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MANAGING TRADE: EVIDENCE FROM CHINA AND THE US
May 2019
Working Paper Number:
CES-19-15
We present a heterogeneous-firm model in which management ability increases both production efficiency and product quality. Combining six micro-datasets on management practices, production and trade in Chinese and American firms, we find broad support for the model's predictions. First, better managed firms are more likely to export, sell more products to more destination countries, and earn higher export revenues and profits. Second, better managed exporters have higher prices, higher quality, and lower quality-adjusted prices. Finally, they also use a wider range of inputs, higher quality and more expensive inputs, and imported inputs from more advanced countries. The structural estimates indicate that management is important for improving production efficiency and product quality in both countries, but it matters more in China than in the US, especially for product quality. Panel analysis for the US and a randomized control trial in India suggest that management exerts causal effects on product quality, production efficiency, and exports. Poor management practices may thus hinder trade and growth, especially in developing countries.
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Aggregating From Micro to Macro Patterns of Trade
February 2018
Working Paper Number:
CES-18-10
We develop a new framework for aggregating from micro to macro patterns of trade. We derive price indexes that determine comparative advantage across countries and sectors and the aggregate cost of living. If firms and products are imperfect substitutes, we show that these price indexes depend on variety, average demand/quality and the dispersion of demand/quality-adjusted prices, and are only weakly related to standard empirical measures of average prices, thereby providing insight for elasticity puzzles. Of the cross-section (time-series) variation in comparative advantage, 50 (90) percent is accounted for by variety and average demand/quality, with average prices contributing less than 10 percent.
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Estimating Unequal Gains across U.S. Consumers with Supplier Trade Data
January 2018
Working Paper Number:
CES-18-04
Using supplier-level trade data, we estimate the effect on consumer welfare from changes in U.S. imports both in the aggregate and for different household income groups from 1998 to 2014. To do this, we use consumer preferences which feature non-homotheticity both within sectors and across sectors. After structurally estimating the parameters of the model, using the universe of U.S. goods imports, we construct import price indexes in which a variety is defined as a foreign establishment producing an HS10 product that is exported to the United States. We find that lower income households experienced the most import price inflation, while higher income households experienced the least import price inflation during our time period. Thus, we do not find evidence that the consumption channel has mitigated the distributional effects of trade that have occurred through the nominal income channel in the United States over the past two decades.
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Import Competition from and Offshoring to Low-Income Countries: Implications for Employment and Wages at U.S. Domestic Manufacturers
January 2017
Working Paper Number:
CES-17-31
Using confidential linked firm-level trade transactions and census data between 1997 and 2012, we provide new evidence on how American firms without foreign affiliates adjust employment and wages as they adapt to import competition from low-income countries. We provide stylized facts on the input sourcing strategies of these domestic firms, contrasting them with multinationals operating in the same industry. We then investigate how changes in firm input purchases from low-income countries as well as domestic market import penetration from these sources are correlated with changes in employment and wages at surviving domestic firms. Greater offshoring by domestic firms from low-income countries correlates with larger declines in manufacturing employment and in the average production workers' wage. Given the negative association, however, the estimated magnitudes are small, even for a narrow measure of offshoring that includes only intermediate goods. Import penetration of U.S. markets from these sources is associated with relatively larger changes in employment for arm's length importing firms, but has no significant correlation with employment changes at firms that do not trade. Given differences in the degree of both offshoring and import penetration, we find substantial variation across industries in the magnitude of changes associated with low-income country imports.
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Are firm-level idiosyncratic shocks important for U.S. aggregate volatility?
January 2017
Working Paper Number:
CES-17-23
This paper quantitatively assesses whether firm-specific shocks can drive the U.S. business cycle. Firm-specific shocks to the largest firms can directly contribute to aggregate fluctuations whenever the firm size distribution is fat-tailed giving rise to the granular hypothesis. I use a novel, comprehensive data set compiled from administrative sources that contains the universe of firms and trade transactions, and find that the granular hypothesis accounts at most for 16 percent of the variation in aggregate sales growth. This is about half of that found by previous studies that imposed Gibrat's law where all firms are equally volatile regardless of their size. Using the full distribution of growth rates among U.S. firms, I find robust evidence of a negative relationship between firm-level volatility and size, i.e. the size-variance relationship. The largest firms (whose shocks drive granularity) are the least volatile under the size-variance relationship, thus their influence on aggregates is mitigated. I show that by taking this relationship into account the effect of firm-specific shocks on observed macroeconomic volatility is substantially reduced. I then investigate several plausible mechanisms that could explain the negative sizevariance relationship. After empirically ruling out some of them, I suggest a 'market power' channel in which large firms face smaller price elasticities and therefore respond less to a givensized productivity shock than small firms do. I provide direct evidence for this mechanism by estimating demand elasticities among U.S. manufactures. Lastly, I construct an analytically tractable framework that is consistent with several empirical regularities related to firm size.
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An 'Algorithmic Links with Probabilities' Crosswalk for USPC and CPC Patent Classifications with an Application Towards Industrial Technology Composition
March 2016
Working Paper Number:
CES-16-15
Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires patents be tied to measures of economic activity, which has proven to be difficult. Recently, Lybbert and Zolas (2014) have constructed an International Patent Classification (IPC) to industry classification crosswalk using an 'Algorithmic Links with Probabilities' approach. In this paper, we utilize a similar approach and apply it to new patent classification schemes, the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system. The resulting USPC-Industry and CPC-Industry concordances link both U.S. and global patents to multiple vintages of the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We then use the crosswalk to highlight changes to industrial technology composition over time. We find suggestive evidence of strong persistence in the association between technologies and industries over time.
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Learning and the Value of Relationships in International Trade
February 2016
Working Paper Number:
CES-16-11
How valuable are long-term supplier relationships? To address this question, this paper explores relationships between U.S. importers and their suppliers abroad. We establish several facts: almost half of U.S. imports involve relationships three years or older, relationship survival and traded quantity increase as a relationship ages, and long-term relationships were more resilient in the 2008-09 financial crisis. We present a model of importer learning and calibrate it using our data. We estimate large differences in the value of relationships across countries. Counterfactuals show that relationships are central to trade dynamics.
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Business Dynamics Statistics of High Tech Industries
January 2016
Working Paper Number:
CES-16-55
Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Technology sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. Tracking the performance of this sector is therefore of primary importance, especially in light of recent evidence that suggests a slowdown in business dynamism in High Tech industries. The Census Bureau produces the Business Dynamics Statistics (BDS), a suite of data products that track job creation, job destruction, startups, and exits by firm and establishment characteristics including sector, firm age, and firm size. In this paper we describe the methodologies used to produce a new extension to the BDS focused on businesses in High Technology industries.
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Are firm-level idiosyncratic shocks important for U.S. aggregate volatility?
January 2016
Working Paper Number:
CES-16-47
This paper assesses the quantitative impact of firm-level idiosyncratic shocks on aggregate volatility in the U.S. economy and provides a microfoundation for the negative relationship between firm-level volatility and size. I argue that the role of firm-specific shocks through the granular channel plays a fairly limited role in the U.S. economy. Using a novel, comprehensive data set compiled from several sources of the U.S. Census Bureau, I find that the granular com-ponent accounts at most for 15.5% of the variation in aggregate sales growth which is about half found by previous studies. To bridge the gap between previous findings and mine, I show that my quantitative results require deviations from Gibrat's law in which firm-level volatility and size are negatively related. I find that firm-level volatility declines at a substantially higher rate in size than previously found. Hence, the largest firms in the economy cannot be driving a sub-stantial fraction of macroeconomic volatility. I show that the explanatory power of granularity gets cut by at least half whenever the size-variance relationship, as estimated in the micro-level data, is taken into account. To uncover the economic mechanism behind this phenomenon, I construct an analytically tractable framework featuring random growth and a Kimball aggrega-tor. Under this setup, larger firms respond less to productivity shocks as the elasticity of demand is decreasing in size. Additionally, the model predicts a positive (negative) relationship between firm-level mark-ups (growth) and size. I confirm the predictions of the model by estimating size-varying price elasticities on unique product-level data from the Census of Manufactures (CM) and structurally estimating mark-ups using plant-level information from the Annual Survey of Manufactures (ASM).
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A Portrait of Firms that Invest in R&D
January 2016
Working Paper Number:
CES-16-41
We focus on the evolution and behavior of firms that invest in research and development (R&D). We build upon the cross-sectional analysis in Foster and Grim (2010) that identified the characteristics of top R&D spending firms and follow up by charting the behavior of these firms over time. Our focus is dynamic in nature as we merge micro-level cross-sectional data from the Survey of Industrial Research and Development (SIRD) and the Business Research & Development and Innovation Survey (BRDIS) with the Longitudinal Business Database (LBD). The result is a panel firm-level data set from 1992 to 2011 that tracks firms' performances as they enter and exit the R&D surveys. Using R&D expenditures to proxy R&D performance, we find the top R&D performing firms in the U.S. across all years to be large, old, multinational enterprises. However, we also find that the composition of R&D performing firms is gradually shifting more towards smaller domestic firms with expenditures being less sensitive to scale effects. We find a high degree of persistence for these firms over time. We chart the history of R&D performing firms and compare them to all firms in the economy and find substantial differences in terms of age, size, firm structure and international activity; these differences persist when looking at future firm outcomes.
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