Related and unrelated variety and convergence to technological frontier: empirical evidence for Polish regions

ABSTRACT

This paper examines the effects of related and unrelated variety on total factor productivity (TFP) in Poland. Based on dynamic panel data regression results for Polish regions in 2003-2019, we find the positive effect of related variety and the strong negative effect of unrelated variety on TFP. This implies that regions with high related and low unrelated variety optimize TFP. Using the estimated TFP values, we tested for TFP convergence to the technological frontier using convergence tests that take into account significant differences in technological advancement across regions. We reject TFP convergence for all regions, but we find evidence of regional club convergence. The results of the convergence tests obtained for the simulation variants indicate that changes in related and unrelated variety structures may lead to the formation of convergence clubs with the regional technological leader. Furthermore, the changes primarily in related variety structures lead to the convergence of some regions to the regional technological frontier.

KEYWORDS:

• Convergence to the technological frontier
• knowledge spillovers
• related/unrelated variety
• TFP

JEL CLASSIFICATIONS:

• D62, O18, R11

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Market proximity includes both the availability of skilled workers, the ease of finding suppliers and customers and the opportunity to learn from nearby competitors and cooperators (agglomeration effects). However, the most important is this last aspect, which can affect the speed and efficiency of information spillover (and tacit knowledge) in the spirit of Marshall's (1890) ‘industrial atmosphere’.

2 An alternative approach is the concept of revealed relatedness based on product space rather than industry classification. Hidalgo et al. (2007) consider that if a country has a comparative advantage in the production of a particular product, it is highly likely that it will also gain an advantage in products that are related to it, e.g. in terms of skills, infrastructure or technology.

3 TFP was estimated using the prodest function in STATA statistical package.

4 These studies used intermediate consumption (raw materials, components and services) and energy consumption as proxy for unobserved TFP to control endogeneity.

5 For the sake of comparison parameters in equation (1) are estimated using both the Rovigatti-Mollisi (RM) and the Wooldridge (WRDG) estimators. The estimation results are reported in Table A1 in the Appendix. TFP is calculated using only the RM estimates.

6 For a more extensive discussion of the convergence test method used, its theoretical framework, the testing of convergence across the group and the steps in identifying convergence clubs, see e.g. Phillips and Sul (2007a, 2007b), Du (2017), Cieślik and Wciślik (2020) or Misiak (2022).

7 We consider Mazowiecki region as the regional technological leader, while if other regions showed convergence to the same steady-state as Mazowiecki region it would imply convergence of these regions to the regional technological frontier.