Incomplete contract theory, supported by anecdotal evidence, suggests that when a firm is acquired, workers may be adversely affected in non-contractible aspects of their work experience.This paper empirically investigates this prediction by combining M\&A events from the Refinitiv database and web-scraped Glassdoor review data.We find that: (a) Controlling for pre-trends, mergers lead to lower satisfaction, especially on non-contractible dimensions of the employee experience (about 6% of a standard deviation); (b) The effect is stronger in the target firm than in the acquiring firm; (c) Text analysis of employee comments indicates that the decline in satisfaction is primarily associated with perceived breaches of implicit contracts.Our findings indicate that mergers may reduce workers' job utility through non-monetary channels.

We analyze the effect of California's $20 fast food minimum wage (Assembly Bill 1228), enacted in September 2023 and implemented in April 2024, on consumer prices using the Bureau of Labor Statistics' Consumer Price Indices for food away from home across 21 metropolitan statistical areas.Food away from home prices in California's four in-sample MSAs increased by 3.3 to 3.6 percent relative to 17 control MSAs through December 2024.Our estimates are stable across a number of specifications.Placebo tests on price indices for goods and services that were not affected by the policy, including food at home, show no differential increases in California's MSAs.The price increases we estimate likely arise in part from spillovers to the full-service sector, as well as changes in the production functions and product quality choices of limited service restaurants.

We show that, to a first-order approximation, estimates of fluctuations in Shiller's fundamental price relative to observed price depend primarily on forecasts of long-horizon expected returns.Researchers using different measures of cash flow and valuation may reach different conclusions about the extent to which values fluctuate excessively relative to fundamentals, but that is only because return forecasts based on different cash-flow-to-value measures will be different.Using U.S. equity data, we demonstrate that the amount of persistence in expected returns, rather than the amount of short-run return predictability, is the key determinant of implied excess volatility.Disagreements about stock market valuation therefore reduce to disagreements about long-run expected returns.

The U.S. hospital sector expanded rapidly in the 1950s and 1960s, largely due to construction subsidies provided under federal legislation known as the Hill-Burton Act.This paper examines the impact of Hill-Burton grants on maternity care access and infant health.We find that grants for public hospitals significantly reduced out-of-hospital births and infant mortality, particularly among non-white populations.In contrast, grants for private non-profit hospitals had no measurable effects on out-of-hospital births or infant mortality.

This paper shows that the pace of technology creation is a key driver of the skill premium.It develops a model in which skilled workers have a comparative advantage in learning new technologies.As technologies age, they become standardized and accessible to other workers.The skill premium is determined by the interplay between the pace of technology creation and standardization.A rapid pace of technology creation leads to a sustained increase in the skill premium.We calibrate the model using novel text-based data on new technologies and their changing demand for skills as they age.These data show that new technologies are initially skill intensive but become less so as they age.The data also point to an increased pace of new technology creation starting in the 1970s and tapering off in the 2000s.In response to this rapid pace of technology creation, the model generates a 32 percent increase in the college premium, which begins to reverse in the 2010s.Our framework also explains why the college premium is higher in dense cities, why its increase was mainly urban, and why it rose first for young workers and later for older workers.

We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce.We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so.Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance.These gains are not primarily driven by firms' capital deepening but instead reflect increases in revenuebased total factor productivity, closely associated with innovation-and demand-oriented channels.We document a productivity paradox, in which perceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations.In labor markets, we find little evidence of near-term aggregate employment declines due to AI, though larger companies anticipate AI-driven workforce reductions, while smaller firms expect modest gains.We also find evidence of compositional reallocation of labor both within and across firms, with routine clerical roles declining and a relative demand for skilled technical roles increasing.We develop an index that ranks job functions most negatively affected by AI.

We establish three facts about work from home (WFH) in the United States.First, employees WFH more often at younger firms -almost twice as often at firms founded after 2015 than at firms founded before 1990.Second, employees working under younger CEOs have higher levels of WFH.The average WFH rate is 1.4 days per week when the CEO is under 30, compared to 1.1 days when the CEO is 60 or older.Third, the self-employed WFH more than twice as often as wage-and-salary employees.These facts highlight the importance of organizational and managerial attributes for the prevalence of WFH.

We study competition between monies that provide separate payment and non-payment (e.g., storeof-value) functions.Our central insight is that payment adoption is governed not by absolute payment superiority, but by comparative advantage between payment and non-payment roles.A money that is "too good" as a store of value may circulate less as a payment instrument, even if it is technologically superior, because agents prefer to hoard it rather than spend it.The model delivers equilibria in which monies either specialize into distinct roles or coexist as payment instruments with one emerging as dominant.These mechanisms provide a unified microfoundation for classic monetary phenomena such as Gresham's law and the big problem of small change, and offer a new perspective on modern debates over stablecoins and central bank digital currencies (CBDCs).Contrary to the common view that interest-bearing digital currencies necessarily threaten bank deposits, we show that higher yields can weaken payment adoption by raising the opportunity cost of spending.As a result, traditional bank deposits may coexist with, and even retain dominance over, technologically superior digital alternatives.