Environment and Planning A 2011, volume 43, pages 2761 ^ 2777
Is the grass greener on the other side of the fence? Graduate mobility and job satisfaction in Italy Simona Iammarino, Elisabetta Marinelli
Department of Geography and Environment, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, England; and SPRU, University of Sussex; e-mail: [email protected]
European Commission, Joint Research Centre, Institute for Prospective Technological Studies, C/ Inca Garcilaso 3, 41092 Seville, Spain; and London School of Economics and Political Science; e-mail: [email protected]
Received 4 March 2011; in revised form 8 June 2011 Abstract. This paper explores the links between spatial mobility and job-related well-being for young Italian graduates. Theoretically it posits that mobility and job satisfaction can be related indirectly, as migration may provide access to new or better job opportunities, and directly, as mobility generates expectations on the outcome of the move. Methodologically it applies sample-selection ordered logit to a survey of graduates conducted by the Italian National Statistical Institute (ISTAT). The paper investigates how personal characteristics and employment features, together with migration behaviour, impact on several domains of job satisfaction, comparing the graduates from Southern regionsöie, the backward Mezzogiornoöto those of the Centre ^ North of Italy. Our most novel results indicate that, whilst indirect effects are qualitatively similar for both Southern and Centre ^ Northern graduates, direct effects are not. This highlights that geography affects satisfaction by shaping individual expectations, adding another dimension to the long-standing debate on Italian spatial inequality.
1 Introduction ``Is it worth it? Am I going to be better off?'': all migrants have confronted such questions, and this paper addresses them by analysing in particular how spatial mobility influences self-reported job satisfaction. There are both theoretical and policy motivations underlying this study. Indeed, whilst the dominant approach to migration has primarily targeted its objective economic gains, such as employment opportunities or salary (Hicks, 1932; Sjaastad, 1962), by looking at job-related well-being we are able to appreciate its subjective consequences: that is, the individual graduate's feelings about her or his move. Furthermore, whilst understanding what makes an employee fulfilled is per se a valuable pursuit, recent evidence has shown that a satisfied workforce is beneficial both at the firm level (eg, Harter et al, 2002) and at the regional level (eg, Rodr|¨ guez-Pose and Vilalta-Bufi, 2005). Our focus is on the interregional flows of university graduates, a segment of the population that has attracted increasing attention. As graduates are a crucial mechanism of knowledge transfer from university to the labour market, scholars have explored their behaviour extensively, looking at the spatial and individual determinants of their mobility (ie, Faggian et al, 2006; 2007a; 2007b; Greenwood, 1972; Jauhiainen, 2011; Lehmer and Ludsteck, 2011; Venhorst et al, 2010; 2011) as well as at the consequences of their relocation (Faggian and McCann, 2006; 2009). Not much attention, however, has been paid to the implication of mobility on their job-related well-being, and this paper addresses this gap.
ô Corresponding author.
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As we look at the Italian case, the country's striking subnational disparities must be taken into account. Building on the insights of Biagi et al (2011), we compare two migration subsystems in Italy: the South to Centre ^ North flow (ie, from the least developed to the most developed regions of the country) and the Centre ^ North to Centre ^ North flow (ie, within the most developed area of the country). In the first, migrants embark on a more complex journey, not only because of the larger geographical distance, but because of the greater social and economic distance to which they have to adjust. For both geographies we compare the level of well-being of mobile and nonmobile graduates. In addition, we look at four domains of satisfaction: two accounting for employment features related to the short term (satisfaction with job tasks and with economic treatment) and two accounting for long-term aspects (stability and security, and career opportunities). The paper is organised as follows. Section 2 summarises the background literature on both the links between higher education and job satisfaction (section 2.1) and those between migration and job satisfaction (section 2.2). Section 3 describes the specificities of the Italian case. Section 4 explains the methodology, covering dataset (section 4.1), econometric technique (section 4.2), and model specification (section 4.3). Section 5 provides some descriptive statistics, whilst section 6 reports and discusses the results of the empirical analysis. Section 7 concludes, highlighting some implications for public policy. 2 Background literature 2.1 Education and job satisfaction
Unlike psychologists and sociologists who, in studying the determinants of job satisfaction, have taken into account the role of organisational structures and personal traits as well as job characteristics (eg, House et al, 1996; Judge et al, 2002), economists have focused mainly on the latter (eg, Clark and Oswald, 1994; 1996; Freeman, 1978; Hamermesh, 1977). This literature has pointed out that wage and work hours are positively or negatively related to job satisfaction, respectively (Clark and Oswald, 1996; Lydon and Chevalier, 2002), and that job security and job interest are more relevant than wages in determining overall well-being (Clark, 1996). Interestingly, scholars have also investigated gender differences in job satisfaction (eg, Clark, 1997; Sloane and Williams, 2000; Souza-Poza, 2000) In particular, Clark (1997) finds that women, who on average earn less and occupy lower positions, tend to be more satisfied than men due to their lower expectations about career prospects. The main focus of the present work is on the relationship between educationö specifically university education öand workers' job-related well-being. Intuitively, the two variables should be positively related as, at least in principle, higher education should provide access to well-remunerated jobs, with good employment conditions and the possibility for professional development (Ross and Van Willigen, 1997). However, the empirical evidence is not fully consistent with this intuition (Fabra and Camison, 2009). Several studies have found a negative impact of education on satisfaction (eg, Clark, 1996; Clark and Oswald, 1996; Gazioglu and Tansel, 2006); a few others have shown that the relationship is either positive or not significant (eg, Idson, 1990; Ross and Reskin, 1992); whilst a third group of contributions has pointed out that the impact of education varies across domains of satisfaction (eg, Groot and Maassen van den Brink, 1999; Vila and Garc|¨ a-Mora, 2005). These contrasting findings seem to be resolved by distinguishing between direct and indirect effects of education (Fabra and Camison, 2009). A higher qualification level influences satisfaction indirectly by giving access to better employment opportunities, and directly by generating higher expectations. This implies that, in an empirical setting,
Graduate mobility and job satisfaction in Italy
when the job characteristics (ie, the indirect effects) are controlled for, a negative effect of education on job satisfaction indicates that the individual's expectations have not been met. These observations are also supported by a large body of research highlighting that overeducated workers (1) are less satisfied than workers with a correct education ^ job match, precisely because their expectations and ambitions are not being fulfilled (Allen and van der Velden, 2001; Battu et al, 1999; Cabral Viera, 2005; Hersch, 1991). Interestingly, Quinn and Rubb (2005) have also found that a job ^ education mismatch is itself an incentive to migrate, precisely because of the dissatisfaction and worse economic rewards it generates. When it comes to graduates, understanding the role of education means evaluating how the university experience has facilitated entry into the labour market. The rather sparse literature on the topic has again confirmed the importance of the education ^ job match (Mora et al, 2007; Schomburg, 2007; Vila and Garc|¨ a-Mora, 2005). At the same time, it has been highlighted that the field of study, by impacting on job opportunities, also influences job satisfaction: in particular, Mora et al (2007) have found that graduates from scientific and engineering disciplines tend to be relatively more satisfied. Scholars have also indicated that job-related well-being is higher for those who enjoyed their university experience; that it increases with the level of parental education (Mora et al, 2005; 2007; Schomburg, 2007); and that it is not affected by the mark at graduation (Mora and Ferrer-i-Carbonell, 2009). Remarkably, even for recent graduates, there are clear gender imbalances. However, whilst studies covering the whole working-age population found women to be more satisfied than men, due to their lower expectations, the opposite holds in this case: female graduates tend to be less satisfied than their male colleagues as they have the same ambitions and yet face discrimination and achieve lower results (Mora and Ferrer-i-Carbonell, 2009). 2.2 Migration and job satisfaction
Spatial mobility can theoretically lead to higher levels of job (and life) satisfaction. This positive link is effectively implicit in traditional economic theory, where migration results from a utility-maximisation process in which the benefits of moving outweigh the costs (Ziegler and Britton, 1981). Furthermore, it has been empirically demonstrated that migration leads to higher extrinsic (earnings) and intrinsic (greater autonomy) job-related rewards (Greenwood, 1975), which are key elements of work well-being (Gruenberg, 1980; Janson and Martin, 1982). Despite these clear connections, the actual job satisfaction of educated migrants has rarely been investigated. By looking more in general at overall subjective satisfaction, Martin and Litcher (1983) find little evidence that mobility translates into increases in self-reported well-being, whilst De Jong et al (2002) show that life satisfaction varies across migration typologies (such as single or repeated movers), and also depends on how recent the move itself was. Lundholm and Malmberg (2006) argue that satisfaction also depends on the migrant's expectations and motives. This scattered evidence suggests that migrants' specific characteristics are relevant in explaining satisfaction, and encourages further research in the area. Drawing upon Fabra and Camison (2009), we apply here the distinction between direct and indirect effects to spatial mobility. Specifically, our first hypothesis is that mobility can influence job satisfaction indirectly, by allowing (or impeding) access to new and more rewarding jobs, and/or directly, by creating expectations what the outcome of the move. In particular, unmet expectations should generate negative direct (1) Overeducated
workers have a level of education higher than their job requirements.
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effects; met expectations should effectively be captured by indirect effects, as they are embedded in the job characteristics; and surpassed expectations should give rise to positive direct effects. In our empirical exercise below we will investigate such effects by considering in particular the role that geography (ie, the area of origin of the graduate) plays in influencing both job accessibility and individual expectations. 3 Italian graduates: satisfaction and interregional mobility As is well known, Italy is characterised by sharp socioeconomic regional differentials, with the South (or Mezzogiorno) lagging behind the rest of the country; the dualistic nature of the country has long historic roots and has caught much scholarly attention (among a vast literature, see Barca, 2006; Iammarino, 2005; Mauro and Podrecca, 1994; Paci and Pigliaru, 1998; SVIMEZ, 2007; 2008; 2009; Vaccaro, 1995; Viesti, 2003). Whilst the typical Italian dualism is not reflected in higher education attainment, with the Centre ^ North having levels of higher education similar to those of the Mezzogiorno (eg, Di Liberto, 2007; Piras, 2005; 2006), (2) there are large differences in the employment opportunities open to graduates from different areas, which suggests that their levels of satisfaction in the labour market may also differ. First of all, Southern regions seem to have weaker conditions in terms of both selection mechanisms and level of satisfaction with the university experience (eg, D'Antonio and Scarlato, 2007; Ghignoni, 2005). Moreover, not only are the jobs for graduates available in the South fewer and less secure (ISTAT, 2005a; 2006), but they are also not accessible by merit alone as in the area, characterised by low social mobility, the family of origin has a strong influence on the individual's employment outcomes (Checchi and Peragine, 2005; Coniglio and Peragine, 2007). As a result of this social rigidity, graduates from Southern universities struggle more than their conationals when entering the labour market: whilst 80% of laureati between 25 and 34 years old in the North are employed, the proportion is just above 50% in the South (SVIMEZ, 2008). Furthermore, graduates from Southern universities, three years after finishing their studies, have lower earnings than their Northern colleagues (Brunello and Cappellari, 2008). These findings are reflected in many empirical studies, which point out that tertiary education in the Mezzogiorno had a weak or null impact on regional economic growth (Baici and Casalone, 2005; Di Liberto, 2007; Piras, 1996). Furthermore, they indicate that the Southern industrial structure, which does not enable highly skilled people to find adequate opportunities, is one of the causes of the increasing brain-drain from the Mezzogiorno, a phenomenon that has recently caught a great deal of attention (Coniglio and Prota, 2008; Di Pietro, 2005; Piras, 1996; 2005; 2006; Piras and Melis, 2007). To give an idea of the dimension of the phenomenon: the share of highly educated (university-level) migrants grew from 5.21% in 1990 to 13.29% in 2002 for the country as a whole, and the proportion of highly educated migrants in the Mezzogiorno went from 36.4% to 42% in the same period.(3) As for recent graduates, the share of those who, having studied in the South, moved to the North grew from 6.9% in 1992 to 22.2% in 2001; at the same time, the share of those from the South who studied in the North and stayed there also increased, going from 7% to 11.5% (D'Antonio and Scarlato, 2007). (2) Nonetheless, it must be noted that the largest cities of the Centre ^ North have a higher proportion of graduates than those in the South (ISTAT, 2005a). (3) These figures exclude migrants within regions. The source of data is the Italian National Statistical Institute (ISTAT) (various years): Iscritti e cancellati per trasferimento anagrafico fra comuni di residenza.
Graduate mobility and job satisfaction in Italy
All in all, this picture suggests that the relationship between spatial mobility and job satisfaction for Southern and Centre ^ North graduates is likely to show some differences. For graduates in the South, who may feel unable to fulfil their life and career ambitions locally, migrating towards richer parts of country may seem a more compelling choice, and may generate higher expectations than for those who graduate in the Centre ^ North. 4 Methodology 4.1 Data
The paper uses the Indagine sull'Inserimento Professionale dei Laureati (ISTAT, 2007) conducted by the ISTAT. The survey investigates the entrance of graduates into the labour market three years after they completed their studies. In what follows, we use the sixth edition of the survey, which was carried out in 2004 and refers to 2001 graduates. The dataset contains 26 006 observations, representative of the universe of 155 664 graduates. The Indagine is characterised by one-stage stratification by gender, university, and degree. Each of the surveyed individuals is attributed a sampling weight which allows one to build indicators representative at the level of the nation, the field of study, and, most importantly, the region of study and the current region of work. As we identify migrants as those whose region of study (origin) is different from the region of employment and residence (destination), (4) this ensures a spatially unbiased analysis. The Indagine provides graduates' self-reported satisfaction öranked on a 1 ^ 4 Likert scale, ranging from `not satisfied at all' to `very satisfied' öwith several jobrelated domains. We focus specifically on the following four: satisfaction with the tasks conducted at work (ie, the job-tasks domain) and with economic treatment, which give insights into the short-term aspects of employment; and satisfaction with job stability and security and with career opportunities, which give insights into fulfilment with respect to long-term career goals. The dataset also provides information on job characteristics, individual features and social background, university performance, and experience which, on the basis of the literature, are crucial to an understanding of job satisfaction (see section 4.3 below). 4.2 Econometric approach
Economic studies of job satisfaction have traditionally explored the effects of different personal and job characteristics on well-being through ordered logit or probit models (Greene and Hensher, 2010). Such an approach, however, ignores a potential selection bias as the self-reported level of satisfaction is observable only for those who are actually employed. Thus, if unobserved factors affecting the response (in the case here the level of satisfaction) are correlated with unobserved factors affecting the selection process (ie. whether graduates are employed or not) standard regression techniques deliver inconsistent estimators (Heckman, 1979). As migration can affect both employability and satisfaction, it seems particularly important to tackle this aspect and here we will do so through an ordered logit (ologit) model with sample selection [introduced by Miranda and Rabe-Hesketh (2006)] for all the domains (4) In our study, migrants do not include those who leave the region of study to go back to their home region (ie, returners), as these graduates' mobility pattern may be driven by different motives (see Marinelli, 2010). As the survey does not provide the home region of graduates previous to their university enrolment, identifying returners requires using other information from the survey. The Indagine identifies (1) whether the graduate left the home region to attend university, and (2) her or his current living arrangements. With this information we classified returners as those who (a) left their home region to study, (b) are currently living in a region different from the one they studied in, and (c) are currently living with their family of origin [see Marinelli (2010) for more details].
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of satisfaction.(5) This model, based on the Heckman selection procedure (Heckman 1979), estimates two equations simultaneously: one selection equation, which accounts for the probability of the graduate being employed; and one outcome equation, where the actual level of job satisfaction is studied. In this model, the indirect effects of migration are visible whenöcontrolling for all the other relevant characteristicsöthe migration coefficient is significant in the selection equation. On the other hand, direct effects are detected in the outcome equation: a positive (negative) and significant coefficient indicates that the expectations associated with the move have been (have not been) more than met, whilst a nonsignificant coefficient indicates that no direct effects have arisen. The model will be applied to study the effects of migration on satisfaction. We will first compare the level of satisfaction of graduates who move from the Mezzogiorno to the Centre ^ North with the level of satisfaction of those who remain in the South. Secondly we will analyse how migrants who move within the Centre ^ North feel compared with their peers who do not relocate. 4.3 Model specification
On the basis of the literature review, mobility behaviour, job characteristics, education ^ job matches, and other personal characteristics are included as determinants of satisfaction. At the same time, educational and social backgrounds, as well as individual characteristics, are taken into account in the selection equation as they determine employability. Therefore, the ologit models include: Outcome: SATISF f(MIGR, JOB CHAR, EDU JOB MATCH, UNI EXP, DISTANCE, INDIVIDUAL); Selection: EMP f(MIGR, (6) UNI, PAREDU, INDIVIDUAL), where MIGR is a dummy variable identifying migrants, and referring either to Southern (MIGR SO) or to Centre ^ Northern (MIGR CN) graduates; JOB CHAR is a vector of job characteristics; EDU JOB MATCH is a vector of variables identifying education ^ skill matches; UNI is a vector of variables identifying university background and performance; UNI EXP is a dummy variable identifying whether the graduate would enrol again in the same degree; it is used to understand whether the graduate was satisfied with the university experience; DISTANCE is the distance in 100 km between origin (region of study) and destination (region of work); we include this variable because moving further away from home may bear higher economic and noneconomic costs that impact on the level of satisfaction;(7) (5) To the best of our knowledge, this is one of the first studies to look at self-selection issues in relation to job satisfaction. Other authors (Luechinger et al, 2008) considered self-selection into different employment sectors and its links to job-related well-being. (6) Inserting migration in the selection equation effectively means considering it exogenous from the labour market. This assumption has been inconclusively discussed in the classic debate on ``whether people follow jobs or vice versa''. The interested reader is referred to Hoogstra et al (2011). (7) This variable takes a value of 0 for those graduates who remain in the region of study and has a positive value for those who leave the region of graduation. With this variable, in the analysis of Southern graduates, we are also able to control for the fact that some of them move within the Mezzogiorno. Whilst this South-to-South mobility is not at the core of our analysis, it may also impact on satisfaction and it is therefore appropriate to take it into account.
Graduate mobility and job satisfaction in Italy
INDIVIDUAL is a vector of other individual characteristics; PAREDU is a dummy variable that identifies whether at least one of the graduate's parents was educated to secondary or tertiary level. It captures the effect of social background on the graduates' level of satisfaction. The vectors of variables are described in detail here below. Job characteristics (JOB CHAR): SALARY is the monthly income of the graduate expressed in euros; PARTIME is a dummy variable identifying part-time jobs; PERMANENT is a dummy variable identifying permanent jobs. Education ^ job (mis)matches (EDU JOB MATCH): The variables identify whether the graduate is using her or his skills at work. It has been constructed by taking into account the following two questions from the survey: 1. Was the degree formally required by the employer to apply for the job? 2. Is the degree effectively needed for the job? Combining the two pieces of information, along the lines of Ungaro and Verzicco (2005) and Quintano et al (2008), we obtain a matrix of four possible education ^ job (mis)matches (see table 1). Table 1. Education ^ job (mis)matches. Was the degree formally required?
Was the degree effectively necessary to do the job? yes
OBJ MAT Objective education ± job match SUB MAT Subjective education ± job match
SUB OVR Subjective overeducation OBJ OVR a Objective overeducation
No a OBJ
OVR is the base category of the variable against which, in the regressions, the other three are compared.
A match or mismatch is defined as objective when the opinion of the graduate on the effective need for her or his qualifications is coherent with the formal requirements of the job. An objective education ^ job match (mismatch/overeducation) arises therefore when the graduate believes (does not believe) that her or his education level is effectively needed in the job and when the degree was (was not) also a formal requirement of the employer. Whenever the opinion of the graduate and the employer's requirement differ, on the other hand, a subjective match or mismatch/overeducation arises. Specifically, when a graduate feels that the degree is needed in her or his work, though the employer did not require it, the graduate is experiencing a subjective education ^ job match. When the graduate is in a job for which the degree was formally required but is effectively unnecessary he or she is experiencing subjective overeducation.(8) Overall, the worst education ^ job combination is experienced by the objectively overeducated, followed by the subjectively overeducated, the subjectively matched, and the objectively matched.
(8) Many indicators of education ^ job match and overeducation have been used in the literature: see Verhaest and Omey (2006) for an overview.
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Other individual characteristics (INDIVIDUAL): AGE is the age of the graduate; FEMALE is a dummy variable identifying whether the graduate is a female. University background (UNI): SCIENTIFIC is a dummy variable that identifies whether the graduate achieved scientific, engineering, or mathematics degrees; GRADE is the graduation mark. Appendix A1 summarises the variables included in the econometric models. 5 The geography of migration and satisfaction Of the 2001 cohort 74.1% of graduates were employed in 2004, and 19.6% of them had left the region of study (the proportion of interregional migrants on the whole graduate population was lower at 18.6%). As for graduates from the South, 61.9% were employed, and migrants to the Centre ^ North represented 20.3% of them (and accounted for 15.5% of total Southern graduates) Table 2 reports the proportion of total employed migrants who have moved between macro-areas. Over a quarter of total Italian graduates moved from the South to the Centre ^ North after university: in particular, 12% moved to the Northwest, 4.2% to the Northeast and 10.3% to the Centre. Remarkably, only 0.7% and 1.7% moved from the Northwest and Northeast, respectively, to the South, whilst those migrating from the Centre to the Mezzogiorno were 4.7% of the total. At the same time, those leaving the Northeast for the Northwest accounted for 10.6% of total graduate migrants, whilst only 3.9% followed the opposite direction.(9) Overall, Southern regions generated the largest number of migrants (33.5% of the total), whilst the Northwest was the macroregion receiving the largest share (37.1%). Table 2. Mobility matrix: percentage of employed migrants in the Italian total. Macroregion of study
Macroregion of employment
Northwest Northeast Centre South
8.0 10.6 6.4 12.0
3.9 9.1 4.7 4.2
2.3 2.9 6.3 10.3
0.7 1.7 4.7 5.7
2.1 1.5 1.6 1.2
16.9 25.7 23.8 33.5
Turning to the proportion of satisfied graduates (ie, the quite and very satisfied), we find that the extent of interregional disparities depends strictly on the domain of satisfaction. The regions of the North are the most rewarding in term of job tasks, whilst Southern regions lie, in this case compactly, at the opposite end of the spectrum: Sicilia has the lowest proportion (48.9%), with a striking differential from the most satisfied Valle d'Aosta (86.8%). When it comes to economic treatment the situation is less clear-cut. Lazio registers the lowest share of satisfied graduates, closely followed by Sardegna, Calabria, Campania, and Sicilia. A few regions in the South, though, have a fairly high proportion of satisfied graduates: Puglia, Abruzzi, Molise, and Basilicata outperform many regions of the Centre and the Northwest. This may be a bit puzzling, given that the average wage is lower in the Mezzogiorno (Barca, 2006): it may suggest, (9) We
are not exploring the behaviour of migrants moving from the Centre ^ North to the South.
Graduate mobility and job satisfaction in Italy
however, that graduates in different areas have different expectations about their economic treatment, which in turn impacts on their levels of satisfaction. All the regions of the Northwest and Northeast, with the exception of Valle d'Aosta, have high shares of graduates satisfied with job stability and security (Lombardia has the highest, at 78.2%), whilst in the South (with the exception of Puglia) all regions have less than 66% satisfied graduates. Again the Northern regions (and especially the Northwest) outperform the rest of the country in terms of career opportunities: Trentino shows the highest share of satisfied graduates (72%), though Campania and Puglia, in the South, have similar levels of satisfaction to Veneto and Friuli in the Northeast. This descriptive picture highlights that the relationship between spatial mobility and job satisfaction is a relevant one to investigate in the Italian regions and suggests that the different expectations of migrants following different geographical directions will be reflected in their level of satisfaction. 6 Estimation results 6.1 Southern graduates
Table 3 reports the results for the models for graduates from Southern universities: in the selection equations all rs are positive and significant, confirming the presence of self-selection and supporting the methodological approach adopted. The results confirm that migration from the South to the Centre ^ North exerts indirect effects on job satisfaction across all domains. The coefficient capturing spatial mobility (MIGR SO) is positive and strongly significant across all models in the selection equation. In the selection equation we also find that having a degree in a scientific discipline (SCIENTIFIC) positively affects employability in all domains. A higher grade, however, is not associated with higher probability of employment, with the (weak) exception of the model for career opportunities. The coefficient for parental education (PAREDU) is never significant. Furthermore, we notice that older and female graduates are more and less likely to be employed, respectively (AGE and FEMALE are significant in all models and positive and negative, respectively). Interesting results emerge in the outcome equation. With the exception of satisfaction with stability and security, those who leave the South experience, ceteris paribus, significantly higher levels of well-being than those who stay in the Mezzogiorno. This indicates that not only has migration allowed access to jobs with desirable characteristics (as shown in the selection equation), but also that the positive expectations associated with the move have been surpassed. As for the other variables, the results are largely in line with the literature. Having a part-time job is negatively associated with satisfaction with job tasks, stability and security, and career opportunities, although it has no influence on economic treatment. Also, having a permanent position impacts positively on satisfaction with stability and security and career opportunities. A higher salary is associated with higher well-being in all domains. Those who had a positive university experience, captured by UNI EXP, are more likely to be satisfied across all domains. The variables capturing education ^ job (mis)matches provide very interesting insights. We see that these variables have no influence at all on satisfaction with stability and security (which is largely determined by the permanent or temporary nature of the job). When it comes to satisfaction with economic treatment, however, those who are subjectively overeducated (SUB OVR) feel significantly less satisfied than their peers. As these graduates are in jobs for which a degree was formally required but is not effectively needed, this finding suggests that their unmet economic expectations are due to the fact that their wages reflect the low-skilled
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Table 3. Ologit with same selection: mobility and job-satisfaction for graduates from the Southern regions.
Outcome equation MIGR SO PARTIME PERMANENT SALARY SUB OVR SUB MAT OBJ MAT UNI EXP AGE FEMALE DISTANCE Selection equation MIGR SO SCIENTIFIC GRADE PAREDU AGE FEMALE Constant cut1 cut2 cut3 r N
stability and security
0.24** (2.30) ÿ0.22** (ÿ2.34) 0.04 (0.61) 0.02* (1.85) 0.22 (1.46) 0.56*** (4.13) 0.81*** (6.88) 0.40*** (5.36) ÿ0.00 (ÿ0.11) ÿ0.06 (ÿ0.70) ÿ0.00 (ÿ1.18)
0.28*** (2.58) 0.08 (0.71) 0.11 (1.57) 0.09*** (6.64) ÿ0.27** (ÿ2.34) ÿ0.17 (ÿ1.31) ÿ0.12 (ÿ1.38) 0.26*** (3.46) ÿ0.01 (ÿ0.49) 0.04 (0.46) ÿ0.00** (ÿ2.06)
0.16 (1.46) ÿ0.35*** (ÿ3.07) 1.06*** (13.10) 0.02** (2.16) 0.10 (0.76) 0.06 (0.47) 0.06 (0.60) 0.34*** (4.52) ÿ0.01 (ÿ0.48) ÿ0.21*** (ÿ2.84) 0.00 (0.38)
0.40*** (3.98) ÿ0.16* (ÿ1.67) 0.18*** (2.65) 0.03*** (3.80) 0.28** (2.39) 0.49*** (4.41) 0.54*** (6.16) 0.47*** (6.73) ÿ0.03** (ÿ2.38) ÿ0.29*** (ÿ4.16) 0.00 (0.07)
0.69*** (8.82) 0.35*** (6.42) 0.01 (1.58) 0.02 (0.39) 0.02** (2.08) ÿ0.33*** (ÿ5.82) ÿ0.86 (ÿ1.58)
0.69*** (8.88) 0.35*** (6.23) 0.01 (1.55) 0.02 (0.42) 0.02** (2.10) ÿ0.33*** (ÿ5.76) ÿ0.88 (ÿ1.57)
0.70*** (8.90) 0.35*** (6.32) 0.01 (1.36) 0.04 (0.74) 0.02** (2.07) ÿ0.33*** (ÿ5.79) ÿ0.80 (ÿ1.43)
0.68*** (8.73) 0.37*** (6.78) 0.01* (1.92) 0.03 (0.59) 0.02** (2.15) ÿ0.32*** (ÿ5.72) ÿ1.02* (ÿ1.87)
ÿ0.56 (ÿ1.32) 0.37 (0.88) 1.89*** (4.50) 0.62*** (11.92) 7850
ÿ0.30 (ÿ0.68) 0.93** (2.10) 2.59*** (5.69) 0.43*** (3.82) 7850
ÿ0.53 (ÿ1.01) 0.41 (0.80) 1.55*** (3.10) 0.44*** (5.02) 7850
ÿ0.87** (ÿ2.10) 0.23 (0.55) 1.46*** (3.54) 0.61*** (15.92) 7850
*p < 0:10; **p < 0:05, ***p < 0:01.
Graduate mobility and job satisfaction in Italy
nature of their job.(10) In the other domains we find that the most satisfied are those who are objectively matched, followed by those subjectively matched (OBJ MATCH and SUB MATCH are positive and significant, but the former has the highest coefficient). In the career opportunities domain, we also notice that subjectively overeducated (SUB OVR) graduates are significantly more satisfied than their objectively overeducated peers. Finally, we see that age does not influence satisfaction, with the exception of the career opportunities domain (in which the coefficient is negative and significant). Being female, on the other hand, is negative and significant in both the domains of satisfaction representing long-term expectations: job stability and future opportunities. Distance is not significant in any domain, with the exception of economic treatment where it has a limited impact. This may reflect the fact that for Southern graduates the noneconomic costs of moving do not depend on the geographical distance between the origin and destination, but rather on the socioeconomic cultural ones, which are effectively engrained in migrants' expectations. The economic costs, however, do depend on how far one relocates and thereby impact on the level of satisfaction with economic treatment. 6.2 Graduates from the Centre ^ North
Table 4 shows the results for the ologit models with sample selection covering graduates from the Centre ^ North. Again, the significant rs across all models indicate that the sample selection model is appropriate. In the selection equations we notice again that mobility increases satisfaction indirectly, by affecting employability (MIGR CN is positive and significant across equations), that those with a scientific background (SCIENTIFIC) are more likely to be employed and that age and gender (FEMALE) exert the same effect as in the South. Interestingly, the parental level of education (PAREDU) has a negative effect on employability. This unexpected result indicates that graduates from highly educated families can afford to postpone their entry into the labour market, engaging either in further study or in other types of training (such as internships). The outcome equation shows that, when it comes to the direct effects of migration, interesting differences emerge between graduates from the two parts of the country. In terms of long-term domains of satisfaction, the results for the Centre ^ North models are exactly the opposite to those for the South: migration affects satisfaction both directly and indirectly in the stability and security domain, but not in the career opportunities one. This gives important insights into the intrinsic expectations of mobility in the two cases: Southern migrants embark on a much longer journey and, whilst they do so with the ambition of improving their career opportunities, the feeling of stability is necessarily undermined by the distance from home. On the other hand, as career opportunities can perhaps be taken for granted in the more developed part of the country, the migration of Centre ^ North graduates increases their employment choices without the psychological costs of long-distance relocation, producing a higher sense of security. As for the short-term domains of satisfaction, we find that Centre ^ Northern migrants are, as in the South, more fulfilled than their peers by the day-to-day tasks of their jobs. However, in the Centre ^ North, migration does not result in higher satisfaction with economic treatment, suggesting that mobility is not a choice driven by necessity. (10) This
finding is in line with Di Pietro and Urwin (2006) who find that Italian employers are increasingly hiring a high-skilled workforce for low-skilled jobs, paying wages that reflect the actual low productivity of the employment.
S Iammarino, E Marinelli
Table 4. Ologit with sample selection: mobility and job satisfaction for graduates from the Centre ^ North regions. Short-term domains
stability and security
0.23*** (3.53) ÿ0.13* (ÿ1.77) ÿ0.07* (ÿ1.66) 0.02*** (4.11) 0.17** (2.36) 0.55*** (7.99) 0.81*** (14.63) 0.41*** (8.34) ÿ0.02 (ÿ1.49) 0.04 (0.83) ÿ0.00* (ÿ1.75)
0.02 (0.29) 0.09 (0.96) 0.07 (1.39) 0.08*** (9.94) ÿ0.07 (ÿ0.89) 0.03 (0.44) 0.10* (1.91) 0.21*** (4.09) ÿ0.03*** (ÿ3.53) 0.01 (0.18) 0.00 (ÿ0.63)
0.22** (1.97) ÿ0.17** (ÿ2.14) 1.34*** (20.47) 0.03*** (3.70) 0.04 (0.44) 0.10 (1.14) 0.16** (2.20) 0.17*** (2.71) ÿ0.02 (ÿ1.47) ÿ0.07 (ÿ1.07) 0.00 (ÿ1.30)
0.08 (1.03) ÿ0.22*** (ÿ2.72) 0.24*** (5.58) 0.03*** (4.65) 0.13* (1.76) 0.30*** (3.76) 0.47*** (8.52) 0.31*** (6.17) ÿ0.03*** (ÿ3.33) ÿ0.22*** (ÿ4.87) 0.00 (ÿ0.95)
0.15** (2.50) 0.17*** (4.15) ÿ0.00 (ÿ1.03) ÿ0.16*** (ÿ3.84) 0.02** (2.19) ÿ0.14*** (ÿ3.09) 0.62 (1.00)
0.15** (2.53) 0.15*** (3.70) 0.00 (ÿ1.12) ÿ0.17*** (ÿ3.97) 0.02** (2.14) ÿ0.14*** (ÿ3.26) 0.90** (2.18)
0.16*** (2.67) 0.15*** (3.88) 0.00 (ÿ0.72) ÿ0.18*** (ÿ4.30) 0.02** (2.31) ÿ0.16*** (ÿ3.51) 0.75** (1.86)
0.15** (2.55) 0.18*** (4.45) 0.00 (ÿ0.35) ÿ0.18*** (ÿ4.25) 0.02** (2.37) ÿ0.14*** (ÿ3.23) 0.61 (1.49)
ÿ1.55 (ÿ1.08) ÿ0.57 (ÿ1.08) 0.85 (1.08) 0.60*** (27.52) 18080
ÿ1.11*** (ÿ3.91) 0.04 (0.13) 1.69*** (5.95) 0.34** (1.97) 18080
ÿ0.66** (ÿ2.03) 0.25 (0.79) 1.32*** (4.05) 0.64*** (19.02) 18080
ÿ1.15*** (ÿ4.08) ÿ0.14 (ÿ0.51) 1.17*** (4.24) 0.58*** (15.95) 18080
Outcome equation MIGR CN PARTIME PERMANENT SALARY SUB OVR SUB MAT OBJ MAT UNI EXP AGE FEMALE DISTANCE Selection equation MIGR FN SCIENTIFIC GRADE PAREDU AGE FEMALE Constant cut1 cut2 cut3 r N
**p < 0:05, ***p < 0:01.
Graduate mobility and job satisfaction in Italy
The results also indicate that having a higher salary, being satisfied with the university (UNI EXP) experience, and having a part-time job exert the same effects as they do for Southern migrants. Interestingly, whilst having a permanent job increases satisfaction with the long-term domains (as for Southern graduates), it decreases satisfaction with job tasks. A tentative explanation for this result is that the higher entrepreneurship and economic dynamism of the area result in high-skilled temporary jobs that are more exciting in their nature than traditional employment roles giving access to permanent positions. The effect of education ^ job matches is broadly in line with that seen for Southern graduates. However, notable differences emerge in the economic treatment domain: subjectively overeducated graduates (SUB OVR) of the Centre ^ North are no less satisfied than the rest, indicating that the practice of recruiting highly skilled individuals for low-skilled jobs, hypothesised above, may be less common in this area. At the same time, we find that objectively matched graduates (OBJ MAT) are significantly more fulfilled than their peers, suggesting that the pecuniary rewards for qualified skills are higher in the Centre ^ North. Finally, distance affects (weakly) only satisfaction with job tasks. This suggests that, other things being equal, those who move within the Centre ^ North seek jobs that they enjoy performing, and experience lower well-being when, in relocating further from home, they do not meet such expectation. All in all, the analysis shows that the striking subnational differences in Italy are reflected in the different expectations of graduates across the country and confirms the value of looking at self-reported well-being to achieve a fuller understanding of mobility patterns. 7 Conclusions This paper has analysed the link between graduate mobility and job-related well-being, highlighting that the former affects the latter indirectly, by providing access to better opportunities, and directly, by generating higher expectations. Through ologit models with sample selection we have studied the behaviour of graduates from the Mezzogiorno regions and graduates from the Centre ^ North areas of Italy, exploring their satisfaction in four different domains. The analysis has confirmed many of the findings of the previous literature. A higher salary, a permanent contract, and a full-time job are overall linked to higher levels of job-related well-being. At the same time, satisfaction is higher for those who had a positive university experience, whilst female graduates feel less fulfilled with their career prospects across the whole country, as they may perceive barriers to their long-term professional development. Whilst, with the few exceptions noted above, job and personal characteristics exert similar effects on the satisfaction of graduates from the South and the Centre ^ North of Italy, migration displays interesting differences. Remarkably, we find that migration has direct effects on the satisfaction of Southern graduates in the domains of job tasks, economic treatment, and career opportunities, but not in terms of stability and security. The long geographical and socioeconomic distance from home means that relocation is more costly, in both economic and noneconomic terms, and this necessarily undermines expectations on the long-run professional stability and overall sense of security. The opposite results emerge for migrants within the Centre ^ North, who have not incurred such high relocation costs. Furthermore, it must be noted that across all models and for both the selection and outcome equations, the migration coefficients are higher and often more strongly significant for the South of Italy, indicating that mobility has a relatively stronger impact on well-being in the Mezzogiorno.
S Iammarino, E Marinelli
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Graduate mobility and job satisfaction in Italy
Appendix Table A1. List of variables. Dependent variables 1. Satisfaction with job tasks 2. Satisfaction with economic treatment 3. Satisfaction with stability and security 4. Satisfaction with career opportunities Independent variables Mobility categories Population of the South Migrant (MIGR SO) Leaves the region of study in the Mezzogiorno to move to another region in the Centre ± North Population of the Centre ± North Migrant (MIGR CN) Leaves the region of study in the Centre ± North to move to another region in the Centre ± North Other Job characteristics Salary (SALARY) Part-time/full time (PARTIME) Permanent/temporary (PERMANENT) Education ± job match Objective overeducation (OBJ OVR) Subjective overeducation (SUB OVR) Subjective match (SUB MAT) Objective match (OBJ MAT) University background Scientific background (SCIENTIFIC) Grade (GRADE) University experience (UNI EXP) Level of education of one parent (PAREDU) Other individual characteristics Age (AGE) Gender (FEMALE) Distance from origin (region of study) to destination (region of work) (DISTANCE)
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