Get access Abstract This study examines how changes in state corporate tax rates affect corporate social responsibility (CSR) performance among U.S. firms. Using staggered state-level tax reforms and a difference-in-differences (DiD) design, we identify an asymmetric causal effect: tax cuts significantly enhance CSR performance by reducing concerns, whereas tax increases only marginally weaken CSR strengths. Drawing primarily on signaling theory, complemented by slack resource and stakeholder perspectives, we argue that tax cuts expand financial slack, enabling firms to use CSR as a positive signal of financial strength, long-term orientation, and responsible use of tax savings. In contrast, firms avoid cutting CSR significantly after tax hikes to prevent negative signaling. In support of the theories, our heterogeneity analyses show that these effects are stronger among financially constrained firms and are concentrated in material CSR issues that are financially relevant to investors. A domain-level analysis further reveals that tax increases reduce environmental strengths, while tax cuts lower concerns related to employee relations, diversity, and environmental practices. These findings highlight how tax policy shapes CSR through its impact on financial flexibility and stakeholder expectation, offering implications for corporate strategy and public policy.

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.

This paper provides new causal evidence on how patent allowances affect firms and their employees based on quasi-random assignment of patent applications to examiners. Exploiting employer-employee records with newly linked German firm data and web-scraped patent documents, we show that patent-induced shocks reduce firm exit, improve productivity, and increase wages, with rent-sharing elasticities between 0.10 and 0.21. Wage gains are broadly observed across occupational tasks, with high heterogeneity: managers benefit disproportionately in publicly traded firms, whereas broader wage increases accrue to workers in non-traded firms. Our findings highlight the role of institutional features and firm organization in shaping how rents are shared.

This study estimates the firm-level employment effects of investment grants in Germany. In addition to the average treatment effect on the treated, we examine discrimination in the funding rules as a potential source of effect heterogeneity. We combine a staggered difference-in-differences approach with a matching procedure at the cohort level. The findings reveal a positive effect of investment grants on employment development. The subsample analyses yield strong evidence for heterogeneous effects based on firm characteristics and the economic environment. They highlight the responsibility of the local funding authorities to clarify ex ante which goals of a funding programme are most important in their regions.

In this paper, we study champions of corporate social responsibility (CSR) performance among the U.S. publicly traded firms and their common characteristics by utilizing machine learning algorithms to identify predictors of firms’ CSR activity. We contribute to the CSR and leadership determinants literature by introducing the first comprehensive framework for analyzing the factors associated with corporate engagement with socially responsible behaviors by grouping all relevant predictors into four broad categories: corporate governance, managerial incentives, leadership, and firm characteristics. We find that strong corporate governance characteristics, as manifested in board member heterogeneity and managerial incentives, are the top predictors of CSR performance. Our results suggest policy implications for providing incentives and fostering characteristics conducive to firms “doing good.”