1 Ipts is doing a valuable work identifying data sources and developing indicators of researchers mobility.

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1 Tracing researchers mobility. Is human and social capital circulating, being transferred and/or increasing through researchers mobility? Ana Fernández Zubieta The aim of this paper is to check if researchers mobility is a source of career development. It presents a typology of researchers mobility that aims to qualify the human and social capital acquired and transferred through this mobility. The empirical analysis shows that changes in job positions seem to act as a late advantage. Job mobile researchers, being less precocious they publish later- than the non- mobile ones, show a higher total and yearly average of publications and citations. However, different correlations within mobility and across field indicate that it is not possible to generalise the positive effect of changes in job positions. Intersectorial mobility is negatively correlated with total publications and citations for pure scientists. International postdoctoral mobility correlates positively with the more traditional proxies for researchers productivity publications and citations-. This could indicate that postdoctoral positions when they act as a source of mobility have positive effect on career development. The results show that different types of mobility have different effects across disciplines and career stages. INTRODUCTION Changes in the research system and its role in the society of knowledge (Castells 1996) have generated an increasing interest in the analysis of researchers mobility. The research system is becoming more dynamic with an increase of interactions among its members (e.g. Third mission of the university). The necessity of a better appropriation of knowledge and technology transfer makes researchers mobility a more valuable source for the development of the research system. At the same time, more dynamic research has it effect on scientists patterns of communication and career development. These changes have broadened the scope of the analysis of researchers mobility. Currently, it is necessary to adopt a systemic and dynamic perspective of researchers mobility to be able to analyse the changes and relationships among the different dimensions involved in its study. Three main dimensions have received attention in the analysis of researchers mobility: geographical, intersectorial mobility, as a mechanism for knowledge and technology transfer - and career development or labour market. The systemic standpoint of researchers mobility aims to integrate the different dimensions involved in its analysis. Its dynamic aspect proposes not seeing mobility as a single event one-change, oneway - including possible sort and long term return opportunities. It is assumed that scientists mobility facilitates knowledge and technology transfer, creation of networks and productivity (OECD 2000, 2002 and EC 2001). All these assumed positive effects of scientists mobility are related to the embedded (Granovetter 1985 and Griliches 1973) character of scientists human and social capital. When moving, scientists can spread and increase their human (Schultz 1961, 1963, 1990; Becker 1962, 1964; Nelson & Phelps 1966 and Denison 1967) and social capital (Bourdieu 1986, Coleman 1988 and Burt

2 1997). These transferences and increments in human and social capital can have a positive effect on scientists performance, patterns of collaboration and career development. In this perspective, it is assumed that both the research system and individual researcher benefit from researchers mobility. However, there is not enough empirical evidence to support all these positive assumptions (Teichler 1996, Musselin 2004, Nerdrum & Sarpebakken 2006, Fontes 2007 and Cañibano et al. 2008). The insufficiency of evidence relies on several factors: lack of statistics, non-comparative studies and non-extensive evidence. Statistics on Human Resources devoted to Science and Technology (HRST) and Labour Force Surveys (LFS) were not developed to measure mobility at individual researcher level (Le Moillour et al. 2005). This drawback is greater in Europe where different national statistics collection practices also create problems of data compatibility between countries 1. Evaluations of specific programs that try to encourage researchers mobility are mainly qualitative and focused on mobile samples (e.g. Irvine & Martin 1980, Halfpenny et al. 1992, Teichler 1991 and Marin-Sampere et al. 1996). Therefore, they do not usually offer enough information to analyse the effects of mobile researchers against the non-mobile ones. Other sources of information concerning researchers mobility come from specific empirical approaches that try to analyse the relationship between mobility and knowledge and technology transfer. Currently, these studies are scarce and are mainly focused on the American biotechnological sector (e.g. Zucker et al. 2002). Nevertheless, the limitation of scope to a sciencedriven sector makes the generalisation of their results difficult (Powell et al. 2005). In Europe and with a broader scope - beyond the biotechnological sector -, the empirical studies that have tried to study the implications of researchers mobility for knowledge and technology transfer (e.g. Crespi et al. 2007) and researchers career development (e.g. Mangematin 2000 and Cruz-Castro & Sanz-Menendez 2005a) offer a more cautious vision of the positive effects of increased researchers mobility. Scientists mobility has been defined as a complex and multidimensional-multidirectional event (Meyer 2001, Ackers 2005, Fontes 2007, Cañibano 2008). It has been claimed that there is not enough theoretical development (Ackers 2005). This paper tries to shed light on some of the difficulties in the analysis of researchers mobility by reviewing some of the new trends in its analysis. The review of the literature particularly highlights the cognitive aspects. These cognitive aspects relate to the embedding of human and social capital in the dynamics of production and dissemination of knowledge. A typology of researchers mobility is proposed at the end of the theoretical section of the paper. The empirical analysis is based on a database that includes detailed information regarding employment patterns, patenting and publishing activities of a sample of UK academic researchers since they received their Doctorate. The structure and time span ( ) of the database allows the study of the geographical, intersectorial and career development dimensions of researchers mobility. The complexity of the subject and the originality of the data allows this paper to provide preliminary evidence about the relationship between researchers mobility, 1 Ipts is doing a valuable work identifying data sources and developing indicators of researchers mobility.

3 academic productivity and career development. The theoretical background provides a framework that integrates the contributions of the economic and sociological approaches to the analysis of researchers mobility. Through them it aims to qualify the human and social capital acquired and transferred through researchers mobility. The paper is divided into four sections. Section one presents the theoretical background. It reviews the geographical aspects, knowledge and technology transfer and the career development dimension of researchers mobility. Section two introduces data and methodology applied in the case study. Section three presents some descriptive statistics. Section four analyses the correlation between different conceptualisations of researchers mobility and diverse proxies for researchers productivity publications, citations and patents-. Finally, the conclusion summarises the results of the study. 1. THEORETICAL BACKGROUND This section reviews some of the literature on researchers mobility. It is focused on the geographical, intersectorial and career development dimensions of such mobility. It highlights the positive and negative cognitive aspects of researchers mobility. Cognitive aspects are the ones that relate embedded human and social capital to the dynamics of production and dissemination of knowledge. The aim is to assess whether the embedded human and social capital is circulating, being transferred and/or increasing through researchers mobility. The section ends proposing a typology for the analysis of researchers mobility. 1.1 Geographical dimension. Migration into a human and social capital process The initial flow of scientists focused on the analysis of the geographical dimension of researchers mobility in terms of efficiency as per neoclassical economics. The concept of the brain-drain appeared in the 60 s in a report by the Royal Society of London. It referred to the migration of British engineers and scientists to the United States (Rhode 1991). Currently the concept refers to the unidirectional migration of skilled people from less developed to more developed countries or regions. The brain drain-gain debate has focused on the benefits and losses for the sending and receiving countries or regions. In the 70s, the laissez passer of the dominant cosmopolitan view defended the compensation and overall efficiency of migrations (Johnson 1968, Berry-Soligo 1969 and Grubel & Scott 1977). Claiming a broader perspective, Patinkin (1968) criticised the analysis of the problem in efficiency terms in favour of a more complex study of researchers migrations. This perspective aims to take into account the failure of certain regions to reach specific productive factors. Recent studies support this demand for a more complex study of geographical researchers mobility (Regets 2001 and Nerdrum & Sarpebakken 2006) by considering productive and educational factors and opportunities of career development (Gaillard & Gaillard 1998). The increased return of scientists to their countries of origin (Saxenian 1999) opened the discussion to a more

4 dynamic analysis of geographical mobility. The brain circulation concept (Mahroum 1998 and Johnson & Regets 1998) addresses geographical mobility as a two-way process in which more attention is paid to the benefits that return to the sending countries (Meyer 2001, Barré et al. 2003, Ackers 2005 and Moguerou 2006). The development of international communications makes geographical mobility a not necessarily physical and not a one-way process. Or in other terms, from a drain to a brain process. Considering the brain effect or cognitive effect of geographical researchers mobility, the sojurn abroad is not considered a migration. It is mainly considered as a human and social capital process in which individual and country (or) region could benefit from present and future returns. The improvement of the communications and the relevance of international scientific networks offer a positive image of geographical researchers mobility. It is assumed that countries and researchers could benefit from geographical mobility 2 (Mahroum 2000). The globalisation of the researchers community gives more relevance to the human and social capital component of geographical mobility - brain or cognitive effect -. A link between geographical mobility and the gains of human 3 and social capital has always existed. The early international travels of scientists exemplify the historical relevance of the brain side of researchers geographical mobility. However, a dynamic international community of researchers makes the brain effect of the geographical dimension of mobility more relevant. In the same way, current changes in the research system make more important the human and social capital cognitive components of the intersectorial researchers mobility. 1.2 Intersectorial dimension. Knowledge and technology transfer through embedded human and social capital mobility The necessity of improving the knowledge and technology transfer has created an increased interest in researchers mobility. The embedded character of knowledge especially its tacit part- gives researchers and inventors specific human and social capital that makes its movements more relevant for the dynamics of knowledge production and dissemination. In the knowledge transfer process more attention has being paid to other mechanisms of knowledge transfer like patents (Jaffe 1989 and Henderson et al. 1998), publications (Crespi & Geuna 2004), investments or, more recently, spin-offs (Bozeman 2000 and Mowery & Shane 2002). Less attention has been given to highly qualified human resources as a mechanism of knowledge and technology transfer (Crespi et al. 2007). Almeida & Kogut (1999), Rosenkopf & Almeida (2003), Palomeras (2004) and Møen (2005) study the agglomeration effect of knowledge and mobility. They pay attention to the highly skilled labour mobility among firms. Considering intersectorial mobility, Zucker et al. (2002) study the probability of an academic star moving into industry. Crespi et al. (2007) analyse the probability of inventors of moving into industry in a European context. These studies show the relevance of the embedded human and social capital for the knowledge and technology transfer process and the conditions that affect the probability of moving from academia to industry or from firm to firm. 2 Teichler (1996) points the question of how long the length of the stay should be in order to make it beneficial. 3 For a historical analysis of researchers mobility see Dedijer (1968) and Moguerou (2006).

5 Considering the cognitive aspects of researchers mobility, mobility is a source of knowledge and technology transfer as well as a source of spillovers. Mobility of highly skilled people could be a threat for firms and a disincentive for their investments in innovation (Cooper 2001). There are several articles focused on the problem of spillover generated by mobility (Pakes & Nitzan 1983, Zucker et al. 1998, Cooper 2001, Møen 2005). These studies investigate the problem of spillover generated by mobility compatible with private investments and innovation through different mechanisms: special contracts (Pakes & Nitzan 1983), early wage compensation (Møen 2005), equilibrium (Cooper 2001) or knowledge characteristics that create natural excludability (Zucker et al. 2002). Then, compatibility between mobility, spillovers and private investments, offers a positive view of mobility where the focus is placed on the cognitive advantages of researchers mobility. The importance of intersectorial relationships for research development is not a new phenomenon. The birth of the Big Science (Price 1963) and the necessary collaboration between government, university and industry pointed out the relevance of intersectorial collaborations for research development 4. Several authors in the sociology of science became interested in the consequences of intersectorial job mobility. The works of Marcson (1960), Krohn (1961), Kornhauser (1962) and Hagstrom (1965) analysed the role strain problem caused by the job transitions between an academic environment to a business one. They focus on the problem of adaptation because of different norms and patterns of behaviour between different research sectors. However, these works do not analyse the relationship between mobility and knowledge and technology transfer. They focus on the normative short-term effect of one academic to industry job change. Even though neither the cognitive aspects of geographical nor the intersectorial dimension of researchers mobility are a new phenomenon, changes in the research system make these aspects more relevant. At the same time this cognitive aspect of mobility makes a more dynamic perspective of researchers mobility necessary. This implies not seeing researchers mobility as a one-way process, rather, taking into account the short and long term return opportunities. This cognitive consideration of the geographical and intersectorial dimensions of mobility also has its effect on the conceptualisation of researchers mobility. Multiple changes in job positions and the geographical and intersectorial character of these changes has to be considered in order to assess the possible return opportunities. In the same way, considering the possible return advantages of geographical and intersectorial mobility makes it necessary to examine other mechanisms that help this purposes. International collaborations and intersectorial collaborations - network creation - need to be included as an important part of the analysis of researchers mobility (Zucker et al. 2002). Consequently the relationship between the broad conceptualisation of mobility collaborations - and the traditional one - changes in job position - needs to be taken into consideration. However, its important to keep broad and narrow conceptualisation of mobility separated (Crespi et al. 2007) to avoid confusing the effects of different mobility types. 4 See Merton (1938) for an analysis of the socio-economic factors in the origins of the institutionalization of science.

6 1.3 Career development. International, intersectorial PhD. market and flexibility of researchers careers Although a PhD. is not a requirement for being defined as a researcher, it is an important step in the human and social capital acquisition process. A PhD. is a main stage in a researcher s career and an important source of human resources for innovation and economic development. Quite a lot of attention has been given to doctoral studies, analysing the entry, dropout and duration of PhDs. Fisher (1987) and James (1988) explain the negative consequences of dropping out and argue that a lowering of the dropout rates is important. However Manski (1989) and Hartog et al. (1989) do not consider dropping out as necessarily negative. Among the different factors that influence the indices of dropout, the nature of funding (Ehrenberg & Panangiostis 1995 and Ferrer de Valero 2001) or discipline have received special attention. Ehrenbergh (1992) summarises the work done in the supply side of academic labour markets during previous decades. However, factors derived from the new changes in the research system, like the role of foreign PhDs in labour markets, remain understudied (Ehrengerg 2003). The segmentation model in which a PhD. is mainly a prerequisite for the development of an academic career has focused the analysis of career trajectories of PhDs in academia (Cruz-Castro & Sanz-Menendez 2005b and Enders & Weert, 2004). Researchers careers trajectories in firms and academia have been studied separately by different disciplines with different approaches (Dietz & Bozeman 2005). Considering career trajectories of PhDs in academia, the first destination and the achievement of full-time permanent position (Carmichael 1988) has received special attention. Productivity, prestige or preferences and attitudes (Fox & Stephan 2001 and Freeman et al. 2001) are the main factors studied explaining the development of an academic career. Recently, more attention is given to the entry of PhDs into firms opening up the question of the circulation model and the flexibility of researchers careers (Mangemartin 2000, Zellner 2003, Enders 2005, Cruz-Castro & Sanz Menendez 2005b). However, especially in Europe, the study of career trajectories of PhDs is scarce (Enders & Weert 2004). The movements of PhD. holders into firms could be an opportunity for knowledge transfer but also an indication of a declining academic labour market. Ehrengerg (2003) sustains that increasing part-time, non-tenure track positions and declining public-private university salary rates remain understudied. These tendencies in the academic labour market indicate an increment of temporariness and declining working conditions for young researchers. The increasing number of postdoctoral fellowships has raised the question of its effect in researchers career development and productivity. The extension of the educational career ladder (Zumeta 1985) could be a source of temporariness and a cheap labour force for young scientists (Stephan 2005, Cruz-Castro & Sanz-Menéndez 2005a, Smith-Doerr 2006). This trend could create future problems in recruiting researchers (Stephan 2005 and

7 Enders & Weert 2004). Lack of autonomy and decreasing opportunities of specialisation (Stephan 2005 and Smith-Doerr 2006) are possible consequences of delaying tenured positions. Gaughan & Robin (2004) show that in the French case postdoctoral positions delay achieving a tenure position. Stephan (2005) warns of a possible relationship between scientists temporary job positions and decreasing scientists productivity 5. This indicates that the temporariness involved in postdoctoral positions could negatively affect scientists knowledge production and their career prospects. However, very few empirical studies 6 have focused their attention on the impact of postdoctoral positions on academic productivity and its relationship with career development. The effects of postdoctoral positions remain mainly in a theoretical stage. However, a postdoctoral stay is also a source of researchers mobility. As far as it is known by the author no study has analysed the effect of postdoctoral position as a source of mobility. Changes in the research system have created a new interest on the flexibility and reversibility of researchers careers. More attention has been demanded by (Ehrenberg 2003 and Enders 2005) and intersectorial (Mangemartin 2000 and Enders & Weert 2004) PhDs training experiences and prospects. The effects of these new tendencies on the research system and researchers careers have remained mainly in a theoretical stage (Enders 2005). In order to check the cognitive effects of these new trends it is necessary to check its repercussion on academic performance and its effects on career development. Figure 1. Cognitive aspects of embedded human and social capital researchers mobility Cognitive advantages and disadvantages of researchers mobility GEOGRAPHICAL INTERSECTORiAL CAREER DEVELOPMENT (-) Brain drain Spillovers Temporariness (+) Brain circulation Knowledge transfer Flexibility 1.4 Is human and social capital circulating, being transferred and/or increasing through researchers mobility? A systemic and dynamic perspective of researchers mobility is required in order to integrate the different dimensions of researchers mobility. The brain effect (cognitive effect) of geographical and intersectorial dimensions has been pointed out as a new trend in researchers mobility analysis. The cognitive effect makes it necessary to consider multiple, narrow and broad - conceptualisations of mobility where narrow involves changes in job position and broad means collaborations. The relationship between narrow and broad conceptualisations has been identified as one of the necessities of this new perspective. Also, it is necessary to 5 Other side effects are related to preference for applied research versus basic research. For an analysis of the consequences of the changing role of the universities see Geuna (2001). This problem is also pointed out by Stephan (2005). 6 Dietz & Bozeman (2005) consider the postdoctoral fellowships in their study of mobility and productivity. However, the coefficients for postdoctoral fellowships are not significant. Long (1978) alludes to the postdoctoral positions, but he includes them inside the PhD. students category. Davis (2005) suggests that could be a positive relationship, but he did not find a causal relationship.

8 consider the dynamic and systemic perspective in researchers career development. For a researcher to change job position and collaborate with other researchers and sectors is part of her or his career. Changes in the research system can make mobility collaborations or changes in job positions - more frequent. Researchers mobility could be affected by different national S&T training policies. Human resources management and labour markets promote different research trajectories (Gaughan & Robin 2004). Mobility can be a requisite of the system and create more mobility by itself (Mahroum 2000). However, the question remains whether there is any measurable cognitive effect - or return opportunities - of researchers mobility in career development. Addressing the relationship between mobility and career development would clarify the direction of the causality between productivity and mobility (See Figure 2 below). It is possible that the relationship between mobility and researchers productivity not only changes across different types of mobility but also across diverse career moments. This relationship is important in order to qualify the researchers movements. The cognitive dimension of researchers mobility assumes that they will spread and increase their human and social capital through mobility. The assumption in a broader interpretation sustains that transference and increments of human and social capital come from changes in job positions and collaborations, either geographical or intersectorial ones. The cognitive interpretation of researchers mobility - transference of embedded knowledge through researches mobility -, assumes that researchers move or collaborate because they have special human and social capital to be transferred. This is the interpretation of Zucker et al. (2002). They consider that knowledge transference and the innovation process are made by star scientists (Rosen 1981) who possess an embedded intellectual human capital. This thesis can be denominated as the elite hypothesis of the human and social capital of researchers mobility. Their interest in explaining the knowledge transfer dimension of researchers mobility focuses on analysing the researchers probability to move. This interpretation involves no assumption about the possible increments of researchers human and social capital through mobility and their effects on researchers productivity and career development. On the other hand the cognitive aspect of researchers mobility assumes that researchers movements increase researchers human and social capital. These increments of human and social capital could have a positive effect on researchers productivity. Dietz & Bozeman (2005) build their S&T Human capital theory (Bozeman et al. 2001) around the cognitive intersectorial dimension of researchers mobility and its effect on career development. They consider that job experiences through different sectors give access to new social networks that provide scientific and technical human capital that increases researchers productivity. According to these authors, intersectorial heterogeneity of movements increases scientists human and social capital and has a positive effect on scientists productivity. This can denominated as the diversity hypothesis of cognitive dimension of researchers mobility. However,

9 they do not find enough evidence to support the diversity hypothesis. They found that precocity - publications before PhD. - is the main factor explaining academic productivity. The number of years spent in industry has a positive effect on patent productivity. In their study they consider postdoctoral fellowships obtaining a nonsignificant negative effect. Figure 2. Productivity and mobility relationship This suggests that intersectorial diversity of job transitions and/or collaborations neither guarantees an increase of human and social capital, nor does it have a positive effect on researchers performance. This makes it necessary of qualifying researchers movements and the human and social capital acquired through them. It is also necessary to pay attention to the process of recognition of the human and social capital acquired through different movements. Different research sectors have different incentives and recognition systems. The qualification of the human and social capital should take this aspect into account considering different effects for different movements and proxies for research productivity. This work focuses on the cognitive advantages of researchers mobility. It pays special attention to the possible benefits that researchers mobility could offer for the circulation and transference of knowledge and the flexibility of researchers careers (Fig. 1). This strategy aims to test the different assumptions that are behind the policy recommendations that encourage researchers mobility. Changes in the research system emphasises the cognitive advantages of researchers mobility. The research system is becoming more international and intersectorial systemic and dynamic -. These changes require a more flexible research system. Part of this flexibility comes from researchers mobility, especially the geographical and intersectorial mobility. However, it does not mean the cognitive disadvantages of increased researchers mobility have disappeared. The advantages of researches mobility and the assumptions associated with them- should be checked controlling for its disadvantages. The cognitive aspects of researchers mobility link researchers performance with mobility (Figure 2). The link between researchers mobility and their performance is made in two different ways. One addresses the dissemination of embedded knowledge. The second focuses on individual knowledge production. In the two cases the direction of the causality between researchers productivity and their mobility is different. In the first case, causality goes from researchers performance to mobility. In the second case, causality goes from mobility to researchers performance. In the first case, mobility disseminates embedded human and social capital. In the second mobility increases human and social capital. In the first case, researchers move because they have a

10 special human and social capital to be transferred. In the second, they produce more because the have acquired special human and social capital through mobility. It can be said that the first question is more relevant for the knowledge and technology transfer the second for career development. This work suggests that in order to clarify the relationship between mobility and performance and the possible advantages associated with researchers mobility it is necessary to consider geographical, intersectorial dimensions of mobility across researchers career moments. This work tries to discriminate more between researchers mobility in order to, as a first step, qualify the human and social capital acquired through researchers mobility. This objective is achieved by several means. Firstly, all the conceptualizations of mobility consider only interinstitutional transitions which is a geographical dimension considering inter-institutional transitions. While postdoctoral mobility also includes a national geographical dimension. Secondly, the intersectorial dimension is considered by analysing changes in job positions between academia and industry. Thirdly, the career development dimension is taken into account by studying the relationship between job and postdoctoral mobility and precocity. Fourthly, postdoctoral positions are only considered if they are a source of mobility. This measure tries to control for the temporarily effect of postdoctoral positions. Finally, three proxies of academic productivity are used in order to test different effects for different proxies for research productivity publications, citations and patents -. Other means for the qualification of the human capital and social capital acquired through mobility are not considered in the conceptualization of mobility used in this work. However, the most important method of qualification of human and social capital should be carried out by a thorough analysis of the role of recognition in science. Science is a social system in which opportunities for research and its symbolic and material rewards for its inquiry tend to accumulate in few individuals and institutions (Merton 1968). This process leads to a structured system of production, access to resources and recognition. As in all the structured systems, mobility among different levels of scientific social structure is limited. Therefore, it is possible to use this limited social mobility to check the quality of the transitions. That is to say, transitions that allow access to a higher level of the scientific social structure would have a positive effect on researchers performance. In this work the role of recognition is only considered by taking into account the different sectorial patterns of recognition and to explain different effects to different types of researchers movements. (See Figure 3 for a detailed typification of researchers mobility) Figure 3. Researchers mobility typification

11 2 DATA AND METHODOLOGY The study is based upon a sample of 66 UK university researchers from 34 academic institutions in 4 scientific fields: chemistry, physics, computer sciences and mechanical aeronautical & manufacturing engineering. The academic researchers included in the dataset are research active. At least once, they have received a project financed by EPSRC (Engineering and Physical Sciences Research Council). The sample is a subset of the one conducted by D Este et al. (2005) which aimed to provide a better understanding of the research collaboration between universities and industry. For the development of this analysis, new variables related to publication, patenting activities and employment patterns were included in the database. The focus on these disciplines aims to check differences on researchers mobility across pure and transfer sciences. Data on job changes was obtained using the CVs of the researchers. The method of collecting data using CVs in addition to ISI Web of Knowledge and European Patent Office (EUPTO) improves the accuracy to a great extent. Mistakes caused by similar names and initials and changes in researcher s institution affiliations are avoided. This method of collecting data shows the potential of using CVs (Dietz et al. 2000, Gaugan & Bozeman, 2002 and Dietz 2004) for analytical and evaluative purposes.

12 Two conceptualisations of researchers mobility are considered in this work. Real labour mobility. This conceptualisation considers changes in job positions between different institutions after the researcher s PhD. The changes in job positions within the same institution are not considered (e.g. a job change in the same university into a higher position). Where a researcher obtained a job in the same university where they obtained their PhD, they are not considered as mobile. Therefore, the geographical dimension of researchers mobility is considered. Only inter-institutional mobility is considered as qualifying researchers mobility. Each researcher was classified according to the different changes in job positions that occurred in his or her career. This classification no transitions, transitions to academia and transitions to industry was done according to the maximum heterogeneity of the job change. For example, if the researcher changed jobs between academia and academia and industry, it was considered as transition to industry. However, the information of the different changes in job positions - time sector and institution - is considered too. Detailed information for each change in job position covers a maximum of three changes in job positions per researcher. Postdoctoral mobility. This measure is operationalised by using postdoctoral fellowships or positions with a duration of 1 year or longer and in a different institution to the one in which the researcher did her or his PhD. Otherwise it is considered that the researcher does not use the postdoctoral fellowship as a source of mobility. Whether the postdoctoral stay takes place in the same country where the researcher did her or his PhD is taken into account. Then, the geographical dimension of mobility is considered by adding the national-international categories to the inter-institutional one. The control sample and mobile sample were built by matching each academic researcher with a mobile academic researcher in the same discipline and with similar academic experience and position. The selection of the matching variables follows previous studies on publication productivity (e.g. Long et al. 1993) and patent productivity (Breschi et al. 2007). However, this study uses academic experience - number of years since the attainment of the researcher s PhD. degree - instead of age as a matching variable. Having the information on the year of the PhD. degree attainment and considering that academic experience is more determinant than age (Levin & Stephan 1991), the study has focused on this variable. Focusing on academic experience allows the study to consider only active scientists across time. Each researcher with transitions in job positions between different institutions was matched with another non mobile researcher. When possible, researchers were chosen from departments with similar RAE score and size. RAE score and size are considered in a departmental level. This allows more accuracy with these institutional variables than using university as a source of information. Stricter rules for constructing the mobile and control group were not applied in order to avoid reducing the sample size.

13 The data of this study aims to provide a preliminary analysis of the relationship between researchers mobility and academic performance. The study aims to analyse this relationship by comparing mobile and non-mobile researchers performance. Other purposes such as analysing time trend in scientific productivity are beyond the scope of this paper. The database includes productivity records for all the researchers career ( ). However, this study is focused on yearly publications from 1981 to 2005 in order to increase the number of active researchers in the mobile and control group. The dataset is a panel that follows all academic researchers productivity - publications and patents - since 1981 until The dataset contains 1649 researcher-year observations. 3. DESCRIPTIVE STATISTICS The basic descriptive statistics are summarised in Table 1. The researcher typically is a male - 92 % of the researchers are men - with an average years of academic experience. He is 42 years old and obtained his PhD. in % of the researchers are pure scientists and 32% of the researchers of the sample are Professors. 39% of the researchers work in departments with more than 40 people. Most of the researchers works in a department with a Research Assessment Exercise (RAE) score of 5 or 5*. 64% of the researchers work in a department with this RAE score level. 24% of the mobile researchers have intersectorial mobility - they have previous job experiences in industry -. 65% of the researchers used the postdoctoral position as a source of mobility. The average researcher has moved at least once. Researchers have an average of 2.30 yearly publications. They patent a total average of 0.70 patents. The average researcher receives a total average of 1,314 citations. As all the academic productivity proxies, the average of citations is very high but skewed. The average researcher publishes 1.74 articles before finishing the PhD. He publishes first 0.33 years before finishing the PhD. The average researcher registers his first patent years after finishing the PhD. Table 1. Descriptive statistics Variable Definition Obs Mean Std. Dev. Min Max gender Gender acadexp Academic experience (PhD.) age Age discipli Discipline (dummy) phdyr Year of PhD graduation 66 1, acadtitl Academic title (dummy) depsz Department size RAE Dep. RAE score (2001) jobmob2 Job mobility (intersectorial) postdmob Postdoctoral mobility (dummy) jobmn No. of changes in job positions pubs Yearly Publications ( ) pat Patents ( ) timescit Citations per researcher 63 1, , ,190 pubbefph No. of publications before PhD precocpub Publication precocity (yrs. bet. PhD. and 1st pub.) precocpat Patenting precocity (yrs. bet. PhD. and 1st pat.) Mobile researchers tend to change job positions between different institutions more than once. If the number of

14 changes in job positions is considered, 69.4% of the mobile researchers move twice. This pattern is the same across research fields where there is no a single researcher with only one change in job position % of mobile researchers move three times in their research career. If the differences across fields are considered, researchers of applied sciences move more times than researchers of pure sciences. Mobile applied scientists move three times more often than pure scientists. However, the number of observations makes it impossible to Research Field Sector of the changes in job positions Academia Intersectoral Total Pure sciences 54 No. of changes in job positions 3 57 Research Field 70.1% 0 3.9% % Applied sciences Pure sciences 18.2% % % Total % 952.8% 16.7% 77 Applied sciences 88.3% % % % 11.1% 11.1% Total % 69.4% 30.6% check for the independency of the events. Table 2. Distribution of academic researchers by no. (and %) of changes in job positions by field Table 3 presents the changes in job positions considering the sector in which the change in job position takes place. In this work, intersectorial changes are the ones that entail changes in job position from academia to industry or vice versa. Governmental positions are not included in this work. Academic positions include job experiences in Research Centres. Researchers change job positions 77 times in total. The majority of them are inter-institutional academic transitions. 88.3% of the changes in job positions are between academic institutions against 11.7% of the changes in job positions that are intersectorial. Changes in job positions of pure scientists tend to be more intraacademic compared to the intersectorial changes of applied scientists. As the knowledge and capabilities of applied sciences - or transfer sciences - have more direct applicability to industry, it is expected that transfer sciences use researchers mobility more as a source of knowledge, capabilities and technology transfer. However, the number of observations in several cross-categories makes it impossible to check if the expected and observed frequencies are significant. Table 3. Distribution of number (and %) of changes in job positions by field 7 Take into account that Table 2 and 3 include changes in job positions before 1981.

15 4. ANALYSIS In this section, the academic productivity of mobile researchers and controls over the period is analysed. Firstly, a study of the averages of cumulative publications of different proxies for academic productivity - publications, patents and citations - is presented across job and postdoctoral mobility. Secondly, a study of the yearly publications over the period is carried out. Thirdly, an analysis of the precocity on publications and patent is considered. 4.1 Cumulative academic productivity The mean differences of cumulative publications from 1981 to 2005 show a higher value for the mobile researchers compared to their controls (Table 4). Mobile researchers publish a mean of articles against of the controls. The difference is also positive between mobile and control group means across fields. Mobile pure scientists publish an average of whereas controls pure scientists publish an average of For the case of applied sciences the difference between mobile and controls is against The differences between mobiles and controls cumulated publications are significantly different in total and in pure sciences, but not in applied sciences. If the sector of the job transitions is considered, the effect of sectorial mobility on average publications is different across fields. Researchers with intersectorial mobility of pure sciences publish less than researchers with academic transitions. However, applied researchers with intersectorial mobility show a higher average of publications. Nevertheless, the differences in means are not significant across fields. The significance of the total average difference between intersectorial mobile researches and academic mobile researches is an effect of the overrepresentation of pure scientists in the sample. Mobility is correlated with higher average of publications but the effect of intersectorial mobility on publication rates differs across fields. Academic mobility is correlated with a higher average of publications for pure scientists. Table 4. Cumulative publications Mobil Group vs. Control Group, by field and sector

16 Mobil Group Control Group Academic Intersectorial Total Total Research Field Pure sciences Mean * * a* N Std. Dev Applied sciences Mean N Std. Dev Total Mean * * * * a** N Std. Dev *-**-*** Mobil-Control distribution difference significant at (Mann-Whitney test for nonparametric data) a* Academic-Control Group significance The averages of citations present a similar pattern as for publications (Table 5). Mobile researchers show a higher average of citations than controls. If the sectorial mobility is considered across fields, researchers with academic transitions show a higher average of citations than researchers with intersectorial transitions for pure. The differences are significant for intesectorial mobility of pure scientist. The significance of the total sectorial mobility should be carefully considered as the effect of sectorial mobility differs across fields. Mobility is correlated with higher citations average but intersectorial mobility is negatively correlated with citations for pure scientists. 8 Mobil Group Control Group Academic Intersectorial Total Total Research Field Pure sciences Mean * * N Std. Dev Applied sciences Mean N Std. Dev Total Mean ** ** a* N Std. Dev *-**-*** Mobil-Control distribution difference significant at (Mann-Whitney test for non-parametric data) a* Academic-Control Group significance Table 5. Cumulative citations Mobil Group vs. Control Group, by field and sector 8 The average on citations is not controlled for the period

17 Considering the total average of patents (table 6), mobile researchers patent more than controls in applied sciences. As was the case for publications and citations, intersectorial mobile researchers patent more than academic mobile researchers for applied sciences. This result shows that the relationship between intersectorial mobility and patent productivity could be independent of field particularities. The correlation between job experiences in industry and patent activity is congruent with the results obtained by Dietz & Bozeman (2005). However, without a temporal analysis of the patent productivity and industrial experience taking industrial job experience as an independent event - it is impossible to know the direction of the causality. That means, knowing whether the experience in industry is previous or subsequent to the patent activity. Crespi et al. (2007) show that patent activity and its quality increases the probability of a move into industry. It would be interesting to know if the contrary is also the case. Nevertheless, the differences in means are not significant. Table 6. Cumulative patens Mobil Group vs. Control Group, by field and sector Mobil Group Control Group Academic Intersectorial Total Total Research Field Pure sciences Mean N Std. Dev Applied sciences Mean N Std. Dev Total Mean N Std. Dev *-**-*** Mobil-Control distribution difference significant at (Mann-Whitney test for nonparametric data) - Postdoctoral mobility The correlation between postdoctoral mobile researchers and academic productivity is similar to that obtained for changes in job positions job mobility. Mobility in either postdoctoral or job is correlated with higher publication and citation productivity. Patent productivity is similar across the different categories of postdoctoral mobility. This result could be relevant for the study of the researchers mobility as a vehicle for knowledge transfer. The result indicates that different researchers mobility have different effects on patent activity. Postdoctoral mobility seems positively correlated to more traditional indicators of academic productivity publications and citations -. However, it is necessary to check if there is an increment of post-doctoral positions with time. If postdoctoral

18 positions become more frequent, postdoctoral mobility could be an indicator of a younger researcher 9. The live course effect and the increasing rate of publications could affect the result obtained for postdoctoral mobility. It is worth noticing that the nationality of the postdoctoral stay is important. If the postdoctoral stay takes place in a different country from which the researcher did his or her PhD., the averages of all the proxies for academic productivity are higher. If it is assumed that the internationality of the postdoctoral stay is an indicator of a stay in an institution with higher status, it can be considered that international postdoctoral fellowships represent a qualify transition. International postdoctoral mobility is positively correlated with more traditional proxies of academic productivity - publications and citations -. Postdoctoral mobility is less relevant than job mobility when explaining patent activity. Table 7. Cumulative publications, patents and citations by postdoctoral mobility Total Postdoctoral mobility Publications Patents Citations* No postdoc Mean N Std. Dev , National postdoc Mean , N Std. Dev , International postdoc Mean * *** 1, N Std. Dev , Total Mean , N Std. Dev , *-**-*** Mobil-Control distribution difference significant at (Kruskal Wallis test for non-parametric data) 4.2 Yearly academic publications The higher academic publication rate of mobile researchers is supported when analysing yearly publication data. Yearly academic publications offer a more accurate measure as it provides a picture of the evolution of the averages on publications of mobile and control group across different years and career moments. In this sense it is more precise than the cumulative academic productivity presented in the previous section. Although the results provide evidence of a positive correlation between mobility and reseachs performance they are inconclusive in terms of causality. Changes in job positions should be considered as independent events in order to have a clearer idea about the relationship. 9 The researchers with postdoctoral mobility have a similar average of academic experience than the researchers that do not use postdoctoral mobility as a source of mobility.