The global technology frontier: productivity growth and the relevance of Kirznerian and Schumpeterian entrepreneurship

Abstract

We evaluate how country-level entrepreneurship—measured via the national system of entrepreneurship—triggers total factor productivity (TFP) by increasing the effects of Kirznerian and Schumpeterian entrepreneurship. Using a database for 45 developed and developing countries during 2002–2013, we employ non-parametric techniques to build a world technology frontier and compute TFP estimates. The results of the common factor models reveal that the national system of entrepreneurship is a relevant conduit of TFP, and that this effect is heterogeneous across countries. Policies supporting Kirznerian entrepreneurship—e.g., increased business formation rates—may promote the creation of low value-adding businesses which is not associated with higher TFP rates. Policy interventions targeting Schumpeterian entrepreneurship objectives—e.g., innovative entrepreneurship and the development of new technologies—are conducive to technical change by promoting upward shifts in the countries’ production function and, consequently, productivity growth.

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Notes

  1. 1.

    The Romer (1990) and Grossman and Helpman (1991) expanding variety models are in that sense more Schumpeterian in nature. In these models, the introduction of new ideas erodes the profitability of the incumbent businesses. Also, the creative destruction process is not explicit in these models as they do not incorporate the possibility of business exit.

  2. 2.

    For Sollow (1957), neutral technical change occurs if the marginal rate of substitution (MRS) between two inputs (x1, x2) is constant and only increase or decrease the output in period t and t + 1: x2t + 1/x1t + 1 = x2t/x1t. Mathematically, neutrality can be written as \( \mathrm{d}/\mathrm{d}t\mathrm{MRS}=\mathrm{d}/\mathrm{d}t\left({F}_1^t/{F}_2^t\right)=-\mathrm{d}/\mathrm{d}t\left(\mathrm{d}x2/\mathrm{d}x1\right)=0 \), where\( {F}_1^t \) and \( {F}_2^t \) are the marginal products and x2/x1 is held constant. Neutrality implies a homothetic inward shift on the unit isoquant (Binswanger 1974).

  3. 3.

    Note that we also ran these tests for country-specific time series. Results, available on request, mostly confirm the persistence of the study variables. At the country level, the result of the Maddala and Wu test rejects the null hypothesis of non-stationarity only for six data series of the GEI variable (Argentina, Greece, Jamaica, Norway, Sweden, and the USA), for three data series of the capital/labor ratio variable (Brazil, Iran, and Romania), for two data series of the GDP variable (Greece and Sweden), and for one data series of the TFP index (Norway). In the case of the CIPS test (Pesaran 2007) results indicate that, for all analyzed countries and all variables, the null hypothesis of non-stationarity cannot be rejected at standard levels of significance.

  4. 4.

    As we indicated in Section 3, the input variables (capital stock and labor) used to compute the TFP index and its components are introduced individually. Thus, the capital-to-labor variable only captures the effect on productivity of movements of this ratio along the isoquant.

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Acknowledgements

Esteban Lafuente acknowledges financial support by the Spanish Ministry of Economy, Industry and Competitiveness (grant no. ECO2017-86305-C4-2-R). Mark Sanders received financial support from the European Union through the Horizon2020 project “Financial and Institutional Reforms to build an Entrepreneurial Society” (FIRES) (grant no. 649378). László Szerb acknowledges financial support by the Higher Education Institutional Excellence Program of the Hungarian Ministry of Human Capacities, within the framework of the 4th thematic program ‘Enhancing the Role of Domestic Companies in the Reindustrialization of Hungary’ of the University of Pécs (reference number of the contract: 20765-3/2018/FEKUTSTRAT); and by the Hungarian National Foundation for Scientific Research (project: OTKA-K-120289 titled ‘Entrepreneurship and competitiveness investigations in Hungary based on the Global Entrepreneurship Monitor surveys 2017-2019’).

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Appendix

Appendix

Table 8 Countries included in the final sample (period 2002–2013)
Table 9 GMM regression results: the relationship between total factor productivity and the national system of entrepreneurship
Table 10 CCEMG regression results: the relationship between TFP and alternative entrepreneurship measures
Table 11 CCEMG regression results: the relationship between TFP and the national system of entrepreneurship among inefficient countries
Table 12 Heterogeneous panel causality test: summary results

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Lafuente, E., Acs, Z.J., Sanders, M. et al. The global technology frontier: productivity growth and the relevance of Kirznerian and Schumpeterian entrepreneurship. Small Bus Econ 55, 153–178 (2020). https://doi.org/10.1007/s11187-019-00140-1

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Keywords

  • National system of entrepreneurship
  • Total factor productivity
  • Technical change
  • Parameter heterogeneity
  • Common factor model
  • International

JEL codes

  • C23
  • E23
  • L26
  • M13
  • O1