Does Mobility Beget Mobility? Coworker Networks and the Sectoral Reallocation of Labor (with Xinyue Lin)
Abstract
Social networks influence labor market outcomes. We investigate how the sectoral composition of an individual’s current coworkers’ past employment affects job-switching decisions. To identify causal effects, we employ multiple strategies, including distinguishing between current-year and non-current-year coworkers, controlling for time-varying shocks specific to the industry pairs, and using unexpected death or retirement events to isolate idiosyncratic changes in coworker networks. Using German administrative matched employer-employee longitudinal data, we find a positive causal relationship between the proportion of coworkers from a sector and both the propensity of transitioning to that sector and the sensitivity to sectoral wage changes. To quantify the coworker mechanism’s contribution to employment and reallocation, we develop and estimate a multi-sector, multi-firm general equilibrium model where perceived wages and adjustment costs for sector transitions depend on coworker shares. Our results show that the welfare effect of COVID-induced productivity shocks is higher when considering coworker networks compared to assuming no influence from coworkers. Maintaining worker-employer ties to reduce competition in positively shocked sectors can further increase welfare.
Coworker Influence on Job Choice: Information, Connection, and Industry Switching (with Xinyue Lin and Armando Miano)
Abstract
We investigate the role of coworkers in shaping job mobility decisions by altering perceived outside options. Leveraging novel survey data administered to a representative sample of wage and salaried workers in the US, we identify two key channels through which current and former coworkers influence workers’ decisions to switch jobs or industries. First, having more current coworkers with prior experience in an industry improves the accuracy of wage beliefs for that industry, as supported by an analysis of perceived wages and coworker composition. Second, having more past coworkers currently employed at a firm increases the perceived likelihood of receiving a job offer from that firm, as evidenced by a survey experiment eliciting job offer probabilities for hypothetical jobs. We investigate the welfare implications these results in a job choice model that incorporates these coworker effects, departing from traditional models that assume perfect information about wages and job-offer probabilities.
Lender Experiences and Mortgage Costs
Abstract
This paper examines how lenders’ past experiences with house price changes influence the mortgage rates they charge, focusing on the role of lender expectations. I hypothesize that lenders extrapolate from past house price changes to balance profit margins with default risk, offering lower rates when they anticipate future price increases. Consistent with this hypothesis, I show that lenders exposed to greater house price growth tend to charge lower mortgage rates. I rule out alternative explanations, such as differential local growth opportunities or the potential of banks to influence local prices, using placebo tests and geographic variation in lending patterns. Specifically, I find that moving from the 25th to the 75th percentile of price growth exposure is associated with a 4.5 percentage point reduction in loan rate spreads.