The Impact of Migration on Assets
for Sending Households
Migration has economic and social costs that require access
to and control over resources. Kothari (2002) presents an analysis
of how poor people’s migration choices are impaired by different
forms of social exclusion, which result from inequitable access
to different capital resources and institutions. These include economic
assets (e.g. land ownership, savings), human capital (e.g. education,
skills, age), social capital (e.g. kinship networks), cultural capital
(e.g. ethnicity, caste, gender, language), geography (e.g. natural
environment, rural remoteness) and political capital (e.g. political
participation and citizenship).
Ownership of economic assets such as land and livestock and financial
savings are often important determinants of whether an individual
or household on the one hand needs (or is sufficiently risk averse)
to pursue livelihood diversification through migration, and on the
other can afford the financial costs of migrating (in the presence
of credit market imperfections that limit opportunities for borrowing).
Furthermore, migration can provide avenues and opportunities to
asset access and accumulation for some migrants, while others experience
asset depletion as a consequence of migration.
Key Research Questions
||To what extent does initial asset access
||Does migration facilitate asset accumulation
for Egyptians and Ghanaians?
||Are different types of migrants able to
accumulate significantly more than others, and why?
Causes and Consequences
1. For this project we will draw on a database collected
by the Netherlands Interdisciplinary Demographic Institute
and the Statistical Office of the European Union for their
project Push and Pull Factors of International Migration.
The DRC has already invested much time in acquiring and exploring
this dataset so it is important that we continue to use it.
We intend to use the country datasets for Ghana and Egypt
to collaborate with our partners in those countries.
2. Our project will utilize quantitative methods to explore
the linkages between assets and migration. Specifically we
will use matching methods to impute values from current Ghanaian
and Egyptian migrants in Italy to non-migrants and returnees
in Ghana and Egypt. The nature of the NIDI data together with
this methodology will allow us to construct a dataset that
will enable us to compare the asset trajectories of non-migrants
and returnees, controlling for household characteristics,
poverty profiles, formal migration status and demographic
characteristics. Furthermore, this paper will compare different
econometric methodologies for analysing the same question
to determine how robust the results are. Specifically, we
will use a Heckman model allowing for migrant selectivity
and a matching model.
A working paper
||An academic publication