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Is distance dying at last? Falling home bias in fixed effects models of patent citations

By Rachel Griffith, Sokbae Lee and John Van Reenen

Abstract

We examine the “home bias” of international knowledge spillovers as measured by the speed of patent citations (i.e. knowledge spreads slowly over international boundaries). We present the first compelling econometric evidence that the geographical localization of knowledge spillovers has fallen over time, as we would expect from the dramatic fall in communication and travel costs. Our proposed estimator controls for correlated fixed effects and censoring in duration models and we apply it to data on over two million citations between 1975 and 1999. Home bias declines substantially when we control for fixed effects: there is practically no home bias for the more “modern” sectors such as pharmaceuticals and information/communication technologies

Topics: T Technology (General), HD Industries. Land use. Labor
Publisher: Centre for Economic Performance, London School of Economics and Political Science
Year: 2007
OAI identifier: oai:eprints.lse.ac.uk:19695
Provided by: LSE Research Online

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Citations

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  3. (1978). 32Table 2: Sample Sizes of Patent Citation Data Technological Period Country of Cited Patents Category
  4. 37Table 7: Number of Rejections of No Home Bias using Sub-Samples Estimation Method: No Fixed Effect Estimator (1) (2) (3) (4) (5) (6) Technological All countries OECD countries EU countries Category Early Late Early Late Early Late
  5. 38Table 8: Number of Rejections of No Home Bias using Sub-Samples Estimation Method: Censored Fixed Effect Estimator (1) (2) (3) (4) (5) (6) Technological All countries OECD countries EU countries Category Early Late Early Late Early Late
  6. 42Table A1: Raw data: home bias in ¯rst citation Citing: Cited:
  7. 43Table A3: Censoring - by early and late time period 1975-1989 Chemicals Computer Drugs Electrical Mechanical Other Total obs
  8. (1985). 44Table A5: Number of Rejections of No Home Bias using Sub-Samples Estimation Method: No Fixed E®ect Estimator Cuto® Year:
  9. (1985). 45Table A6: Number of Rejections of No Home Bias using Sub-Samples Estimation Method: Censored Fixed E®ect Estimator Cuto® Year:
  10. d N(0;): (A4) The proof of Theorem A.1 is omitted and it can be proved as in the proof of Theorem 1 of Lee (2007). The asymptotic variance can be consistently estimated by ^
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