This paper provides theory and evidence on micro-level pricing behavior needed to model an aggregate New Keynesian Phillips Curve. We start with individual firms that are heterogeneous in their production technology and in the demand curves they face. We estimate the parameters of supply and demand curves by utilizing prices and quantities of outputs and factor inputs of firms along with exogenous downstream demand instruments from global input-output and trade data. The research addresses model heterogeneity using a clustering method to classify firms according to their production technology and observed price pass-through. The results show that more productive firms exhibit a lower price response to changes in demand. We find that the aggregate price response to demand shocks will be smaller when more productive firms absorb a larger portion of demand shocks, which generally is the case. At the same time, our results imply that idiosyncratic shifts in demand to clusters of firms with more rapidly rising marginal cost curves, or cost shocks to clusters of firms with high pass-through, will result in a higher aggregate price response. Finally, this paper provides a framework to incorporate heterogeneous pricing behavior into an estimate of the slope of the aggregate Phillips Curve.

We study the procurement patterns of non-listed firms and examine how these often-overlooked, yet pivotal players in global supply chains adjust their sourcing when they anticipate accountability for externalities beyond their organizational boundaries. Using granular customs data and a surprise information release about the German Supply Chain Due Diligence Act, product-level regressions reveal that importing firms are 3.5 percentage points less likely to source a product from countries where the relevant production sector exhibits elevated ESG-related risks, suggesting that firms tend to cut ties with higher-risk suppliers. The effects are concentrated among firms with well-diversified supplier networks for a product and higher profitability, suggesting they have the necessary flexibility to respond quickly to anticipated regulatory pressure. Our findings suggest that mandates requiring firms to incorporate broad sustainability considerations into their operational decisions may have limits, particularly for non-listed firms.

In this study, establishment-level employment effects of investment grants in Germany are estimated. In addition to the quantitative effects, I provide empirical evidence of funding effects on different aspects of employment quality (earnings, qualifications, and job security) for the period 2004 to 2020. The database combines project-level treatment data, establishment-level information on firm characteristics and employee structure, and regional information at the district level. For the estimations, I combine the difference-in-differences approach of Callaway and Sant’Anna (J Econom 2252: 200–230, 2021) with ties matching at the cohort level. The estimations yield positive effects on the number of employees, but point to contradicting effects of investment grants on different aspects of employment quality.

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.

This paper studies how minimum wage policy affects firms’ adoption of automation technologies. Using both state-level measures of robot exposure and novel plant-level data on industrial robot imports linked to U.S. Census microdata from 1992–2021, we show that increases in minimum wages raise the likelihood of robot adoption in manufacturing. Our preferred identification exploits discontinuities at state borders, comparing otherwise similar firms exposed to different wage floors. Across specifications, a 10 percent increase in the minimum wage increases robot adoption by roughly 8 percent relative to the mean.

The effects of private equity buyouts on employment, productivity, and job reallocation vary tremendously with macroeconomic and credit conditions, across private equity groups, and by type of buyout. We reach this conclusion by examining the most extensive database of U.S. buyouts ever compiled, encompassing thousands of buyout targets from 1980 to 2013 and millions of control firms. Employment shrinks 12% over two years after buyouts of publicly listed firms—on average, and relative to control firms—but expands 15% after buyouts of privately held firms. Postbuyout productivity gains at target firms are large on average and much larger yet for deals executed amid tight credit conditions. A postbuyout tightening of credit conditions or slowing of gross domestic product growth curtails employment growth and intrafirm job reallocation at target firms. We also show that buyout effects differ across the private equity groups that sponsor buyouts, and these differences persist over time at the group level. Rapid upscaling in deal flow at the group level brings lower employment growth at target firms. We relate these findings to theories of private equity that highlight agency problems at portfolio firms and within the private equity industry itself.

Using brand-level sales data from Chinese e-commerce platforms, this study examines how geopolitical tensions affect multinational brands operating in China. Merging these sales data with a U.S.–China tension index, we use panel regressions and local projections to show that rising tensions significantly reduce the market share of U.S. brands in China relative to brands from other countries, with the effects persisting for up to 12 months. An event study employing a difference-in-differences framework, centered on brand-specific incidents of political tension with China, reveals similar market share declines among affected brands, highlighting consumer sentiment as a key transmission channel.