Because of the dramatic decline in the United States Trade Balance since the early 1970's, many economists and policy makers have become increasingly concerned about the ability of U.S. manufacturers to compete with foreign producers. Initially concern was limited to a few basic industries such as shoes, clothing, and steel; but more recently foreign producers have been effectively competing with U.S. manufacturers in automobiles, electronics, and other consumer products. It now seems that foreign producers are even challenging the dominance of America in high technology industries. The most recent publication from the International Trade Administration shows that the U.S. Trade Balance in high technology industries fell from a $24 billion surplus in 1982, to a $2.6 billion deficit in 1986, before rebounding to a $591 million surplus in 1987. As part of the efforts of the U.S. Census Bureau to provide policy makers and other interested parties with the most complete and accurate information possible, we recently completed a review of the methodology and data used to construct trade statistics in the area of high technology trade. Our findings suggest that the statistics presented by the International Trade Administration, although technically correct, do not provide an accurate picture of international trade in high or advanced technology products because of the level of aggregation used in their construction. The ITA statistics are based on the Department of Commerce's DOC3 definition of high technology industries. The DOC3 definition requires that each product classified in a high tech industry be designated high tech. As a result, many products which would not individually be considered high tech are included in the statistics. After developing a disaggregate, product- based measure of international trade in Advanced Technology Products (ATP), we find that although the trade balance in these products did decline over the 1982-1987 period, the decline is much smaller (about $5 billion) than reported by ITA (approximately $24 billion). This paper discusses the methodology used to define the ATP measure, contrasts it to the DOC3 measure, and provides a comparison of the resulting statistics. After discussing alternative approaches to identifying advanced technology products, Section 2 describes the advanced technologies in the classification. (Appendix A, provides definitions and examples of the products which embody these technologies. In addition, Appendix B, available on request, provides a comprehensive list of Advanced Technology Products by technology grouping.) Having described the ATPs, Section 3 examines annual trade statistics for ATP products, in 1982, 1986, and 1987, and compares these statistics with equivalent ones based on the DOC3 measure. The differences between the two measures over the 1982- 87 period stem from changes in the balance of trade of items included in the DOC3 measure but excluded by the Census ATP measure; i.e. the differences are due to changes in the trade balance of "low tech" products which are produced in "high tech" industries. This finding corroborates a principal argument for construction of the ATP measure, that the weakness of the DOC3 measure of high technology trade is the level of aggregation used in its construction. It also suggests that at the level of individual products the high technology sectors of the economy continue to enjoy a strong comparative advantage and are surprisingly healthy. Nonetheless, some areas of weakness are identified, such as low tech products in high tech industries. (Appendix C, supplements this material by providing a detailed listing of traded products included and excluded from the Advanced Technology definition for each DOC3 high tech commodity grouping. These Tables enable the reader to directly assess the Census classification.)
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Estimating the Distribution of Plant-Level Manufacturing Energy Efficiency with Stochastic Frontier Regression
March 2007
Working Paper Number:
CES-07-07
A feature commonly used to distinguish between parametric/statistical models and engineering models is that engineering models explicitly represent best practice technologies while the parametric/statistical models are typically based on average practice. Measures of energy intensity based on average practice are less useful in the corporate management of energy or for public policy goal setting. In the context of company or plant level energy management, it is more useful to have a measure of energy intensity capable of representing where a company or plant lies within a distribution of performance. In other words, is the performance close (or far) from the industry best practice? This paper presents a parametric/statistical approach that can be used to measure best practice, thereby providing a measure of the difference, or 'efficiency gap' at a plant, company or overall industry level. The approach requires plant level data and applies a stochastic frontier regression analysis to energy use. Stochastic frontier regression analysis separates the energy intensity into three components, systematic effects, inefficiency, and statistical (random) error. The stochastic frontier can be viewed as a sub-vector input distance function. One advantage of this approach is that physical product mix can be included in the distance function, avoiding the problem of aggregating output to define a single energy/output ratio to measure energy intensity. The paper outlines the methods and gives an example of the analysis conducted for a non-public micro-dataset of wet corn refining plants.
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Business Dynamics Statistics of High Tech Industries
January 2016
Working Paper Number:
CES-16-55
Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Technology sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. Tracking the performance of this sector is therefore of primary importance, especially in light of recent evidence that suggests a slowdown in business dynamism in High Tech industries. The Census Bureau produces the Business Dynamics Statistics (BDS), a suite of data products that track job creation, job destruction, startups, and exits by firm and establishment characteristics including sector, firm age, and firm size. In this paper we describe the methodologies used to produce a new extension to the BDS focused on businesses in High Technology industries.
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An 'Algorithmic Links with Probabilities' Crosswalk for USPC and CPC Patent Classifications with an Application Towards Industrial Technology Composition
March 2016
Working Paper Number:
CES-16-15
Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires patents be tied to measures of economic activity, which has proven to be difficult. Recently, Lybbert and Zolas (2014) have constructed an International Patent Classification (IPC) to industry classification crosswalk using an 'Algorithmic Links with Probabilities' approach. In this paper, we utilize a similar approach and apply it to new patent classification schemes, the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system. The resulting USPC-Industry and CPC-Industry concordances link both U.S. and global patents to multiple vintages of the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We then use the crosswalk to highlight changes to industrial technology composition over time. We find suggestive evidence of strong persistence in the association between technologies and industries over time.
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Getting Patents and Economic Data to Speak to Each Other: An 'Algorithmic Links with Probabilities' Approach for Joint Analyses of Patenting and Economic Activity
September 2012
Working Paper Number:
CES-12-16
International technological diffusion is a key determinant of cross-country differences in economic performance. While patents can be a useful proxy for innovation and technological change and diffusion, fully exploiting patent data for such economic analyses requires patents to be tied to measures of economic activity. In this paper, we describe and explore a new algorithmic approach to constructing concordances between the International Patent Classification (IPC) system that organizes patents by technical features and industry classification systems that organize economic data, such as the Standard International Trade Classification (SITC), the International Standard Industrial Classification (ISIC) and the Harmonized System (HS). This 'Algorithmic Links with Probabilities' (ALP) approach incorporates text analysis software and keyword extraction programs and applies them to a comprehensive patent dataset. We compare the results of several ALP concordances to existing technology concordances. Based on these comparisons, we select a preferred ALP approach and discuss advantages of this approach relative to conventional approaches. We conclude with a discussion on some of the possible applications of the concordance and provide a sample analysis that uses our preferred ALP concordance to analyze international patent flows based on trade patterns.
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Primary Versus Secondary Production Techniques in U.S. Manufacturing
October 1994
Working Paper Number:
CES-94-12
In this paper we discuss and analyze a classical economic puzzle: whether differences in factor intensities reflect patterns of specialization or the co-existence of alternative techniques to produce output. We use observations on a large cross-section of U.S. manufacturing plants from the Census of Manufactures, including those that make goods primary to other industries, to study differences in production techniques. We find that in most cases material requirements do not depend on whether goods are made as primary products or as secondary products, which suggests that differences in factor intensities usually reflect patterns of specialization. A few cases where secondary production techniques do differ notably are discussed in more detail. However, overall the regression results support the neoclassical assumption that a single, best-practice technique is chosen for making each product.
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Are All Trade Protection Policies Created Equal? Empirical Evidence for Nonequivalent Market Power Effects of Tariffs and Quotas
September 2010
Working Paper Number:
CES-10-27
The steel industry has been protected by a wide variety of trade policies, both tariff- and quota-based, over the past decades. This extensive heterogeneity in trade protection provides the opportunity to examine the well-established theoretical literature predicting nonequivalent effects of tariffs and quotas on domestic firms' market power. Robust to a variety of empirical specifications with U.S. Census data on the population of U.S. steel plants from 1967-2002, we find evidence for significant market power effects for binding quota-based protection, but not for tariff-based protection. There is only weak evidence that antidumping protection increases market power.
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The Classification of Manufacturing Industries: an Input-Based Clustering of Activity
August 1990
Working Paper Number:
CES-90-07
The classification and aggregation of manufacturing data is vital for the analysis and reporting of economic activity. Most organizations and researchers use the Standard Industrial Classification (SIC) system for this purpose. This is, however, not the only option. Our paper examines an alternative classification based on clustering activity using production technologies. While this approach yields results which are similar to the SIC, there are important differences between the two classifications in terms of the specific industrial categories and the amount of information lost through aggregation.
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Price Dispersion in U.S. Manufacturing
October 1989
Working Paper Number:
CES-89-07
This paper addresses the question of whether products in the U.S. Manufacturing sector sell at a single (common) price, or whether prices vary across producers. The question of price dispersion is important for two reasons. First, if prices vary across producers, the standard method of using industry price deflators leads to errors in measuring real output at the firm or establishment level. These errors in turn lead to biased estimates of the production function and productivity growth equation as shown in Abbott (1988). Second, if prices vary across producers, it suggests that producers do not take prices as given but use price as a competitive variable. This has several implications for how economists model competitive behavior.
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Price Dispersion In U.S. Manufacturing: Implications For The Aggregation Of Products And Firms
March 1992
Working Paper Number:
CES-92-03
This paper addresses the question of whether products in the U.S. Manufacturing sector sell at a single (common) price, or whether prices vary across producers. Price dispersion is interesting for at least two reasons. First, if output prices vary across producers, standard methods of using industry price deflators lead to errors in measuring real output at the industry, firm, and establishment level which may bias estimates of the production function and productivity growth. Second, price dispersion suggests product heterogeneity which, if consumers do not have identical preferences, could lead to market segmentation and price in excess of marginal cost, thus making the current (competitive) characterization of the Manufacturing sector inappropriate and invalidating many empirical studies. In the course of examining these issues, the paper develops a robust measure of price dispersion as well as new quantitative methods for testing whether observed price differences are the result of differences in product quality. Our results indicate that price dispersion is widespread throughout manufacturing and that for at least one industry, Hydraulic Cement, it is not the result of differences in product quality.
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The Longitudinal Research Database (LRD): Status And Research Possibilities
July 1988
Working Paper Number:
CES-88-02
This paper discusses the development and use of the Longitudinal Research Data available at the Center for Economic Studies of the Bureau of the Census in terms of what has been accomplished thus far, what projects are currently in progress, and what plans are in place for the near future. The major achievement to date is the construction of the database itself, which contains data for manufacturing establishments collected by the Census in 1963, 1967, 1972, 1977 and 1982, and the Annual Survey of Manufactures for non-Census years from 1973 to 1985. These data now reside in the Center's computer in a consistent format across all years. In addition, a large software development task that greatly simplifies the task of selecting subsets of the database for specific research projects is well underway. Finally, a number of powerful microcomputers have been purchased for use by researchers for their statistical analysis. Current efforts underway at the Center include research on such policy-relevant issues as mergers and their impact on profits and production, high technology trade, import competition, plant level productivity, entry and exit, and productivity differences between large and small firms. Due to the confidentiality requirements of the Census data, most of their research is performed by Center staff and Special Sworn Employees. Under certain circumstances, the Center accepts user-written programs from outside researchers. These routines are executed by Center staff, and the resultant output is reviewed thoroughly for disclosure problems. The Center is also an active member of a task force working on methods on release "masked" or "cloned" microdata in public-use files that will protect the confidentiality of the data while at the same time provide a research tool for outside users. The Center research program contributes directly to future research possibilities. The current batch of research projects is adding insight into the nature of the LRD database. This information is continually being incorporated into the Center's software system, thus facilitating yet more research activity. Moreover, since a good portion of the research involves linking the Longitudinal Research Data to other data files, such as the NSF/Census R&D data, the scope of the databases is continually being expanded. Furthermore, the Center is exploring the possibility of linking the demographic data collected by the Census Bureau to the LRD database.
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