Household and Spatial Drivers of Migration Patterns in Africa:...

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Household and Spatial Drivers of Migration Patterns in Africa: Evidence from Five Countries Valerie Mueller (IFPRI) Emily Schmidt (IFPRI) Nancy Lozano-Gracia (World Bank) Urbanization and Spatial Development of Countries Research Workshop July 13, 2015

Transcript of Household and Spatial Drivers of Migration Patterns in Africa:...

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Household and Spatial Drivers of Migration Patterns in Africa: Evidence from Five

Countries

Valerie Mueller (IFPRI)

Emily Schmidt (IFPRI)

Nancy Lozano-Gracia (World Bank)

Urbanization and Spatial Development of Countries Research Workshop

July 13, 2015

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Introduction

• Migration – key force shaping both origins and destinations

• Economic and physical mobility as forces to achieve structural change

• But SSA seems to be different - no clear agricultural or industrial revolution as in other countries to encourage rural-urban migration (Jedwab and Vollrath, 2015)

• Migration in sub-Saharan Africa characterized by labor ‘chasing’ due to distress or risk-reduction strategies (Campbell, 2011)

• Much yet to be understood…

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Objectives and research questions

• Is migration in Africa different?

• What are the key factors determining migration in SSA?

• How do they compare to places that faced an industrial (China), agricultural (India) revolution?

• What are the types of flows that dominate? Is rural-urban migration the main patter of movement?

• Is migration being used to diversify employment?

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Data

• LSMS-ISA Surveys• Ethiopia (2011-2, 2013-4)

• Malawi (2010-1, 2012-3)

• Nigeria (2010-1, 2012-3)

• Tanzania (2008-9, 2010-1, 2012-3)

• Uganda (2009-1, 2010-1, 2011-2)

• Detailed questions about individuals and households over time

• But… no perfect measure of migration, and short panels

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Measures of Migration

• Temporary migration - All countries document if household member moved over last 12 months (but don’t know where they go or why)

• Different measures of individual permanent migration out of the household

• Tracked migrants in waves after baseline (Malawi and Tanzania)

• Self-reported migration by proxy in waves after baseline (Ethiopia and Nigeria)

• Low long-distance household migration is low over two-year horizon

• Different place than birth location (NOT used here because we don’t know anything about pre-migration characteristics)

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Ethiopia requires careful interpretation – large urban areas excluded from wave 1

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Rural-Urban Migration

Country Year Time Period Source Rural-Urban Migration

Ethiopia 2013-4 2 years LSMS-ISA 25.3

Malawi 2012-3 2 years LSMS-ISA 6.1

Nigeria 2012-3 2 years LSMS-ISA 11.1

Tanzania 2012-3 2 years LSMS-ISA 14.1

China 2000 5 years Census, Cai,Park, and Zhao (2008)

40.8

India 2001 9 years Census, Ministry of Home Affairs

21.1

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Hypotheses – patterns of migration

• Hypothesis: Rural-rural migration patterns is driven by land scarcity, big households, and high population densities. People are NOT diversifying out of agriculture, they are moving to find a job in agriculture or access land for their own farm

• Hypothesis: Rural-rural migration patterns dominate because roads, liquidity constraints, education deficits and other factors pose barriers to moving to a city (Stark and Bloom, 1985; Stark, 1991; Rozelle et al., 1999; Wouterse and Taylor, 2008; Dillon et al., 2011). People are diversifying out of agriculture into non-agriculture in rural areas (e.g., to satisfy rise in demand for services).

• Hypothesis: Rural-urban patterns are predominantly explained by an absence of insurance mechanisms (Barrios et al., 2006; Poelhekke, 2011). People are diversifying out of agriculture into non-agriculture in cities where climate or conflict risk is low.

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“Migrating for Land” Hypothesis

Rural Urban

Non-Mig. Mig. t-test Non-Mig. Mig. t-test

ETHIOPIA

Household size 5.63 6.36 0.74*** 4.92 5.95 1.04***

Owned land 4.21 5.31 1.1 0.5 0.45 -0.04

GRUMP Pop. Density 180.19 183.27 3.09 149.29 142.8 -6.49

MALAWI

Household size 5.51 6.26 0.75*** 5.3 5.88 0.58***

Owned land 3.74 1.84 -1.9 0.45 0.31 -0.13**

GRUMP Pop. Density 208.23 198.72 -9.51** 1794.59 1914.98 120.39**

NIGERIA

Household size 7.91 8.13 0.21 6.78 7.10 0.31*

Owned land 2.63 3.52 0.88* 0.35 0.66 0.31***

GRUMP Pop. Density 325.39 402.23 76.84*** 1862.38 2007.89 145.51

TANZANIA

Household size 6.24 7.62 1.38*** 5.75 6.90 1.15***

Owned land 7.48 8.34 0.86 1.34 1.56 0.22

GRUMP Pop. Density 207.28 161.18 -46.11* 1242.25 1189.02 -53.23

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Constrained Migration HypothesisRural Urban

Non-Mig. Mig. t-test Non-Mig. Mig. t-testETHIOPIAPrimary Education 0.07 0.21 0.14*** 0.32 0.44 0.12***No. of rooms 1.70 1.86 0.16** 2.31 2.48 0.17Travel Time 223.44 223.54 0.10 179.27 207.02 27.75**

Distance to major road 16.44 14.61 -1.83** 14.29 16.48 2.20MALAWIPrimary Education 0.10 0.11 0.00 0.15 0.13 -0.02No. of rooms 2.70 2.83 0.12*** 3.23 3.41 0.17**Travel Time 131.68 130.85 -0.83 42.83 37.74 -5.09***

Distance to major road 9.50 9.20 -0.30 1.74 1.81 0.07NIGERIAPrimary Education 0.29 0.39 0.10*** 0.31 0.31 0.00No. of rooms 4.43 4.70 0.27** 3.57 3.75 0.17Travel Time 176.63 156.96 -19.67*** 65.99 75.44 9.45*

Distance to major road 17.76 15.69 -2.07*** 5.78 5.77 -0.00TANZANIAPrimary Education 0.51 0.57 0.06** 0.18 0.11 -0.07***No. of rooms 3.68 4.12 0.45*** 3.53 3.98 0.45***Travel Time 210.50 219.06 8.56 52.70 60.46 7.76

Distance to major road 22.89 23.84 0.96 45.76 41.47 -4.29

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Migration for insurance hypothesis

Rural Urban

Non-Mig. Mig. t-test Non-Mig. Mig. t-test

ETHIOPIA

Temperature wettest Q 19.26 19.32 0.05 19.21 19.54 0.33

Rainfall wettest Q 557.61 573.15 15.54*** 601.88 616.30 14.42

Conflict fatalities 0.82 0.93 0.11 0.80 0.93 0.13

MALAWI

Temperature wettest Q 23.08 23.21 0.13* 22.01 21.86 -0.15**

Rainfall wettest Q 674.62 657.51 -17.11*** 668.74 662.09 -6.65*

Conflict fatalities 0.02 0.02 0.00 2.52 2.90 0.38

NIGERIA

Temperature wettest Q 25.24 25.09 -0.15*** 25.29 25.16 -0.13***

Rainfall wettest Q 728.83 822.37 93.54*** 723.17 766.05 42.88***

Conflict fatalities 7.68 4.70 -2.97* 39.43 21.06 -18.36***

TANZANIA

Temperature wettest Q 23.51 23.38 -0.13 25.48 25.18 -0.31*

Rainfall wettest Q 582.72 538.48 -44.24*** 607.59 573.77 -33.83***

Conflict fatalities 0.14 0.14 -0.01 2.94 3.39 0.45

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Pre- and Post-Migration Employment Patterns

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What’s next?

• What is rural and what is urban?

• Are dynamics of peri-urban areas masked within the rural classification?• Explore breakdown of spatial patterns

• Uncovering the patterns of migration across five African countries:• Estimate multivariate regressions of migration to examine which hypotheses

dominate

• Robustness to measure of migration (temporary versus permanent)

• Robustness to panel framework (temporary, Tanzania permanent)