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<!doctype html>
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<title>Theories of International Mobility and the Incorporation of Immigrants</title>
<meta name="description" content="Slides for Economics of Migration class">
<meta name="author" content="John R.B. Palmer">
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<section>
<h2>Theories of International Mobility and the Incorporation of Immigrants</h2>
<h3>Class 4: Synthesizing and Testing Determinants of Migration</h3>
<p><a href="http://johnrbpalmer.com">John Palmer</a>
</section>
<section>
<section>
<h3><a href="https://aulaglobal.upf.edu/pluginfile.php/1375341/mod_resource/content/1/Massey_et_al_1998_ch2.pdf">Massey et al. (1998)</a></h3>
</section>
</section>
<section>
<section>
<h3><a href="https://www.jstor.org/stable/3006176?seq=1#metadata_info_tab_contents">Kanaiaupuni (2000)</a></h3>
</section>
<section>
<ul>Starting point: Gender (the product of social relationships in which men
and women are embedded) influences individual decisions and action.</ul>
</section>
<section>
<ul>"[M]igration is a profoundly gendered process and ... conventional explanations of men's migration in many cases do not apply to women. Migration decisions are
made within a context of socially recognized and mutually reinforcing expectations
that reflect several dimensions of gender relations - between individuals, within
families, and in societal institutions."</ul>
</section>
<section>
<ul>"[G]ender must be treated as a theoretical basis of differentiation and not
simply a control variable in migration analyses."</ul>
</section>
<section>
<ul>"Gender relations, influenced by macro-level and community structures, are
mediated within the family in response to household needs and function."</ul>
</section>
<section>
<ul>
<li>methods: 3 years qualitative field work</li>
<li>quantitative data from MMP - longitudinal data over 10 years from households randomly sampled in 43 Mexican villages</li>
<li>village level data from archives and census</li>
<li>outcome: first trip to US</li>
</ul>
</section>
<section>
<img src="images/Kanai_F1.png" class="stretch">
</section>
<section>
<img src="images/Kanai_F2.png" class="stretch">
</section>
<section>
<img src="images/Kanai_T1.png" class="stretch">
</section>
<section>
<ul>
<li>74% of migrants' wives never migrated</li>
<li>9% of those women who did migrate had migrant partners and migrated before their partners (usually before marrying)</li>
<li>10% of those women who did migrate had nonmigrant partners</li>
</ul>
</section>
<section>
<img src="images/Kanai_T3.png" class="stretch">
</section>
<section>
<p>Key network measures</p>
<ul><li>Village migrant networks: Proportion of migrants to village population</li>
<li>Sex composition of networks: Ratio of female migrant proportion to male migrant proportion</li>
</ul>
</section>
<section>
<img src="images/Kanai_F3.png" class="stretch">
</section>
</section>
<section>
<h3><a href="https://www.demographic-research.org/volumes/vol35/13/35-13.pdf">Baizán & González-Ferrer (2016)</a></h3>
</section>
<section>
<h3><a href="https://link.springer.com/content/pdf/10.1007/s10680-015-9341-5.pdf">Palmer & Pytlikova (2015)</a></h3>
</section>
<section>
<section>
<h3>Migrant Selection</h3>
<p>Ongoing research with Alicia Adsera and Mariola Pytlikova</p>
</section>
<section>
<h4>Data</h4>
<ul>
<li><b>Migrant Flows</b>: “Brain-Drain” data from German Federal Employment Agency. Gender and education-level-specific migration flows and rates for migrants aged 25 and over in 20 OECD destination states during 5-year intervals from 1980 to 2010.</li>
<li><b>Immigrants' Rights</b>: Index of economic and social rights in each destination accorded to immigrants from each country of origin in each year.</li>
</ul>
</section>
<section>
<h4>Data</h4>
<ul>
<li><b>Welfare Spending</b>: Total public welfare expenditure as a percentage of GDP from OECD Social Expenditure Database (SOCX).</li>
<li><b>Co-National Immigrant Stock</b>: Dataset compiled by Mariola Pytlikova, covering migration to 42 OECD destination countries from every country in the world during 1980–2010.</li>
<li><b>Origin and Destination Characteristics</b>: Annual per capita GDP, adjusted for purchasing power parity and measured in international dollars, tertiary education enrollment ratio, geographic distance between origin and destination states, indicators of whether these states are contiguous and whether they have ever had a colonial link, linguistic distance index.</li>
</ul>
</section>
<section data-background="images/total_flows.png" data-background-size="contain">
</section>
<section data-background="images/total_rates.png" data-background-size="contain">
</section>
<section data-background="images/ed_dest.png" data-background-size="contain">
</section>
<section data-background="images/selection_mult_effects.png"data-background-size="contain">
</section>
<section>
<h4>Preliminary Conclusions</h4>
<ul>
Positive relationship between private sector employment rights and migration rates only for people with high education levels. Consistent with highly educated migrants choosing destinations based on access to the formal labor market.
</ul>
</section>
<section>
<h4>Preliminary Conclusions</h4>
<ul>
Positive relationship between non-contributory welfare rights and migration rates, with effects greatest for those with medium education. This might reflect some combination of differential information availability and expected valuation of the benefits.
</ul>
</section>
<section>
<h4>Preliminary Conclusions</h4>
<ul>
For destination state welfare spending, the estimated coefficients are negative for highly educated migrants and for women with medium education; they are indistinguishable from zero for low education females and males with medium education; and they are slightly positive for men with low education. This casts doubt on the welfare magnet hypothesis. Pattern for welfare rights may have less to do with actual expectations of welfare receipt than with preferences for destinations with equality of access. If spending on welfare attracts migrants, it does not appear to attract many and it is likely that effects are overshadowed by other criteria.
</ul>
</section>
<section>
<h4>Preliminary Conclusions</h4>
<ul>
Positive relationship between co-national stock and migration rates, with effect larger for those with low and medium education than for those with high education. This could reflect a greater ability for high education migrants to obtain information and support outside of their co-national networks.
</ul>
</section>
</section>
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