We examine whether free-speech protections influence corporate environmental performance. Using the staggered enactment of U.S. anti-SLAPP statutes in a stacked difference-in-differences design from 1990 to 2019, we find that these laws significantly reduce firms’ toxic emissions without curbing economic activity. Anti-SLAPP enactments also promote environmental investment through green innovation, abatement spending, and waste reduction management, and strengthen governance via improved sustainability oversight, ESG-linked executive pay, employee training, and supply chain management. The effects are stronger when stakeholder monitoring is stronger and when managerial incentives embed sustainability goals. Overall, free-speech protections generate powerful environmental benefits.

This paper analyzes the economic impact of plant-parasitic nematodes in the U.S. potato industry, focusing on how both unanticipated and anticipated yield losses affect producer decisions, market outcomes, and welfare. We use a modified Cournot model and estimate a system of supply and demand equations using Three-Stage Least Squares (3SLS). We simulate scenarios to measure how varying levels of nematode infestation influence producer profits and consumer surplus in the short-run and the long-run. Simulations suggest that reducing nematode damage could yield substantial gains in output and consumer welfare particularly in concentrated markets where strategic producer behavior amplifies these effects. Our findings underscore the need to account for both biological uncertainty and market structure when evaluating pest impacts and designing policy responses.

In high-dimensional (HD) sparse linear regression, parameter selection and estimation are addressed using a constraint $l_0$ on the direction of the parameter vector. We begin by establishing a general result that identifies this direction through the leading generalized eigenspace of specific measurable matrices. Using this result, we propose a novel approach to the selection of the best subsets by solving an empirical generalized eigenvalue problem to estimate the direction of the HD parameter. We then introduce a new estimator based on the RIFLE algorithm, providing a non-asymptotic bound for the estimation risk, minimax convergence, and a central limit theorem. Simulations demonstrate the superiority of our method over existing $l_0$-constrained estimators.

A large body of literature examines the drivers of individual attitudes towards international trade policies. This article contributes to this literature by exploring the role of border regions across the European Union (EU). Border regions offer a unique context for examining trade attitudes. Residency in either EU, non-EU, or maritime borders generates differential impacts on individuals’ support for distinct trade policies. Focusing on attitudes towards import duties and EU trade agreements, this article demonstrates that individuals in non-EU borderlands and maritime border regions are particularly supportive of lowering import duties, whereas support for extra-EU trade agreements is largely uniform across regions, with only a modest positive tendency among maritime residents. Broader sentiment on trade shows limited regional differences, chiefly between EU-border and non-EU-border residents. Including a battery of control variables drawn from the literature, the article leverages individual-level data at the most fine-grained level available in the EU to explore these dynamics relying on several regression models. This article speaks to both the literature on trade attitudes and border studies by offering a conceptualization of borders that distinguishes between EU borders, non-EU borders, and maritime borders, each of which has distinct implications for individuals’ trade attitudes.

The incorporation of algorithmic systems into organizations is reconfiguring decision-making processes and raising new ethical challenges related to transparency, impartiality, and accountability. This study maps the field of algorithmic ethics in organizational contexts through a co-citation–based bibliometric analysis of 1,437 Web of Science publications (search conducted on August 20, 2025). The analysis identifies 12 thematic clusters and reveals a robust intellectual structure, with high modularity (Q = 0.726) and a high weighted mean silhouette value (S = 0.894). The findings highlight the centrality of algorithmic management, responsible artificial intelligence, and explainability, as well as bridging works that connect technical, normative, and management-oriented perspectives. The study advances an integrative conceptual model and a future research agenda that point to the emergence of algorithmic ethics as an institutional logic of organizational governance. For managers, the results underscore the need to embed algorithmic ethics within organizational decision-making and control systems.

Researchers have struggled to identify heirs’ property (HP) via the use of real estate records for years. This paper evaluates seven distinct methodological approaches to identify HP using CoreLogic’s national property database. We find minimal convergence among these algorithms, with different methods flagging largely non-overlapping sets of properties. Certain approaches show promise – particularly in identifying properties with characteristics consistent with documented HP patterns. The lack of agreement across methods, however, makes estimating the prevalence of HP difficult. Several paths exist forward to identify HP such as adding extra property characteristics into existing algorithms, developing more sophisticated algorithms, and establishing protocols for cross-jurisdictional validation.

Applying the New Entrepreneurial History framework, this paper examines how ArcBest Corporation, an integrated logistics firm based in Fort Smith, Arkansas, became the last legacy less-than-load (LTL) carrier operating in the United States. It argues that the firm’s enduring viability is partially the product of an internal distributed agency among executives over a century that involved continual entrepreneurial processes: Envisioning and valuing opportunities informed by the multiplicative form of values, strategically reallocating and reconfiguring resources, and legitimizing novelty to stakeholders in response to profound market and regulatory shifts. These entrepreneurial processes, paired with the company’s commitments to a unionized labor force, informed executives’ strategic decisions that transformed the carrier from a regional hauler into a national, technologically sophisticated, integrated logistics provider. In applying the new entrepreneurial history to ArcBest, it considers how entrepreneurial opportunities are enacted within the context of a single firm over time.

This article is based on comments that I submitted to the Office of Management and Budget (OMB) as one of eight peer reviewers of OMB’s 2023 draft revisions to Circular A-4, “Regulatory Analysis.” Since that time, OMB issued a final version of Circular A-4, which was then rescinded in January 2025. This article summarizes some of my main comments on the 2023 draft version that I submitted as a peer reviewer, along with a “prologue” that summarizes some of the main issues raised in my peer review and an “epilogue” recognizing both the initial revision of Circular A-4 that was initially adopted, as well as the 2025 decision to rescind the revised version and return to the 2003 version of the circular. The 2003 Circular continues to provide useful guidance, but could have been improved by expanding the scope of regulatory impact analysis in ways discussed in my peer review comments.

Traditional leadership theories often portray influence as stable traits or behaviors, yet complex organizations require leadership to be understood as an emergent, feedback-driven process that co-evolves with contextual demands and follower motivation. This study conceptualizes servant leadership as a nonlinear, adaptive process rather than a fixed style, integrating Complexity Leadership Theory with the Job Demands Resources model and Regulatory Focus Theory. Servant leadership is theorized as an enabling mechanism through which shifting job demands and resources are translated into employees’ promotion and prevention orientations, shaping person-job fit, satisfaction, intrinsic motivation, initiative, and experienced responsibility. Using a two-phase longitudinal design, Phase 1 tested simple and serial mediation with structural equation modeling, and Phase 2 employed a cross-lagged panel model to examine reciprocal feedback dynamics. Results support a four-path process in which servant leadership differentially activates promotion and prevention focus and participates in ongoing feedback loops.