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来源类型 | REPORT |
规范类型 | 报告 |
Economic Intelligence | |
Andrew D. Reamer | |
发表日期 | 2012-01-19 |
出版年 | 2012 |
语种 | 英语 |
概述 | Andrew D. Reamer looks at ways the federal statistical system can better support the nation's economic competitiveness. |
摘要 | Download this report (pdf) Download the introduction and summary (pdf) Read this report in your web browser (Scribd) See also: Overview: Series on U.S. Science, Innovation, and Economic Competitiveness, Rewiring the Federal Government for Competitiveness by Jonathan Sallet and Sean Pool, Universities in Innovation Networks by Krisztina “Z” Holly, Building a Technically Skilled Workforce by Louis Soares and Stephen Steigleder, and Immigration for Innovation by Marshall Fitz. In discussing about policy options for promoting U.S. economic competitiveness, it’s unusual for anyone to consider producing better statistics. Grants, tax credits, regulation, agency reorganizations, yes. But numbers? The federal data system sits like a large black box in a dark shadow. We know a few high-profile stats shed light on how we’re doing economically, such as GDP and unemployment, but most everything else is opaque. We don’t quite understand what else the system contributes to economic policy or, to be honest, how it works. And so it may not be immediately obvious how the statistical system could better support the nation’s economic competitiveness. Federal economic statistical agencies—particularly the Census Bureau, the Bureau of Labor Statistics, and the Bureau of Economic Analysis—produce the data that guide federal economic policy. For many decades, the primary focus of federal economic policy has been managing the business cycle, that is, preventing recession and inflation. Statistical agencies’ explicit priority, therefore, is to provide the macroeconomic data to work the levers of fiscal and monetary policy. Even though U.S. competitiveness has become progressively more vulnerable since the early 1980s, the federal government yet to construct a coherent, well-integrated approach to addressing the global challenges to the nation’s economic structure. Consequently, the statistical system hasn’t been asked to come up with the numbers that would support intelligent competitiveness policy. What would those numbers look like? Federal competitiveness policy, if one existed, would systematically identify and address barriers to the efficient functioning of markets. These barriers contribute to what economists call “market failures” that impede the ability of traded industries to successfully respond to market issues and opportunities. Distinct from the broad “top-down” orientation of macroeconomic policy, federal competitiveness policy would involve more “bottom-up” efforts aimed at improving the likelihood that market actors make decisions that enhance competitiveness. These market participants include business, research and education institutions, workers, and students, as well as thousands of public purpose organizations at all geographic levels, such as regional economic and workforce development agencies. Identifying and addressing market failures requires sufficient data on the structure and competitiveness of key traded industries (number of jobs, productivity, international trade), the building blocks of competitiveness (innovation, entrepreneurship), the basic factors of firm operations (workforce, finance, research and development expenditures), and the impacts of public programs that support firm competitiveness. The private sector does not have the capability to provide the numbers needed to assess and enhance the nation’s competitiveness. But the federal government does, at a remarkably low cost. Its current annual cost to track the workings of a $14 trillion economy is about $1.7 billion.2 Additional statistical funds needed to support competitiveness policies would bring the total closer to $2 billion. And yet the U.S. statistical system doesn’t produce the numbers needed to assess and guide national competitiveness. In the absence of a coherent approach to federal competitiveness policy, statistical agencies continue to give priority to the data needs of macroeconomic policy. The production and analysis of competitiveness-relevant data are further crimped by inadequate congressional funding, lack of understanding of data user needs, lack of coordination and collaboration among agencies, insufficient encouragement to be innovative, and outside analysts’ difficulties in gaining access to and working with the data. Consider:
PrinciplesTo provide the data needed for competitiveness policy, the federal economic statistical system should adhere to five principles:
RecommendationsPutting these principles into action, the federal government should improve economic statistical programs to better support competitiveness by facilitating analysis of traded sectors, the intermediate outcomes that determine competitiveness (innovation, entrepreneurship), the underlying factors of competitiveness (R&D expenditures, workforce), and program impacts. The relative cost of these recommendations is minimal compared to their substantial potential long-term impacts on jobs, wages, and government revenues in a $14 trillion economy. Improving traded sector analysisProblem: Economic analysts lack access to data needed to assess the competitiveness of key traded industries. Solutions:
Improving measures of intermediate outcomes that influence competitivenessProblem: Federal statistical agencies do not provide adequate measures of intermediate outcomes that influence competitiveness, particularly innovation, entrepreneurship, and relationships between organizations. Solutions:
Improving factor analysisProblem: The federal statistical system does not provide sufficient data regarding the factors that influence competitiveness, including R&D expenditures, workforce, education and training, business finance, and energy. Solutions:
Improve evaluation of competitiveness programsProblem: Federal, state, and regional competitiveness-related program agencies lack data on the impacts of their programs. Solution: The Census Bureau should create a program to use the Longitudinal Business Database to assess the impact of program support to individual firms in terms of survival, revenues, jobs, wages, exports, innovation, and other outcomes related to competitiveness. Andrew D. Reamer is Research Professor at the George Washington University Institute of Public Policy. Download this report (pdf) Download the introduction and summary (pdf) Read this report in your web browser (Scribd) See also:
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主题 | General |
URL | https://www.americanprogress.org/issues/general/reports/2012/01/19/10905/economic-intelligence/ |
来源智库 | Center for American Progress (United States) |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/435186 |
推荐引用方式 GB/T 7714 | Andrew D. Reamer. Economic Intelligence. 2012. |
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