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Zoltan J. Acs

Bio: Zoltan J. Acs is an academic researcher from George Mason University. The author has contributed to research in topics: Entrepreneurship & Human capital. The author has an hindex of 95, co-authored 409 publications receiving 41997 citations. Previous affiliations of Zoltan J. Acs include University of Colorado Boulder & University of South Carolina.


Papers
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Book
01 Jan 1990
TL;DR: Innovation and Small Firms as discussed by the authors provides a rich empirical analysis of the increased importance of small firms in generating technological innovations and their growing contribution to the U.S. economy.
Abstract: Utilizing a unique data set, Zoltan Acs and David Audretsch provide a rich empirical analysis of the increased importance of small firms in generating technological innovations and their growing contribution to the U.S. economy. They identify the contributions made by both small and large firms to the innovative process and the manner in which market structure, and the firm-size distribution in particular, responds to technological change. The authors' analysis relies on traditional theories of industrial organization and tests existing hypotheses, many of them previously untested due to data constraints.Innovation and Small Firms brings together two large data bases recently released by the U. S. Small Business Administration - one directly measuring innovative activity for large and small firms, the other providing a detailed census of economic activity for all manufacturing firms and plants across a broad spectrum of industries.Acs and Audretsch describe and evaluate the data bases in the context of the literature on innovation, market structure, and firm size. They present their findings on the presence of small firms, small-firm entry in manufacturing, small-firm growth and flexible technology, and mobility and firm size. They compare static and dynamic measures of small-firm viability and address the relationships between R&D, innovation, and productivity, and analyze the interaction between technological regimes and the role of government in innovation.Zoltan Acs is an Associate Professor of Economics at the Merrick School of Business, the University of Baltimore. David Audretsch is a Research Fellow at the Wissenschaftszentrum Berlin fur Sozialforschung in West Berlin.

1,881 citations

Posted Content
TL;DR: In this article, the impact of various industry characteristics on the innovative output of firms was examined through examination of over 100 technology, engineering, and trade journals, and it was shown that lower levels of concentration are associated with increased innovation activity.
Abstract: Probes the impact that various industry characteristics have on the innovative output of firms. Data used for this analysis were gathered by the U.S. Small Business Administration (SBA) through examination of over 100 technology, engineering, and trade journals. The SBA data on new products, processes and services introduced to the market in 1982 was broken down by firm size, industry, and significance. Innovation activity is measured by the number of innovations in each four-digit SIC industry. Prior studies have utilized such data as patents and stock market value for large firms; through this more direct measure of innovation activity, several key findings are made. In an industry composed primarily of large firms, the level of innovation will be higher, though that activity will occur mostly in the smaller firms of that industry -- i.e., innovation appears to be an important competitive strategy for small firms in that environment. Results indicate that lower levels of concentration are associated with increased innovation activity. Further, as industry R&D increases, the number of innovations increases, but this increase is at a decreasing rate. Unionization is found to be negatively related to innovation activity. Although the results do not shed much light on the exact relationship between R&D, appropriability, and innovation activity, they do show support for the proposition that differences in economic and technological environments lead to differences in the innovation activity of large and small firms. (SRD)

1,864 citations

Journal ArticleDOI
TL;DR: In this paper, the authors re-examine the empirical evidence on the degree of spatial spillover between university research and high technology innovations and find evidence of local spatial externalities between research and development activities and university research in the MSA and in the surrounding counties.

1,709 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an exploratory and a regression-based comparison of the innovation count data and data on patent counts at the lowest possible levels of geographical aggregation, and determine the extent to which the innovation data can be substituted by other measures for a deeper understanding of the dynamics involved.

1,537 citations

Posted Content
TL;DR: In this article, the authors present a model suggesting that innovative output is influenced by RD and that these d eterminants have disparate effects on large and small firms, and they show that these effects have different effects on different companies.
Abstract: The authors present a model suggesting that innovative output is influenced by RD and (2) these d eterminants have disparate effects on large and small firms. Copyright 1988 by American Economic Association.

1,536 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, the authors draw upon previous research conducted in the different social science disciplines and applied fields of business to create a conceptual framework for the field of entrepreneurship, and predict a set of outcomes not explained or predicted by conceptual frameworks already in existence in other fields.
Abstract: To date, the phenomenon of entrepreneurship has lacked a conceptual framework. In this note we draw upon previous research conducted in the different social science disciplines and applied fields of business to create a conceptual framework for the field. With this framework we explain a set of empirical phenomena and predict a set of outcomes not explained or predicted by conceptual frameworks already in existence in other fields.

11,161 citations

Book
01 Jan 2009

8,216 citations

ReportDOI
TL;DR: In this paper, the authors present a survey on the use of patent data in economic analysis, focusing on the patent data as an indicator of technological change and concluding that patent data remain a unique resource for the study of technical change.
Abstract: This survey reviews the growing use of patent data in economic analysis. After describing some of the main characteristics of patents and patent data, it focuses on the use of patents as an indicator of technological change. Cross-sectional and time-series studies of the relationship of patents to R&D expenditures are reviewed, as well as scattered estimates of the distribution of patent values and the value of patent rights, the latter being based on recent analyses of European patent renewal data. Time-series trends of patents granted in the U.S. are examined and their decline in the 1970s is found to be an artifact of the budget stringencies at the Patent Office. The longer run downward trend in patents per R&D dollar is interpreted not as an indication of diminishing returns but rather as a reflection of the changing meaning of such data over time. The conclusion is reached that, in spite of many difficulties and reservations, patent data remain a unique resource for the study of technical change.

5,075 citations

Journal ArticleDOI
TL;DR: In this paper, a theoretical framework that relates three aspects of a firm's ego network (direct ties, indirect ties, and indirect ties) is proposed to assess the effects of a firms network of relations on innovation.
Abstract: To assess the effects of a firm's network of relations on innovation, this paper elaborates a theoretical framework that relates three aspects of a firm's ego network—direct ties, indirect ties, an...

4,829 citations

Posted Content
TL;DR: A theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification.
Abstract: Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

4,284 citations