global food crises of 2007-08 and 2010-11 sparked a number of efforts to understand the poverty impacts of higher real food prices

• On the one hand, World Bank simulation approaches suggested global poverty rose by 160 million people

• However, subjective survey data from Gallup suggest substantial variation of impacts, and that strong economic growth in developing countries limited the impacts of higher prices (Headey 2011)

• A third less common approach is to deflate wages by (food) prices as a proxy for disposable income

1) Background

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• Some precedent on agricultural wages & food prices

• Literature is almost solely confined to Bangladesh (Ravallion 1992; Palmer-Jones; Rashid 2002), and Philippines (Lasco et al. 2008).

• Bangladesh: limited short run impacts of prices on wages; Philippines: fairly large short run impacts

• More recent study, by Mason et al. (2010) , looks at urban manufacturing wages in Zambia and Kenya. No econometrics, but “food-disposable” wages fell in 2008, but were still high by historical terms because of strong economic growth.

1) Background (cont.)

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In this paper we have two objectives:1. To track real wages in (as per Mason et al.)

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

Our context – Ethiopia - is a particularly interesting one: 3. Very poor (60% of urban pop. with <$2/day; 20% uN rate)4. Very understudied in World Bank & Gallup studies5. Unusually, we have monthly panel data on informal or casual

wages (much better than previous data)6. Arguably the most rapid food inflation in the world in 2008 and

2011

2) Objectives

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2004

2005

2006

2007

2008

2009

2010

2011

-1.0

0.0

1.0

2.0

3.0

4.0Food inflation (%)

Other developing countries Ethiopia

2004

2005

2006

2007

2008

2009

2010

2011

-2.0

-1.0

0.0

1.0

2.0

3.0

Relative food inflation (%)

Figure 1. Average monthly inflation in Ethiopia relative to other developing countries: 2004-2011

Source: ILO (2012).

2) Objectives (cont.)

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• CSA consumer price data from 115 “urban” markets around the country, from July 2001 to October 2011

• In addition to prices on food & non-food items, CSA asks about daily laborer wages, maids wages, guards,… (more than 700 items)

• But since maids and guards are partly paid with food-in-kind, we only focus on laborers (trends the same)

• Prices and wages collected for 3 respondents (firms or households) in each market and then averaged

• Enumerators try to measure the same respondents (kind of a panel?)

2. Data and methods

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• To create a better wage welfare proxy, we create food and non-food price indices specifically for the poor

• We used the 2004/05 HICES expenditure data, and measure expenditure shares just for the bottom 40%

• We do this for rural and urban areas of each region, then apply these weights to the CSA price data to derive a set of spatially disaggregated “poor person’s price indices” (PPPIs) for food, non-food and all items

• We deflate laborer’s wages by both food prices and total prices for the poor.

2. Data and methods (cont.)

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• In principle, deflating by total prices is most appropriate for welfare interpretation, but deflating food prices may be more relevant for ultra-poor who may spend almost all of their income on food

• More generally, are daily laborer’s wages are a good welfare indicator for the poor?

• For India, Deaton and Dreze argue that wage series for casual labor are a good poverty indicator, because they represent the reservation wage for the poor

• For urban Ethiopia we make the same argument

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 model (PVEC) & spatially disaggregate by town/city size & regions

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

• We are more interested in the short run adjustments as they are more welfare-relevant.

2. Data and methods (cont.)

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3. Results

2001m7 2002m7 2003m7 2004m7 2005m7 2006m7 2007m7 2008m7 2009m7 2010m70

50

100

150

200

250

300

350

Poor person's food CPI

Poor person's nonfood CPI

Nominal wage index

Pric

e an

d w

age

indi

ces (

Dec.

200

6=10

0)

Source: Author’s calculations from CSA (2011b) data. See section 2 for methods used.

Fig. 2. Price trends for the urban poor: 2001-2011

2 sharp food price spikes, but

2011 saw nonfood inflation too

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2001m7 2002m7 2003m7 2004m7 2005m7 2006m7 2007m7 2008m7 2009m7 2010m750

100

150

200

250

300

350

General food CPI

Poor persons' food CPI

Food

CPI

(Dec

. 200

6=10

0)Fig. 3. Comparing food price trends for the poor and general population: 2001-2011

3. Results (cont.)

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

Source: Author’s calculations from CSA (2011b) data. See section 2 for methods used.

2001m7 2002m7 2003m7 2004m7 2005m7 2006m7 2007m7 2008m7 2009m7 2010m7 2011m77

8

9

10

11

12

13

10% fall

26% fall 26% fall

21% fallWages deflated by poor person's food CPI

Wages deflated by poor person's total CPI

Real

dai

ly w

age

of la

bore

rs (D

ec. 2

006

birr

)

3. Results (cont)

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Table 1. National and regional trends in daily laborers' wage (2006 birr), deflated by the poor person’s food CPI: 2001-2011

3. Results (cont)

Year National Addis Amhara Oromia SNNP Somali Tigray2001 11.7 10.6 10.0 11.8 9.2 14.2 14.52002 11.4 10.4 9.3 11.5 8.9 14.9 13.92003 10.5 9.4 8.7 10.4 8.5 14.2 12.42004 10.7 10.2 9.3 10.2 9.1 13.5 12.32005 10.8 11.1 9.7 10.0 8.9 12.3 12.72006 10.7 11.3 10.5 9.8 8.8 11.5 11.52007 10.9 11.6 9.6 9.9 8.7 14.2 12.32008 9.2 10.2 8.5 7.7 6.8 12.6 11.42009 10.0 10.8 9.7 8.5 7.4 14.4 11.42010 11.5 11.3 10.4 9.6 9.3 15.4 12.92011 9.7 9.3 8.7 8.2 7.6 12.2 13.0

%D: 2007-08 -15.5% -11.8% -11.5% -22.4% -21.8% -11.2% -6.8%

%D: : 2010-11-15.8% -17.4% -16.5% -14.2% -17.4% -20.7% 0.8%

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Table 2. National and regional trends in daily laborers' wage (2006 birr), deflated by the poor person’s total CPI: 2001-2011

3. Results (cont)

year National Addis Amhara Oromia SNNP Somali Tigray2001 9.5 9.0 8.6 9.7 7.6 12.9 12.12002 9.5 8.8 8.3 9.7 7.3 13.3 11.92003 9.3 8.6 8.1 9.5 7.4 13.3 11.02004 9.7 9.2 8.6 9.4 8.3 13.0 10.72005 9.9 10.3 9.1 9.4 8.5 12.0 11.52006 10.4 10.7 10.1 9.7 8.9 11.7 11.32007 11.3 12.3 10.0 10.5 9.2 15.3 13.52008 10.8 11.9 9.9 9.4 8.3 15.1 13.62009 11.2 12.1 10.8 9.8 8.6 16.0 13.42010 12.2 11.7 10.9 10.6 10.0 17.3 14.62011 10.9 10.0 9.5 9.9 9.1 15.9 14.7

%D: 2007-08 -4.9% -3.4% -1.5% -11.0% -9.8% -1.4% 0.9%

%D: : 2010-11 -10.4% -15.0% -13.0% -7.3% -8.5% -8.3% 0.3%

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• The long run relationship shows substantial adjustment of wages to food prices (elasticity of greater than 1), but not to non-food prices:

Wages = -2.9 +1.2*Food CPI -0.1* Nonfood CPI -0.001* t

• However, it is obviously difficult to put a welfare interpretation on this equation

• Especially, since the short run results show scarcely any adjustment . . .

3. Results (cont)

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VariableFull

sample“Cities”

>20K

Small towns<20K

Addis Ababa Amhara Oromia SNNP

∆ FPIt-1 -0.039*** -0.038** -0.041*** -0.057** -0.062** -0.038* 0.023∆ FPIt-2 -0.028** -0.012 -0.037** -0.067** -0.045* -0.013 -0.032∆ FPIt-3 0.014 0.019 0.01 -0.037 -0.001 0.035 0.055*

∆ NFPIt-1 -0.004 0.006 -0.013 0.011 -0.004 -0.003 -0.0130∆ NFPIt-2 0.007 0.002 0.011 0.029 -0.008 0.022 0.009∆ NFPIt-3 0.002 0 0.003 0.009 -0.003 -0.005 0.005

Number of

observations 13571 5343 8228

3,549

2,240

2,839

719

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

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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 year, region, indicator

2011 crisis (ongoing) seems worse than 2008 crisis

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

Given that households could have many coping mechanisms (e.g. longer working 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, but the capacity to fully reduce inflation may be limited given higher international prices and growth scenarios

So, does Ethiopia need an urban social safety net?

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

4. Conclusions (cont.)

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Research implications: Further work could try to validate the wage series as a relevant

and accurate welfare indicator for poor

CSA could consider asking about food-in-kind for maids salaries, guards salaries

Arguably, the collection of wage series by statistical agencies elsewhere should be scaled up

They appear to be a cost-effective and very useful high frequency indicator of urban welfare, and in some contexts, agricultural welfare (e.g. South Asia)

4. Conclusions (cont.)

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Thank you!

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