"Cross-firm" Inventors and Social Networks: Localized Knowledge Spillovers Revisited
Bibliographic record
Abstract
The paper explores the role of inventors' mobility and social networks in generating localized knowledge flows. Using a sample of Italian inventors, we replicate Jaffe's, Trajtenberg's, and Henderson's [1993] test on patent citations and find similar results. We then control for the role of firm (inventors who move across, or do research for different companies), who generate personal self-citations and help creating social links across companies by entering various teams of inventors, which in turn will cite each others' patents. When controlling for personal self-citations, no localization of knowledge flows remains to be seen at the city or province level. What remains of localization effects at the regional level diminishes sensibly after controlling also for the social ties between inventors from cited, citing, and control patents. Knowledge flows thus appear to be localized to the extent that cross firm activity of inventors and the resulting social networks are also localized. The weight of personal self-citations suggests that frequent interpretations of localized knowledge flows as spillovers, that is externalities, may be misplaced. ? Inventeurs multi-f irmes ? et r?seaux sociaux : un r?-examen des externalit?s de connaissance localis?es? R?SUM?. Cet article explore le r?le de la mobilit? des inventeurs et de leurs r?seaux sociaux en tant que producteurs de flux localis?s de connaissance. ? partir d'un ?chantillon d'inventeurs italiens, nous r?pliquons le test de Jaffe, Trajtenberg et Henderson's [1993] sur les citations de brevet et nous obtenons des r?sultats similaires. Nous contr?lons ensuite pour le r?le des ? inventeurs multi-firmes ? (inventeurs changeant de firmes ou faisant de la recherche dans plusieurs firmes). Ils g?n?rent des auto-citations et permettent de cr?er des r?seaux sociaux entre entreprises de part leur pr?sence dans plusieurs ?quipes d'inventeurs, qui chacune citeront les brevets des autres ?quipes. En contr?lant pour les auto-citations, il ne reste plus d'effet de la localisation des flux de connaissance au niveau de la ville ou de la province. Les effets de localisation qui persistent au niveau r?gional diminuent sensiblement en tenant compte des liens sociaux entre inventeurs des brevets. Les flux de connaissance apparaissent ainsi comme localis?s ? l'?tendue des activit?s ? multi-firmes ? des inventeurs et des r?seaux sociaux qui en d?coulent. L'importance des auto-citations sugg?rent que les interpr?tations fr?quentes des flux de connaissances localis?s comme spillovers peuvent ?tre erron?es. Research for this paper has been supported by a grant provided by the Italian Ministry for Research and University (MIUR). We also gratefully acknowledge financial support from Bocconi University, Milan (Breschi) and the Italian Fulbright Commission (Lissoni); and the kind hospitality of the Sloan School of Management at MIT (Lissoni). The insightful comments of two anony mous referees and the editors have contributed to substantially improve an earlier version of this paper presented at the International Conference in Memory ofZvi Griliches, Paris, 25-27 August 2003. We also wish to thank participants at seminars and workshops held at Cespri (Bocconi University, Milan), UQAM (Montreal), Max-Planck Gesellschaft (Jena), ZEW (Mannheim), and Sloan-MIT (Cambridge, MA). We are of course responsible for any remaining error. * S. Breschi: Associate Professor of Applied Economics and Senior Fellow of CESPRI (Centre for Research on Innovation and Internationalization) at Bocconi university, Milan (Italy). ** Fr. Lissoni: Associate Professor of Applied Economics at the university of Brescia (italy),and Senior Fellow of CESPRI (Centre for Research on Innovation and Internationalization), Bocconi university, Milan (Italy). This content downloaded from 157.55.39.100 on Wed, 06 Jul 2016 05:20:29 UTC All use subject to http://about.jstor.org/terms 190 ANNALES D'?CONOMIE ET DE STATISTIQUE
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".