Measuring knowledge spillovers in manufacturing and services: an empirical assessment of alternative approaches
AbstractIn this paper it is tested which of the various alternative approaches for constructing knowledge spillover pools suggested in existing literature measures the extent to which a firm can costlessly receive external knowlegde best. Since knowledge spillovers are unmeasurable, a 'goodness of fit' measure is constructed using innovation survey data. It turns out that measures of the uncentered correlation of firm characteristics seem to fit actual knowledge spillovers best. Direct measures constructed from innovation survey data appear to work reasonably well while measures of the Euclidean technological distance and of the geographical distance lead to counterintuitive results. Empirical evidence is provided for both the German service sector and the manufacturing sector. --
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Bibliographic InfoArticle provided by Elsevier in its journal Research Policy.
Volume (Year): 31 (2002)
Issue (Month): 1 (January)
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Other versions of this item:
- Kaiser, Ulrich, 1999. "Measuring Knowledge Spillovers in Manufacturing and Services: An Empirical Assessment of Alternative Approaches," ZEW Discussion Papers 99-62, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
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