ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE
Off-farm income and labor markets in rural Ethiopia
PRELIMINARY RESULTS
Fantu Bachewe, Guush Berhane, Bart Minten, and Alemayehu S. TaffesseIFPRI ESSP
Addis Ababa, Ethiopia
1
2
1. Introduction • Development of well-functioning labor markets crucial for economic
growth and livelihood opportunities, especially for youth• Rural wages strongly linked with poverty reduction; important to
understand these labor markets• Ethiopia’s economy is changing fast but unclear how important the
off-farm economy and labor income is in rural areas• Purpose of the presentation: - How important is the rural off-farm economy?- What are the associates with off-farm income and rural income
diversification?- Are rural wages changing?- What are drivers and implications of that change?
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2. Data
• CSA: Wage data collected during monthly price survey (120 markets covered in the country)
• Agricultural Growth Programme (AGP) survey: fielded in May 2011 (information on 2010/11 agricultural season); collected in 4 major regions in the country;
• Other datasets used: 1/ large teff (2012) and coffee (2014) surveys; 2/ FTF survey (2015); 3/ ERSS (2014)
• In all surveys, information collected on agricultural crop production, livestock, agricultural wage and non-wage income, and enterprise income for 12 months preceding the survey
• Crop income is value of output less variable costs; livestock income is value of livestock sold and slaughtered and value of livestock products, minus variable costs; enterprise income is gross enterprise income minus variable costs
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3. Off-farm income in rural areas • Crop income as source of rural income overwhelming (71%) • Wage income (10%) as important as livestock income • Agricultural wages twice as important as non-ag. wages• Enterprise income: 8%
All Tigray Amhara Oromiya SNNP0
20
40
60
80
100
Income sources in rural areas (AGP)
Crop Livestock Agricultural wageNon-ag. wage Enterprise
%
5
3. Off-farm income in rural areas • ERSS (national representative) paints a rather similar picture • Differences: 1/ Livestock more important than in AGP areas; 2/ Wage
and enterprise income less important than in AGP areas; 3/Wage/enterprise income seemingly higher in high potential areas
All Tigray Amhara Oromiya SNNP0
20
40
60
80
100
Income sources in rural areas (ERSS)
Crop Livestock Casual laborSalaried workers Enterprise
%
6
3. Off-farm income in rural areas • Look at female/male youth/mature headed household differences• Youth-headed households depend more on off-farm income• Female-headed households depend more on off-farm income
Male-youth Female-youth Female-mature Male-mature0
20
40
60
80
100
Income sources inrural areas (AGP)
Crop Livestock Agricultural wageNon-ag. wage Enterprise
%
7
3. Off-farm income in rural areas • Off-farm income and wage income especially important for the poor• Enterprise income shares higher for poorest and richest, reflecting
different enterprises (brewing/liquor versus agricultural trade resp.)
Quintile I Quintile II Quintile III Quintile IV Quintile V0
2
4
6
8
10
12
14
20
30
40
50
60
70
80
90
Livestock Wage, agricultural Wage, non-agriculturalEnterprise Crop
Cont
ributi
on o
f non
-cro
p in
com
e (%
)
Cont
ributi
on o
f cro
p in
com
e (%
)
Crafts17%
Trade-grains16%
Trade-livestock11%
Trade-non agricultural10%
Milling1%
Tella (local ale)5%
Araqi (local liquor)
19%
Enjera/Dabbo (bread)
3%
Other19%
Type of business enterprise engaged, (%)
3. Off-farm income in rural areas
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3. Off-farm income in rural areas • Associates of diversification; run tobit model with share of income in
off-farm as dependent variable; and diversification index Diversification index
Coeff. St.errorAge of household head (years) -0.003*** 0.000Education of head 0.018*** 0.005Household size 0.011*** 0.003Purchased at least one input on credit 0.026* 0.014Land quality index -0.006** 0.002Tropical livestock units -0.012*** 0.002Travel time to nearest 50K town (mns) -0.0002*** 0.000Distance from Addis Ababa (00 KMs) -0.014* 0.006
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3. 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 agricultural wages and enterprise income)
2. Education associated with more enterprise income and non-ag. income
3. Gender link. Women make up 1/3rd of hired labor; men 2/3rds.4. More and better quality agricultural assets associated with less
diversification5. Distance to cities an important associate of non-farm income.
Households 100 kms farther from Addis have 11% lower share of off-farm income.
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3. Off-farm income in rural areas • 18% off-farm income in rural Ethiopia:- Small compared to other African countries- Small compared to Asia and Latin-America
Africa Asia Latin-America0
10
20
30
40
50
60
Local non-farm Migration income
%
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4. Agricultural wage labor • Hired agricultural wage labor: 7% of all labor• Relatively more important in Tigray and SNNP
All Tigray Amhara Oromiya SNNP0
20
40
60
80
100Hired labor in crop production
Family labor Hired labor
%
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4. Agricultural wage labor • Importance of hired labor varies by task• In teff, less hired labor during production; most at harvest and
afterwards
Tilling Input use Weeding Harvest Post-harvest Threshing0
20
40
60
80
100
Labor by crop activity
Family Hired Exchange
%
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4. Agricultural wage labor • Associates of agricultural wages:1. Time of year: compare to land preparation, 13 % lower at planting,
12% higher at weeding; 17% higher at harvesting 2. Gender: men earn 8% more3. 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 wage6. Regions: higher wages in Tigray and Amhara
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4. 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 labor3. Location- Higher in Tigray than in other regions- Poorer districts use more hired labor- Distance to Addis: More used if closer to Addis
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4. Agricultural wage labor • Labor arrangement in teff differ by remoteness• Monetization when less remote; in more remote areas, more reliance
on exchange labor instead of hired labor
020
4060
80sh
are
(%)
0 50 100 150distance to Addis (Birr/quintal)
95% CI family labor95% CI wage labor95% CI exchange labor
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4. Agricultural wage labor • Average agricultural wages on average 1.27 USD per day (in AGP
zones); however significant variation • Compared to other (Asian) countries, wages significantly lower; 0.95
USD higher in Nepal; 1.59 USD higher in Bangladesh; 1 USD higher in Myanmar
05
1015
20
Obs
erva
tions
(per
cent
)
0 2 4 6 8Agricultural wages (USD/day)
Nepal (2010)
Myanmar (2004)
Bangladesh (2010)
0 3 6 9 12
USD/day
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5. Rural wages - changes • Rely on CSA price data from 2004 to 2015• Use different ways of converting/deflation (exchange rate; CPI)• Wages over times higher in nominal USD in 2015 compared to 2004
Jul-0
4Ja
n-05
Jul-0
5Ja
n-06
Jul-0
6Ja
n-07
Jul-0
7Ja
n-08
Jul-0
8Ja
n-09
Jul-0
9Ja
n-10
Jul-1
0Ja
n-11
Jul-1
1Ja
n-12
Jul-1
2Ja
n-13
Jul-1
3Ja
n-14
Jul-1
4Ja
n-15
Jul-1
50.00
0.50
1.00
1.50
2.00
2.50
3.00Wages in USDWages in US CPI deflated real USD
Wag
es in
nom
inal
and
real
USD
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5. Rural wages - changes • Urban and rural wages deflated by the CPI• Between 2004 and 2015: Real rural wages increased by 46%; real
urban wages increased by 72%
Jul-04
Feb-05
Sep-05
Apr-06
Nov-06Jun-07
Jan-08
Aug-08
Mar-09Oct-
09
May-10
Dec-10Jul-1
1
Feb-12
Sep-12
Apr-13
Nov-13Jun-14
Jan-15
Aug-1520
25
30
35
40
45
50
GCPI deflated-ruralGCPI deflated-urban
Real
wag
es in
Dec
. 201
1 pr
ices
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5. Rural wages - changes• Regional differences for rural wages deflated by the CPI• Least changes in SNNP; biggest improvement in Tigray
15
20
25
30
35
40
45
50
55 Tigray Amhara
Oromiya SNNP
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5. Rural wages - changes • Urban and rural wages deflated by the Poor People’s CPI• Between 2004 and 2015: Real rural wages increased by 46%; real
urban wages increased by 52%; lower than with other methods
Jul-04Jan
-05Jul-0
5Jan
-06Jul-0
6Jan
-07Jul-0
7Jan
-08Jul-0
8Jan
-09Jul-0
9Jan
-10Jul-1
0Jan
-11Jul-1
1Jan
-12Jul-1
2Jan
-13Jul-1
3Jan
-14Jul-1
4Jan
-15Jul-1
520
25
30
35
40
45
50PP-GCPI deflated-ruralPP-GCPI deflated-urban
Real
wag
es in
Dec
. 201
1 pr
ices
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5. Rural wages - drivers
Look at the drivers for wage changes: • Estimate the following regression:Ln (real wage) = a + b lnY + e• Growth-unskilled real wage elasticity
Real… Zones where woreda pop. <
30 k
Zones where woreda pop. <
50 k
Rural areas Non-urban regions
GDP 0.22 0.18 0.15 0.12
Agricultural GDP
0.24 0.20 0.17 0.15
Manufacturing GDP
0.19 0.16 0.14 0.12
Industry GDP 0.17 0.14 0.12 0.10
Services GDP 0.15 0.12 0.11 0.09
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5. Rural wages - implications
1. Poverty
Correlation of real wages and poverty head count index0
2040
6080
Pov
erty
hea
d co
unt i
ndex
10 20 30 40 50 60
Real wages, December 2011 prices
95% confidence intervalPredicted poverty head count index
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5. Rural wages - implications
1. Poverty • Estimate the following regression (at zonal level; 4 years):Ln (Poverty) = a + b ln real wage + e• A 1% increase in poverty is associated with a 0.26% - 0.35% decrease
in wages
OLS FE
Model 1 Model 2 Model 3 Model 1 Model 2
Log real wages
0.13 -0.26 -0.49 -0.30 -0.35
Bold: significant at 5% or 10%
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5. Rural wages - implications
2. Increasing use of herbicides
20022003
20042005
20062007
20082009
20102011
20122013
0
4
8
12
16
Herbicides imports (millions USD)
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5. Rural wages - implications
2. Increasing use of herbicidesHerbicides is a substitute for weeding; rapidly taking off in Ethiopia
01
23
log(
valu
e he
rbic
ides
/ha)
0 2 4 6Log(weeding labor/ha)
95% interval correlation
020
4060
8010
0%
of f
arm
ers
0 50 100 150Transport costs to Addis (Birr/quintal)
95% CI herbicides 201295% CI herbicides 2002
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5. Rural wages - implications
3. Mechanization - Higher wages provide incentives for mechanization in agriculture- In Ethiopia, mechanization is still rather low; In FTF survey, estimated:1. 9% of farmers use some form of mechanization2. 5% in plowing; 3% in harvesting; 2% in threshing3. Strong threshold effect (Berhane et al., 2016)
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5. Rural wages - implications
4. Impact of off-farm income on modern input use - Off-farm income might lead to relaxation of credit constraints in
period of input needs- Study association of off-farm income and modern inputs with AGP
data through probit model- Find slightly significant (10%) and positive association between
fertilizer use and off-farm income: households that had off-farm income were 7% more likely to use chemical fertilizer
- No association with improved seeds and agro-chemicals
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6. Conclusions
• Major findings:1/ Off-farm income makes up 18% of total income; Wage income is 10% of total income, as important as livestock income2/ Off-farm income (26% of their income) and agricultural wage income especially important for the poorest (13% of their income); push factors for diversification still relatively more important 3/ Wages significantly lower than in other countries; however, rural wages are rapidly increasing; 50% higher in real terms in 2015 compared to 2004; especially improved agricultural performance has contributed to that change4/ Implications of wage changes on poverty and agricultural production practices (more use of herbicides)
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6. Conclusions
• Implications:1/ Low wages have been an asset for the attraction of labor-intensive industries. That might be changing and Ethiopia might lose that edge. Ensure that the youth will upgrade skills towards higher labor productivity2/ Push for the adoption of labor-saving technologies; important that Ethiopia implements pro-actively policies that allow appropriate technologies at low costs3/ Ensure flexible labor markets so that people can benefit from these opportunities
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