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The Alpha Beta Gamma of the Labor Market
April 2022
Working Paper Number:
CES-22-10
Using a large panel dataset of US workers, we calibrate a search-theoretic model of the labor market, where workers are heterogeneous with respect to the parameters governing their employment transitions. We first approximate heterogeneity with a discrete number of latent types, and then calibrate type-specific parameters by matching type-specific moments. Heterogeneity is well approximated by 3 types: as, 's and ?s. Workers of type a find employment quickly because they have large gains from trade, and stick to their jobs because their productivity is similar across jobs. Workers of type ? find employment slowly because they have small gains from trade, and are unlikely to stick to their job because they keep searching for jobs in the right tail of the productivity distribution. During the Great Recession, the magnitude and persistence of aggregate unemployment is caused by ?s, who are vulnerable to shocks and, once displaced, they cycle through multiple unemployment spells before finding stable employment.
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Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning
November 2021
Working Paper Number:
CES-21-35
This paper considers the problem of record linkage between a household-level survey and an establishment-level frame in the absence of unique identifiers. Linkage between frames in this setting is challenging because the distribution of employment across establishments is highly skewed. To address these difficulties, this paper develops a probabilistic record linkage methodology that combines machine learning (ML) with multiple imputation (MI). This ML-MI methodology is applied to link survey respondents in the Health and Retirement Study to their workplaces in the Census Business Register. The linked data reveal new evidence that non-sampling errors in household survey data are correlated with respondents' workplace characteristics.
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Small Business Pulse Survey Estimates by Owner Characteristics and Rural/Urban Designation
September 2021
Working Paper Number:
CES-21-24
In response to requests from policymakers for additional context for Small Business Pulse Survey (SBPS) measures of the impact of COVID-19 on small businesses, we researched developing estimates by owner characteristics and rural/urban locations. Leveraging geographic coding on the Business Register, we create estimates of the effect of the pandemic on small businesses by urban and rural designations. A more challenging exercise entails linking micro-level data from the SBPS with ownership data from the Annual Business Survey (ABS) to create estimates of the effect of the pandemic on small businesses by owner race, sex, ethnicity, and veteran status. Given important differences in survey design and concerns about nonresponse bias, we face significant challenges in producing estimates for owner demographics. We discuss our attempts to meet these challenges and provide discussion about caution that must be used in interpreting the results. The estimates produced for this paper are available for download. Reflecting the Census Bureau's commitment to scientific inquiry and transparency, the micro data from the SBPS will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.
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Heavy Tailed, but not Zipf: Firm and Establishment Size in the U.S.
July 2021
Working Paper Number:
CES-21-15
Heavy tails play an important role in modern macroeconomics and international economics.
Previous work often assumes a Pareto distribution for firm size, typically with a shape parameter approaching Zipf's law. This convenient approximation has dramatic consequences for the importance of large firms in the economy. But we show that a lognormal distribution, or better yet, a convolution of a lognormal and a non-Zipf Pareto distribution, provides a better description of the U.S. economy, using confidential Census Bureau data. These findings hold even far in the upper tail and suggest heterogeneous firm models should more systematically explore deviations from Zipf's law.
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Business Formation: A Tale of Two Recessions
January 2021
Working Paper Number:
CES-21-01
The trajectory of new business applications and transitions to employer businesses differ markedly during the Great Recession and COVID-19 Recession. Both applications and transitions to employer startups decreased slowly but persistently in the post-Lehman crisis period of the Great Recession. In contrast, during the COVID-19 Recession new applications initially declined but have since sharply rebounded, resulting in a surge in applications during 2020. Projected transitions to employer businesses also rise but this is dampened by a change in the composition of applications in 2020 towards applications that are more likely to be nonemployers.
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Business-Level Expectations and Uncertainty
December 2020
Working Paper Number:
CES-20-41
The Census Bureau's 2015 Management and Organizational Practices Survey (MOPS) utilized innovative methodology to collect five-point forecast distributions over own future shipments, employment, and capital and materials expenditures for 35,000 U.S. manufacturing plants. First and second moments of these plant-level forecast distributions covary strongly with first and second moments, respectively, of historical outcomes. The first moment of the distribution provides a measure of business' expectations for future outcomes, while the second moment provides a measure of business' subjective uncertainty over those outcomes. This subjective uncertainty measure correlates positively with financial risk measures. Drawing on the Annual Survey of Manufactures and the Census of Manufactures for the corresponding realizations, we find that subjective expectations are highly predictive of actual outcomes and, in fact, more predictive than statistical models fit to historical data. When respondents express greater subjective uncertainty about future outcomes at their plants, their forecasts are less accurate. However, managers supply overly precise forecast distributions in that implied confidence intervals for sales growth rates are much narrower than the distribution of actual outcomes. Finally, we develop evidence that greater use of predictive computing and structured management practices at the plant and a more decentralized decision-making process (across plants in the same firm) are associated with better forecast accuracy.
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Business Dynamics on American Indian Reservations: Evidence from Longitudinal Datasets
November 2020
Working Paper Number:
CES-20-38
We use confidential US Census Bureau data to analyze the difference in business establishment dynamics by geographic location on or off of American Indian reservations over the period of the Great Recession, and subsequent recovery (2007-2016). We geocoded U.S. Census Bureau's Longitudinal Business Database, a dataset with records of all employer business establishments in the U.S. for location in an American Indian Reservation and used it to examine whether there are differences in business establishment survival rates over time by virtue of their location. We find that business establishments located on American Indian reservations have higher survival rates than establishments located in comparable counties. These results are particularly strong for the education, arts and entertainment, wholesale and retail, and public administration industries. While we are not fully able to explain this result, it is consistent with the business establishments being positively selected with respect to survival given the large obstacles necessary to start a business on a reservation in the first place. Alternatively, there may be certain safeguards in a reservation economy that protect business establishments from external economic shocks.
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Compositional Nature of Firm Growth and Aggregate Fluctuations
March 2020
Working Paper Number:
CES-20-09
This paper studies firm dynamics over the business cycle. I present evidence from the United Kingdom that more rapidly growing firms are born in expansions than in recessions. Using administrative records from Census data, I find that this observation also holds for the last four recessions in the United States. I also present suggestive evidence that financial frictions play an important role in determining the types of firms that are born at different stages of the business cycle. I then develop a general equilibrium model in which firms choose their managers' span of control at birth. Firms that choose larger spans of control grow faster and eventually get to be larger, and in this sense have a larger target size. Financial frictions in the form of collateral constraints slow the rate at which firms reach their target size. It takes firms longer to get up to scale when collateral constraints tighten; therefore, businesses with the largest target size are affected disproportionately more. Thus, fewer entrepreneurs find it profitable to choose larger projects when financial conditions deteriorate. Using Bayesian methods, I estimate the model using micro and aggregate data from the United Kingdom. I find that financial shocks account for over 80% of fluctuations in the formation of businesses with a large target size, and TFP and labor wedge shocks account for the remaining 20%. An independently estimated version of the model with no choice over the span of control needs larger aggregate shocks in order to account for the same data series, suggesting that the intensive margin of business formation is important at business cycle frequencies. The model with the choice over the span of control generates an empirically relevant and non-targeted collapse in the right tail of the cumulative growth distribution among firms started in recessions, while the model without such a choice does not. The paper also discusses implications for micro-targeted government stimulus policies.
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Rising Import Tariffs, Falling Export Growth: When Modern Supply Chains Meet Old-Style Protectionism
January 2020
Working Paper Number:
CES-20-01
We examine the impacts of the 2018-2019 U.S. import tariff increases on U.S. export growth through the lens of supply chain linkages. Using 2016 confidential firm-trade linked data, we document the implied incidence and scope of new import tariffs. Firms that eventually faced tariff increases on their imports accounted for 84% of all exports and represented 65% of manufacturing employment. For all affected firms, the implied cost is $900 per worker in new duties. To estimate the effect on U.S. export growth, we construct product-level measures of import tariff exposure of U.S. exports from the underlying firm micro data. More exposed products experienced 2 percentage point lower growth relative to products with no exposure. The decline in exports is equivalent to an ad valorem tariff on U.S. exports of almost 2% for the typical product and almost 4% for products with higher than average exposure.
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Demographic Origins of the Startup Deficit
July 2019
Working Paper Number:
CES-19-21
We propose a simple explanation for the long-run decline in the startup rate. It was caused by a slowdown in labor supply growth since the late 1970s, largely pre-determined by demographics. This channel explains roughly two-thirds of the decline and why incumbent firm survival and average growth over the lifecycle have been little changed. We show these results in a standard model of firm dynamics and test the mechanism using shocks to labor supply growth across states. Finally, we show that a longer startup rate series imputed using historical establishment tabulations rises over the 1960-70s period of accelerating labor force growth.
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