We propose life history (LH) theory as an overarching theoretical explanation of CEO preferences and decision-making. LH theory has the potential to integrate prior research on variation in top executives’ impact on decision outcomes and to demonstrate how observable differences in behavior can be explained by evolutionary drivers. According to LH theory, individuals pursue fast or slow LH strategies. Fast individuals tend to follow accelerated reproduction strategies and engage in impulsive, opportunistic, and risk-seeking behavior. We theorize how CEO LH strategies shape both on-the-job and off-the-job decisions and thus add to a growing body of research on evolutionary drivers of preferences and decision-making in accounting. We measure CEO LH strategies based on biodemographic micro-data related to reproductive behavior. Our findings linked to on-the-job decisions suggest that firms managed by CEOs who pursue fast LH strategies exhibit more financial irregularities, lower accounting conservatism, and higher earnings management. Findings related to CEO off-the-job decisions show that fast CEOs are more likely to engage in criminal behavior and to have a higher conspicuous consumption and a higher personal leverage. By applying an LH theory lens, we reconcile and advance prior fragmented research on CEO preferences by showing a clear theoretical link between on-the-job and off-the-job decisions.

Abstract Cryptocurrency has been the subject of heightened regulatory and investor attention in recent years, and regulators and policymakers across the globe are deliberating on how to account for, regulate, tax, and oversee digital assets and cryptocurrency marketplaces. Yet researchers have a limited understanding of key attributes of those who deal in crypto assets, such as whether their financial sophistication differs from that of other investors. Using U.S. administrative data, we provide evidence on (i) the attributes of taxpayers reporting cryptocurrency sales to the IRS, (ii) how these attributes are evolving, and (iii) how investors treat cryptocurrency versus other financial assets in certain settings. The results suggest that average reporting cryptocurrency sellers exhibit demographic attributes generally associated with less financial sophistication and are more likely to trade in meme stocks. Overall, we provide timely evidence that can inform cryptocurrency policy deliberations by highlighting the characteristics of taxpayers who appear to report cryptocurrency sales.

ABSTRACT This paper provides early evidence on the integration and impact of generative artificial intelligence (GenAI) in accounting at the accountant and task levels. Using survey data from 277 professional accountants, we document substantial heterogeneity in adoption patterns, perceived benefits, and concerns about GenAI. Using proprietary field data from an AI‐enabled accounting platform serving 79 small‐ and medium‐sized enterprises, we analyze over 200,000 transaction‐level records. We document that GenAI adoption is associated with significant productivity gains and systematic reallocation of effort away from routine data entry toward business communication and quality assurance tasks. GenAI use is also associated with improvements to financial reporting quality, evidenced by more granular ledgers and faster month‐end closing. Examining human–AI interaction, we find that accountants selectively intervene when AI confidence scores are low, consistent with complementarity between professional expertise and AI. A framed field experiment further shows that while AI assistance improves classification accuracy on average, reliance on non‐consensus AI recommendations can increase the risk of error. Overall, our findings highlight both the promise and the risks of GenAI in accounting and suggest that, in practice, AI is most effective as a tool that augments—rather than replaces—professional judgment.

Abstract This study examines turnover experiences in public accounting, including the exit phase (from public accountants' initial thoughts of leaving to their exit) and the post‐exit phase (from their exit to the present moment) of the turnover process. Drawing on social exchange theory and organizational support theory, we also investigate the relationship between these phases by exploring how turnover characteristics within the exit phase impact alumni's decisions to engage in post‐employment citizenship in the post‐exit phase (e.g., recommending the firm's services to others). Using the experiential questionnaire method, we rely upon two separate surveys to investigate the turnover process from the perspective of 284 firm alumni (“leavers”) and 83 experienced public accountants (“stayers”). Our process‐based research method allows us to gather a large and rich data set that provides multiple perspectives on the turnover experience in public accounting. Our results not only provide insights into the underlying factors influencing turnover but also indicate several places in the turnover decision process where firms can strategically intervene. Finally, our results show that several turnover characteristics within the exit phase impact post‐employment citizenship behaviors in the post‐exit phase. Consequently, our results demonstrate that the characteristics that drive employees' decisions to leave the firm also play a significant role in shaping their post‐employment citizenship behaviors following their departure.

Entrepreneurship is thought to be a key driver of economic growth. While there are myriad forms of entrepreneurship, ranging from self-employment to small and medium size enterprises to technology- and innovation-driven startups, recent research provides evidence that the relationship between entrepreneurship and economic growth is driven not by overall quantity of new firm entry, but rather by a small subset of high-growth startups that are primarily categorized as innovation-driven. This paper provides a survey of the growing literature on the economics of such innovation-driven entrepreneurship. We begin by distinguishing between the various forms of entrepreneurship, which are often confounded in both theory and empirical work. We lay out the current state of knowledge, and describe the challenges faced by researchers in the field, particularly around measurement, data and identification. We conclude with an overview of the major open questions and directions for future research in the area.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Abstract A common concern surrounding minimum wage policies is their impact on independent businesses, which are often feared to be less able to bear or pass on cost increases. We examine how these typically small and medium-size firms accommodate minimum wage increases along product and labor market margins using a matched owner-firm-worker panel data set drawn from the universe of U.S. tax records over a 10-year period, and using state minimum wage changes as identifying variation. We find that on average, firms in highly exposed industries do not substantially reduce employment—they do not lay off workers but moderately reduce part-time hiring. Instead, these firms are able to fully finance the new labor costs with new revenues, leaving average owner profits unchanged. Higher wage floors, however, forestall entry, particularly for less productive firms, reducing the number of independent firms operating in these industries by roughly 2%. Yet these industries do not shrink; instead, incumbent responses and strong positive selection among entrants reshape industries that rely heavily on low-wage workers, yielding fewer but more productive firms after the cost shock. We also take a worker-level perspective to examine how potentially vulnerable individuals are affected by minimum wage increases. Using panels of low-earning and young workers, we find that their average earnings rise substantially with the minimum wage, while they are no less likely to be employed. Worker transitions indicate that minimum wage increases boost retention and that worker reallocation from independent firms toward corporations buffers disemployment impacts from reduced hiring at independent firms.

Abstract Gun violence is a major problem in the United States, and extensive prior work has shown that higher temperatures increase violent behavior. We consider whether restricting the concealed carry of firearms mitigates or exacerbates the effect of temperature on violence. We use two identification strategies that exploit daily variation in temperature and variation in gun control policies between and within states. We provide evidence that more-prohibitive concealed-carry laws attenuate the temperature-homicide relationship. Our findings are consistent with more-prohibitive policy regimes reducing the lethality of altercations.

ABSTRACT The digital evolution in auditing has triggered a rapid shift in auditors' required skill sets, with audit firms heavily investing in and extolling advanced data analytics and artificial intelligence (AI) capabilities. However, this strong emphasis on newly required digital skills can lead many experienced auditors, who perceive these competencies as their weaker areas, to feel disaffirmed in their abilities. We predict and find, across two experiments, that auditors who feel disaffirmed in their digital skills more defensively discount specialist advice that places higher versus lower reliance on AI, but that an intervention in which auditors affirm their traditional audit skills mitigates this defensive reaction. Absent self‐affirmation, higher specialist reliance on AI results in auditors denigrating the competence and quality of advice that specialists provide. These findings suggest that disaffirmation escalates AI aversion, offering important insights into how audit firms can foster less defensive decision‐making in the rapidly evolving audit environment.

Abstract Using sales and leasing data, this paper finds three novel effects of a higher property transaction tax: higher buy-to-rent transactions alongside lower buy-to-own transactions despite both being taxed, a lower sales-to-leases ratio, and a lower price-to-rent ratio. This paper explains these facts by developing a search model with entry of investors and households, households choosing to own or rent in the presence of credit frictions, and homeowners deciding when to move house. A higher transaction tax reduces homeowners’ mobility and increases demand for rental properties, which explains the empirical facts and leads to a lower homeownership rate. The deadweight loss is large at 111% of tax revenue, with more than half of this due to distorting decisions to own or rent.