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Effects of migration and remittances on poverty and inequality A comparison between Burkina Faso, Kenya, Nigeria, Senegal, South Africa, and Uganda Y.

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Presentation on theme: "Effects of migration and remittances on poverty and inequality A comparison between Burkina Faso, Kenya, Nigeria, Senegal, South Africa, and Uganda Y."— Presentation transcript:

1 Effects of migration and remittances on poverty and inequality A comparison between Burkina Faso, Kenya, Nigeria, Senegal, South Africa, and Uganda Y. Bambio F. Cissé D. Gaye Consortium pour la Recherche Economique et Sociale Dakar, June 5 th 2014

2 Outline Objectives and hypotheses Context Theory Methodology Preliminary results Main remarks

3 Objectives and hypotheses Objective: Evaluate impact of migration and remittances on poverty and inequality in Burkina Faso, Kenya, Nigeria, Senegal, South Africa and Uganda. Hypotheses: – Migration and remittances decrease poverty, and increase inequality. – The impact of international remittances on poverty and inequality is greater compared to that from internal remittances.

4 Context Increase in migration and remittances in Africa – Stock of emigrants: 22 millions (2.5% of population) [World Bank, 2010], – Of which 30% are doctors and nurses (World Bank, 2010)

5 International Remittances Recipients By Region in 2008 (%)

6 Top Ten International Remittances Recipient Countries in Africa, 2008 (US$ million)

7 Context (ctd) Increasing interest in research on impacts of migration and remittances. Challenge in identifying micro impacts. – Availability of appropriate data. – Appropriate econometric methods, etc. Several approaches exist.

8 Theory Several theories on migration and remittances – Micro analysis: migration results essentially from individual or household rational choice, and social capital. – Neoclassical economy, New migration economy. – Close link between migration and remittances. – Maximization of household income and relative “privation” – Various reasons for remittances: altruism, risk sharing, inheritance, etc. Theoretical basis: maximization of joint utility under budget constraint.

9 Methodology  Some approaches Experimental Methods Difference-in-Difference Propensity Score Matching Instrumental Variables Before/After method Etc.

10 Methodology (ctd)  Model and estimation Counterfactual approach – Combination of Propensity Score Matching and Instrumental Variables methods. – Objective of this combination: reduce both biases from observables et aux non-observables characteristics. – Main potential risk: limits in sample sizes and appropriate instruments.

11 Methodology (ctd) Following Garip (2007):  Model and estimation (ctd)

12 Methodology (ctd)  Model and estimation Appropriate treatment of errors: – Consider predicted error for non-migrants households, – Generate an error using weighted cumulative probability function, and a random error term for migrant households. Calculate and compare poverty and inequality indicators from the 2 groups.

13 Methodology (ctd)  Data Source: Data from Migration and Remittances Household Surveys in Burkina Faso, Kenya, Nigeria, Senegal, South Africa, and Uganda (Africa Migration Project – World Bank) Contents: – Cross-section household data (2009-2010), – About 2,000 households per country, – Same data collection methodology, – Various information, including migration, remittances, social- economic characteristics (education, marital status, housing conditions, labor force participation, assets, access to finance, etc.).

14 Table 1: Determinants of international migration Burkina FasoNigeriaSenegal Age of household head0.007*0.006**-0.014*** Squared age of household head0.0000010.000040.0002*** Sex of household head (1 = male)0.055-0.063**-0.156*** Own house/building (1 = yes)-0.0880.096***0.130*** Own agricultural land (1 = yes-0.045-0.034***-0.098*** Highest education of household head: primary level (1 = yes)0.0060.0210.044 Highest education of household: head: secondary level (1 = yes)-0.0430.025**0.056* Highest education of household head: tertiary level (1 = yes)-0.0470.0150.024 Log household size0.132***-0.028***0.193*** Household residence: in most urban region (1 = yes)-0.0130.028-0.021 Constant-0.303**-0.0250.153 F (.)17.7***18.98***41.64*** F test of excluded instruments: F (.)23.03***35.89***43.33*** Angrist-Pischke multivariate F test of excluded instruments: F (.)0.471.863.66* Number of observations2,0832,2011,950 Preliminary results

15 Table 2: Determinants of international remittances Burkina FasoNigeriaSenegal Age of household head0.010***0.006***-0.017*** Squared age of household head0.000030.00005**0.0002*** Sex of household head (1 = male)0.050-0.011-0.220*** Own house/building (1 = yes)-0.0410.077***0.085*** Own agricultural land (1 = yes0.001-0.025**-0.089*** Highest education of household head: primary level (1 = yes)-0.0020.024**-0.081*** Highest education of household: head: secondary level (1 = yes)0.0190.0160.026 Highest education of household head: tertiary level (1 = yes)0.068-0.002-0.004 Log household size0.116***-0.025***0.210*** Household residence: in most urban region (1 = yes)-0.055-0.023-0.055** Constant-0.485***-0.091*0.282** F (.)19.34***14.87***43.94*** F test of excluded instruments: F (.)26.29***28.32***45.58 Angrist-Pischke multivariate F test of excluded instruments: F (.)0.541.473.85*** Number of observations2,0832,2011,950 Preliminary results (ctd)

16 Table 3: Effects of international migration and remittances on per capita expenditure Burkina FasoNigeriaSenegal Migrant household-2.6622.5072.136*** Remittance receiving household2.4992.872-1.109 Own agricultural land (1 = yes-0.311*0.041-0.374 Highest education of household head: primary level (1 = yes)0.029-0.1010.085 Highest education of household: head: secondary level (1 = yes)0.620***0.119*0.276*** Highest education of household head: tertiary level (1 = yes)1.504**0.583***0.375** Log household size-0.130*-0.329***-0.688*** Household residence: in most urban region (1 = yes)0.646**0.539**0.246*** Constant11.965***11.576***13.247*** F (.)9.23***46.14***79.94*** Number of observations2,0832,2011,950 Preliminary results (ctd)

17 Table 4: Identification and instrument tests Burkina FasoNigeriaSenegal Underidentification test2.458.26**14.67*** Weak identification test0.612.063.68 Weak-instrument-robust inference Anderson-Rubin Wald test [F (.)]4.08***83.11***18.96*** Stock-Wright LM S statistic [Chi-sq (.)]16.29***290.08***73.41*** Overidentification test (Sargan)]2.77812.309***3.345 Preliminary results (ctd)

18 Table 5: Average Treatment Effect of international migration on per capita expenditure Burkina FasoNigeriaSenegal Nearest Neighbor Number of observations, treatment692565661 Number of observations, comparison634511491 Average treatment effect on the treated (ATT)0.0870.4020.242 t-Statistics1.7933.6304.025 Stratification Matching Number of observations, treatment692565661 Number of observations, comparison137516131290 Average treatment effect on the treated (ATT)0.0760.3380.260 t-Statistics2.1254.3985.884 Kernel Matching Number of observations, treatment692565661 Number of observations, comparison137516131290 Average treatment effect on the treated (ATT)0.0730.4140.255 t-Statistics2.0885.1596.025 Direct Matching using Nearest neighbor Coefficient (SATT)0.03550.2168**0.1222 Number of observations2,0832,2081,953 Number of matches111 Preliminary results (ctd)

19 Table 6: Average Treatment Effect of international remittances on per capita expenditure Burkina FasoNigeriaSenegal Nearest Neighbor Number of observations, treatment419285579 Number of observations, comparison461301441 Average treatment effect on the treated (ATT)0.0600.3970.308 t-Statistics1.1202.7494.941 Stratification Matching Number of observations, treatment419285579 Number of observations, comparison1,6491,8971,371 Average treatment effect on the treated (ATT)-0.0340.2930.264 t-Statistics-0.8263.3475.902 Kernel Matching Number of observations, treatment419285579 Number of observations, comparison16491,8971371 Average treatment effect on the treated (ATT)-0.0210.3880.262 t-Statistics-0.5403.9215.181 Direct Matching using Nearest neighbor Coefficient (SATT)-.02760.241*0.2014** Number of observations2,0832,2081,950 Number of matches111 Preliminary results (ctd)

20 Table 7: Determinants of internal migration Burkina FasoNigeriaSenegal Age of household head 0.0030.018*** 0.003 Squared age of household head 0.00001-0.00010** 0.00001 Sex of household head (1 = male) -0.026-0.132*** -0.054** Own house/building (1 = yes) 0.0970.026 -0.027 Own agricultural land (1 = yes 0.120***0.041* 0.079*** Highest education of household head: primary level (1 = yes) 0.0450.060** -0.093*** Highest education of household: head: secondary level (1 = yes) 0.0080.091*** 0.001 Highest education of household head: tertiary level (1 = yes) 0.0190.119*** -0.078 Log household size 0.001-0.071*** -0.064*** Household residence: in most urban region (1 = yes) 0.0620.116* -0.200*** Constant -0.016-0.143 0.374*** F (.)1.87**13.36***14.61*** F test of excluded instruments: F (.)2.47**26.58***1.85 Angrist-Pischke multivariate F test of excluded instruments: F (.)0.724.21***1.48 Number of observations2,0832,2011,950 Preliminary results (ctd)

21 Table 8: Determinants of internal remittances Burkina FasoNigeriaSenegal Age of household head 0.0030.009** -0.005 Squared age of household head -0.00001-0.00005 0.00008** Sex of household head (1 = male) 0.078***-0.107*** -0.094*** Own house/building (1 = yes) 0.154***0.069*** 0.031 Own agricultural land (1 = yes 0.114***-0.004 0.087*** Highest education of household head: primary level (1 = yes) 0.0270.002 -0.074** Highest education of household: head: secondary level (1 = yes) 0.089*-0.001 0.039 Highest education of household head: tertiary level (1 = yes) -0.0090.022 -0.053 Log household size -0.007-0.013 0.015 Household residence: in most urban region (1 = yes) 0.057-0.014 -0.194*** Constant -0.206**-0.077 0.292** F (.)4.63***9.75***18.80*** F test of excluded instruments: F (.)8.64***23.51***14.65*** Angrist-Pischke multivariate F test of excluded instruments: F (.)2.54*3.72**11.75*** Number of observations2,0832,2011,950

22 Preliminary results (ctd) Table 9: Effects of internal migration and remittances on per capita expenditure Burkina FasoNigeriaSenegal Migrant household -1.824-3.729** -1.522 Remittance receiving household 1.4668.737*** 2.128*** Own agricultural land (1 = yes -0.1440.081 -0.558*** Highest education of household head: primary level (1 = yes) 0.0670.210 0.294** Highest education of household: head: secondary level (1 = yes) 0.687***0.557*** 0.307*** Highest education of household head: tertiary level (1 = yes) 1.864***0.840*** 0.464** Log household size -0.170***-0.568*** -0.627*** Household residence: in most urban region (1 = yes) 0.584***1.091** 0.375* Constant 11.769***12.112*** 13.310*** F (.)15.49***9.95***68.17*** Number of observations2,0832,2011,950

23 Preliminary results (ctd) Table 10: Identification and instrument tests Burkina FasoNigeriaSenegal Underidentification test3.4011.42***5.39 Weak identification test0.852.861.34 Weak-instrument-robust inference Anderson-Rubin Wald test [F (.)]4.0883.11***18.96*** Stock-Wright LM S statistic [Chi-sq (.)]16.29290.08***73.41*** Overidentification test (Sargan)]7.031**3.0874.856*

24 Preliminary results (ctd) Table 11: Average Treatment Effect of internal migration on per capita expenditure Burkina FasoNigeriaSenegal Nearest Neighbor Number of observations, treatment654854594 Number of observations, comparison660639491 Average treatment effect on the treated (ATT)-0.048-0.019-0.130 t-Statistics-0.983-0.247-2.088 Stratification Matching Number of observations, treatment653854594 Number of observations, comparison142213531359 Average treatment effect on the treated (ATT)-0.055-0.054-0.163 t-Statistics-1.429-0.913-4.021 Kernel Matching Number of observations, treatment654854594 Number of observations, comparison142113531359 Average treatment effect on the treated (ATT)-0.033-0.049-0.158 t-Statistics-0.889-0.819-3.696 Direct Matching using Nearest neighbor Coefficient (SATT)0.02880.080-0.2037** Number of observations2,0832,2081,950 Number of matches111

25 Preliminary results (ctd) Table 12: Average Treatment Effect of internal remittances on per capita expenditure Burkina FasoNigeriaSenegal Nearest Neighbor Number of observations, treatment348358435 Number of observations, comparison349366389 Average treatment effect on the treated (ATT)-0.0200.104-0.103 t-Statistics-0.3081.213 Stratification Matching Number of observations, treatment347358435 Number of observations, comparison173518181483 Average treatment effect on the treated (ATT)-0.1040.044-0.105 t-Statistics-2.2420.575-2.498 Kernel Matching Number of observations, treatment348358435 Number of observations, comparison173418181483 Average treatment effect on the treated (ATT)-0.0720.057-0.096 t-Statistics-1.5980.854-2.507 Direct Matching using Nearest neighbor Coefficient (SATT)0.01830.070-0.1417* Number of observations2,0832,2081,950 Number of matches111

26 Quick remarks Model instruments need to be improved, particularly for some countries; Data are collected on a year that is specific for most of countries; Challenge in using external data on poverty (e.g. poverty line); Both migration and remittances seem to have positive impact on per capita expenditure; with different amplitude per country.

27 Thank you !


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