This paper examines the effect of property rights on economic development within local labor markets, including how property rights change the equilibrium response to place-based policies. It does so in the context of federally recognized American Indian reservations, where a fraction of the land is held in trust by the US federal government and associated with restrictions on transactions. I find that incomplete property rights on reservations are responsible for lower wages and higher levels of unemployment. The direction of these findings is robust to an instrumental variables approach to dealing with the endogeneity of property rights. Next I shed light on the extent to which place-based policies can improve economic outcomes on reservations. I use a spatial equilibrium framework to study the incidence of casino adoption, a place-based policy unique to reservations. The key insight from the model is that incomplete property rights impose frictions in the housing market that lower the migration response to casino adoption, improving the likelihood that the local population benefits. Consistent with the model's predictions, I find that casino adoption raises average wages and that the wage effect is greater on reservations with more land in trust. My estimates suggest that wage increases correspond to welfare improvements. This paper provides insights into how place-based policies and property rights jointly shape economic outcomes through changes in the labor market, the housing market, and the mobility of workers.
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THE OPTION TO QUIT: THE EFFECT OF EMPLOYEE STOCK OPTIONS ON TURNOVER
January 2014
Working Paper Number:
CES-14-06
We show that in the years following a large broad-based employee stock option (BBSO) grant, employee turnover falls at the granting firm. We find evidence consistent with a causal relation by exploiting unexpected changes in the value of unvested options. A large fraction of the reduction in turnover appears to be temporary with turnover increasing in the 3rd year following the year of the adoption of the BBSO plan. We also find that the effect of BBSO plans is larger at market leaders, identified as firms with high industry-adjusted market-to-book ratios, market share or industry-adjusted profit margins, as measured at the time of the grant.
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The Consequences of Long Term Unemployment:
Evidence from Matched Employer-Employee Data*
January 2016
Working Paper Number:
CES-16-40
It is well known that the long-term unemployed fare worse in the labor market than the short-term unemployed, but less clear why this is so. One potential explanation is that the long-term unemployed are 'bad apples' who had poorer prospects from the outset of their spells (heterogeneity). Another is that their bad outcomes are a consequence of the extended unemployment they have experienced (state dependence). We use Current Population Survey (CPS) data on unemployed individuals linked to wage records for the same people to distinguish between these competing explanations. For each person in our sample, we have wage record data that cover the period from 20 quarters before to 11 quarters after the quarter in which the person is observed in the CPS. This gives us rich information about prior and subsequent work histories not available to previous researchers that we use to control for individual heterogeneity that might be affecting subsequent labor market outcomes. Even with these controls in place, we find that unemployment duration has a strongly negative effect on the likelihood of subsequent employment. This finding is inconsistent with the heterogeneity ('bad apple') explanation for why the long-term unemployed fare worse than the short-term unemployed. We also find that longer unemployment durations are associated with lower subsequent earnings, though this is mainly attributable to the long-term unemployed having a lower likelihood of subsequent employment rather than to their having lower earnings once a job is found.
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Going Entrepreneurial? IPOs and New Firm Creation
January 2017
Working Paper Number:
CES-17-18
Using matched employee-employer US Census data, we examine the effect of a successful initial public offering (IPO) on employee departures to startups. Accounting for the endogeneity of a firm's choice to go public, we find strong evidence that going public induces employees to leave for start-ups. Moreover, we document that the increase in turnover following an IPO is driven by employees departing to start-ups; we find no change in the rate of employee departures for established firms. We present evidence that, following an IPO, many employees who received stock grants experience a positive shock to their wealth which allows them to better tolerate the risks associated with joining a startup or to obtain funding. Our results suggest that the recent declines in IPO activity and new firm creation in the US may be causally linked. The recent decline in IPOs means fewer workers may move to startups, decreasing overall new firm creation in the economy.
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On The Role of Trademarks: From Micro Evidence to Macro Outcomes
March 2023
Working Paper Number:
CES-23-16R
What are the effects of trademarks on the U.S. economy? Evidence from comprehensive micro data on trademark registrations and outcomes for U.S. employer firms suggests that trademarks protect firm value and are linked to higher firm growth and marketing activity. Motivated by this evidence, trademarks are introduced in a general equilibrium framework to quantify their aggregate effects. Firms invest in product quality and engage in both informative and persuasive advertising to build a customer base subject to depreciation. Persuasive advertising induces a perception of higher quality. Firms can register trademarks to reduce customer depreciation and enhance product awareness. The model's predictions about trademark registrations, firm growth, and advertising expenditures align with the empirical evidence. The analysis shows that, compared to the counterfactual economy without trademarks, the U.S. economy with trademarks generates higher average product quality but lower variety, ultimately resulting in greater welfare and higher industry concentration. While informative advertising improves welfare, persuasive advertising reduces it. Nevertheless, the positive welfare impact of trademarks outweighs the negative effects of persuasive advertising.
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Taking the Leap: The Determinants of Entrepreneurs Hiring their First Employee
January 2016
Working Paper Number:
CES-16-48
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.
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Estimating A Multivariate Arma Model with Mixed-Frequency Data: An Application to Forecasting U.S. GNP at Monthly Intervals
July 1990
Working Paper Number:
CES-90-05
This paper develops and applies a method for directly estimating a multivariate, autoregressive moving-average (ARMA) model with mixed-frequency, time-series data. Unlike standard, single-frequency methods, the method does not require the data to be transformed to a single frequency (by temporally aggregating higher-frequency data to lower frequencies for interpolating lower-frequency data to higher frequencies) or the model to be restricted by frequency. Subject to computational constraints, the method can handle any number of variable and frequencies. In addition, variable can be treated as temporally aggregated and observed with errors and delays. The key to the method is to view lower-frequency data as periodically missing and to use the missing-data variant of the Kalman filter.
In the application, a bivariate, ARMA model is estimated with monthly observations on total employment and quarterly observations on real GNP, in the U.S., for January 1958 to December 1978. The estimated model is, then, used to compute monthly forecasts of the variables for 1 to 12 months ahead, for January 1979 to December 1988. Compared with GNP forecasts, in particular, for similar periods produced by established econometric and time series models, present GNP forecasts are generally more accurate for 1 to 4 months ahead and about equally or slightly less accurate for 5 to 12 months ahead. The application, thus, shows that the present method is tractable and able to effectively exploit cross-frequency sample information, in ARMA estimate and forecasting, which standard methods cannot exploit at all.
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Production Function and Wage Equation Estimation with Heterogenous Labor: Evidence from a New Matched Employer-Employee Dataset
April 2004
Working Paper Number:
CES-04-05
In this paper, we first describe the 1990 DEED, the most recently constructed matched employeremployee data set for the United States that contains detailed demographic information on workers (most notably, information on education). We then use the data from manufacturing establishments in the 1990 DEED to update and expand on previous findings, using a more limited data set, regarding the measurement of the labor input and theories of wage determination (Hellerstein, et al., 1999). We find that the productivity of women is less than that of men, but not by enough to fully explain the gap in wages, a result that is consistent with wage discrimination against women. In contrast, we find no evidence of wage discrimination against blacks. We estimate that both the wage and productivity profiles are rising but concave to the origin (consistent with profiles quadratic in age), but the estimated relative wage profile is steeper than the relative productivity profile, consistent with models of deferred wages. We find a productivity premium for marriage equal to that of the wage premium, and a productivity premium for education that somewhat exceeds the wage premium. Exploring the sensitivity of these results, we also find that different specifications of production functions do not have any qualitative effects on the these results. Finally, the results indicate that the returns to productive inputs (capital, materials, labor quality) as well as the residual variance are virtually unaffected by the choice of the construction of the labor quality input.
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Business Applications as a Leading Economic Indicator?
May 2021
Working Paper Number:
CES-21-09R
How are applications to start new businesses related to aggregate economic activity? This paper explores the properties of three monthly business application series from the U.S. Census Bureau's Business Formation Statistics as economic indicators: all business applications, business applications that are relatively likely to turn into new employer businesses ('likely employers'), and the residual series -- business applications that have a relatively low rate of becoming employers ('likely non-employers'). Growth in applications for likely employers significantly leads total nonfarm employment growth and has a strong positive correlation with it. Furthermore, growth in applications for likely employers leads growth in most of the monthly Principal Federal Economic Indicators (PFEIs). Motivated by our findings, we estimate a dynamic factor model (DFM) to forecast nonfarm employment growth over a 12-month period using the PFEIs and the likely employers series. The latter improves the model's forecast, especially in the years following the turning points of the Great Recession and the COVID-19 pandemic. Overall, applications for likely employers are a strong leading indicator of monthly PFEIs and aggregate economic activity, whereas applications for likely non-employers provide early information about changes in increasingly prevalent self-employment activity in the U.S. economy.
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Spinout Formation: Do Opportunities and Constraints Benefit High Capital Founders?
June 2015
Working Paper Number:
CES-15-07
We examine the role of human capital in employees' decisions to leave their parent firms andform spinouts. Using a large sample of individuals who formed spinouts in manufacturing industries between 1992 and 2005, and their co-workers who did not, we find that after controlling for age, education level, gender and alien status, individuals with higher human capital (measured as their earnings or experience) are more likely to form spinouts. We then examine the impact of industry opportunities and constraints on the propensity of high human capital individuals to form spinouts. Counterintuitively, we find that both industry constraints (measured as industry capital intensity) and opportunities (industry R&D intensity) reduce the propensity of higher human capital individuals to form spinouts. We interpret these results as being consistent with the argument that high human capital founders are more likely to choose larger, more capital-intensive projects than low human capital individuals, and thus face greater constraints. On the other side, R&D intensive industries appear to present abundant entrepreneurial opportunities, allowing low human capital individuals to identify their own opportunities thus decreasing the relative advantage of high human capital individuals.
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The Impact of Immigration on Firms and Workers: Insights from the H-1B Lottery
April 2024
Working Paper Number:
CES-24-19
We study how random variation in the availability of highly educated, foreign-born workers impacts firm performance and recruitment behavior. We combine two rich data sources: 1) administrative employer-employee matched data from the US Census Bureau; and 2) firm level information on the first large-scale H-1B visa lottery in 2007. Using an event-study approach, we find that lottery wins lead to increases in firm hiring of college-educated, immigrant labor along with increases in scale and survival. These effects are stronger for small, skill-intensive, and high-productivity firms that participate in the lottery. We do not find evidence for displacement of native-born, college-educated workers at the firm level, on net. However, this result masks dynamics among more specific subgroups of incumbents that we further elucidate.
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