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Asset Allocation in Bankruptcy
February 2016
Working Paper Number:
CES-16-13
This paper investigates the consequences of liquidation and reorganization on the allocation and subsequent utilization of assets in bankruptcy. We identify 129,000 bankrupt establishments and construct a novel dataset that tracks the occupancy, employment and wages paid at real estate assets over time. Using the random assignment of judges to bankruptcy cases as a natural experiment that forces some firms into liquidation, we find that even after accounting for reallocation, the long-run utilization of assets of liquidated firms is lower relative to assets of reorganized firms. These effects are concentrated in thin markets with few potential users, in areas with low access to finance, and in areas with low economic growth. The results highlight that different bankruptcy approaches affect asset allocation and utilization particularly when search frictions and financial frictions are present.
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Making a Motivated Manager: A Census Data Investigation into Efficiency Differences Between Franchisee and Franchisor-Owned Restaurants
January 2016
Working Paper Number:
CES-16-54
While there has been significant research on the reasons for franchising, little work has examined the effects of franchising on establishment performance. This paper attempts to fill that gap. We use restricted-access US Census Bureau microdata from the 2007 Census of Retail Trade to examine establishment-level productivity of franchisee- and franchisor-owned restaurants. We do this by employing a two-stage data envelopment analysis model where the first stage uses DEA to measure each establishment's efficiency. The DEA efficiency score is then used as the second-stage dependent variable. The results show a strong and robust effect attributed to franchisee ownership for full service restaurants, but a smaller and insignificant difference for limited service restaurants. We believe the differences in task programability between limited and full service restaurants results in a very different role for managers/franchisees and is the driving factor behind the different results.
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Measuring Cross-Country Differences in Misallocation
January 2016
Working Paper Number:
CES-16-50R
We describe differences between the commonly used version of the U.S. Census of Manufactures available at the RDCs and what establishments themselves report. The originally reported data has substantially more dispersion in measured establishment productivity. Measured allocative efficiency is substantially higher in the cleaned data than the raw data: 4x higher in 2002, 20x in 2007, and 80x in 2012. Many of the important editing strategies at the Census, including industry analysts' manual edits and edits using tax records, are infeasible in non-U.S. datasets. We describe a new Bayesian approach for editing and imputation that can be used across contexts.
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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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Evidence for the Effects of Mergers on Market Power and Efficiency
January 2016
Working Paper Number:
CES-16-43
Study of the impact of mergers and acquisitions (M&As) on productivity and market power has been complicated by the difficulty of separating these two effects. We use newly-developed techniques to separately estimate productivity and markups across a wide range of industries using confidential data from the U.S. Census Bureau. Employing a difference-in-differences framework, we find that M&As are associated with increases in average markups, but find little evidence for effects on plant-level productivity. We also examine whether M&As increase efficiency through reallocation of production to more efficient plants or through reductions in administrative operations, but again find little evidence for these channels, on average. The results are robust to a range of approaches to
address the endogeneity of firms' merger decisions.
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Cogeneration Technology Adoption in the U.S.
January 2016
Working Paper Number:
CES-16-30
Well over half of all electricity generated in recent years in Denmark is through cogeneration. In U.S., however, this number is only roughly eight percent. While both the federal and state governments provided regulatory incentives for more cogeneration adoption, the capacity added in the past five years have been the lowest since late 1970s. My goal is to first understand what are and their relative importance of the factors that drive cogeneration technology adoption, with an emphasis on estimating the elasticity of adoption with respect to relative energy input prices and regulatory factors. Very preliminary results show that with a 1 cent increase in purchased electricity price from 6 cents (roughly current average) to 7 cents per kwh, the likelihood of cogeneration technology adoption goes up by about 0.7-1 percent. Then I will try to address the general equilibrium effect of cogeneration adoption in the electricity generation sector as a whole and potentially estimate some key parameters that the social planner would need to determine the optimal cogeneration investment amount. Partial equilibrium setting does not consider the decrease in investment in the utilities sector when facing competition from the distributed electricity generators, and therefore ignore the effects from the change in equilibrium price of electricity. The competitive market equilibrium setting does not consider the externality in the reduction of CO2 emissions, and leads to socially sub-optimal investment in cogeneration. If we were to achieve the national goal to increase cogeneration capacity half of the current capacity by 2020, the US Department of Energy (DOE) estimated an annual reduction of 150 million metric tons of CO2 annually ' equivalent to the emissions from over 25 million cars. This is about five times the annual carbon reduction from deregulation and consolidation in the US nuclear power industry (Davis, Wolfram 2012). Although the DOE estimates could be an overly optimistic estimate, it nonetheless suggests the large potential in the adoption of cogeneration technology.
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Energy Prices, Pass-Through, and Incidence in U.S. Manufacturing*
January 2016
Working Paper Number:
CES-16-27
This paper studies how increases in energy input costs for production are split between consumers and producers via changes in product prices (i.e., pass-through). We show that in markets characterized by imperfect competition, marginal cost pass-through, a demand elasticity, and a price-cost markup are suffcient to characterize the relative change in welfare between producers and consumers due to a change in input costs. We and that increases in energy prices lead to higher plant-level marginal costs and output prices but lower markups. This suggests that marginal cost pass-through is incomplete, with estimates centered around 0.7. Our confidence intervals reject both zero pass-through and complete pass-through. We and heterogeneous incidence of changes in input prices across industries, with consumers bearing a smaller share of the burden than standards methods suggest.
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The Impact of Bank Credit on Labor Reallocation and Aggregate Industry Productivity
January 2016
Working Paper Number:
CES-16-26
Using a difference-in-difference methodology, we find that the state-level deregulation of local U.S. banking markets leads to significant increases in the reallocation of labor within local industries towards small firms with higher marginal products of labor. Using plant-level data, we propose and examine an approach that quantifies the industry productivity gains from labor reallocation and find that these gains are economically important. Our analysis suggests that labor reallocation is a significant channel through which local banking markets affect the aggregate productivity and performance of local industries.
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Data in Action: Data-Driven Decision Making in U.S. Manufacturing
January 2016
Working Paper Number:
CES-16-06
Manufacturing in America has become significantly more data-intensive. We investigate the adoption, performance effects and organizational complementarities of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for 2005 and 2010, we observe the extent to which manufacturing firms track and use data to guide decision making, as well as their investments in information technology (IT) and the use of other structured management practices. Examining a representative sample of over 18,000 plans, we find that adoption of DDD is earlier and more prevalent among larger, older plants belonging to multi-unit firms. Smaller single-establishment firms adopt later but have a higher correlation with performance than similar non-adopters. Using a fixed-effects estimator, we find the average value-added for later DDD adopters to be 3% greater than non-adopters, controlling for other inputs to production. This effect is distinct from that associated with IT and other structured management practices and is concentrated among single-unit firms. Performance improves after plants adopt DDD, but not before ' consistent with a causal relationship. However, DDD-related performance differentials decrease over time for early and late adopters, consistent with firm learning and development of organizational complementarities. Formal complementarity tests suggest that DDD and high levels of IT capital reinforce each other, as do DDD and skilled workers. For some industries, the benefits of DDD adoption appear to be greater for plants that delegate some decision making to frontline workers.
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Plant Exit and U.S. Imports from Low-Wage Countries
January 2016
Working Paper Number:
CES-16-02
Over the past twenty years, imports to the U.S. from low-wage countries have increased dramatically. In this paper we examine how low-wage country import competition in the U.S. influences the probability of manufacturing establishment closure. Confidential data from the U.S. Bureau of the Census are used to track all manufacturing establishments between 1992 and 2007. These data are linked to measures of import competition built from individual trade transactions. Controlling for a variety of plant and firm covariates, we show that low-wage import competition has played a significant role in manufacturing plant exit. Analysis employs fixed effects panel models running across three periods: the first plant-level panels examining trade and exit for the U.S. economy. Our results appear robust to concerns regarding endogeneity.
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