This paper estimates long-run demand functions for production workers, production worker hours, and nonproduction workers using micro data from U.S. establishment surveys. The paper focuses on estimation of the wage and output elasticities of labor demand using data on over 41,000 U.S. manufacturing plants in 1975 and more than 30,000 plants in 1981. Particular attention is focused on the problems of unobserved producer heterogeneity and measurement errors in output that can affect labor demand estimates based on establishment survey data. The empirical results reveal that OLS estimates of both the own-price elasticity and the output elasticity of labor demand are biased downward as a result of unobserved heterogeneity. Differencing the data as a solution to this problem greatly exaggerates measurement error in the output coefficients. The use of capital stocks as instrumental variables to correct for measurement error in output significantly alters output elasticities in the expected direction but has no systematic effect on own-price elasticities. All of these patterns are found in estimates that pool establishment data across industries and in industry-specific regressions for the vast majority of industries. Estimates of the output elasticity of labor demand indicate that there are slight increasing returns for production workers and production hours, with a pooled data estimate of .92. The estimate for nonproduction workers in .98. The variation in the output elasticities across industries is fairly small. Estimates of the own-price elasticity vary more substantially with the year, type of differencing used, and industry. They average -.50 for production hours, -.41 for production workers, and -.44 for nonproduction workers. The price elasticities vary widely across manufacturing industries: the interquartile range for the industry estimates is approximately .40.
-
The Effects of Outsourcing on the Elasticity of Labor Demand
March 2006
Working Paper Number:
CES-06-07
In this paper, I focus on the effects of outsourcing on conditional labor demand elasticities. I begin by developing a model of outsourcing that formalizes this relationship. I show that the increased possibility of outsourcing (modeled as a decline in foreign intermediate input prices and an increase in the elasticity of substitution between foreign and domestic intermediate inputs) should increase labor demand elasticities. I also show that, a decline in the share of unskilled labor, due either to skill biased technological change or to movement of unskilled labor intensive stages abroad, can work in the opposite direction and reverse the increasing trend in elasticities. I then test the predictions of the model using the U.S. Census Bureau's Longitudinal Research Database (LRD). The instrumental variable approach used in the estimation of labor demand equations is the main methodological contribution of this paper. I directly address the endogeneity of wages in the labor demand equation by using average nonmanufacturing wages for each location and year as an instrumental variable for the plant-level wages in the manufacturing sector. The results support the main predictions of my model. U.S. manufacturing plants operating in industries that heavily outsource experienced an increase in their conditional labor demand elasticities during the 1980-1992 period. After 1992 elasticities began to decrease in outsourcing industries. This finding is consistent with the model which suggests that a decline in the share of unskilled labor in total cost could result in such a decrease in labor demand elasticities, precisely when the level of outsourcing is high. Estimates at the two-digit industry level provide further evidence in support of the hypothesis that heavily outsourcing industries experience greater increases in their elasticities.
View Full
Paper PDF
-
Health Insurance and Productivity: Evidence from the Manufacturing Sector
September 2009
Working Paper Number:
CES-09-27
This paper examines the relationship between employer-sponsored offers of health insurance and establishments' labor productivity. Our empirical work is based on unique plant level data that links the 1997 and 2002 Medical Expenditure Panel Survey-Insurance Component with the 1992, 1997, and 2002 Census of Manufactures. These linked data provide information on employer-provided insurance and productivity. We find that health insurance offers are positively associated with levels of establishments' labor productivity. These findings hold for all manufacturers as well as those with fewer than 100 employees. Our preliminary results also show a drop in health care costs from the 75th to the 25th percentile would increase the probability of a plant offering insurance by 1.5-2.0 percent in both 1997 and 2002. The results from this paper provide encouraging and new empirical evidence on the benefits employers may reap by offering health insurance to workers.
View Full
Paper PDF
-
The Importance of Reallocations in Cyclical Productivity and Returns to Scale: Evidence from Plant-Level Data
March 2007
Working Paper Number:
CES-07-05
This paper provides new evidence that estimates based on aggregate data will understate the true procyclicality of total factor productivity. I examine plant-level data and show that some industries experience countercyclical reallocations of output shares among firms at different points in the business cycle, so that during recessions, less productive firms produce less of the total output, but during expansions they produce more. These reallocations cause overall productivity to rise during recessions, and do not reflect the actual path of productivity of a representative firm over the course of the business cycle. Such an effect (sometimes called the cleansing effect of recessions) may also bias aggregate estimates of returns to scale and help explain why decreasing returns to scale are found at the industry-level data.
View Full
Paper PDF
-
Output Price And Markup Dispersion In Micro Data: The Roles Of Producer And Heterogeneity And Noise
August 1997
Working Paper Number:
CES-97-10
This paper provides empirical evidence on the extent of producer heterogeneity in the output market by analyzing output price and price-marginal cost markups at the plant level for thirteen homogeneous manufactured goods. It relies on micro data from the U.S. Census of Manufactures over the 1963-1987 period. The amount of price heterogeneity varies substantially across products. Over time, plant transition patterns indicate more persistence in the pricing of individual plants than would be generated by purely random movements. High-price and low-price plants remain in the same part of the price distribution with high frequency, suggesting that underlying time-invariant structural factors contribute to the price dispersion. For all but two products, large producers have lower output prices. Marginal cost and the markups are estimated for each plant. The markup remains unchanged or increases with plant size for all but four of the products and declining marginal costs play an important role in generating this pattern. The lower production costs for large producers are, at least partially, passed on to purchasers as lower output prices. Plants with the highest and lowest markups tend to remain so over time, although overall the persistence in markups is less than for output price, suggesting a larger role for idiosyncratic shocks in generating markup variation.
View Full
Paper PDF
-
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.
View Full
Paper PDF
-
Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.
View Full
Paper PDF
-
Energy Intensity, Electricity Consumption, and Advanced Manufacturing Technology Usage
July 1993
Working Paper Number:
CES-93-09
This paper reports on the relationship between the usage of advanced manufacturing technologies (AMTs) and energy consumption patterns in manufacturing plants. Using data from the Survey of Manufacturing Technology and the 1987 Census of Manufactures, we model the energy intensity and the electricity intensity of plants as functions of AMT usage and plant age. The main findings are that plants which utilize AMTs are less energy intensive than plants not using AMTs but consume proportionately more electricity as a fuel source. Additionally, older plants are generally more energy intensive and rely on fossil fuels to a greater extent than younger plants.
View Full
Paper PDF
-
Manufacturing Plants' Use of Temporary Workers: An Analysis Using Census Micro Data
December 2008
Working Paper Number:
CES-08-40
Using plant-level data from the Plant Capacity Utilization (PCU) Survey, we examine how manufacturing plants' use of temporary workers is associated with the nature of their output fluctuations and other plant characteristics. We find that plants tend to hire temporary workers when their output can be expected to fall, a result consistent with the notion that firms use temporary workers to reduce costs associated with dismissing permanent employees. In addition, we find that plants whose future output levels are subject to greater uncertainty tend to use more temporary workers. We also examine the effects of wage and benefit levels for permanent workers, unionization rates, turnover rates, seasonal factors, and plant size and age on the use of temporary workers; based on our results, we discuss various views of why firms use temporary workers.
View Full
Paper PDF
-
Entrant Experience and Plant Exit
August 2004
Working Paper Number:
CES-04-12
Producers entering a market can differ widely in their prior production experience, ranging from none to extensive experience in related geographic or product markets. In this paper, we quantify the nature of prior plant and firm experience for entrants into a market and measure its effect on the plant's decision to exit the market. Using plant-level data for seven regional manufacturing industries in the U.S., we find that a producer's experience at the time it enters a market plays an important role in the subsequent exit decision, affecting both the overall probability of exit and the method of exit. After controlling for observable plant and market profit determinants, there remain systematic differences in failure patterns across three groups of plants distinguished by their prior experience: de novo entrants, experienced plants that enter by diversifying their product mix, and new plants owned by experienced firms. The results indicate that the exit decision cannot be treated as determined solely by current and future plant, firm, and market conditions, but that the plant's history plays an important independent role in conditioning the likelihood of survival.
View Full
Paper PDF
-
Using the Survey of Plant Capacity to Measure Capital Utilization
July 2011
Working Paper Number:
CES-11-19
Most capital in the United States is idle much of the time. By some measures, the average workweek of capital in U.S. manufacturing is as low as 55 hours per 168 hour week. The level and variability of capital utilization has important implications for understanding both the level of production and its cyclical fluctuations. This paper investigates a number of issues relating to aggregation of capital utilization measures from the Survey of Plant Capacity and makes recommendations on expanding and improving the published statistics deriving from the Survey of Plant Capacity. The paper documents a number of facts about properties of capital utilization. First, after growing for decades, capital utilization started to fall in mid 1990s. Second, capital utilization is a useful predictor of changes in capacity utilization and other factors of production. Third, adjustment of productivity measures for variable capital utilization improves statistical and economic properties of these measures. Fourth, the paper constructs weights to aggregate firm level capital utilization rates to industry and economy level, which is the major enhancement to available data.
View Full
Paper PDF