Shock in Brazil

lower the changes in lifetime utility of workers (figure 3.4, panel a) and the fewer the changes in external labor market opportunities (that is, job options outside the region) (panel b).

Based on this research on Brazil, Artuc, Bastos, and Lee (2021) suggest that a 20 percent increase in migration could boost the aggregate national welfare gain from a positive export shock to a particular region by 14 percent.

In the United States, a country traditionally celebrated for its domestic labor mobility, the slowdown in convergence between lagging and leading areas has been driven in part by a decline in migration over the past 40 years (see Ganong and Shoag 2017).6 Autor, Dorn, and Hanson (2013) find no robust evidence that shocks to local manufacturing induced by trade with China have led to substantial changes in population. There is a tendency for low-skill workers to migrate away from high-income areas partly because their return to migration in high-income states has eroded in recent years. Such “stuck” labor is increasingly becoming a major issue for public policy because it exacerbates spatial inequalities and fuels populist sentiment.

Even in China, migration intensity and productivity gains hinge on the entry of migrants into higher-skilled jobs. Even with zero migration costs, Gai et al. (2021) show that migration shares would increase by only 20 percent and aggregate productivity would increase by 2.6 percent; the modest productivity gains are partly due to the fact that most migrant workers in China work in low-skill manufacturing and service industries.

FIGURE 3.4 Frictions in Labor Mobility Are Associated with Lesser Changes in Lifetime Utility and Fewer Job Options in Other Job Markets Following an Export Shock in Brazil

Residual changes in lifetime utility

a. Lifetime utility b. External option values

8

6

4

2

0

–2

–4 Residual changes in external option values –2.0 –1.5 –1.0 –0.6 0.5 1.0 1.5 2.0 2.5 3.0 0 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 Remoteness of the labor market Remoteness of the labor market

Source: Artuc, Bastos, and Lee 2021. Note: Panel a plots the residual changes in lifetime utility of each labor market as a percentage of the annual wage against the remoteness measure of each labor market measured as the cost of moving from the labor market of one region to the other. Panel b plots the residual changes in external option values (job opportunities) of each labor market as a percentage of the annual wage against the remoteness measure of each labor market.

Information Barriers and Social Networks

In addition to skills mismatch, inadequate information can hold people back from moving. An experiment in Kenya found that a simple intervention providing information about average food prices and wages in Nairobi to a set of Kenyan village households raised expectations about average urban wages and increased migration to Nairobi from 20 percent to 28 percent of rural households. Two years later, migration rates were still higher among those getting the information treatment, and migrants reported higher subjective well-being on average. Information also travels through social networks. Bryan, Chowdhury, and Mobarek (2014) and Akram, Chowdhury, and Mobarek (2017) find that rural individuals with strong networks in cities face a relatively lower cost of finding work and housing after migrating, while those with greater ties to risk-sharing networks in villages have relatively higher costs of leaving those behind.

Mobility across certain administrative boundaries can be costly, especially if these boundaries reflect differences in societal characteristics—such as language, culture, laws, and institutions—or geographic barriers (Belot and Ederveen 2012). Border costs across regions further impede migration (Helliwell 1997; Poncet 2006). For example, migration between Canadian provinces is almost 100 times more likely than migration to Canadian provinces from the United States, Helliwell (1997) suggests.

Social networks and cultural norms also influence migration decisions. Munshi and Rosenzweig (2016) explore the relationship between the caste networks in rural areas in India and migration incentives. They argue that emigration of an income-earning individual reduces the family’s access to the caste network as a social safety net and subsequently reduces the incentives for internal migration considerably (box 3.2).

Network effects are also critical and vary by area and culture. In Tunisia, families frequently identify one member to move, and only those with strong networks will move (Zuccotti et al. 2018). In the Syrian Arab Republic, individuals who move are more likely to receive help from relatives (Khawaja 2002). The presence of other household members at a destination encourages migration to it, Mora and Taylor (2006) find for Mexico.

This network effect is also studied by Akay et al. (2014), using data from China. They distinguish between the presence at the destination of immediate family members (strong ties) and the presence of other residents from the same village (weak ties). A theoretical model predicts a larger migration effect from weak ties, and the Chinese evidence supports this prediction. Marre (2009) shows that family size and home ownership are important factors reducing the incentive to migrate because they are strongly and positively associated with the costs of moving.

The presence of previous migrants at the destination may also have an influence; they can help migrating individuals adapt and find jobs, hence inducing them to migrate (Brueckner and Lall 2015). For Mexico, Munshi (2003) finds that an individual