Research Database

While health affects many economic outcomes, its dynamics are still poorly understood. We use k-means clustering, a machine learning technique, and data from the Health and Retirement Study to identify health types during middle and old age. We identify five health types: the vigorous resilient, the fair-health resilient, the fair-health vulnerable, the frail resilient, and the frail vulnerable. They are characterized by different starting health and health and mortality trajectories. Our five health types account for 84% of the variation in health trajectories and are not explained by observable characteristics, such as age, marital status, education, gender, race, health-related behaviors, and health insurance status, but rather, by one’s past health dynamics. We also show that health types are important drivers of health and mortality heterogeneity and dynamics. Our results underscore the importance of better understanding health type formation and of modeling it appropriately to properly evaluate the effects of health on people’s decisions and the implications of policy reforms.

The Frisch labor supply elasticity plays a key role in many economic policy debates, but its magnitude remains controversial. Many studies estimate the Frisch elasticity using 2SLS regressions of hours changes on wage changes. But a little appreciated power asymmetry property of 2SLS causes estimates to appear spuriously imprecise when they are shifted away from the OLS bias. This makes it difficult for a 2SLS t-test to detect a true positive Frisch elasticity. We illustrate this problem in an application to NLSY97 data. We obtain an estimate of 0.60 for young men, but the t-test indicates it is insignificant. In contrast, the Anderson-Rubin (AR) test – which avoids the power asymmetry problem – implies the estimate is highly significant. The same power asymmetry issue that afflicts the t-test here will arise in many IV applications. Thus, we argue the AR test should be widely adopted in lieu of the t-test.

We study how negative sentiment around an industry impacts beliefs and behaviors, focusing on demands for racial justice after the murder of George Floyd and the salience of the “defund the police” movement. We assess stakeholder beliefs on the impact of protests on the stock prices of police-affiliated firms. In our survey experiment, laypeople and finance professionals predicted more negative stock price outcomes when they lacked details on the products supplied by such firms. Exposure to narratives about the context of the protests further reduced the prediction accuracy of these groups. In contrast, product information improved the prediction accuracy of respondents. Turning to real-life behavior, we find that mutual funds exposed to protests were 20% less likely to hold police stocks, after the protests, than funds in areas without protests. Political support for maintaining police funding, though in the majority, declined by 4.3 percentage points in protest areas. The salience of the “defund the police” narrative led to significant overreactions in both financial predictions and real-life behavior.

Using rural household survey data from West Bengal, we find that voters respond positively to excludable government welfare benefits but not to local public good programs, while reporting having benefited from both. Consistent with these voting patterns, shocks to electoral competition induced by exogenous redistricting of villages resulted in upper-tier governments manipulating allocations across local governments only for excludable benefit programs. Using a hierarchical budgeting model, we argue these results provide credible evidence of the presence of clientelism rather than programmatic politics.

After 1980, larger US cities experienced substantially faster wage growth than smaller ones. We show that this urban bias mainly reflected wage growth at large Business Services firms. These firms stand out through their high per-worker expenditure on information technology and disproportionate presence in big cities. We introduce a spatial model of investment-specific technical change that can rationalize these patterns. Using the model as an accounting framework, we find that the observed decline in the investment price of information technology capital explains most urban-biased growth by raising the profits of large Business Services firms in big cities.

We explore the evolution of income inequality and mobility in the U.S. for a large number of subnational groups defined by race and ethnicity, using granular statistics describing income distributions, income mobility, and conditional income growth derived from the universe of tax filers and W-2 recipients that we observe over a two-decade period (1998–2019). We find that income inequality and income growth patterns identified from administrative tax records differ in important ways from those that one might identify in public survey sources. The full set of statistics that we construct is available publicly alongside this paper as the Income Distributions and Dynamics in America, or IDDA, dataset. Using two applications, we illustrate IDDA’s relevance for understanding income inequality trends. First, we extend Bayer and Charles (2018) beyond earnings gaps between Black and White men and document that, unlike those for other groups, earnings for both Black men and Black women fell behind earnings for White men following the Great Recession. This trend lasted through 2019, the end of the data period. Second, we document a significant reversal in the convergence of earnings for Native earners in Native areas.

Property taxes impact the housing distribution across generations. Low property taxes lead to concentrated ownership among elderly empty-nesters, limiting housing for financially constrained young families. Conversely, high property taxes act as a “forced mortgage,” reducing upfront downpayments and enabling greater homeownership among younger households. We show in an overlapping generations model that raising property taxes in low-tax California to match those in higher-tax Texas increases homeownership in California by 4.6% and among younger households by 7.4% in steady state. Asset taxes can reallocate housing to higher-valuation households in the presence of financial constraints, providing an independent rationale for property taxes.

We build a scenario for inflation in the United States in the years to come. Following Gao, Kulish, and Nicolini (2021), we use the quantity theory of money as a conceptual framework and confront the theory with evidence from both the United States and other OECD countries. We argue that a) the quantity theory of money works very well in the medium term, which we define to be close to four years; b) deviations from the inflation rate predicted by the quantity theory tend to disappear in the medium term; c) the burst in inflation that started in 2012 in the United States is a deviation from the inflation rate predicted by the quantity theory; and d) if the policy framework does not change, we expect inflation to be back close to its 2% target no later than 2025.

We build a scenario for inflation in the United States in the years to come. Following Gao, Kulish, and Nicolini (2021), we use the quantity theory of money as a conceptual framework and confront the theory with evidence from both the United States and other OECD countries. We argue that a) the quantity theory of money works very well in the medium term, which we define to be close to four years; b) deviations from the inflation rate predicted by the quantity theory tend to disappear in the medium term; c) the burst in inflation that started in 2021 in the United States is a deviation from the inflation rate predicted by the quantity theory; and d) if the policy framework does not change, we expect inflation to be back close to its 2% target no later than 2025.

The goal of this paper is twofold. First, we wish to better explain the relationship between Sargent and Wallace’s (1981) unpleasant monetarist arithmetic, the closely connected fiscal theory of the price level (FTPL), and the monetarist view of inflation. Second, we discuss how the recent inflationary episode has contributed to redistributing real resources from holders of government debt to the public purse. In particular, financial prices before the onset of the COVID pandemic suggest that investors viewed an inflationary shock such as the one we experienced as extremely unlikely, so the magnitude of this redistribution caught them by surprise.