Could the Ease of Doing Business be considered a predictor of countries' Socio-Economic Wealth? An empirical analysis using PLS-SEM

Abstract

The wealth of nations differs significantly due to different factors. One of the reasons identified by previous studies is the level of entrepreneurship promotion by governments. This aspect has scarcely been studied empirically to date. Therefore, this paper sheds some light on this regard through building a construct out of ten Ease of Doing Business Index (EDBI) measures developed by the World Bank and relating it with a construct shaped by two measures of socio-economic wealth (SEW), namely gross domestic product and the Human Development Index. To this end, we conduct a structural equation model analysis using partial least squares (PLS-SEM) method with a 2018 database comprising secondary data from 190 countries. As the main contribution of this study, the results show that good performance in the EDBI ranking predicts good performance in the SEW ranking. Additionally, this study is pioneer in the use of these rankings to build composite constructs (latent variables) and relate them. For these reasons, our findings are useful for both academia and governments responsible for promoting entrepreneurship, as this latter is identified as the key enabler of economic development.

Bibliography

1. Acs, Z. J., & Storey, D. J. (2004). Introduction: Entrepreneurship and economic development. Regional Studies. https://doi.org/10.1080/0034340042000280901

2. Andrieu, E. C. (2010, April). The entrepreneur according to the Austrian school. In Businesses Report OPENS Forum (2014): Study Reports On Growth of Women-Owned Businesses. Retrieved from http://hdl.handle.net/10500/3779%3E

3. Becker, J.-M., Rai, A., & Rigdon, E. (2013). Predictive validity and formative measurement in structural equation modeling: Embracing practical relevance. Proceedings of 34th International Conference on Information Systems, Milan, 1–19.

4. Book, J. (2019). [Review of the book Capitalism in America: A History by A. Greenspan & A. Wooldridge]. The QuarTerly Journalof AusTrian Economics, 22(1), 82–90. Retrieved from https://qjae.scholasticahq.com/article/9142

5. Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Methodology for business and management. Modern methods for business research (pp. 295-336). Mahwah, NJ, US: Lawrence Erlbaum Associates P

6. Cooley, A. (2015). The emerging politics of international rankings and ratings. In A. Cooley & J. Snyder (Eds.), Ranking the World: Grading States as a Tool of Global Governance (pp. 1-38). Cambridge: Cambridge University Press. doi:10.1017/CBO97813161615

7. Dolce, P., Vinzi, V. E., & Lauro, C. (2017). Predictive path modeling through PLS and other component-based approaches: Methodological issues and performance evaluation. In Partial Least Squares Path Modeling (pp. 153-172). Springer, Cham. https://doi.org

8. Evermann, J., & Tate, M. (2016). Assessing the predictive performance of structural equation model estimators. Journal of Business Research, 69(10), 4565-4582. https://doi.org/10.1016/j.jbusres.2016.03.050

9. Felipe, C., Roldán, J., & Leal-Rodríguez, A. (2017). Impact of organizational culture values on organizational agility. Sustainability, 9(12), 2354. https://doi.org/10.3390/su9122354

10. Fukuyama, F. (2011). Friedrich A. Hayek, Big-Government Skeptic. The New York Times, p. BR12. Retrieved from https://www.nytimes.com/2011/05/08/books/review/f-a-hayek-big-government-skeptic.html

11. Gries, T., & Naudé, W. (2010). Entrepreneurship and structural economic transformation. Small Business Economics, 34(1), 13-29. https://doi.org/10.1007/s11187-009-9192-8

12. Hair, J.F., Ringle, C.M. and Sarstedt, M. (2011). PLS-SEM: Indeed, a Silver Bullet. Journal of Marketing Theory and Practice, 19, 139-151. https://doi.org/10.2753/MTP1069-6679190202

13. Hayek, F. A. (1960). The Constitution or Liberty. Chicago: University of Chicago Press.

14. Huerta-De Soto, J. H. (2010). Socialism, economic calculation and entrepreneurship. Edward Elgar.

15. JASP Team (2019). JASP (Version 0.11.1) [Computer software].

16. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.

17. von Mises, L. (2004). Abstract of Human Action, treatise of economy. Paris, Les belles lettres.

18. Mongay, J. (2018). Ease of Doing Business and Wealth Creation. In Examining the Private Sector’s Role in Wealth Creation and Poverty Reduction (pp. 29–50). https://doi.org/10.4018/978-1-5225-3117-3.ch002

19. Petter, S., Straub, D., & Rai, A. (2007). Specifying Formative Constructs in Information Systems Research. MIS Quarterly, 31(4), 623-656. doi:10.2307/25148814

20. Rigdon, E. E. (2012). Rethinking partial least squares path modeling: In praise of simple methods. Long Range Planning, 45(5–6), 341–358.

21. Rigdon, E. E., Sarstedt, M.,&Ringle, C. M. (2017). On comparing results from CBSEM and PLS-SEM: Five perspectives and five recommendations. Marketing ZFP, 39(3), 4–16.

22. Ringle, C., Wende, S., Becker, J., Ringle, Christian M., Wende, Sven, & Becker, J.-M., Ringle, C., Wende, S., & Becker, J. (2015). SmartPLS 3. Retrieved From https://doi.org/http://www.smartpls.com

23. Roldán, J. L., & Sánchez-Franco, M. J. (2012). Variance-Based Structural Equation Modeling: Guidelines for Using Partial Least Squares in Information Systems research. In Research Methodologies, Innovations and Philosophies in Software Systems Engineering

24. Ruiz, F., Cabello, J. M., & Pérez-Gladish, B. (2018). Building Ease-of-Doing-Business synthetic indicators using a double reference point approach. Technological Forecasting and Social Change, 131, 130-140. https://doi.org/10.1016/j.techfore.2017.06.005

25. Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010.

26. Schueth, S. (2011). Assembling international competitiveness: The Republic of Georgia, USAID, and the Doing Business project. Economic geography, 87(1), 51-77. https://doi.org/10.1111/j.1944-8287.2010.01103.x

27. Shmueli, G. (2010). To explain or to predict? Statistical science, 25(3), 289-310. https://doi.org/10.2139/ssrn.1351252

28. Shmueli, G., & Koppius, O. R. (2011). Predictive analytics in information systems research. MIS quarterly, 553-572. doi:10.2139/ssrn.1606674

29. Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552-4564. https://doi.org/10.1016/j.jbusres.2016.03.049

30. Szirmai, A., Naudé, W., & Goedhuys, M. (2011). Entrepreneurship, Innovation, and Economic Development. In Entrepreneurship, Innovation, and Economic Development. https://doi.org/10.1093/acprof:oso/9780199596515.001.0001

31. Szirmai, A., Naudé, W., & Goedhuys, M. (Eds.). (2011). Entrepreneurship, Innovation, and Economic Development. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199596515.001.0001

32. World Bank (2008). Doing business: an independent evaluation - taking the measure of the World Bank-IFC Doing Business Indicators (English). Washington, DC: World Bank. Retrieved from http://documents.worldbank.org/curated/en/102811468157765042/Doing-busi

33. Doing Business (2018, October). Doing Business 2018: Reforming to Create Jobs (15th. Annual Report). World Bank Group. Retrieved from https://www.doingbusiness.org/en/reports/global-reports/doing-business-2018