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The Matching Multiplier and the Amplification of Recessions
June 2022
Working Paper Number:
CES-22-20
This paper shows that the unequal incidence of recessions in the labor market amplifies aggregate shocks. Using administrative data from the United States, I document a positive covariance between worker marginal propensities to consume (MPCs) and their elasticities of earnings to GDP, which is a key moment for a new class of heterogeneous-agent models. I define the Matching Multiplier as the increase in the multiplier stemming from this matching of high MPC workers to more cyclical jobs. I show that this covariance is large enough to increase the aggregate MPC by 20 percent over an equal exposure benchmark.
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Structural Change Within Versus Across Firms: Evidence from the United States
June 2022
Working Paper Number:
CES-22-19
We document the role of intangible capital in manufacturing firms' substantial contribution to
non-manufacturing employment growth from 1977-2019. Exploiting data on firms' 'auxiliary' establishments, we develop a novel measure of proprietary in-house knowledge and show that it
is associated with increased growth and industry switching. We rationalize this reallocation in a
model where irms combine physical and knowledge inputs as complements, and where producing
the latter in-house confers a sector-neutral productivity advantage facilitating within-firm structural
transformation. Consistent with the model, manufacturing firms with auxiliary employment pivot towards services in response to a plausibly exogenous decline in their physical input prices.
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Has toughness of local competition declined?
May 2022
Working Paper Number:
CES-22-13
Recent evidence on rm-level markups and concentration raises a concern that market
competition has declined in the U.S. over the last few decades. Since measuring competition is difficult, methodologies used to arrive at these findings have merits but also raise technical concerns which question the validity of these results. Given the significance of documenting how competition has changed, I contribute to this literature by studying a different measure of competition. Specifically, I estimate the toughness of local competition over time. To derive this estimate, I use a generalized monopolistic competition model with variable markups. This model generates insights that allows me to measure competition as the sensitivity of weighted-average markup to changes in the number of competitors using directly observable variables. Compared to firm-level markups estimation, this method relaxes the need to estimate production functions. I then use confidential Census data to estimate toughness of local competition from 1997 to 2016, which shows that local competition has decreased in non-tradable industries on average in the U.S. during this time period.
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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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Firm Finances and Responses to Trade Liberalization: Evidence from U.S. Tariffs on China
November 2021
Working Paper Number:
CES-21-37
This paper examines the relationship between a firm's finances and its response to trade liberalization. Using a landmark change in U.S. tariff policy vis-'-vis Chinese imports and micro level data from the U.S. Census Bureau, I find larger manufacturing job losses in better capitalized firms - those with less leverage and more cash on hand. The effects concentrate in industries where weaker balance sheets are likely to lead to collateral and other borrowing constraints, helping rule out alternative explanations. Finally, domestic manufacturing job losses are not accompanied by greater reductions in sales or aggregate employment, but better capitalized firms do exhibit reduced input costs and increased productivity. These findings point to offshoring as the predominant firm response to trade liberalization and suggest a role for financial capacity in facilitating offshoring investments.
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Climate Change, The Food Problem, and the Challenge of Adaptation through Sectoral Reallocation
September 2021
Working Paper Number:
CES-21-29
This paper combines local temperature treatment effects with a quantitative macroeconomic model to assess the potential for global reallocation between agricultural and non-agricultural production to reduce the costs of climate change. First, I use firm-level panel data from a wide range of countries to show that extreme heat reduces productivity less in manufacturing and services than in agriculture, implying that hot countries could achieve large potential gains through adapting to global warming by shifting labor toward manufacturing and increasing imports of food. To investigate the likelihood that such gains will be realized, I embed the estimated productivity effects in a model of sectoral specialization and trade covering 158 countries. Simulations suggest that climate change does little to alter the geography of agricultural production, however, as high trade barriers in developing countries temper the influence of shifting comparative advantage. Instead, climate change accentuates the existing pattern, known as 'the food problem,' in which poor countries specialize heavily in relatively low productivity agricultural sectors to meet subsistence consumer needs. The productivity effects of climate change reduce welfare by 6-10% for the poorest quartile of the world with trade barriers held at current levels, but by nearly 70% less in an alternative policy counterfactual that moves low-income countries to OECD levels of trade openness.
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A Search and Learning Model of Export Dynamics
August 2021
Working Paper Number:
CES-21-17
Exporting abroad is much harder than selling at home, and overcoming hurdles to exporting takes time. Our goal is to identify specific barriers to exporting and to measure their importance. We develop a model of firm-level export dynamics that features costly customer search, network effects in finding buyers, and learning about product appeal. Fitting the model to customs records of U.S. imports of manufactures from Colombia we replicate patterns of exporter maturation. A potentially valuable intangible asset of a firm is its customer base and knowledge of a market. Our model delivers some striking estimates of what such assets are worth. Averaging across active exporters, the loss from total market amnesia (losing its current U.S. customer base along with its accumulated knowledge of product appeal) is US$ 3.4 million, about 34 percent of the value of exporting overall. About half is the loss of future sales to existing customers while the rest is the cost of relearning its appeal in the market and reestablishing visibility as an exporter. Given the importance of search, learning, and visibility, the 5-year response of total export sales to an exchange rate shock exceeds the 1-year response by about 40 percent.
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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 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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U.S. Long-Term Earnings Outcomes by Sex, Race, Ethnicity, and Place of Birth
May 2021
Working Paper Number:
CES-21-07R
This paper is part of the Global Income Dynamics Project cross-country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12-year average earnings for a single cohort of age 25-54 eligible workers. Differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings, although even after controlling for labor supply substantial earnings differences across demographic groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost all the earnings gap, however above the median the contribution of the differences in the returns to characteristics becomes the dominant component.
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