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Comparison of Survey, Federal, and Commercial Address Data Quality
June 2014
Working Paper Number:
carra-2014-06
This report summarizes matching of survey, commercial, and administrative records housing units to the Census Bureau Master Address File (MAF). We document overall MAF match rates in each data set and evaluate differences in match rates across a variety of housing characteristics. Results show that over 90 percent of records in survey data from the American Housing Survey (AHS) match to the MAF. Commercial data from CoreLogic matches at much lower rates, in part due to missing address information and poor match rates for multi-unit buildings. MAF match rates for administrative records from the Department of Housing and Urban Development are also high, and open the possibility of using this information in surveys such as the AHS.
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Micro Data and the Macro Elasticity of Substitution
March 2012
Working Paper Number:
CES-12-05
We estimate the aggregate elasticity of substitution between capital and labor in the US manufacturing sector. We show that the aggregate elasticity of substitution can be expressed as a simple function of plant level structural parameters and sufficient statistics of the distribution of plant input cost shares. We then use plant level data from the Census of Manufactures to construct a local elasticity of substitution at various levels of aggregation. Our approach does not assume the existence of a stable aggregate production function, as we build up our estimate from the cross section of plants at a point in time. Accounting for substitution within and across plants, we find that the aggregate elasticity is substantially below unity at approximately 0.7. Lastly we assess the sources of the bias of aggregate technical change from 1987 to 1997. We find that the labor augmenting character of aggregate technical change is due almost exclusively to labor augmenting productivity growth at the plant level rather than relative growth in capital intensive plants.
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A Guide to the MEPS-IC Government List Sample Microdata
September 2011
Working Paper Number:
CES-11-27
The Medical Expenditure Panel Survey-Insurance Component (MEPS-IC) is conducted to provide nationally representative estimates on employer sponsored health insurance. MEPSIC data are collected from private sector employers, as well as state and local governments. While similar information is gathered from these two sectors, differences in the survey process exist. The goal of this paper is to provide details on the public sector including types of state and local government employers, sample design, general information on the data collected in the MEPS-IC, and additional sources of information.
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Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation
April 2011
Working Paper Number:
CES-11-14
Benefit receipt in major household surveys is often underreported. This misreporting leads to biased estimates of the economic circumstances of disadvantaged populations, program takeup, and the distributional effects of government programs, and other program effects. We use administrative data on Food Stamp Program (FSP) participation matched to American Community Survey (ACS) and Current Population Survey (CPS) household data. We show that nearly thirty-five percent of true recipient households do not report receipt in the ACS and fifty percent do not report receipt in the CPS. Misreporting, both false negatives and false positives, varies with individual characteristics, leading to complicated biases in FSP analyses. We then directly examine the determinants of program receipt using our combined administrative and survey data. The combined data allow us to examine accurate participation using individual characteristics missing in administrative data. Our results differ from conventional estimates using only survey data, as such estimates understate participation by single parents, non-whites, low income households, and other groups. To evaluate the use of Census Bureau imputed ACS and CPS data, we also examine whether our estimates using survey data alone are closer to those using the accurate combined data when imputed survey observations are excluded. Interestingly, excluding the imputed observations leads to worse ACS estimates, but has less effect on the CPS estimates.
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Beyond Cobb-Douglas: Estimation of a CES Production Function with Factor Augmenting Technology
February 2011
Working Paper Number:
CES-11-05
Both the recent literature on production function identification and a considerable body of other empirical work on firm expansion assume a Cobb-Douglas production function. Under this assumption, all technical differences are Hicks neutral. I provide evidence from US manufacturing plants against Cobb-Douglas and present an alternative production function that better fits the data. A Cobb Douglas production function has two empirical implications that I show do not hold in the data: a constant cost share of capital and strong comovement in labor productivity and capital productivity (revenue per unit of capital). Within four digit industries, differences in cost shares of capital are persistent over time. Both the capital share and labor productivity increase with revenue, but capital productivity does not. A CES production function with labor augmenting differences and an elasticity of substitution between labor and capital less than one can account for these facts. To identify the labor capital elasticity, I use variation in wages across local labor markets. Since the capital cost to labor cost ratio falls with local area wages, I strongly reject Cobb-Douglas: capital and labor are complements. Now productivity differences are no longer neutral, which has implications on how productivity affects firms' decisions to expand or contract. Non neutral technical improvements will result in higher stocks of capital but not necessarily more hiring of labor. Specifying the correct form of the production function is more generally important for empirical work, as I demonstrate by applying my methodology to address questions of misallocation of capital.
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Plant-Level Productivity and Imputation of Missing Data in the Census of Manufactures
January 2011
Working Paper Number:
CES-11-02
In the U.S. Census of Manufactures, the Census Bureau imputes missing values using a combination of mean imputation, ratio imputation, and conditional mean imputation. It is wellknown that imputations based on these methods can result in underestimation of variability and potential bias in multivariate inferences. We show that this appears to be the case for the existing imputations in the Census of Manufactures. We then present an alternative strategy for handling the missing data based on multiple imputation. Specifically, we impute missing values via sequences of classification and regression trees, which offer a computationally straightforward and flexible approach for semi-automatic, large-scale multiple imputation. We also present an approach to evaluating these imputations based on posterior predictive checks. We use the multiple imputations, and the imputations currently employed by the Census Bureau, to estimate production function parameters and productivity dispersions. The results suggest that the two approaches provide quite different answers about productivity.
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Why Do Firms Own Production Chains?
September 2009
Working Paper Number:
CES-09-31
Many firms own links of production chains--i.e., they own both upstream and downstream plants in vertically linked industries. We use broad-based yet detailed data from the economy's goods-producing sectors to investigate the reasons for such vertical ownership. It does not appear that vertical ownership is usually used to facilitate transfers of goods along the production chain, as is often presumed. Shipments from firms' upstream units to their downstream units are surprisingly low, relative to both the firms' total upstream production and their downstream needs. Roughly one-third of upstream plants report no shipments to their firms' downstream units. Half ship less than three percent of their output internally. We do find that manufacturing plants in vertical ownership structures have high measures of 'type' (productivity, size, and capital intensity). These patterns primarily reflect selective sorting of high plant types into large firms; once we account for firm size, vertical structure per se matters much less. We propose an alternative explanation for vertical ownership that is consistent with these results. Namely, that rather than moderating goods transfers down production chains, it instead allows more efficient transfers of intangible inputs (e.g., managerial oversight) within the firm. We document some suggestive evidence of this mechanism.
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Misallocation and Manufacturing TFP in China and India
February 2009
Working Paper Number:
CES-09-04
Resource misallocation can lower aggregate total factor productivity (TFP). We use micro data on manufacturing establishments to quantify the potential extent of misallocation in China and India compared to the U.S. Compared to the U.S., we measure sizable gaps in marginal products of labor and capital across plants within narrowly-defined industries in China and India. When capital and labor are hypothetically reallocated to equalize marginal products to the extent observed in the U.S., we calculate manufacturing TFP gains of 30-50% in China and 40-60% in India.
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Firm Structure, Multinationals, and Manufacturing Plant Deaths
October 2005
Working Paper Number:
CES-05-18
Plant shutdowns shape industry and aggregate productivity paths and play a major role in the dynamics of employment and industrial restructuring. Plant closures in the U.S. manufacturing sector account for more than half of gross job destruction. While multi-plant firms and multinationals dominate U.S. manufacturing, theoretical and empirical work has largely ignored the role of firms in the plant shutdown decision. This paper examines the effects of firm structure on manufacturing plant closures. Using U.S. data, we find that plants belonging to multi-plant firms are less likely to exit. Similarly, plants owned by U.S. multinationals are less likely to close. However, the superior survival chances are due to the characteristics of the plants themselves rather than the nature of the firms. Controlling for plant and industry attributes that reduce the probability of death, we find that plants owned by multi-unit firms and U.S. multinationals are much more likely to close. A recent change in ownership also increases the chances that a plant will be closed.
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Market Structure and Productivity: A Concrete Example
June 2001
Working Paper Number:
CES-01-06
This paper shows that imperfect output substitutability explains part of the observed persistent plant-level productivity dispersion. Specifically, as substitutability in a market increases, the market's productivity distribution exhibits falling dispersion and higher central tendency. The proposed mechanism behind this result is truncation of the distribution from below as increased substitutability shifts demand to lower-cost plants and drives inefficient plants out of business. In a case study of the ready-mixed concrete industry, I examine the impact of one manifestation of this effect, driven by geographic market segmentation resulting from transport costs. A theoretical foundation is presented characterizing how differences in the density of local demand impact the number of producers and the ability of customers to choose between suppliers, and through this, the equilibrium productivity and output levels across regions. I also introduce a new method of obtaining plant-level productivity estimates that is well suited to this application and avoids potential shortfalls of commonly used procedures. I use these estimates to empirically test the presented theory, and the results support the predictions of the model. Local demand density has a significant influence on the shape of plant-level productivity distributions, and accounts for part of the observed intra-industry variation in productivity, both between and within given market areas.
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