Alexander Busch

We document the expansive geographic scope of labor unions in the US and study the implications for the propagation of shocks. The average union local (branch) represented workers dispersed across three states in 2011. Consequently, shocks to a union’s workers in one state can have spillovers in other states through the response of the union. We show this in the context of state-level Right-to-Work (RTW) laws, which create a free-riding problem for unions by making dues payments optional. A model of a multistate union predicts spillovers whose sign depends on the relative magnitudes of two forces akin to substitution and scale effects. Negative spillovers become more likely as cross-state complementarities in membership production increase. We test for spillovers using the adoption of five RTW laws between 2012 and 2017. RTW laws have positive spillovers in non-adopting states; unions increase the number of bargaining units represented in these states, making up for about 35 percent of the workers lost in the adopting states. Notably, more than half of the spillover occurs in non-bordering states. New organizing explains 42 percent of the spillover; the rest appears to be driven by the increased likelihood of contract renegotiation for existing bargaining units. The spillovers are not driven by changes in the price or quality of union services.

We use a newly digitized panel of collective bargaining agreements linked to quarterly labor market data to study how sectoral agreements shaped aggregate wage inequality in Germany between 1950 and 2025.

We study the effect of explicitly and implicitly gendered pay scales in West German collective bargaining agreements on gender gaps in wages and employment.

LPDID performs the Local Projections Difference-in-Differences estimator (LP-DiD) proposed by Dube, Girardi, Jordà and Taylor (2023). LP-DiD is a convenient and flexible regression-based framework for implementing Difference-in-Differences with multiple time periods. It can provide both dynamic event-study estimates and pooled estimates of the overall average effect in a post-treatment window. Treatment can be absorbing or non-absorbing. The estimation sample is restricted to units entering treatment and “clean” controls, thus avoiding the negative-weights bias of two-way fixed-effects estimators. The command allows reweighting to estimate an equally-weighted average effect, flexible choice of the pre-treatment base period, and inclusion of control variables.