The determinants of exit in a developing country: core and peripheral regions

Abstract

This paper analyses the regional determinants of exit in developing countries, using Argentina as an illustrative case. We find evidence of a dynamic revolving door by which past entrants increase current exits, particularly in the peripheral regions. In the central regions, current and past incumbents cause an analogous displacement effect. Also, exit shows a U-shaped relationship with respect to the informal economy, although the positive effect is weaker in the central regions. These findings point to the existence of a core–periphery structure in the spatial distribution of exits.

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Notes

  1. 1.

    Notice that the factors driving the dynamics of firms (entry and exit) are not necessarily the same and/or have the same impact in developed and developing countries (see, e.g. Calá et al. 2014 for evidence on the entry process). In particular, the exit process in developing countries may be distinctively affected by macroeconomic instability (Stiglitz 1998; Ocampo et al. 2009; Bértola and Ocampo 2012), the size of the informal sector (Schneider 2005) and structural regional heterogeneity (Sunkel 1978; Cassiolato et al. 2009).

  2. 2.

    A number of studies also use firm-level data: e.g. Frazer (2005) for Ghana, Eslava et al. (2006) for Colombia, and López (2006), Álvarez and Görg (2009) and Álvarez and Vergara (2010, 2013) for Chile.

  3. 3.

    Previous studies of firm exit in Argentina are merely descriptive (Bartelsman et al. 2004; MTEySS 2007; Katz and Bernat 2011; Calá and Rotondo 2012). Of these, Calá and Rotondo (2012) is the only one that adopts a regional approach.

  4. 4.

    We use the terms “region” and “area” to refer to any geographical unit within a country. They are therefore not necessarily linked to administrative units (e.g. regions and provinces). However, most of the studies considered in this section use NUTS-II levels (i.e. regional level) and only a few smaller units (e.g. counties, as in the case of Love (1996).

  5. 5.

    This “structural heterogeneity” has accentuated in recent years: while there are now many more “world-class” firms in developing countries, there is also a growing proportion of employment concentrated in low-productivity informal sector activities (ECLAC 2002).

  6. 6.

    See e.g. Calá et al. (2014) for details on the construction of this data set and the limitations involved in using the NHS data.

  7. 7.

    The cross-sectional correlation between these explanatory variables was generally low, except for the density and its square, lagged entries, and incumbents and the industrial tradition, which showed values above 0.9. It is, however, hard to assess the potential impact of these correlations in nonlinear models. Still, the robustness exercises we performed (see below) suggest that these correlations are not a major concern here.

  8. 8.

    The coefficient estimates in Table 3 can be interpreted as semi-elasticities. We do not report marginal effects because of the difficulties in integrating out the unobserved heterogeneity in nonlinear models (Cameron and Trivedi 2009).

  9. 9.

    We also run separate regressions for the central and periphery regions and, as expected, obtained coefficient estimates very close to those reported in Table 3. In particular, we obtained essentially the same results with respect to the periphery regions. In the central regions, however, none of the coefficient estimates turned out to be statistically significant (probably due to the small degrees of freedom implied by this specification).

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Acknowledgments

This paper was partially funded by ECO2013-42310-R, ECO2014-55553-P the “Xarxa de Referència d’R+D+I en Economia i Polítiques Públiques” and the SGR programme (2014-SGR-299) of the Catalan Government. We would like to acknowledge research assistance by Magda Lleixà and Elisenda Jové. We also thank the Employment and Business Dynamics Observatory from The Ministry of Labour, Employment and Social Security from Argentina for kindly providing the data set.

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Correspondence to Carla Daniela Calá.

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Calá, C.D., Arauzo-Carod, JM. & Manjón-Antolín, M. The determinants of exit in a developing country: core and peripheral regions. Ann Reg Sci 54, 927–944 (2015). https://doi.org/10.1007/s00168-015-0695-8

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  • R12
  • R30
  • C33