Title

The Impacts of Immigration on the Wage Distribution Using Both Reduced-Form and Structural Approaches

Award Year

2018

Grant Type

Early Career Research Award

Description

Over the last several decades the US wage distribution has experienced significant and uneven changes, resulting in an increase in overall wage inequality. Over the same time period the stock of immigrants to the US has been rapidly increasing and affecting labor markets across the entire country. The classic labor demand model predicts that, if immigrants' skills differ from those of natives, a labor supply influx of foreign-born workers will result in changes of relative wages among natives, increasing inequality. Motivated by theoretical considerations, a large body of literature estimates the impacts of immigration on “high-" versus “low-skill" native workers. While this type of analysis is warranted, economic theory itself does not yield clear-cut classification of “low-skill” workers. There is a heated debate about leading scholars in the field on the correct definition of “low-skill” labor the estimated effects heavily depend on whether high school dropouts and graduates are considered belonging in the same skill group (Card 2009, Ottaviano and Peri 2012 and Borjas, Grogger and Hanson 2012). Even if researchers agreed on which workers constitute “low-“ and “high-skill” groups, much less is known about how these differential impacts map onto changes in the wage distribution and to what extend has immigration contributed to the observed dynamics of the US wage distribution. I propose studying the impacts of immigration on the wage distribution using both a reduced-form and structural approaches. In the reduced-form section I will extend published estimates on mean wages impacts across local labor markets via both conditional and unconditional quantile regression. To account for the endogenous location of foreign-born workers, I will accommodate the commonly-used shift-share instrument based on historical networks in a control function framework. The estimates will give an insight on the way immigration exposure at the labor market level impacts workers differentially depending on their wage rank. In order to interpret the estimated coefficients in a stylized economic framework, in the second part of the paper I will build a structural model following Card (2001) where skill groups are defined by workers position in the wage distribution. This is contrary to most existing approaches where workers’ education and experience levels determine the skill groups. Being agnostic about how these observable characteristics map into skill groups avoids the possible misclassification of migrant workers due to skill downgrading (Dustmann et al. 2013). In this framework foreign-born workers raise relative skill group shares across local labor markets.

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