The Determinants and Welfare Implications of US Workers' Diverging Location Choices by Skill: 1980–2000

Abstract

From 1980 to 2000, the rise in the US college/high school graduate wage gap coincided with increased geographic sorting as college graduates concentrated in high wage, high rent cities. This paper estimates a structural spatial equilibrium model to determine causes and welfare consequences of this increased skill sorting. While local labor demand changes fundamentally caused the increased skill sorting, it was further fueled by endogenous increases in amenities within higher skill cities. Changes in cities' wages, rents, and endogenous amenities increased inequality between high school and college graduates by more than suggested by the increase in the college wage gap alone. (JEL D31, I26, J24, J31, J61, R23)

Money vs. Time: Family Income, Maternal Labor Supply, and Child Development

“…We then could use this variation to predict changes in family income and mother's labor supply. Following the approach first developed by Bartik (1991) and used in many previous empirical works (see for example Blanchard and Katz, 1992;Autor and Duggan, 2003;Luttmer, 2005;Aizer, 2010;Notowidigdo, 2011;Bertrand et al, 2015;Diamond, 2016;Charles et al, 2015Charles et al, , 2017, we construct an empirical analogue of the above-mentioned thought experiment by considering the cross-state differences in industrial composition and aggregate growth in the employment level.…”

Agglomeration and Innovation

“…From the perspective of this chapter, the most needed area of further inquiry is a sharper connection of wage levels 18 Recently, researchers have demonstrated how ignoring rent differentials across cities (a measure of cost of living differentials) can bias estimates of real income inequality. Several studies document that an increased share of college grads sorted into high-wage U.S. cities between 1980 and 2000 (Moretti, 2013;Lindley and Machin, 2014;Diamond, 2012). As college workers are increasingly located in expensive cities, Moretti (2013) calculates that at least 22 percent of the increase in spatial college wage premium between 1980 and 2000 can be explained by geographic differences in the cost of living.…”

Location as an Asset

“…Furthermore, as implied by the model in Section 2, residents of cities with higher z will have higher average incomes. Hence, we can determine the z rank of cities using the rank of their average income 21 (see Figure 1). Finally, the model tells us that the highest income individuals in any city are the ones that are not constrained.…”