We study the local economic spillovers generated by LeBron James’ presence on a team in the National Basketball Association. Mr. James, the first overall pick of the 2003 NBA draft, spent the first seven seasons of his career at the Cleveland Cavaliers, and then moved to the Miami Heat in 2010, only to return to Cleveland in 2014. Long considered one of the NBA’s superstars, he has received the league’s MVP award four times, won three NBA championships, and been a part of two victorious US teams at the Olympics. We trace the impact a star of Mr. James’ caliber can have on economic activity by analyzing the impact his departures and arrivals had on business activity close to the Cleveland Cavaliers and Miami Heat stadiums. We find that Mr. James has a statistically and economically significant positive effect on both the number of restaurants and other eating and drinking establishments near the stadium where he is based, and on aggregate employment at those establishments. Specifically, his presence increases the number of such establishments within one mile of the stadium by about 13%, and employment by about 23.5%. These effects are very local, in that they decay rapidly as one moves farther from the stadium.
State and local government pension funds in the United States collectively manage a very large and diverse pool of assets to meet the even large sum of accrued liabilities. Recent research has emphasized that widely-used accounting practices, like matching discount rates to expected asset returns, understate the market value of these liabilities. Less work has explored the risks inherent in existing diverse set asset allocations, and the accounting practices used by most state and local pensions do not capture or report this risk at all. To explore the effect of asset market risk, we build and simulate a dynamic model of pension funding using a realistic return generating process. We find that the range of potential outcomes is very large, meaning that state and local governments need to prepare for an extremely wide range of possible funding shocks in the next few decades. Moreover, this wide range of outcomes makes the ultimate impact of policy choices – such as changing the discount rate or failing to sufficiently contribute to the fund – nonlinear and difficult to anticipate. Together, these findings suggest the need for more attention and reporting of these risks and the attendant range of possible outcomes by public plans.
Many localities have in recent years limited the use of questions about criminal history in hiring, or "banned the box." We show that these bans increased employment of residents in high-crime neighborhoods by up to 4%. This effect can be seen both across and within census tracts, in employment levels as well as in commuting patterns. The increases are particularly large in the public sector and in lower-wage jobs. We also establish that employers respond to Ban the Box measures by raising experience requirements. On net, black men benefit from the changes.
In the past decade, most states have banned or have considered banning the use of credit checks in hiring decisions, a screening tool that is widely used by employers. Using new Equifax data on employer credit checks, the Federal Reserve Bank of New York Consumer Credit Panel/Equifax, and the LEHD Origin-Destination Employment data, we show that these bans increased employment of residents in the lowest credit score areas. The largest gains occurred in higherpaying jobs and in the government-sector. At the same time, using a large database of job postings, we show that employers increased their demands for other signals of applicants’ job performance, like education and experience. On net, the changes induced by these bans generate relatively worse outcomes for those with mid-to-low credit scores, for those under 22 years old, and for Blacks, groups commonly thought to benefit from such legislation.
The effect of government spending on income and employment is a central unresolved question in macroeconomics. This paper employs a novel identification strategy to isolate exogenous and unexpected variation in state government spending. State governments manage large defined-benefit pension plans for which they bear the investment risk. Using a newly-collected dataset on the returns and portfolios of these plans, I show that the idiosyncratic component of their returns is a strong predictor of subsequent state government spending. Instrumenting with this ‘windfall’ component of returns, I find that state government spending has a large positive effect on income and employment. Baseline estimates indicate that each dollar of spending raises in-state income by 2.12, and that 35,000 of spending generates one additional job. These effects are not due to in-state investment bias, are concentrated in the non-traded sector, and are larger during times of labor force ‘slack.’ Finally, I consider how these results compare with the predictions of a standard macroeconomic model and outline which features in the model are consistent with the empirical findings.
In the wake of the Great Recession, policymakers and academics have expressed concerns about rising employer skill requirements. Using a large database of online job postings for middle-skill occupations, we demonstrate that employers opportunistically raise education and experience requirements, within occupations, in response to increases in the supply of relevant job seekers. This relationship is robust to numerous tests for potentially confounding factors, is present even within firm-job title pairs, and is consistent with the predictions of a standard employer search model. We further identify this effect by exploiting the natural experiment arising from troop-withdrawals in Iraq and Afghanistan as an exogenous shock to local, occupation-specific labor supply. Our results imply that increases in the number of people looking for work can account for roughly 30 percent of the total increase in employer skill requirements observed between 2007 and 2010.
The past thirty years have seen a dramatic decline in the rate of income convergence across states and in population flows to wealthy places. These changes coincide with (1) an increase in housing prices in productive areas, (2) a divergence in the skill-specific returns to living in those places, and (3) a redirection of unskilled migration away from productive places. We develop a model in which rising housing prices in wealthy areas deter unskilled migration and slow income convergence. Using a new panel measure of housing supply regulations, we demonstrate the importance of this channel in the data. Income convergence continues in less-regulated places, while it has mostly stopped in places with more regulation.
We report three findings: (1) Using evidence from national chain bankruptcies and a data set on 12-18 million establishments per year, we show that large retailers have significant positive effects on nearby establishments that decay quickly with distance. (2) Local governments respond to the size of these externalities. When a town’s political boundaries allow it to capture a larger share of retail spillovers, it is more likely to offer retail subsidies. (3) These subsidies, however, crowd out private-sector mechanisms that also subsidize large retailers, such as shopping malls. Together these facts provide powerful evidence of the Coase theorem at work and highlight a concern for local development policies even when externalities can be targeted.
Recent research has stressed the importance of long-run place effects on income and economic mobility, but the literature has struggled to isolate the causal impact of location. This paper provides new evidence on these effects using administrative data on over 100,000 Japanese- Americans who were interned during World War II. Internees were conditionally randomly assigned to camps in seven different states and held for several years. Restitution payments paid in the early 1990s to the universe of surviving internees allow us to measure their locations and outcomes nearly half a century after the camp assignments. Using this unique natural experiment we find, first, that camp assignment had a lasting effect on individuals’ long-term locations. Next, using this variation, we find large place effects on individual economic outcomes like income, education, socioeconomic status, house prices, and housing quality. People assigned to richer locations do better on all measures. Random location assignment affected intergenerational economic outcomes as well, with families assigned to more socially mobile areas (as designated by Chetty et al., 2014) displaying lower cross-generational correlation in outcomes. Finally, we provide evidence that assignment to richer places impacted people’s values and political views, a new and intriguing mechanism through which place effects operate. Together, this new causal evidence on location effects has broad implications for urban economics, as well as potential policy implications for policymakers struggling to resettle and integrate large refugee or immigrant populations.
Using a novel database of 66.8 million online job postings, we show that employer skill requirements fell as the labor market improved from 2010-2014. We find that a 1 percentage point reduction in the local unemployment rate is associated with 0.20 percentage point reduction in the fraction of jobs requiring at least a bachelor’s degree and a 0.22 percentage point reduction in the fraction requiring 5 or more years of experience. This pattern is established using multiple measures of labor availability, is bolstered by similar trends along heretofore unmeasured dimensions of skill, and even occurs within firm-job title pairs. We further confirm the causal effect of labor market tightening on skill requirements using a natural experiment based on the fracking boom in the U.S. as an exogenous shock to local labor supply in tradable, non-fracking industries. These industries are not plausibly affected by local demand shocks or natural gas extraction technology, but still show fewer skill requirements in response to tighter labor markets. Our results imply this labor-market induced downskilling reversed much of the cyclical increase in education and experience requirements that occurred during the Great Recession.
The variation in a state-level measure of local economic-policy uncertainty during the 2007-2009 recession matches the cross-sectional distribution of unemployment outcomes in this period. This relationship is robust to numerous controls for other determinants of labor market outcomes. Using preexisting state institutions that amplified uncertainty, we find evidence that this type of local uncertainty played a causal role in increasing unemployment. Together, these results suggest that increased uncertainty contributed to the severity of the Great Recession.
State and local pension plans are increasingly moving from the traditional defined benefit (DB) model to non-DB models that generally allow for participant-directed investment. This shift has important implications for the management of the more than US$3 trillion in assets held to finance public employee retirement benefits. To investigate these implications, we introduce new data from a nationwide survey of public DB and non-DB plans and a unique data set on thousands of individual investors in the state of Florida’s defined contribution (DC) plan. Using these sources, we explore how participant involvement in the public sector affects the distribution of asset class allocations, management fees, investment outcomes, and portfolio rebalancing at both the individual and aggregate levels. We found that there is little difference between the DB and non-DB plans in terms of asset mix, returns, and fees, except that DB plan have greater access and allocations to alternative investments. We also found that while the average individual DC plan participant allocated their asset similarly to the DB plan, black females and older white males, on average, invested on opposite tails of the risk spectrum.
Can data from mobile phones be used to observe economic shocks and their consequences at multiple scales? Here we present novel methods to detect mass layoffs, identify individuals affected by them, and predict changes in aggregate unemployment rates using call detail record (CDR) data from mobile phones. Using the closure of a large manufacturing plant as a case study, we first describe structural break and Bayesian classification models to detect a mass layoff and the individuals affected by it by observing changes in calling behavior. For these affected individuals, we find measure significant declines in social behavior and mobility following job loss. We then apply these findings to the macro level and show that the same changes in these calling behaviors, aggregated at the regional level, can improve forecasts of unemployment rates.
Can protests cause political change, or are they merely symptoms of underlying shifts in policy preferences? We address this question by studying the Tea Party movement in the United States, which rose to prominence through coordinated rallies across the country on Tax Day, April 15, 2009. We exploit variation in rainfall on the day of these rallies as an exogenous source of variation in attendance. We show that good weather at this initial, coordinating event had significant consequences for the subsequent local strength of the movement, increased public support for Tea Party positions, and led to more Republican votes in the 2010 midterm elections. Policymaking was also affected, as incumbents responded to large protests in their district by voting more conservatively in Congress. Our estimates suggest significant multiplier effects: an additional protester increased the number of Republican votes by a factor well above one. Together our results show that protests can build political movements that ultimately affect policymaking, and that they do so by influencing political views rather than solely through the revelation of existing political preferences.