Papers Containing Tag(s): 'Annual Survey of Manufactures'
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Viewing papers 231 through 240 of 246
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Working PaperA Comparison of Job Creation and Job Destruction in Canada and the United States
May 1994
Working Paper Number:
CES-94-02
In recent years a growing number of countries have constructed data series on job creation and job destruction using establishment-level data sets. This paper provides a description and detailed comparison of these new data series for the United States and Canada. First, the Canadian and United States industry-level job creation and destruction data are remarkably similar. Industries with high (low) job creation in the US are evidenced by high (low) job creation in Canada. The same is true for job destruction. In addition, the overall magnitude of gross job flows in the two countries is comparable. Second, the time-series patterns of creation and destruction are qualitatively similar but do differ in a number of important respects. In both countries, job destruction is much more cyclically volatile than job creation. This cyclical asymmetry is, however, more pronounced in the United States. The paper finishes with a characterization of the job flow patterns using a modified Blanchard and Diamond (1992) model.View Full Paper PDF
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Working PaperThe Long-Run Demand for Labor: Estimates From Census Establishment Data
September 1993
Working Paper Number:
CES-93-13
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.View Full Paper PDF
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Working PaperCONSTRUCTION OF REGIONAL INPUT-OUTPUT TABLES FROM ESTABLISHMENT-LEVEL MICRODATA: ILLINOIS, 1982
August 1993
Working Paper Number:
CES-93-12
This paper presents a new method for use in the construction of hybrid regional input-output tables, based primarily on individual returns from the Census of Manufactures. Using this method, input- output tables can be completed at a fraction of the cost and time involved in the completion of a full survey table. Special attention is paid to secondary production, a problem often ignored by input-output analysts. A new method to handle secondary production is presented. The method reallocates the amount of secondary production and its associated inputs, on an establishment basis, based on the assumption that the input structure for any given commodity is determined not by the industry in which the commodity was produced, but by the commodity itself -- the commodity-based technology assumption. A biproportional adjustment technique is used to perform the reallocations.View Full Paper PDF
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Working PaperEnvironmental Regulation And Manufacturing Productivity At The Plant Level
March 1993
Working Paper Number:
CES-93-06
This paper presents results for an analysis of plant-level data from three manufacturing industries (paper, oil, and steel). We combine productivity data from the Longitudinal Research Database ( LRD ) with pollution abatement expenditures from the Census Bureau's Pollution Abatement Cost and Expenditures (PACE) survey, as well as regulatory measures taken from datasets maintained by the Environmental Protection Agency. We use data from 1979 to 1985, considering both labor and total factor productivity, both levels and growth rates, and both annual measures and averages over the period. We find a strong connection between regulation and productivity when regulation is measured by compliance costs. More regulated plants have significantly lower productivity levels and slower productivity growth rates than less regulated plants. The magnitude of the impacts are larger than expected: a $1 increase in compliance costs appears to reduce TFP by the equivalent of $3 to $4. Thus, commonly used methods of calculating the impact of regulation on productivity are substantially underestimated. These results are generally consistent across industries and for different estimation methods. Our other measures of regulation (compliance status, enforcement activity, and emissions) show much less consistent results. Higher enforcement, lower compliance, and higher emissions are generally associated with lower productivity levels and slower productivity growth, but the coefficients are rarely significant.View Full Paper PDF
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Working PaperManufacturing Establishments Reclassified Into New Industries: The Effect Of Survey Design Rules
November 1992
Working Paper Number:
CES-92-14
Establishment reclassification occurs when an establishment classified in one industry in one year is reclassified into another industry in another year. Because of survey design rules at the Census Bureau these reclassifications occur systematically over time, and affect the industry-level time series of output and employment. The evidence shows that reclassified establishments occur most often in two distinct years over the life of a sample panel. Switches are not only numerous in these years, they also contribute significantly to measured industry change in industry output and employment. The problem is that reclassifications are not necessarily processed in the year that they occur. The survey rules restrict most change to certain years. The effect of these rules is evidenced by looking at the variance across industry growth rates which increases greatly in these two years. Whatever the reason for reclassifying an establishment, the way the switches are processed raises the possibility of measurement errors in the industry level statistics. Researchers and policymakers relying upon observations in annual changes in industry statistics should be aware of these systematic discontinuities, discrepancies and potential data distortions.View Full Paper PDF
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Working PaperEstimating Capital Efficiency Schedules Within Production Functions
May 1992
Working Paper Number:
CES-92-04
The appropriate method for aggregating capital goods across vintages to produce a single capital stock measure has long been a contentious issue, and the literature covering this topic is quite extensive. This paper presents a methodology that estimates efficiency schedules within a production function, allowing the data to reveal how the efficiency of capital goods evolve as they age. Specifically we insert a parameterized investment stream into the position of a capital variable in a production function, and then estimate the parameters of the production function simultaneously with the parameters of the investment stream. Plant level panel data for a select group of steel plants employing a common technology are used to estimate the model. Our primary finding is that when using a simple Cobb Douglas production function, the estimated efficiency schedules appear to follow a geometric pattern, which is consistent with the estimates of economic depreciation of Hulten and Wykoff (1981). Results from more flexible functional forms produced much less precise and unreliable estimates.View Full Paper PDF
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Working PaperThe Dynamics Of Productivity In The Telecommunications Equipment Industry
February 1992
Working Paper Number:
CES-92-02
Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. We estimate the parameters of a production function for the equipment industry and then use those estimates to analyze the evolution of plant-level productivity over this period. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Since firms choices on whether to liquidate and the on the quantities of inputs demanded should they continue depend on their productivity, we develop an estimation algorithm that takes into account the relationship between productivity on the one hand, and both input demand and survival on the other. The algorithm is guided by a dynamic equilibrium model that generates the exit and input demand equations needed to correct for the simultaneity and selection problems. A fully parametric estimation algorithm based on these decision rules would be both computationally burdensome and require a host of auxiliary assumptions. So we develop a semiparametric technique which is both consistent with a quite general version of the theoretical framework and easy to use. The algorithm produces markedly different estimates of both production function parameters and of productivity movements than traditional estimation procedures. We find an increase in the rate of industry productivity growth after deregulation. This in spite of the fact that there was no increase in the average of the plants' rates of productivity growth, and there was actually a fall in our index of the efficiency of the allocation of variable factors conditional on the existing distribution of fixed factors. Deregulation was, however, followed by a reallocation of capital towards more productive establishments (by a down sizing, often shutdown, of unproductive plants and by a disproportionate growth of productive establishments) which more than offset the other factors' negative impacts on aggregate productivity.View Full Paper PDF
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Working PaperThe Influence Of Location On Productivity: Manufacturing Technology In Rural And Urban Areas
December 1991
Working Paper Number:
CES-91-10
Policies to counter the growing discrepancy between economic opportunities in rural and urban areas have focused predominantly on expanding manufacturing in rural areas. Fundamental to the design of these strategies are the relative costs of production and productivity of manufacturing in rural and urban areas. This study aims to develop information that can be used to assess the productivity of manufacturing in rural and urban areas. Production functions are estimated in the meat products and household furniture industries to investigate selected aspects of the effect of rural, small urban, and metropolitan location on productivity. The results show that the effect of location on productivity varies with industry, size, and the timing of the entry of the establishment into the industry. While the analysis is specific to two industries, it suggests that development policies targeting manufacturing can be made more effective by focusing on industries and plants with characteristics that predispose them to the locations being supported.View Full Paper PDF
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Working PaperMultiple Classification Systems For Economic Data: Can A Thousand Flowers Bloom? And Should They?
December 1991
Working Paper Number:
CES-91-08
The principle that the statistical system should provide flexibility-- possibilities for generating multiple groupings of data to satisfy multiple objectives--if it is to satisfy users is universally accepted. Yet in practice, this goal has not been achieved. This paper discusses the feasibility of providing flexibility in the statistical system to accommodate multiple uses of the industrial data now primarily examined within the Standard Industrial Classification (SIC) system. In one sense, the question of feasibility is almost trivial. With today's computer technology, vast amounts of data can be manipulated and stored at very low cost. Reconfigurations of the basic data are very inexpensive compared to the cost of collecting the data. Flexibility in the statistical system implies more than the technical ability to regroup data. It requires that the basic data are sufficiently detailed to support user needs and are processed and maintained in a fashion that makes the use of a variety of aggregation rules possible. For this to happen, statistical agencies must recognize the need for high quality microdata and build this into their planning processes. Agencies need to view their missions from a multiple use perspective and move away from use of a primary reporting and collection vehicle. Although the categories used to report data must be flexible, practical considerations dictate that data collection proceed within a fixed classification system. It is simply too expensive for both respondents and statistical agencies to process survey responses in the absence of standardized forms, data entry programs, etc. I argue for a basic classification centered on commodities--products, services, raw materials and labor inputs--as the focus of data collection. The idea is to make the principle variables of interest--the commodities--the vehicle for the collection and processing of the data. For completeness, the basic classification should include labor usage through some form of occupational classification. In most economic surveys at the Census Bureau, the reporting unit and the classified unit have been the establishment. But there is no need for this to be so. The basic principle to be followed in data collection is that the data should be collected in the most efficient way--efficiency being defined jointly in terms of statistical agency collection costs and respondent burdens.View Full Paper PDF
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Working PaperPublished Versus Sample Statistics From The ASM: Implications For The LRD
January 1991
Working Paper Number:
CES-91-01
In principle, the Longitudinal Research Database ( LRD ) which links the establishments in the Annual Survey of Manufactures (ASM) is ideal for examining the dynamics of firm and aggregate behavior. However, the published ASM aggregates are not simply the appropriately weighted sums of establishment data in the LRD . Instead, the published data equal the sum of LRD-based sample estimates and nonsample estimates. The latter reflect adjustments related to sampling error and the imputation of small-establishment data. Differences between the LRD and the ASM raise questions for users of both data sets. For ASM users, time-series variation in the difference indicates potential problems in consistently and reliably estimating the nonsample portion of the ASM. For LRD users, potential sample selection problems arise due to the systematic exclusion of data from small establishments. Microeconomic studies based on the LRD can yield misleading inferences to the extent that small establishments behave differently. Similarly, new economic aggregates constructed from the LRD can yield incorrect estimates of levels and growth rates. This paper documents cross-sectional and time-series differences between ASM and LRD estimates of levels and growth rates of total employment, and compares them with employment estimates provided by Bureau of Labor Statistics and County Business Patterns data. In addition, this paper explores potential adjustments to economic aggregates constructed from the LRD. In particular, the paper reports the results of adjusting LRD-based estimates of gross job creation and destruction to be consistent with net job changes implied by the published ASM figures.View Full Paper PDF
