2019
DOI: 10.1111/sjoe.12355
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How Borrowing Constraints Hinder Migration: Theoretical Insights from a Random Utility Maximization Model*

Abstract: We provide a theoretical framework to analyze how financial constraints hinder migration. Introducing wealth heterogeneity and borrowing constraints into a random utility maximization model of migration, we find evidence of multilateral resistance to migration stemming from borrowing constraints. We calibrate the model on 22 European countries, and we show that omitting the constraints biases upward the estimation of bilateral migration rates. We then simulate an increase in the bilateral cost of migration to … Show more

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Cited by 7 publications
(8 citation statements)
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“…This has been shown, for instance, by Clemens (2014), Angelucci (2015), Djajic et al (2016), Bazzi (2017) or Dao et al (2018). Liquidity constraints imply that the set of affordable destinations is smaller than the choice set (Marchal and Naiditch, 2019), and hence this pattern in the data poses a threat to our interpretation of the results in Table 3. Migrants from lower-income countries might not value information less, but (because of liquidity constraints) they might be less able to react to variations in economic conditions at destination and their past distribution could be more concentrated in the main (affordable) destination.…”
Section: Liquidity Constraintsmentioning
confidence: 85%
“…This has been shown, for instance, by Clemens (2014), Angelucci (2015), Djajic et al (2016), Bazzi (2017) or Dao et al (2018). Liquidity constraints imply that the set of affordable destinations is smaller than the choice set (Marchal and Naiditch, 2019), and hence this pattern in the data poses a threat to our interpretation of the results in Table 3. Migrants from lower-income countries might not value information less, but (because of liquidity constraints) they might be less able to react to variations in economic conditions at destination and their past distribution could be more concentrated in the main (affordable) destination.…”
Section: Liquidity Constraintsmentioning
confidence: 85%
“…44 Migration decisions can be subject to binding liquidity constraints, as shown notably by Clemens (2014), Angelucci (2015), Djajic et al (2016), Bazzi (2017) or Dao et al (2018). Liquidity constraints imply that the set of affordable destinations is smaller than the choice set (Marchal and Naiditch, 2020), and hence this pattern in the data poses a threat to our interpretation of the results in Table 2. Migrants from lower-income countries might not value information less, but they might be less able to react to variations in economic conditions, and their past distribution could be more concentrated in the main (affordable) destination.…”
Section: Liquidity Constraintsmentioning
confidence: 99%
“…Some analyses indicate an increasing number of immigrants in Organisation for Economic Co‐operation and Development (OECD) countries as a consequence of increasing total and/or bilateral aid (Berthélemy et al., 2009; Menard & Gary, 2017; Restelli, 2021), whereas others (Lanati & Thiele, 2018, 2020) find that increasing total transferred aid is associated with a reduction of regular migrants to donor countries, even from poor countries. It is also concluded that bilateral aid increases migration to the donor country due to increased information, whereas multilateral aid to less poor countries reduces migration through its development effects (Marchal et al., 2022).…”
Section: Migration Development and Foreign Aidmentioning
confidence: 99%