Decomposing the contribution of migration to poverty reduction: methodology and application to Tanzania

ABSTRACT

In an economy with migration, poverty changes are composed of a number of forces, including the income gains and losses realized by the various migration streams. We present a simple but powerful decomposition methodology that uses panel data to measure the contributions of different migration streams to overall poverty change. An application to Tanzania shows the new insights that are provided – in particular on the role of migration to secondary towns in poverty reduction.

KEYWORDS:

• Panel data
• household surveys
• internal migration
• urbanization
• poverty reduction
• decomposable poverty indices

JEL CLASSIFICATION:

• J61
• O15
• O55

Acknowledgements

We thank the editor and an anonymous referee for helpful comments. We gratefully acknowledge support by the World Bank Research Committee and the Research Foundation Flanders (FWO) under grant EOS ID G0G4318N. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The basic facts are reviewed in Christiaensen and Kanbur (2017).

² This form of decomposition is common, but can result in share contributions that lie under −1 or above 1. This can happen, for example, when large but opposite poverty changes are observed across the different migration streams, which largely cancel each other out to result in little overall change in poverty. An alternative is to define ε’_rk = [x_rk ΔP_α,rk]/ ΔP’_α with ΔP’_α = x₁ |ΔP_α,1| + x₂ |ΔP_α,2| + …… + x _G |ΔP_α,G|. Using the weighted sum of the absolute poverty changes in each group as the denominator gives values ε’_rk between 0 and 1 for positive contribution and between −1 and 0 for negative contributions. The sum of the absolute values of these shares will also be 1.

³ The survey is described in detail in De Weerdt et al. (2012).

⁴ See http://surveys.worldbank.org/lsms/integrated-surveys-agriculture-ISA for a number of recent examples.

⁵ In 2010, households were found in three cities: Dar es Salaam, Mwanza and Kampala. This is defining cities as locations (districts) with more than 500,000 inhabitants. The 2012 census puts the population of Dar es Salaam at 4.36m and Mwanza at 0.7m. One caveat to bear in mind is that the census classification is based on 2002 data, while we observe respondents in 2010.