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Research Funding and Regional Economies
January 2016
Working Paper Number:
CES-16-32
Public support of research typically relies on the notion that universities are engines of economic development, and that university research is a primary driver of high wage localized economic activity. Yet the evidence supporting that notion is based on aggregate descriptive data, rather than detailed links at the level of individual transactions. Here we use new micro-data from three countries - France, Spain and the United States - to examine one mechanism whereby such economic activity is generated, namely purchases from regional businesses. We show that grant funds are more likely to be expended at businesses physically closer to universities than at those farther away. In addition, if a vendor has been a supplier to a grant once, that vendor is subsequently more likely to be a vendor on the same or related grants. Firms behave in a way that is consistent with the notion that propinquity is good for business; if a firm supplies a research grant at a university in a given year it is more likely to open an establishment near that university in subsequent years than other firms.
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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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Where Has All the Skewness Gone? The Decline in High-Growth (Young) Firms in the U.S.
November 2015
Working Paper Number:
CES-15-43
The pace of business dynamism and entrepreneurship in the U.S. has declined over recent decades. We show that the character of that decline changed around 2000. Since 2000 the decline in dynamism and entrepreneurship has been accompanied by a decline in high-growth young firms. Prior research has shown that the sustained contribution of business startups to job creation stems from a relatively small fraction of high-growth young firms. The presence of these high-growth young firms contributes to a highly (positively) skewed firm growth rate distribution. In 1999, a firm at the 90th percentile of the employment growth rate distribution grew about 31 percent faster than the median firm. Moreover, the 90-50 differential was 16 percent larger than the 50-10 differential reflecting the positive skewness of the employment growth rate distribution. We show that the shape of the firm employment growth distribution changes substantially in the post-2000 period. By 2007, the 90-50 differential was only 4 percent larger than the 50-10, and it continued to exhibit a trend decline through 2011. The reflects a sharp drop in the 90th percentile of the growth rate distribution accounted for by the declining share of young firms and the declining propensity for young firms to be high-growth firms.
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Allocation of Company Research and Development Expenditures to Industries Using a Tobit Model
November 2015
Working Paper Number:
CES-15-42
This paper uses Census microdata and a regression-based approach to assign multi-division firms' pre-2008 Research and Development (R&D) expenditures to more than one industry. Since multi-division firms conduct R&D in more than one industry, assigning R&D to corresponding industries provides a more accurate representation of where R&D actually takes place and provides a consistent time-series with the National Science Foundation R&D by line of business information. Firm R&D is allocated to industries on the basis of observed industry payroll, as befits the historic importance of payroll in Census assignments of firms to industry. The results demonstrate that the method of assigning R&D to industries on the basis of payroll works well in earlier years, but becomes less effective over time as firms outsource their manufacturing function.
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Collateral Values and Corporate Employment
September 2015
Working Paper Number:
CES-15-30R
We examine the impact of real estate collateral values on corporate employment. Our empirical strategy exploits regional variation in local real estate price growth, firm-level data on real estate holdings, as well as establishment-level data on employment and the location of firms' operations from the U.S. Census Bureau. Over the period from 1993 until 2006, we show that a typical U.S. publicly-traded firm increases employment expenditures by $0.10 per $1 increase in collateral. We show this additional hiring is funded through debt issues and the effects are stronger for firms likely to be financially constrained. These firms increase employment at establishments outside of their core industry focus and away from the location of real estate holdings, leading to regional spillover effects. We document how shocks to collateral values influence labor allocation within firms and how these effects show up in the aggregate.
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The Evolution of National Retail Chains: How We Got Here
March 2015
Working Paper Number:
CES-15-10
The growth and dominance of large, national chains is a ubiquitous feature of the US retail sector. The recent literature has documented the rise of these chains and the contribution of this structural change to productivity growth in the retail trade sector. Recent studies have also shown that the establishments of large, national chains are both more productive and more stable than the establishments of single-unit firms they are displacing. We build on this literature by following the paths of retail firms and establishments from 1977 to 2007 using establishment- and firm-level data from the Census of Retail Trade and the Longitudinal Business Database. We dissect the shift towards large, national chains on several margins. We explore the differences in entry and exit as well as job creation and destruction patterns at the establishment and firm level. We find that over this period there are consistently high rates of entry and job creation by the establishments of single-unit firms and large, national firms, but net growth is much higher for the large, national firms. Underlying this difference is far lower exit and job destruction rates of establishments from national chains. Thus, the story of the increased dominance of national chains is not so much due to a declining entry rate of new single-unit firms but rather the much greater stability of the new establishments belonging to national chains relative to their single-unit counterparts. Given the increasing dominant role of these chains, we dissect the paths to success of national chains, including an analysis of four key industries in retail trade. We find dramatically different patterns across industries. In General Merchandise, the rise in national chains is dominated by slow but gradual growth of firms into national chain status. In contrast, in Apparel, which has become much more dominated by national chains in recent years, firms that quickly became national chains play a much greater role.
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Multiregional Firms and Region Switching in the US Manufacturing Sector
January 2015
Working Paper Number:
CES-15-22
This paper uses data on US manufacturing firms to study a new extensive margin, the reallocation of resources that takes place within surviving firms as they open and close establishments in different regions. To motivate the empirical analysis, I extend existing models of industry dynamics to include production-location decisions within firms. The empirical results provide support for the mechanisms emphasized by the theoretical model. In the data, only about 3 percent of firms make the same product in more than one region, but these multiregional firms are more productive on average
compared to single-region firms, and they account for about two-thirds of output. The results also show that "region-switching" is pervasive among multiregional firms, is correlated with changes in firm characteristics, and leads to a more efficient allocation of resources within firms.
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RECOVERING THE ITEM-LEVEL EDIT AND IMPUTATION FLAGS IN THE 1977-1997 CENSUSES OF MANUFACTURES
September 2014
Working Paper Number:
CES-14-37
As part of processing the Census of Manufactures, the Census Bureau edits some data items and imputes for missing data and some data that is deemed erroneous. Until recently it was difficult for researchers using the plant-level microdata to determine which data items were changed or imputed during the editing and imputation process, because the edit/imputation processing flags were not available to researchers. This paper describes the process of reconstructing the edit/imputation flags for variables in the 1977, 1982, 1987, 1992, and 1997 Censuses of Manufactures using recently recovered Census Bureau files. Thepaper also reports summary statistics for the percentage of cases that are imputed for key variables. Excluding plants with fewer than 5 employees, imputation rates for several key variables range from 8% to 54% for the manufacturing sector as a whole, and from 1% to 72% at the 2-digit SIC industry level.
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None
September 2014
Working Paper Number:
CES-14-35
This paper presents a novel empirical study of innovation practices of U.S. companies and their relation to productivity levels using new business micro data from the Business Research and Development and Innovation Survey (BRDIS) for the years 2008-2011. We use factor analysis to reduce a set of inputs and outputs of innovation activities into four latent unobserved innovation modes or practices. Companies are grouped according to their scores across the four factors to see that in large, small and medium companies more than one mode of innovation practices prevails. The next step in the analysis links different types of innovation practices to levels of productivity using regression analysis. The innovation modes have a statistically significant positive relation with the level of productivity. The paper demonstrates the possibility of taking into account the multidimensionality of innovation without the use of composite indicators.
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HOW IMPORTANT ARE SECTORAL SHOCKS
September 2014
Working Paper Number:
CES-14-31
I quantify the contribution of sectoral shocks to business cycle fluctuations in aggregate output. I develop a multi-industry general equilibrium model in which each industry employs the material and capital goods produced by other sectors, and then estimate this model using data on U.S. industries sales, output prices, and input choices. Maximum likelihood estimates indicate that industry-specific shocks account for nearly two-thirds of the volatility of aggregate output, substantially larger than previously assessed. Identification of the relative importance of industry-specific shocks comes primarily from data on industries intermediate input purchases, data that earlier estimations of multi-industry models have ignored.
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