Tracing mobile inventors—The causality between inventor mobility and inventor productivity
Introduction
In 1998, Kai-Fu Lee, an expert on speech recognition and search technologies, moved to Microsoft to found the Chinese Microsoft research division in Beijing. In 2000, he became vice president of interactive services at Microsoft. In July 2005, Lee left Microsoft to work for Google. While working for Microsoft, Lee had signed a non-compete agreement, which barred him from working in research areas competing with Microsoft within 1 year after leaving the company. On 19 July 2005, after Google had announced that Lee would “serve as President of the company's growing Chinese operations”1 Microsoft sued Google and Lee. Microsoft claimed that Lee was violating his non-compete agreement, since working for Google would unavoidably lead to the disclosure of technical know-how to Google. On 28 July, the Washington State Superior Court enacted a preliminary injunction, which prevented Lee from working on Google projects that competed with Microsoft. On 22 December 2005, Google and Microsoft announced that they had entered into a private agreement, which put an end to the dispute between the two companies.2
The Google–Microsoft story gives first insights into possible consequences of a key employee leaving a firm. Kai-Fu Lee is an expert in the field of speech recognition and search technology. A move from Microsoft to Google not only weakened the position of Microsoft in this research field but also strengthened the position of the competitor. For Microsoft a legitimate reason to take court action. Given this story, it would be interesting to learn more about the mobility of productive inventors.
On the one hand mobility may effect productivity. R&D personnel3 are exposed to a new environment that affects their activity. For instance, Topel and Ward (1992) propose that mobility can lead to an increase of the match quality between employer and employee. A better match quality should lead to an increase in the inventor's own productivity. A move can, therefore, be interpreted as a search and sorting process to improve the employer–employee match. The importance of match quality is also confirmed by Jovanovic (1979) and Liu (1986). Furthermore, the inventor may profit from the knowledge of his new colleagues. This could also increase the productivity of an inventor in the after-move period. One might, therefore, expect that mobility increases productivity.4
On the other hand the causality may run in the opposite direction with productivity increasing mobility. The literature reveals that hiring a key inventor from another firm can lead to knowledge transfer (Arrow, 1962, Song et al., 2003). Firms characterized by a lower technology level can use this knowledge to catch up and thus are motivated to attract productive inventors (Gilfillan, 1935). In particular, the transfer of tacit knowledge, that is otherwise immobile, is facilitated by inventor mobility (Dosi, 1988). One could, therefore, assume that the causality runs from productivity to mobility: the more productive an inventor is, the higher the probability to observe a move. Nevertheless, one has to bear in mind that inventors who are very valuable to their employers may be treated with particular attention. Consequently, employers try to increase the commitment of these inventors to the firm by providing certain incentives. Gersbach and Schmutzler (2003), e.g., propose that firms can keep their employees from leaving by offering sufficiently high wages. Assuming that the firms are able to observe the quality of an R&D employee one would expect that valuable employees get job offers from competitors but mobility does not actually occur.
With the exception of Trajtenberg's work, no other research focusing on inventors has been carried out on the simultaneous relationship between productivity and mobility. Trajtenberg (2005) and Trajtenberg et al. (2006) addresses the causality between mobility and productivity of 1,565,780 inventors listed on U.S. patent documents. Overall, 216,581 (33%) of the inventors are movers, which means that these inventors changed their employer at least once. Results show that the patents of inventors who moved receive more citations. Additionally, inventors who are responsible for a valuable patent and who ex ante have more information as to the value of this patent compared to their employers are more likely to move. A possible explanation is that asymmetric information makes it difficult for the employer to impede mobility of high performing inventors. Especially if another firm has better information and appropriately compensates the inventor.
The following study improves on the current literature by (1) allowing for a simultaneous relationship of productivity and mobility, whereas existing research on inventors – with the exception of Trajtenberg (2005) – implicitly assumes causality to point in one way (from mobility to productivity or from productivity to mobility) and (2) including inventor characteristics as explanatory variables. One reason for the lack of literature dealing with this causality is the absence of appropriate data. First of all, a matching problem exists with respect to name and address information derived from the patent documents.5 Furthermore, bibliographic and procedural data hardly suffice to represent the most important determinants of productivity or mobility. Additional information is needed on the inventor himself, for instance, on the inventor's age or educational background. This paper makes use of data collected in a large-scale survey of 3049 German inventors who hold at least one granted European patent. The inventors were requested to provide demographic information as well as information on the R&D process underlying their patented invention. To trace the mobility and the productivity of each inventor over time, the EPOLINE database of the European Patent Office was used to search for all patent applications belonging to the 3049 inventors with priority dates between 1977 and 2002, resulting in a total of 39,417 EP patent applications.
To deal with the expected endogeneity problem caused by mobility and productivity, instrumental variables techniques will be employed. The results show that the level of education has no influence on inventor productivity. Making use of external sources of knowledge, on the contrary, has a significant effect on productivity. In particular, exploiting the knowledge from scientific literature increases inventive output. Finally, firm size has a positive impact on productivity. Firm size also influences inventor mobility, although negatively. Furthermore, the temporal concentration of inventive activity and the inventive environment are major determinants of mobility. The number of moves decreases with the temporal concentration of inventive activity and it is higher in large cities compared to rural areas. Overall, results confirm the simultaneous relationship between inventor productivity and inventor mobility. Whereas mobility increases productivity, an increase in productivity reduces the probability to observe a move.
The remainder of this paper is organized as follows. Section 2 contains the derivation of the hypotheses from the literature. A description of the dataset as well as the operationalization of the variables used in the empirical part of the paper are provided in Section 3. Section 4 provides descriptive statistics, followed by two models using instrumental variables techniques (IVREG and IVPROBIT) to analyze the causality between inventor productivity and inventor mobility. Finally, Section 5 discusses the estimation results and provides implications for further research.
Section snippets
Hypotheses
This section derives from the existing literature hypothesised determinants of inventor productivity and mobility.
Description of the data
Data were collected in the course of a European project (called PatVal) sponsored by the European Commission. Units of observation are inventors who lived in Germany at the time of application of the respective patents. Ten thousand and five hundred EP patents attributed to inventors living in Germany were chosen as a stratified random sample based on a list of all granted EP patents with priority dates between 1993 and 1997 (15,595 EP patents). A stratified random sample was used in order to
Descriptive results
Table 4 presents descriptive statistics. The final sample consists of 2409 different inventors,15 of which 37% changed their employer at least once. In the following, these inventors are classified as mobile. Each inventor is on average responsible for 14.7 EP
Conclusion
In this paper, the causality between inventor productivity and inventor mobility was analyzed using instrumental variable approaches to deal with the endogeneity problem between productivity and mobility. One of the key findings of this paper is that there exists a simultaneous relationship between inventor mobility and inventor productivity. Movers are more productive than non-moving inventors. In contrast, more productive inventors are less likely to move.
The results concerning the
Acknowledgements
I would like to thank the conference audience at the 33rd Conference of E.A.R.I.E. in August 2006 as well as the conference audience at the first Annual Conference of the EPIP Association “Policy, Law and Economics of Intellectual Property” in September 2006 for helpful comments. Special thanks go to Dietmar Harhoff, Jesse Giummo, Marc Gruber, Stefan Wager, and two anonymous referees for valuable comments. The survey responses used in this analysis originate from a coordinated survey effort in
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