1. From Rural to Urban, But not through Migration: Household Livelihood Responses to Urbanization in Northern Ethiopia Tsega G. Mezgebo1 2 nd International Conference on Sustainable Development in Africa, Dakar, November 27, 2015 Tsega G. Mezgebo and Catherine Porter

2. Outline Tsega G. Mezgebo2 1. Motivation 2. Peri-urbanization in Ethiopia: overview 3. Conceptual and Empirical Framework 4. Data, Summary Statistics and Descriptive analysis 5. Estimation Results 6. Conclusions and recommendation

3. Motivation Tsega G. Mezgebo3  Urban expansion is going to accelerate in most areas of the world. Urban population of  developing world to be about 64% by 2050  Africa to be about 50% by 2035 – i.e. about 37% in 2015.  Urban expansion is land intensive in these countries. They redraw their urban boundaries to fulfill the growing demand of urban land use.  This limits availability of arable land to the existing farming communities in peri-urban areas where natural resource based livelihoods eventually vanish and be replaced by nonfarm activities  So, there may be high transaction cost for those who are less able to adopt (i.e. negative adaptation due a shift from rewarding farm to low-return nonfarm activities).

4. Motivation tsegagi@gmail.com4  Hence, crucial to identify factors that contribute to smooth rural to urban livelihoods transitions for the those who are directly affected.  The literature on livelihood adaptation and diversification focus on rural areas.  However, peri-urban areas different from rural  No uniform definition for peri-urban areas.  Dynamic urban and rural livelihoods co-exits where the later vanish with time.  Diversification to nonfarm is essential for the farm households to make a living.  Given the peculiar feature, applying the common assumptions of rural livelihood diversification could be less appropriate to policy.

5. This study  Objective:  to investigate factors that influence the farm household’s, in peri-urban, decision to adopt specific income diversification strategies using data collected for the purpose.  to compare if the strategies and associated factors depend on the administration that the farm household belong – i.e. urban versus rural administration.  Aim: to contribute to policy in designing effective interventions to the poor in peri-urban to improve access to assets and productivity of the assets they already own. 5Tsega G. Mezgebo

6. Peri-urbanization in Ethiopia: an Overview Tsega G. Mezgebo6  Urban Ethiopia is expanding rapidly, annual urban population growth was 4.9% in 2013 (World Bank, 2015).  The urbanization process:  Land is owned by the sate; and urban and rural areas have defined boundary.  Urban authorities prepare development plan. Following endorsement of the plan, nearby rural villages incorporated to the town administrations (FDRE, 2008).  Then land is expropriated to different (nonfarm) investments.  Affected households receive compensation equivalent to the lost farm-income and property damages (FDRE, 2005).  This is the course where urbanization of peri-urban areas (peri- urbanization) starts formally.  However, rural urban divisions are vital in the policy sphere.  Urban focus on manufacturing, service and trade while rural on agriculture

7. Conceptual and Empirical Framework Tsega G. Mezgebo7  Ellis (2000), in rural context, classifies the causes to diversify into nonfarm as:  Choice or pull factors to accumulate wealth  Necessity or push factors to survive  We argue peri-urban farm households diversify to alternative income sources likely of Necessity.  Farmers who their lost farmland have to diversify to nonfarm for a living.  In contexts where markets for credit and insurance are missing, a household has to possess the necessary capital (skill, tools, and/finance) to enter high-niche nonfarm.  Households with experience in nonfarm activities have an advantage in accessing better-paying nonfarm activities.

8. Estimation model Tsega G. Mezgebo8  The farm household is assumed to choose a livelihood strategy over the other to maximize utility.  Maddala’s (1983) random utility model is applied to examine the factors associated with the decision.  We used MNL model and applied Hausman test (seemingly unrelated estimation).  We group the households into three main income diversification strategies in our data.  We have panel data but treated as pooled cross-section data and the time effect is controlled.

9. Data Tsega G. Mezgebo9  The study is based on panel data collected in 2011 and 2012 from farm households in peri-urban villages (from 17 villages in 9 districts) of Tigray, Ethiopia.  Peri-urban, in this study, is the sub-villages within 15kms from edge of the town built up.  Towns with a population of 20,000 were identified.  Then four towns (Mekelle, Adigrat, Axum and Alamata) were purposely selected for the study considering the expansion rate but households were selected randomly.

10. Data Tsega G. Mezgebo10  Each survey site has two groups – in urban versus rural administration, we call them rur-urban and rural respectively.  In 2011, the sample was 478 HH ( 240 rur-urban & 238 rural). Second round, in 2012, attrition rate was 3% and seemingly random.  Household income was collected from all sources  Income in per-adult equivalent unit is used for the analysis.  We classify the nonfarm sector to skilled and unskilled employments.

11. Figure 1: Map of survey sites Tsega G. Mezgebo11

12. Summary statistics, time-invariant vars Tsega G. Mezgebo 12

13. Summary statistics, time-variant vars Tsega G. Mezgebo13

14. Percentage distribution of income sources Tsega G. Mezgebo 14 2011 2012 Q1Q2Q3Q4Average UseQ1Q2Q3Q4AverageUse Rur-urban farm households Farm income On-farm (crop and livestock)433117242761483128232576 Nonfarm Skilled employment12149504440525 453935 Unskilled employment517189121812293118 32 Productive safety net (PSNP)135212415211137 Rent, remittance, etc.3822131512562814 121646 Mean income (ETB)604177433118251 10772673450110862 Rural households Farm income On-farm (crop and livestock)404255604992425449524991 Off-farm2233214322017 Nonfarm Skilled employment316262918417931352038 Unskilled employment192183123414201071330 Productive safety net (PSNP)2113831173141174963 Rent, remittance, etc.1551263519322726 Mean income (ETB)14312622382110358 1537302344799255

15. Percentage distribution of diversification strategies Tsega G. Mezgebo 15

16. Tsega G. Mezgebo16 Percentage d istribution of diversification strategies (re-grouped) Rur-urbanRural 2011 2012Average20112012Average Farm with skilled or skilled nonfarm only (“Skilled”) 42 3538444042 Farm with unskilled or unskilled nonfarm only (“Unskilled”) 18 3125343133 Farm with transfer income or transfer income only (“Transfer”) 40 3337222925 Observations (N) 240 234238227

17. Estimation results, pooled data Tsega G. Mezgebo 17

18. Estimation results, separate urban and Rural Tsega G. Mezgebo18

19. 5.Conclusion Tsega G. Mezgebo19  The results show that:  Agriculture is an important source of livelihood, although access to farmland is limited.  Almost all households earn income from diversified sources, i.e. diversification is a norm.  Participation in nonfarm employments is higher for the rural compared to the rur-urban.  Production behaviour of the better-off farm households is similar regardless of the administration they belong but not for the poor.  Factors associated with decision to choose income strategy depend on the administration that the farm household belongs.  Labor-poor farm households are marginalized in the emerging employment opportunities.  Experience in nonfarm play crucial role to engage in rewarding activities but not cash (money).

20. 6. Recommendation Tsega G. Mezgebo20  Targeted interventions should be designed to improve the productive capacity of the poor.  The land compensation packages should be revised and incorporate capacity building trainings with special emphasis to labor-poor farm households.  Further study to understand the poverty dynamics and risk perceptions of farm households.

21. Tsega G. Mezgebo21