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Spatial patterns and determinants of firm exit: an empirical analysis on France

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Abstract

The purpose of this research is to study the role of spatial agglomeration economies as drivers of firm exit in France over the period 2009–2013 by focusing on two regional variables (local financial development and local specialization). The spatial autocorrelation detected in the data leads us to apply spatial econometric techniques (Spatial Dynamic Panel models and spatial GMM) that permit us to control the estimation of spatial spillover effects. Our results show that firm exit is significantly influenced by positive spatial autocorrelation. Therefore, locations with high exit rates tend to be surrounded by similar ones. However, this phenomenon differs according to the period. In addition, we find that greater local financial development reduces the exit rate in a department, whereas local specialization seems not to exert any effect.

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Fig. 1

Source: own elaboration from the Eurostat dataset

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Notes

  1. As expected, in this case, the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) support the application of the SAC model.

  2. We did not add year dummy variables in the estimations to control for macroeconomic shocks (as suggested by Coad and Rao 2008), since the effect of the economic conjuncture in France in the years of the analysis differently affected the various sectors (Fougère et al. 2013). However, estimations with year dummy variables are reported in Table 6 in “Appendix” and confirm the relevance of the clustering effect.

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Authors and Affiliations

  1. EconomiX CNRS, Université Paris Nanterre, 200, Avenue de la République, 92001, Nanterre Cedex, France

    Giuseppe Arcuri, Marc Brunetto & Nadine Levratto

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  1. Giuseppe Arcuri
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  2. Marc Brunetto
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  3. Nadine Levratto
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Correspondence to Giuseppe Arcuri.

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Appendix

Appendix

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Table 6 Estimations with time dummies
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Table 7 Correlation matrix
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Arcuri, G., Brunetto, M. & Levratto, N. Spatial patterns and determinants of firm exit: an empirical analysis on France. Ann Reg Sci 62, 99–118 (2019). https://doi.org/10.1007/s00168-018-0887-0

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