Productivity. (Conferences)

NBER Reporter, Winter 2002 | Go to article overview
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Productivity. (Conferences)


The NBER's Program on Productivity met in Cambridge on December 6. Bronwyn H. Hall, NBER and University of California, Berkeley, organized this program:

Bee Yan Aw-Roberts, Pennsylvania State University; Mark J. Roberts, NBER and Pennsylvania State University; and Tor Winston, U.S. Department of Justice, "Export Market Participation, Investments in R and D and Worker Training, and the Evolution of Firm Productivity"

Discussant: Amil Petrin, NBER and University of Chicago

Hajime Katayarna, Pennsylvania State University; Shihua Lu, Charles River Associates; and James R. Tybout, NBER and Pennsylvania State University; "Why Plant-Level Productivity Studies Are Often Misleading, and an Alternative Approach to Inference"

Discussant: Marc Melitz, Harvard University

Barbara M. Fraumeni and Sumiye Okubo, Bureau of Economic Analysis, "R and D in the National Income and Product Accounts: A First Look at Its Effects on GDP"

Discussant: Bronwyn H. Hall

Saul Lach, NBER and Hebrew University, Jerusalem, and Mark Schankerman, London School of Economics, "Incentives, Academic Research, and Licensing"

Discussant: Arvids Ziedonis, University of Michigan

James D. Adams, NBER and University of Florida; Grant C. Black and Paula E. Stephan, Georgia State University; and Roger Clemmons, University of Florida, "Patterns of Research Collaboration in U.S. Universities, 1981-99"

Discussant: Manuel Trajtenberg, NBER and Tel Aviv University

Aw, Roberts, and Winston use data for firms in the Taiwanese electronics industry in 1986, 1991, and 1996 to investigate a firm's decision to invest in two sources of knowledge: participation in the export market and investments in R and D and/or worker training. They also assess the effects of these investments on the firm's future total factor productivity. They find that past experience in exporting increases the likelihood that a firm currently exports, but that past experience in R and D and/or worker training does not have lasting effects on a firm's investment decisions. These results are consistent with the belief that exporting is less costly for firms that have already incurred some necessary sunk costs. In addition, the results indicate that larger firms and more productive firms are more likely to participate in each activity. The findings also suggest that, on average, firms that export but do not invest in R and D and/or worker training have significantly higher future productivity than firms th at do not participate in either activity. In addition, firms that export and invest in R and D and/or worker training have significantly higher future productivity than firms that only export. These findings are consistent with the hypothesis that export experience is an important source of productivity growth for Taiwanese firms and that firm investments in R and D and worker training facilitate their ability to benefit from their exposure to the export market.

Applied economists often wish to measure the effects of policy changes (such as trade liberalization) or managerial decisions (for example, how much to spend on R and D) on plant-level productivity patterns. But plant-level data on physical quantities of output, capital, and intermediate inputs are usually unavailable. Therefore, when constructing productivity measures, most analysts proxy these variables with real sales revenues, depreciated capital spending, and real input expenditures. The first objective of Katayama, Lu, and Tybout is to show that the resultant productivity indexes have little to do with technical efficiency, product quality; or contributions to social welfare. Nonetheless, they are likely to be correlated with policy shocks and managerial decisions in misleading ways. The authors' second objective is to develop an alternative approach to inference. Applying their methodology to panel data on Colombian pulp and paper plants, the authors then study the relation between their welfare-based measures and conventional productivity measures.

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