Rule of law and regulatory quality as drivers of entrepreneurship

ABSTRACT

This paper investigates empirically the effects of institutions on new business formation in the Italian provinces over the period 2004–12. According to the results, local institutional quality positively affects entry rates, and its impact is stronger in high-tech industries. Among different institutional dimensions, rule of law turns out to be more important in southern lagging regions, while regulatory quality seems more relevant in the developed centre–north. In times of crisis, institutional quality loses importance in determining entries, which become more sensitive to the propensity to innovate and to human capital and infrastructural endowments.

KEYWORDS:

• entrepreneurship
• institutions
• rule of law
• regulatory quality
• Italy

JEL:

• D02
• L26

ACKNOWLEDGEMENTS

The authors are very grateful to the participants at the 47th Annual Conference of the Regional Science Association International, Cambridge, UK, 16–18 July 2019, and at the 16th c.MET05 Workshop, Naples, Italy, 12–14 June 2019. The authors also warmly thank two anonymous reviewers and the editor for their precious suggestions, as well as Professor Domenico Scalera for his tireless support and encouragement. The usual disclaimer applies.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. The time span of the investigation is limited by data availability on institutional quality indicators.

2. Moreover, the constitutional reform of 2001 overhauling Title V of the Italian Constitution has significantly enhanced the scope of ‘regional autonomy’, introducing a ‘multi-level institutional system mirrored by several provisions introduced into the regulatory framework’ (Marchetti, 2010, p. 92), so as to allow significant diversity even in formal aspects of the legal and administrative structure.

3. The relationship between entrepreneurship and economic development is analysed by a broad literature starting at least from Murphy et al. (1991), who pinpoint entrepreneurial talent as a primary source of growth for the economy, with many subsequent contributions emphasizing different effects of entry on saving rates (Cagetti & De Nardi, 2006), human capital accumulation (Dias & McDermott, 2006), knowledge accumulation (Peretto, 1999), etc. For comprehensive surveys on the topic, see Naudé (2008) and Audretsch, Keilbach, and Lehmann (2016).

4. Rather than using the net entry rate, we prefer the gross entry rate (controlling for exits), for several reasons (Fotopoulos & Spence, 1997). First, combining entry and exit into a net measure implies assuming that the same causal underpinnings drive the two processes. Second, a net measure hides important information on the absolute values of entries and exits, and the interpretation of regression coefficients does not allow one to disentangle the impact of explanatory variables on entries and exits.

5. High-technology industries are detailed in Table A1 in Appendix A in the supplemental data online.

6. Moreover, in the present study, the fixed effect approach is not suitable as the institutional quality regressors do not vary substantially within provinces over time. Hence, we mitigate the assumption mentioned above by including several control variables at the provincial level and sector fixed effects.

7. Building on this literature, we adopt the instrumental variables detailed in Tables 1 and 2. Further, the dummy variable cadastre is employed as provinces with a geometric cadastre had a more detailed source of data in disputes among landowners, and also a means of more precise tax assessment, resulting in higher administrative efficiency, which is presumably correlated with the current efficiency of administrations, but exogenous with respect to new businesses formation nowadays.

8. Nifo and Vecchione (2014) supply IQI values for 2004 only. The data set for the whole period 2004–12 is freely downloadable at https://sites.google.com/site/institutionalqualityindex/home.

9. Likewise, EXIT is defined on LL firms as well.

10. Inconsistency between individual and joint significance may be due to multicollinearity induced by the inclusion of interaction terms. As Brambor, Clark, and Golder (2006, p. 70) highlight:

Even if there is high multicollinearity and this leads to large standard errors on the model parameters, it is important to remember that these standard errors are never in any sense ‘too’ large, they are always the ‘correct’ standard errors. High multicollinearity simply means that there is not enough information in the data to estimate the model parameters accurately and the standard errors rightfully reflect this.

11. Figure A1 in Appendix A in the supplemental data online shows that at a low level of RUL, no significant difference between the regression line relative to HMTI firms and the line of the other firms comes up, that is, the rule of law exerts a similar impact on firms’ creation for any technological category. However, as rule of law increases, the gap between HMTI and other firms gets bigger and statistically significant (the confidence bands do not overlap): HMTI firms seem to benefit more from an increase in rule of law than other firms do. Figures A2 and A3 in Appendix A in the supplemental data online convey similar information.

12. This result is consistent with the idea that the influence of both economic development and unemployment on firm creation is ambiguous (Verheul et al., 2002). On the one hand, when economic development is accompanied by an increase in wage levels, the opportunity cost of self-employment increases, making dependent jobs more attractive; on the other, increasing wealth implies higher consumer needs and increasing demand of new and specialized goods that new-born flexible firms can satisfy. Besides, a higher need of self-realization, characterizing wealthier societies, may lead preferring self-employment to routine jobs. Regarding unemployment, if entrepreneurship is necessity driven, when ‘unemployment is high, then more individuals would be prepared to offer themselves for self-employment, because of the shortage of alternative job opportunities’ (Storey, 1994, p. 69). Alternately, a high rate of unemployment can negatively impact on entrepreneurship, as a depressed economy is characterized by lower availability as well as lower expectations of business opportunities.