IFPRI/ESSP presentation

1. Rural Labour Markets in Transforming
Agricultural Economies: The Case of Ethiopia
Fantu Bachewe, Guush Berhane, Bart Minten, and Alemayehu S. Taffesse
IFPRI-ESSP
Ethiopia’s Rural – Urban Transformation: Opportunities and Gaps
21 February 2019
Addis Ababa
1

2. 2
Outline
1. Motivation
2. Share of different income sources, focusing on off farm income,
3. Importance of hired-in labor;
4. Trends in rural wages, drivers, and likely implications
5. Summary and policy implications

3. 3
1. Introduction
• Development of well-functioning labor markets crucial for
economic growth and livelihood opportunities, especially for youth
• Rural wage increases strongly linked with poverty reduction
• The poor regularly depend on such wages for their livelihood
• Important to understand the off-farm sector and labor markets
• Ethiopia’s economy is changing fast but unclear how important the
off-farm economy and labor income is in rural areas

4. 4
1. Introduction
• Presentation addresses:
- How important is the rural off-farm economy?
- What are the associates of off-farm income?
- Are rural wages changing?
- What are the drivers and implications of that change?
• Datasets:
- CSA: daily wages of unskilled laborers;
- Agricultural Growth Program (AGP) baseline survey (2011);
- Other datasets: 1/ large teff (2012) and coffee (2014) surveys; 2/ FTF
survey (2015); 3/ ERSS (2014)
• Data collected on crop & livestock production, agricultural & non-
agricultural wage income, and enterprise [self-employed non-
agricultural] income for 12 months preceding each HH survey

5. 5
2. Off-farm income in rural areas
• Contribution of sources to rural income
1. Agricultural income: 82% (Crop 71%; livestock: 10.7%)
• Share of livestock income higher, 21%, when all regions included
2. Wage income: 10% , as important as livestock income
3. Enterprise income: 8.1%, mostly agriculture based businesses
Crop
71.5%
Livestock
10.7%
Agricultural
wages
6.6%
Non-
agricultural
wages
3.1%
Enterprise
8.1%

6. 6
2. Off-farm income in rural areas
• Enterprise and wage income especially important for the poor
• Youth and female headed HHs rely more on off-farm income
• Enterprise important for poorest & richest, reflecting different enterprises
Income shares, by wealth quintile (%)
0
10
20
30
40
50
60
70
80
90
0
2
4
6
8
10
12
14
Quintile I Quintile II Quintile III Quintile IV Quintile V
Contributionofcropincome(%)
Contributionofnon-cropincome(%)
Ag wage Non-ag wage Enterprise Livestock Crop

7. • Prepared food/drinks & crafts more important for the poor
• Agricultural output & merchandise trade more important for the rich
Type of business enterprises engaged, by wealth quintile (%)
2. Off-farm income in rural areas
0
5
10
15
20
25
30
35
40
Quintile I Quintile II Quintile III Quintile IV Quintile V
Food and local drinks Crafts Trade-agricultural Outputs Trade-merchendise

8. 8
2. Off-farm income in rural areas
• 18% off-farm income in rural Ethiopia:
• Small compared to other African countries, and Asia & Latin-America
Off-farm income as share of total income in rural areas
0
10
20
30
40
50
60
Ethiopia Africa Asia Latin-America
%
Local non-farm Migration income

9. 9
2. Off-farm income in rural areas
• Associates of diversification; run tobit model with share of off-farm
income as dependent variable; and diversification index
Diversification index
Coeff. St.error
Age of household head (years) -0.003*** 0.000
Education of head 0.018*** 0.005
Household size 0.011*** 0.003
Purchased at least one input on credit 0.026* 0.014
Land quality index -0.006** 0.002
Tropical livestock units -0.012*** 0.002
Travel time to nearest 50K town (mns) -0.0002*** 0.000
Distance from Addis Ababa (00 KMs) -0.014* 0.006

10. 10
2. Off-farm income in rural areas
• Major results on diversification:
1. Younger heads of households are more likely to be associated with
off-farm income (especially ag. wage and enterprise income)
2. Education associated with more enterprise & non-ag. wage income
3. Gender link: wage income negatively associated with proportion of
females in the HH (women make up 1/3rd of hired labor)
4. More and better quality agricultural assets associated with less
diversification
5. Distance to cities an important associate of non-farm income.
Households 100 kms farther from Addis have 11% lower share of off-
farm income.

11. 11
3. Agricultural wage labor
• Hired-in agricultural wage labor: 7% of all labor
• Relatively more important in Tigray and SNNP
0
20
40
60
80
100
All Tigray Amhara Oromiya SNNP
%
Hired labor in crop production
Family labor Hired labor

12. 12
3. Agricultural wage labor
• Labor arrangement in teff producing areas differ by remoteness
• Monetization/use of hired labor higher when less remote;
• In more remote areas, more reliance on exchange labor
Family, wage, and exchange labor use in teff production
0
20406080
share(%)
0 50 100 150
distance to Addis (Birr/quintal)
95% CI family labor
95% CI wage labor
95% CI exchange labor

13. 13
3. Agricultural wage labor
• Associates of hiring-in of agricultural wage laborers (tobit):
1. Household characteristics
- Bigger households use less hired labor
- Higher dependency ratio lead to more hired-in labor
- Educated households use more hired labor
2. Characteristics of the farm
- Larger farms use more hired-in labor (1 hectare more; share 12% up)
- Quality land associated with more hired labor
3. Location
- Higher in Tigray than in other regions
- Poorer districts use more hired labor
- Distance to Addis: More used if closer to Addis

14. 14
4. Rural wages - changes
• Rely on CSA data from 2004 to 2018
• Use different ways of converting/deflation (exchange rate; CPI)
• Wages in US dollars 3.8 times higher in 2018 compared to 2004
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Jul-04
Feb-05
Sep-05
Apr-06
Nov-06
Jun-07
Jan-08
Aug-08
Mar-09
Oct-09
May-10
Dec-10
Jul-11
Feb-12
Sep-12
Apr-13
Nov-13
Jun-14
Jan-15
Aug-15
Mar-16
Oct-16
May-17
Dec-17
Jul-18
Wages in US dollars

15. 15
4. Rural wages - changes
• Between 3rd quarters of 2004 and 2018: real wages increased by 69%
in rural areas and by 70% in urban areas (4% per year in rural areas)
20
25
30
35
40
45
50
55
Jul-04
Mar-05
Nov-05
Jul-06
Mar-07
Nov-07
Jul-08
Mar-09
Nov-09
Jul-10
Mar-11
Nov-11
Jul-12
Mar-13
Nov-13
Jul-14
Mar-15
Nov-15
Jul-16
Mar-17
Nov-17
Jul-18
RealwagesinDecember2011prices
GCPI deflated-rural
GCPI deflated-urban

16. 16
4. Rural wages - changes
• Agricultural wages on average 1.27 USD per day (in AGP zones);
however significant variation
• Compared to Asian countries, wages significantly lower; about 1 USD
higher in Nepal and Myanmar; 1.59 USD higher in Bangladesh
05
101520
0 2 4 6 8
Agricultural wages (USD/day) 0 3 6 9 12
Nepal (2010)
Sri Lanka (2012)
Myanmar (2004)
Malaysia (2012)
Bangladesh (2010)
Ethiopia (2012)
USD/day
Distribution of wages in AGP zones Comparison of wages in Ethiopia with
Asian countries

17. 17
4. Rural wages - drivers
• Associates of agricultural wages:
1. Time of year: compared to land preparation, 13 % lower at planting,
12% higher at weeding; 17% higher at harvesting
2. Gender: men earn 8% more
3. Age: older people earn less (0.2% less per year extra)
4. Remoteness: 100 kms away from Addis reduces wage by 7%
5. Poverty in the district: The higher the poverty, the lower the wage
6. Regions: higher wages in Tigray and Amhara

18. 18
4. Rural wages - drivers
Look at the drivers for wage changes:
• Growth in unskilled real wage linked with economic growth,
particularly with agricultural growth
Economic growth and unskilled real wage elasticity (1999-2014)
Real… Elasticity of rural wages
GDP 0.230
Agricultural GDP 0.305
Manufacturing GDP 0.215
Industry GDP 0.187
Services GDP 0.161
Note: All estimates are statistically significant at 1%.

19. 19
4. Rural wages - drivers
• Role of the Productive Safety Net Program (PSNP)
20
25
30
35
40
45
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Real wage PSNP vs non-PSNP areas (real birr/day)
PSNP non-PSNP

20. 20
4. Rural wages - implications
1. Herbicides use increasing
• Rapidly taking off in Ethiopia (2013 imports 5 times higher than 2002)
• Herbicides use negatively associated with (substitutes) weeding labor
2. Mechanization:
- Higher wages provide incentives for mechanization in agriculture
- In Ethiopia, mechanization is still rather low;
- FTF survey: estimated 9% farmers use some form of mechanization
0
20406080
Povertyheadcountindex
10 20 30 40 50 60
Real wages, December 2011 prices
95% confidence interval
Predicted poverty head count index
3. Poverty:
Real wages and poverty
head count index
negatively correlated

21. 21
5. Conclusions
• Major findings:
1/ Off-farm income makes up 18% of total income of rural households;
• Wage income contributes 10%, as important as livestock income
2/ Off-farm income especially important for the poorest
• Makes up 26% of their total income (agricultural wage 13%)
• Push factors for diversification still relatively more important
3/ Off-farm income and wages significantly lower than other countries
• Rural wages are rapidly increasing: 70% higher in 2018 than in 2004;
• Drivers: improved agricultural performance among important
4/ Implications of wage changes on poverty and agricultural production
practices (more herbicides use & mechanization after threshold wages)

22. 22
5. Conclusions
• Implications:
1/ Low wages have been an asset to attract labor-intensive industries.
• This might be changing and Ethiopia might slightly lose that edge
• Ensure that the youth upgrade skills towards higher labor productivity
2/ Create conducive policies that allow the adoption of appropriate
modern technologies at low costs
3/ Ensure flexible labor markets so that people can benefit from these
opportunities

23. Thank you.