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«Paper No. 365 Determinants of self-employment among commuters and non-commuters Mikaela Backman Charlie Karlsson May, 2014 The Royal Institute of ...»

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One could hypothesis that it is beneficial for individuals to commute to more urban locations (Commuter, urban) since these are characterised by a larger market and access to more people and more diversified set of individuals. As the number of interaction increases with the size of a location, locations higher up in the urban-rural dichotomy have an advantage in creating social and professional networks. Those individuals that do commute to more urban locations within the functional region are however not more or less likely to become self-employed as the dummy is insignificant. The length of the commuting in time (Years of commuting) is positively associated with becoming self-employed, this holds for all occupational types and educational levels except those with an intermediate level of education (between secondary and bachelor degree). This supports the notation that it takes some time to build up networks, in this case business networks, and as individuals get a stronger network they are also more likely to become self-employed.

The control variables overall do not alter for commuters compared to non-commuters (live and work in the same municipality). One difference is that individuals with more schooling and with a social occupation is less likely to become self-employed. Another difference is that the dummy indicating whether you have stayed in the same municipality for the last five years (Stayer) is only negatively associated with the probability to become self-employed for those in social occupations. For the other occupation types it is insignificant. Turning to the educational levels, we observe that for highly educated individuals having lived in the same municipality for the last five years increases the likelihood that the individual will become self-employed.

In the last scenario we observe those individuals that work and live in different functional regions. Hence, they are long-distance commuters as it normally takes at least 45 to 60 minutes to reach another functional region. The results are presented in Table 4. Similar to Table 3, we separate the access to self-employed in the municipality of residence and municipality of work and add the same at the region level, i.e. access to self-employed in the region where the individual live and where she/he works.

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In the last scenario we observe those individuals that commute long-distances, i.e. here defined as across functional regions. This gives us the opportunity to analyse the work and home economic environment at the municipal and regional level. Starting with the local environment (Network municipality) there is no consistent pattern across occupational groups.

For individuals having a cognitive occupation both the network opportunities in the home and work municipality increase the prospects in becoming self-employed. For the other occupation groups, except individuals with a standardized occupation, it is the network built up in the home municipality that is important. The network opportunities in the work municipality is even hampering the effect of becoming self-employed in some cases. The regional level (Network region) does not overall influence the decision to become selfemployed. The only case where it is significant and positive is for individuals with a cognitive occupation where the work environment is important. For individuals with a social occupation having access to many other self-employed in the home region is negatively associated with the probability of becoming self-employed.

Again, we confirm that commuting to more urban locations (Commuter, urban) does not influence the choice of self-employment. How long time you have commuted (Years of commuting) is however positively associated with choosing to become self-employed, irrespectively of occupation and years of schooling. Building on this we would also like to analyse if there is any optimal time-length for commuting. We start by simply checking if the is a decreasing marginal effect from commuting by adding the squared years of commuting in the estimation. By adding this variable there is no consistent pattern across occupational groups and educational levels. We follow this up by also including dummies for each year that an individual can commute, i.e. one to ten, and see which of the dummies have the highest coefficient (using ten years of commuting as a base). Here we find a more consistent pattern where the probability of becoming self-employed is a function of the number of years commuting. Thus, as the network grow stronger you are more willing to become selfemployed.

4. Conclusions In this paper, we have analysed how the “business network” characteristics of work and home localities and work and home region of individuals influence their probability of becoming self-employed. By making a distinction between non-commuters, and short- and long-distance commuters we are able to highlight the influence of the “business network” characteristics.

The results are not totally clear-cut but we show a number of interesting results. For noncommuters we find that living and working in a locality with rich “business networks” significantly reduces the probability of becoming self-employed except for those with a high education. On the other hand living and working in a labour market region with rich “business networks” increases significantly the probability of becoming self-employed. Why “business networks” have different effects at the locality level and the level of the labour market region is a question for future research.

For short-distance commuters, rich “business networks” in the work locality has a significant positive effect on the probability to become self-employed except for those in management and administrative occupations, where the effect is insignificant. Perhaps, those in management and administrative occupations due to their work tasks and work experience have so much insights in becoming self-employed that they are not dependent on stimuli from those that already are self-employed. Interestingly, rich “business networks” in the home locality has no significant effects. Rich “business networks” at the regional level is only significantly positive in one case and significantly negative in one case. It is a question for future research to find out why we have this difference between non-commuters and shortdistance commuters in terms of the effects of “business networks” at the regional level.

Long-distance commuters seem to differ from short-distance commuters in the sense that for them in five out of seven categories we get a significant positive effect on the probability of becoming self-employed from rich “business networks” in the home locality. The business networks in the home and work regions in almost all cases show insignificant effects. If we summarise, our results indicate that obviously rich “business networks” are important for peoples’ decision to become self-employed. However, the effects are quite different for noncommuters, short-distance and long-distance commuters which implies that we have to dig deeper into this question in future research.

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