This work examines the impact of manufacturing extension services on establishment productivity. It builds on an earlier study conducted by Jarmin in the 1990s, by matching the Census of Manufacturers (CMF) with the Manufacturing Extension Partnership (MEP) customer and activity datasets to generate treatment and comparison groups for analysis. The scope of the study is the period 1997 to 2002, which was a period of economic downturn in the manufacturing sector and budgetary challenges for the MEP. The paper presents some preliminary findings from this analysis. Both lagged dependent variable (LDV) and difference in difference (DiD) models are employed to estimate the relationship between manufacturing extension and labor productivity. The results presented are inconclusive and paint a mixed picture as they demonstrate the benefits and limitations of using Census microdata in program evaluation. They also point to the need to conduct analyses that could help to better understand the dynamic impact of MEP services.
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Evaluating the Long-Term Effect of NIST MEP Services on Establishment Performance
March 2015
Working Paper Number:
CES-15-09
This work examines the effects of receipt of business assistance services from the Manufacturing Extension Partnership (MEP) on manufacturing establishment performance. Several measures of performance are considered: (1) change in value-added per employee (a measure of productivity); (2) change in sales per worker; (3) change in employment; and (4) establishment survival. To analyze these relationships, we merged program records from the MEP's client and project information files with administrative records from the Census of Manufacturers and other Census databases over the periods 1997'2002 and 2002'2007 to compare the outcomes and performance of 'served' and 'unserved' manufacturing establishments. The approach builds on, updates, and expands upon earlier studies comparing matched MEP client and non-client performance over time periods ending in 1992 and 2002. Our results generally indicate that MEP services had positive and significant impacts on establishment productivity and sales per worker for the 2002'2007 period with some exceptions based on employment size, industry, and type of service provided. MEP services also increased the probability of establishment survival for the 1997'2007 period. Regardless of econometric model specification, MEP clients with 1'19 employees have statistically significant and higher levels of labor productivity growth. We also observed significant productivity differences associated with MEP services by broad sector, with higher impacts over the 2002'2007 time period in the durable goods manufacturing sector. The study further finds that establishments receiving MEP assistance are more likely to survive than those that do not receive MEP assistance. Detailed findings of the study, as well as caveats and limitations, are discussed in the paper.
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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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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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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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The 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.
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Statistics on the Small Business Administration's Scale-Up America Program
April 2019
Working Paper Number:
CES-19-11
This paper attempts to quantify the difference in performance, of 'treated' (program participant) and 'non-treated' (non-participant) firms in SBA's Scale-Up initiative. I combine data from the SBA with administrative data housed at Census using a combination of numeric and name and address matching techniques. My results show that after controlling for available observable characteristics, a positive correlation exists between participation in the Scale-Up initiative and firm growth. However, publicly available survey results have shown that entrepreneurs have a variety of goals in-mind when they start their businesses. Two prominent, and potentially contradictory ones are work-life balance and greater income. That means that not all firms may want to grow and I am unable to completely control for owner motivations. Finally, I do not find a statistically significant relationship between participation in Scale-Up and firm survival once other business characteristics are accounted for.
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Statistics on the International Trade Administration's Global Markets Program
September 2015
Working Paper Number:
CES-15-17
Recent mandates for evidence-based policy choices from both the Executive and Legislative branches of the federal government underscore the importance of understanding the relationship between program participation and business outcomes. In this paper, we examine the correlations between participation in an export-promotion program and business outcomes. We use this experience to provide more general lessons learned about combining program data on treatments with Census Bureau micro data that can be used as a control. Note this paper does not evaluate a program, but instead provides critical information about a program.
The mission of the Commercial Service/Global Markets program is to help companies either start or increase their exports of goods and services. It pursues this mission through advocacy, events, and counseling. This study looks at a very small part of the overall program. While we cannot rule-out several sources of bias in our results, we do observe several consistent patterns across our models. In particular, program participation is positively correlated with export growth and change and, for small businesses, also with positive employment growth. However, overall, and for large firms in particular, there is a negative correlation with employment growth and counseling. The paper concludes with a 'Lessons Learned' section that highlights areas where measurement can be improved.
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Computer Networks and U.S. Manufacturing Plant Productivity: New Evidence from the CNUS Data
January 2002
Working Paper Number:
CES-02-01
How do computers affect productivity? Many recent studies argue that using information technology, particularly computers, is a significant source of U.S. productivity growth. The specific mechanism remains elusive. Detailed data on the use of computers and computer networks have been scarce. Plant-level data on the use of computer networks and electronic business processes in the manufacturing sector of the United States were collected for the first time in 1999. Using these data, we find strong links between labor productivity and the presence of computer networks. We find that average labor productivity is higher in plants with networks. Computer networks have a positive and significant effect on plant labor productivity after controlling for multiple factors of production and plant characteristics. Networks increase estimated labor productivity by roughly 5 percent, depending on model specification. Model specifications that account for endogenous computer networks also show a positive and significant relationship. Our work differs from others in several important aspects. First, ours is the first study that directly links the use of computer networks to labor productivity using plant-level data for the entire U.S. manufacturing sector. Second, we extend the existing model relating computers to productivity by including materials as an explicit factor input. Third, we test for possible endogeneity problems associated with the computer network variable.
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