This paper quantifies how much people would be willing to pay to remove frictions that prevent them from working their ideal number of hours using two sufficient statistics: (1) the percentage difference between ideal and actual hours and (2) the Hicksian elasticity of ideal hours with respect to the after-tax wage rate. We estimate willingness-to-pay to remove these frictions in the U.S. and Germany. Three core findings emerge: (1) adjustment frictions—including fixed costs, discrete choice sets, and search costs—are costly for any reasonable value of the Hicksian elasticity, even when accounting for endogenous wages, multiple labor supply decisions, and dynamics; (2) the cumulative cost of adjustment frictions and tax misperceptions is even larger, with individuals willing to pay at least 10% of their income on average to remove both; and (3) adjustment frictions are much costlier than tax misperceptions.

How do employers respond to automation shocks? We investigate this question using a randomized information intervention that exogenously shifts employers’ beliefs about automation rates of their workforce. Focusing on the tax consulting and auditing sectors—where well-defined job titles and high exposure to generative language models create credible automation potential—we assign firms to one of three treatment groups or a control group. Treated firms revise revenue and profit expectations upward but do not alter hiring or firing decisions, suggesting automation enhances efficiency without immediate labor displacement. Notably, wages remain unchanged, indicating firms intend to retain productivity gains rather than share them with employees.

This paper examines the heterogeneous effects of the Tax Cuts and Jobs Act (TCJA) of 2018 on firms with varying capital intensities and the subsequent labor market implications. Using firm-level Compustat data, we document that capital-intensive firms benefit disproportionately from corporate tax reductions, leading to higher sales growth. We develop a theoretical model to rationalize this pattern and to analyze wage adjustments in response to increased firm profitability. Relying on a fair-wage mechanism, our model predicts that wage increases are more pronounced in capital-intensive sectors. Using county-level employment and wage data, we implement an event-study approach to quantify labor market effects, finding that wages rise more in capital-intensive regions, reinforcing pre-existing wage disparities. Our findings have important implications for regional inequality in the U.S., as the counties that benefited most from the tax cuts already had higher wages prior to the reform.

We provide evidence on the impacts of job loss among female factory workers in Ethiopia and on how these impacts can be mitigated. We leverage quasi-experimental variation in job loss, experimental variation in job-loss support payments, and high-frequency data spanning a period of 13 months after displacement. We find that job loss is a persistent shock that reduces employment and consumption spending for longer than one year, and almost doubles the rate of poverty. An additional lump-sum payment encourages early spending and reduces both overall and manufacturing employment. In contrast, providing an equivalent amount in monthly tranches -- a payment modality preferred by a majority of workers -- enables workers to better smooth consumption expenditures without negative employment effects. We show that workers have high willingness to pay for additional job-loss insurance, but also heterogeneous preferences over the payment modality. This generates a key trade-off between workers' private welfare and the government industrialization objectives.