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The Effects of Low-Valued Transactions on the Quality of U.S. International Export Estimates: 1994-1998
August 2004
Working Paper Number:
CES-04-11
This paper uses data from the U.S. Census Bureau Annual Survey of Manufactures (ASM) to examine the effects that a growth of low-valued transactions likely has on the quality of export estimates provided in the U.S. International Trade in Goods and Services (FT-990) series. These transactions, valued at less than $2,500, do not legally require the filing of export declarations. As a result, they are often not captured in the administrative records data used to construct FT-990 estimates. By comparing industry-level estimates created from the ASM to related FT-990 estimates, this paper estimates that the undercounting of low-valued transactions in the FT-990 export series increases by roughly $30 billion over the period of 1994-1997. It also finds that regression analysis provides little insight into the undercounting issue as results are primarily driven by industries whose contributions to total manufacturing exports are small.
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Productivity Growth Patterns in U.S. Food Manufacturing: Case of Dairy Products Industry
May 2004
Working Paper Number:
CES-04-08
A panel constructed from the Census Bureau's Longitudinal Research Database is used to measure total factor productivity growth at the plant-level and analyzes the multifactor bias of technical change at three-digit product group level containing five different four-digit sub-group categories for the U.S. dairy products industry from 1972 through 1995. In the TFP growth decomposition, analyzing the growth and its components according to the quartile ranks show that scale effect is the most significant element of TFP growth except the plants in the third quartile rank where technical change dominates throughout the time periods. The exogenous input bias results show that throughout the time periods, technical change is 1) capital-using; 2) labor-using after 1980; 3) material-saving except 1981-1985 period; and, 4) energy-using except 1981-1985 and 1991-1995 periods. Plant productivity analysis indicate that less than 50% of the plants in the dairy products industry stay in the same category, indicating considerable movement between productivity rank categories. Investment analysis results indicate that plant-level investments are quite lumpy since a relatively small percent of observations account for a disproportionate share of overall investment. Productivity growth is found to be positively correlated with recent investment spikes for plants with TFP ranking in the middle two quartiles and uncorrelated with plants in the smallest and largest quartiles. Similarly, past TFP growth rates present no significant correlation with future investment spikes for plants in any quartile.
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Productivity Growth Patterns in U.S. Food Manufacturing: Case of Meat Products Industry
March 2004
Working Paper Number:
CES-04-04
A panel constructed from the Census Bureau's Longitudinal Research Database is used to measure total factor productivity growth at the plant-level and analyzes the multifactor bias of technical change for the U.S. meat products industry from 1972 through 1995. For example, addressing TFP growth decomposition for the meat products sub-sector by quartile ranks shows that the technical change effect is the dominant element of TFP growth for the first two quartiles, while the scale effect dominates TFP growth for the higher two quartiles. Throughout the time period, technical change is 1) capital-using; 2) material-saving; 3) labor-using; and, 4) energy-saving and becoming energy-using after 1980. The smaller sized plants are more likely to fluctuate in their productivity rankings; in contrast, large plants are more stable in their productivity rankings. Plant productivity analysis indicate that less than 50% of the plants in the meat industry stay in the same category, indicating considerable movement between productivity rank categories. Investment analysis results strongly indicate that plant-level investments are quite lumpy since a relatively small percent of observations account for a disproportionate share of overall investment. Productivity growth is found to be positively correlated with recent investment spikes for plants with TFP ranking in the middle two quartiles and uncorrelated with firms in the smallest and largest quartiles. Similarly, past TFP growth rates are positively correlated with future investment spikes for firms in the same quartiles. \
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Do Tax Incentives Affect Local Economic Growth? What Mean Impacts Miss in the Analysis of Enterprise Zone Policies
September 2003
Working Paper Number:
CES-03-17
Geographically-targeted tax incentives remain popular initiatives in response to deteriorating economic conditions of urban and industrial areas. This paper exploits the exogenous variations of the U.S. state Enterprise Zone programs to estimate the impact of various incentive features on a number of dimensions of local economic growth. The econometric analysis uses plant level data to sort out growth outcomes into gross flows separately accounted for by new, existing, and vanishing businesses in the target areas. Results offer empirical evidence to support a number of specific policy recommendations and show that the impact of the incentives has more complex dynamics than those revealed by the null mean impact estimates obtained from analyzing net growth outcomes.
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The Survival of Industrial Plants
October 2002
Working Paper Number:
CES-02-25
The study seeks to explain the attrition rate of new manufacturing plants in the United States in terms of three vectors of variables. The first explains how survival of the fittest proceeds through learning by firms (plants) about their own relative efficiency. The second explains how efficiency systematically changes over time and what augments or diminishes it. The third captures the opportunity cost of resources employed in a plant. The model is tested using maximum-likelihood probit analysis with very large samples for successive census years in the 1967-97 period. One sample consists of an unbalanced panel of about three-fourths of a million plants of single and multi-unit firms, or alternatively of about 300,000 plants if only the most reliable data are considered. The second is restricted to the plants of multi-unit firms in the same time span and consists of an unbalanced panel of more than 100,000 plants. The empirical analysis strongly confirms the predictions of the model.
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When Do Firms Shift Production Across States to Avoid Environmental Regulation?
December 2001
Working Paper Number:
CES-01-18
This paper examines whether a firm's allocation of production across its plants responds to the environmental regulation faced by those plants, as measured by differences in stringency across states. We also test whether sensitivity to regulation differs based on differences across firms in compliance behavior and/or differences across states in industry importance and concentration. We use Census data for the paper and oil industries to measure the share of each state in each firm's production during the 1967-1992 period. We use several measures of state environmental stringency and test for interactions between regulatory stringency and three factors: the firm's overall compliance rate, a Herfindahl index of industry concentration in the state, and the industry's share in the state economy. We find significant results for the paper industry: firms allocate smaller production shares to states with stricter regulations. This impact is concentrated among firms with low compliance rates, suggesting that low compliance rates are due to high compliance costs, not low compliance benefits. The interactions between stringency and industry characteristics are less often significant, but suggest that the paper industry is more affected by regulation where it is larger or more concentrated. Our results are weaker for the oil industry, reflecting either less opportunity to shift production across states or a greater impact of environmental regulation on paper mills.
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The Demand for Human Capital: A Microeconomic Approach
December 2001
Working Paper Number:
CES-01-16
We propose a model for explaining the demand for human capital based on a CES production function with human capital as an explicit argument in the function. The resulting factor demand model is tested with data on roughly 6,000 plants from the Census Bureau's Longitudinal Research Database. The results show strong complementarity between physical and human capital. Moreover, the complementarity is greater in high than in low technology industries. The results also show that physical capital of more recent vintage is associated with a higher demand for human capital. While the age of a plant as a reflection of learning-by-doing is positively related to the accumulation of human capital, this relation is more pronounced in low technology industries.
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Diversification Discount or Premium? New Evidence from BITS Establishment-Level Data
December 2001
Working Paper Number:
CES-01-13
This paper examines whether the finding of a diversification discount in U.S. stock markets is only a data artifact. Segment data may give rise to biased estimates of the value effect of diversification because segments are defined inconsistently across firms, and that inconsistency does not occur at random. I use a new establishment-level database that covers the whole U.S. economy (BITS) to construct business units that are more consistently and objectively defined across firms, and thus more comparable. Using a common methodological approach on a sample of firms which exhibit a diversification discount according to segment data, I find that, when BITS data are used, diversified firms actually trade at a significant average premium. The premium is robust to variations in the method, sample, business unit definition, and measures of excess value and diversification used.
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The Life Cycles of Industrial Plants
October 2001
Working Paper Number:
CES-01-10
The paper presents a dynamic programming model with multiple classes of capital goods to explain capital expenditures on existing plants over their lives. The empirical specification shows that the path of capital expenditures is explained by (a) complementarities between old and new capital goods, (b) the age of plants, (c) an index that captures the rate of technical change and (d) the labor intensiveness of a plant when it is newly born. The model is tested with Census data for roughly 6,000 manufacturing plants that were born after 1972.
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Scale Economies and Consolidation in Hog Slaughter
March 2000
Working Paper Number:
CES-00-03
We use establishment based panel data to estimate a cost function which identifies the role of scale economies in hog slaughter consolidation. We find modest by extensive technological scale economies in the 1990s, and they became more important over time. But wages rose sharply with plant size through the 1970s and those wage premiums generated a pecuniary scale diseconomy that largely offset the effects of technological scale economies. The size-wage relation disappeared in the 1980; with growing technological scale economies and disappearing pecuniary diseconomies, large plants realized growing cost advantages over smaller plants, and production shifted to larger plants.
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