Location and Jobs Creation: Do Institutions Matter? an Empirical Analysis on 2004-2010 France

Sunday, June 26, 2016: 9:00 AM-10:30 AM
219 Dwinelle (Dwinelle Hall)
Nadine Levratto, EconomiX-CNRS, university of Paris Ouest Nanterre, Paris Nanterre, France; Kedge Business School, Marseille, France
Aziza Garsaa, EconomiX-University Paris Ouest Nanterre La Défense, Paris Nanterre, France
The work so far on the importance of geographical location for firms is intriguing; the local characteristics seem to be important for determining some firm performance and growth indices, above and beyond industry effects. But how pervasive and important are geographical effects in determining firm growth? Are local economic conditions, such as the education levels of the people living nearby, the agglomeration effects, and the general economic health of an area important? Do these local effects are autonomous or do they combine with sector and individual characteristics?

In this paper, we address these important questions by studying whether there exists a robust relation between a firm growth rate and the economic characteristics of the area where it is located.

The selection of these geographical variables is based on the Urban Economics literature that ties local economic and population data to the success of firms, industries, and places. This literature defines characteristics of an area possibly having an impact on the firm performance using local measures related to unemployment, industrial structure, agglomeration, density, education, the labor force structure, etc. (Rosenthal and Strange, 2004).

The difficulties however arrive when one mix in the same model individual and local determinants of firm growth rate. Indeed, traditional multiple regression techniques treat the units of analysis as independent observations. One consequence of failing to recognize hierarchical structures is that standard errors of regression coefficients will be underestimated, leading to an overstatement of statistical significance. In order to circumvent these difficulties, we implement a multilevel model which recognizes the existence of such data hierarchies by allowing for residual components at each level in the hierarchy.

We run our estimations using a unique large dataset of establishments and enterprises built by merging three sources provided by the French National Institute of Statistics and Economic Studies (INSEE). The final datasets we obtained is composed of an unbalanced panel of about 130,000 establishments and 70,000 enterprises. We estimate four different specification of the multilevel model. Our results show that, other thing equals, a firm growth rate depends on the local context and that the magnitude of this effect is influenced by the industry in which the company operates.


Rosenthal, S. S., and W. C. Strange. 2004. Evidence on the nature and sources of agglomeration economies. In Handbook of regional and urban economics, vol. 4, ed. V. Henderson and J.- F. Thisse, 2119–71. Amsterdam: North- Holland.