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IT Investment and Firm Performance in U.S. Retail Trade
June 2002
Working Paper Number:
CES-02-14
We examine the relationships between investments in information technology (IT) and two measures of retail firm performance -- productivity and establishment growth -- over the 1992 to 1997 period. We use untapped firm and establishment micro data from the Censuses of Retail Trade and the Assets and Expenditures Survey. We show that large firms account for most retail IT investment, employment and establishment growth. We find evidence of a significant relationship between IT investment intensity and productivity growth. We found no such evidence of a link between IT growth in the number of establishments operated by retail firms.
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The Trend to Smaller Producers in Manufacturing in Canada and the U.S.
March 2002
Working Paper Number:
CES-02-06
This paper examines the trend in the importance of small producers in the Canadian and U.S. manufacturing sectors from the early 1970s to the late 1990s in order to investigate whether there was a common North American trend in changes in plant size. It finds that small plants in both countries increased their share of employment up to the 1990s, but their share remained stable in the 1990s. Small plants increased their share of output up to the 1990s, but then saw their share of output decline. Over the entire time period, their share of output increased less than their share of employment and, therefore, their relative labour productivity has fallen. The similarity in the trends in the two countries suggests that causes of this phenomenon should be sought in similarities such as the technological environment rather than in country-specific factors like unionization or trade intensities.
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Measuring the Electronic Economy: Current Status and Next Steps
June 2000
Working Paper Number:
CES-00-10
The recent growth of consumer retailing over the Internet draws attention to the electronic economy. However, businesses also conduct other business processes over computer networks, and many have been doing so for some time. Uses of computer networks attract attention because of assertions that they lead to new products and services, new delivery methods, streamlined or re-engineered business processes, new business structures, and enhanced business performance. These changes, in turn, potentially affect the performance of the entire economy, including economic growth, productivity, prices, employment, trade, and the structures of businesses, regions, and markets. Evaluating these assertions, and their effects on economic performance, requires solid statistical information about the electronic economy. This paper develops principles for identifying information critical to measuring the size and evaluating the potential effects of the electronic economy, relates that information to current data collection programs, and notes relevant measurement issues. Some of the required information about the electronic economy can be collected by adding questions to existing surveys, making the scope of existing surveys consistent, or developing new surveys. However, many key pieces of information pose significant challenges to economic measurement. While some of those challenges are specific to the electronic economy, others are long-standing ones. Interest in the electronic economy highlights the importance of continuing attempts to address these challenges. Improving and enhancing the statistical system to provide information about the electronic economy, therefore, would also substantially improve the baseline information available for evaluating the performance of the entire economy.
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GOVERNMENT TECHNICAL ASSISTANCE PROGRAMS* AND PLANT SURVIVAL: THE ROLE OF PLANT OWNERSHIP TYPE
February 1999
Working Paper Number:
CES-99-02
This paper compares the survival rates of plants participating in manufacturing extension programs to nonparticipating plants. Participating plants receive technical and business assistance from one of a nationwide network of extension centers intended to assist smaller manufacturers. Results suggest that plant survival is related to plant size, age, productivity, capital intensity and ownership type. Importantly, the impact of extension services differs across ownership types. Participating in extension increases the probability of survival for single unit plants, but not for multi units. This result is consistent with the notion that single unit plants have less access to information on new technologies and would, therefore, benefit more from technical assistance programs such as manufacturing extension.
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Manufacturing Extension And Productivity Dynamics
June 1998
Working Paper Number:
CES-98-08
This paper presents results from an investigation of the effects of manufacturing extension on the productivity dynamics of client plants. Previous econometric studies of manufacturing extension had very little time series information. This limited what researchers could say about the relative timing of extension services and performance improvements. In turn, this makes it difficult to attribute performance improvements to the receipt of extension services. In this paper, I use a panel of client and nonclient plants to more carefully analyze the dynamics of extension and productivity. The results suggest that the timing of observed productivity improvements at client plants is consistent with a positive impact of manufacturing extension. Estimated program impacts are within the range of those found in previous studies.
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Measuring The Performance Of Government Technology Programs: Lessons From Manufacturing Extension
December 1997
Working Paper Number:
CES-97-18
Managers of government technology programs are under increasing pressure to demonstrate the effectiveness of their programs. In this paper we examine the issues involved in credibly evaluating such programs in the context of recent efforts to evaluate manufacturing extension programs in the U.S. We provide a stylized model of the dynamic competitive environment in which the plants and firms targeted by these programs operate and discuss its implications for evaluation. We compare and contrast the various methodologies and data sets used to evaluate manufacturing extension. We conclude that the best currently available method for measuring the overall effectiveness of programs such as manufacturing extension is to combine program administrative data with existing panel data sets.
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Measuring the Impact of the Manufacturing Extension Partnership
September 1996
Working Paper Number:
CES-96-08
In this paper, I measure the impact of the Manufacturing Extension Partnership (MEP) on productivity and sales growth at manufacturing plants. To do this, I match MEP client data to the Census Bureau's Longitudinal Research Database (LRD). The LRD contains data for all manufacturing establishments in the U.S. and provides a number of measures of plant performance and characteristics that are measured consistently across plants and time. This facilitates valid comparisons between both client and non-client plants and among clients served by different MEP centers. The National Institute of Standards and Technology (NIST) administers the MEP as part of their effort to improve the competitiveness of U.S. manufacturing. The program provides business and technical assistance to small and medium sized manufacturers much as agricultural extension does for farmers. The goal of the paper is to see if measures of plant performance (e.g., productivity and sales growth) are systematically related to participation in the MEP, while controlling for other factors that are known or thought to influence performance. Selection bias is often a problem in evaluation studies so I specify an econometric model that controls for selection. I estimate the model with data from 8 manufacturing extension centers in 2 states. The control group includes all plants from each state in the LRD. Preliminary results indicate that MEP participation is systematically related to productivity growth but not to sales growth.
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Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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Using Matched Client And Census Data To Evaluate The Performance Of The Manufacturing Extension Partnership
April 1995
Working Paper Number:
CES-95-07
This paper proposes a framework for evaluating the Manufacturing Extension Partnership (MEP). The MEP is administered by the National Institute of Standards and Technology (NIST) as part of its effort to improve the global competitiveness of U.S. manufacturing industries. As the name implies, the MEP is modelled after agricultural extension. Rather than farmers the MEP's target population is small and medium sized manufacturers, generally those with less than 500 employees. The MEP currently supports 44 manufacturing extension centers around the country. These centers provide technical and business assistance for manufacturers much as county extension agents do for farmers. The goal of evaluation is to see if MEP engagements lead to positive outcomes from the view of important MEP stakeholders (e.g., MEP clients, MEP centers, NIST, state and local governments and Congress). These outcomes are discussed in McGuckin and Redman (1995) and include: Process Outcomes (e.g., adoption of a new technology by a client); Intermediate Outcomes (e.g., reduction in the clients defect rate); Business Outcomes (e.g., survival and profits) and Policy Outcomes (increases in employment,wages and/or exports). The evaluation framework described in this paper has two components. The first component is an evaluation dataset which contains measures of many of the program outcomes listed above for both MEP clients and a representative control group of non- clients. This dataset will be constructed by linking MEP client records with plant level Census data housed at the Center for Economic Studies of the Census Bureau. The Census data provides measures of several outcome and control variables which are comparable across both plants and time. The Census data include observations for all manufacturing plants in the U.S. from which representative control groups can be constructed. The MEP client records provide data on the type and intensity of extension engagements. Linking these rich sources of information yields a comprehensive and powerful dataset for MEP evaluation. The second component is an evaluation methodology which exploits this rich dataset to make statistical inferences about the impact of MEP services, while carefully controlling for other influences. By using this methodology, we can address many of the shortcomings which plagued previous attempts to evaluate extension services. In addition to evaluation, the dataset described in this paper may be used to profile the characteristics of MEP clients and compare them to non-clients. The Census data contain the complete universe of manufacturing establishments in the U.S.
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Asymmetric Learning Spillovers
April 1993
Working Paper Number:
CES-93-07
In this paper, I employ a linear-quadratic model of an industry characterized by learning by doing to examine the implications of asymmetric learning spillovers. Importantly, I show that distribution of spillover benefits can influence market structure in ways that can not be seen in models where spillovers are symmetric. If spillovers are asymmetric, a tradeoff between improved industry performance and increased market concentration can arise which does not occur when they are symmetric. This tradeoff leads to a policy dilemma; whether to promote static or dynamic efficiency in markets where learning is important.
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