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Regional Heterogeneity in Firm Dynamics: The Case of Italy

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Abstract

We document how firm dynamics differ for firms located in the South versus the Center-North of Italy, using the universe of private sector firms with at least one employee over the last three decades. Controlling for industry fixed-effects, we find that in both areas of the country firms’ age and size negatively correlate with their growth, but this negative correlation is much stronger in the South. Also, Southern firms show markedly higher unconditional entry and exit rates, but the decrease in the exit rates of larger and older firms is stronger in the South than in the rest of the country, a fact that suggests a lower level of selection faced by incumbent firms in Southern regions. These empirical facts point to structural differences in the selection and growth dynamics of Southern firms with respect to the rest of the country that go beyond different sectoral specializations, and call for decisive reforms to the institutional environment—judicial and bureaucratic—as well as for the need of a significant increase in human capital.

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Fig. 1

Source: own calculations on INPS dataset

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Notes

  1. See Manaresi (2015) for an analysis of firm dynamics at the national level; see Bripi et al (2021) for the regional dynamics of net employment growth.

  2. Firm dynamics affect productivity growth (see Haltiwanger 2011). In particular, “countries (or regions within a country) may differ substantially in the extent to which more productive firms are large and/or are becoming larger and less productive firms are small and/or becoming smaller. A challenge for both emerging and advanced economies is that achieving such static and dynamic allocative efficiency requires an ongoing process of restructuring and reallocation”.

  3. For instance, the South suffers from less efficient civil justice and public administration.

  4. When the dependent variable is the Davis–Haltiwanger growth rate, the model can still be consistently estimated by OLS, see Angrist (2001).

  5. Statistics by firms’ size and sector specializations are better captured through the National Statistical Institute (Istat) dataset, and are reported by Bripi et al. (2021): they show how firms located in the South are on average almost a quarter smaller than those producing in the rest of the country.

  6. For each firm in each year, we compute the net employment growth rate proposed by Davis et al. (1998). Let L(t) be the firm’s average employment in year t, the net employment growth is then equal to DH = 2[L(t)−L(t−1)]/[L(t) + L(t−1)]. This indicator has two features that make it particularly suitable for analyzing the role of firm dynamics in net employment growth. First, it encompasses net employment growth both on the extensive and intensive margin: it has support [− 2, 2], taking value − 2 when the firm exits (i.e. L(t) = 0), and 2 when it enters (i.e. L(t − 1) = 0). Second, averaging size in the denominator over two periods avoids biases due to regression-to-the-mean effects.

  7. Theoretically, in a simple setting with a Cobb–Douglas production function with decreasing return to scales, competitive markets, and collateral constraints on debt accumulation, financial frictions shouldn’t affect the optimal size of a firm over the long run, since a producer can always accumulate enough internal savings to eventually escape the borrowing constraint. In most settings and for reasonably calibrated economies, financial frictions would exert at most a temporary constraint on the growth of young firms, but not on their optimal size over the long term.

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Acknowledgements

We want to thank Antonio Accetturo, Gian Luca Clementi, Francesca Lotti, Roberto Torrini, and an anonymous referee for their helpful comments. The views and opinions expressed in this paper are those of the authors and do not represent those of the Bank of Italy.

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Correspondence to Filippo Scoccianti.

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Appendix

Appendix

See Tables 5, 6, 7 and Figs. 2, 3, 4.

Table 5 Aggregate statistics by region
Table 6 Revenues, assets and TFP by macroarea
Table 7 Profitability by macroarea
Fig. 2
figure 2

Source: own calculations on INPS dataset

Entry and exit rates in the industry sector.

Fig. 3
figure 3

Source: own calculations on INPS dataset

Entry and exit rates in the commerce-tourism sectors.

Fig. 4
figure 4

Source: own calculations on INPS dataset

Entry and exit rates in the service sector excluding commerce and tourism.

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Scoccianti, F., Sette, E. Regional Heterogeneity in Firm Dynamics: The Case of Italy. Ital Econ J (2024). https://doi.org/10.1007/s40797-024-00278-2

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