Prague Economic Papers 2019, 28(3):276-295 | DOI: 10.18267/j.pep.671

Selected Socioeconomic Determinants of the Size of the Nonprofit Sector Serving Households in the OECD Countries

Jindřich ©pičkaa, Markéta Arltováb, Petr Boukala
a Faculty of Business Administration, University of Economics, Prague, Czech Republic
b Faculty of Informatics and Statistics, University of Economics, Prague, Czech Republic

The article investigates the differences in socioeconomic determinants of the size of the nonprofit sector serving households in the wealthy and less wealthy OECD countries. Based on panel data modelling of 22 wealthy OECD countries and 17 less wealthy OECD countries in the long-term period 2000-2014, authors revealed distinctive determinants of the size of the nonprofit sector serving households in the wealthy and less wealthy countries. The model identified GDP per capita, government health care expenditures per capita, number of refugees per hundred thousand inhabitants and unemployment rate as significant long-term determinants of the size of the nonprofit sector in the wealthy OECD countries. Alternatively, GDP per capita, age and educational structure are significant long-term determinants of the size of the nonprofit sector in the less wealthy OECD countries. Authors found opposing effect of GDP per capita on the size the nonprofit sector between the two groups of countries.

Keywords: econometric modelling, government failure, nonprofit sector serving households, wealth
JEL classification: H50, L31

Received: June 14, 2017; Accepted: March 2, 2018; Published: July 10, 2019  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
©pička, J., Arltová, M., & Boukal, P. (2019). Selected Socioeconomic Determinants of the Size of the Nonprofit Sector Serving Households in the OECD Countries. Prague Economic Papers28(3), 276-295. doi: 10.18267/j.pep.671
Download citation

References

  1. Arlt, J., Arltová, M. (2005). Vztah deficitu běľného účtu platební bilance a rozpočtového deficitu - analýza panelových dat. (The Relationship of Budget Deficit and Current Account Balance - Panel Data Analysis.) Politická ekonomie, 53(6), 747-764, https://doi.org/10.18267/j.polek.535 Go to original source...
  2. Baltagi, B. H., Fomby, T. B., Hill, R. C. (eds.) (2000). Nonstationary Panels, Panel Cointegration, and Dynamic Panels. Advances in Econometrics, Vol. 15, Amsterdam: Elsevier Science. Go to original source...
  3. Ben-Ner, A., van Hoomissen, T. (1991). Nonprofit Organisations in the Mixed Economy: a Demand and Supply Analysis. Annals of Public and Cooperative Economics, 62(4), 519-550. Go to original source...
  4. Breitung, J. (2000). The Local Power of Some Unit Root Tests for Panel Data, in Baltagi, B., ed., Advances in Econometrics, Vol. 15: Nonstationary Panels, Panel Cointegration, and Dynamic Panels. Amsterdam: JAI Press, pp. 161-178. Go to original source...
  5. Clerkin, R. M., Swiss, J. E. (2013). Religious Motivations and Social Service Volunteers: The Interaction of Differing Religious Motivations, Satisfaction, and Repeat Volunteering. Interdisciplinary Journal of Research on Religion, 9(11), 1-19.
  6. EC (2013). European Systems of Accounts 2010. Luxembourg: Publications Office of the European Union. Available at: http://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-02-13-269
  7. Gazley, B. (2010). Linking Collaborative Capacity to Performance Measurement in Government - Nonprofit Partnerships. Nonprofit and Voluntary Sector Quarterly, 39(4), 653-673, https://doi.org/10.1177/0899764009360823 Go to original source...
  8. Gazley, B., Brudney, J. L. (2007). The Purpose (and Perils) of Government-nonprofit Partnership. Nonprofit and Voluntary Sector Quarterly, 36(3), 389-415, https://doi.org/10.1177/0899764006295997 Go to original source...
  9. Gil-Lacruz, A., Marcuello, C. (2013). Voluntary Work in Europe: Comparative Analysis among Countries and Welfare Systems. Social Indicators Research, 114(2), 371-382, https://doi.org/10.1007/s11205-012-0150-5 Go to original source...
  10. Gonzalez, L. I. A., Vijande, M. L. S., Casielles, R. V. (2002). The Market Orientation Concept in the Private Nonprofit Organization Domain. International Journal of Nonprofit and Voluntary Sector Marketing, 7(1), 55-67, https://doi.org/10.1002/nvsm.167 Go to original source...
  11. Grønbjerg, K. A., Paarlberg, L. (2001). Community Variations in the Size and Scope of the Nonprofit Sector: Theory and Preliminary Findings. Nonprofit and Voluntary Sector Quarterly, 30(4), 684-706, https://doi.org/10.1177/0899764001304004 Go to original source...
  12. Hansmann, H. (1987). Economic Theories of Nonprofit Organization, in Powell, W.W., ed., The Nonprofit Sector: A Research Handbook. New Haven, CT: Yale University Press, pp. 27-42.
  13. Im, K. S., Pesaran, M. H., Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74, https://doi.org/10.1016/s0304-4076(03)00092-7 Go to original source...
  14. Jesse, D., Lecy, J. D., van Slyke, D. M. (2013). Nonprofit Sector Growth and Density: Testing Theories of Government Support. Journal of Public Administration Research Theory, 23(1), 189-214, https://doi.org/10.1093/jopart/mus010 Go to original source...
  15. Kao, C. (1999). Spurious Regression and Residual-based Tests for Cointegration in Panel Data. Journal of Econometrics, 90(1), 1-44, https://doi.org/10.1016/s0304-4076(98)00023-2 Go to original source...
  16. Levin, A., Lin, C. F. (1992). Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties. University of California at San Diego. Discussion Paper 92-93.
  17. Levin, A., Lin, C. F., Chu, C. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108(1), 1-24, https://doi.org/10.1016/s0304-4076(01)00098-7 Go to original source...
  18. Luksetich, W. (2008). Government Funding and Nonprofit Organizations. Nonprofit and Voluntary Sector Quarterly, 37(3), 434-442, https://doi.org/10.1177/0899764007310415 Go to original source...
  19. Maddala, G. S., Wu, S. (1999). A Comparative Study of Unit Root Tests with Panel Data and A New Simple Test. Oxford Bulletin of Economics and Statistics, 61(S1), 631-652, https://doi.org/10.1111/1468-0084.0610s1631 Go to original source...
  20. Marcuello, C. (1998). Determinants of the Nonprofit Sector Size: An Empirical Analysis in Spain. Annals of Public and Cooperative Economics, 69(2), 175-192, https://doi.org/10.1111/1467-8292.00078 Go to original source...
  21. Matsunaga, Y., Yamauchi, N., Okuyama, N. (2010). What Determines the Size of the Nonprofit Sector? A Cross-country Analysis of the Government Failure Theory. Voluntas, 21(2), 180-201, https://doi.org/10.1007/s11266-010-9125-9 Go to original source...
  22. O'Regan, K., Oster, S. (2002). Does Government Funding Alter Nonprofit Governance? Evidence from New York City Nonprofit Contractors. Journal of Policy Analysis and Management, 21(3), 359-379, https://doi.org/10.1002/pam.10050 Go to original source...
  23. OECD (2016). OECD. Stat. Statistical database. Paris: Organisation for Economic Co-operation and Development. Available at: http://stats.oecd.org/
  24. Pesaran, M. H. (2015). Time Series and Panel Data Econometrics. Oxford: Oxford University Press. ISBN 978-01-987-3691-2. Go to original source...
  25. Pestoff, V. A. (1992). Third Sector and Co-operative Services. From Determination to Privatization. Journal of Consumer Policy, 15(1), 21-45, https://doi.org/10.1007/bf01016352 Go to original source...
  26. Pevcin, P. (2012). Analysis of Cross-Country Differences in the Nonprofit Sector Size. Prague Economic Papers, 21(2), 186-204, https://doi.org/10.18267/j.pep.418 Go to original source...
  27. Phillips, P. C. B., Moon, H. (1999). Linear Regression Limit Theory for Nonstationary Panel Data. Econometrica, 67(5), 1057-1111, https://doi.org/10.1111/1468-0262.00070 Go to original source...
  28. Phillips, P. C. B., Moon, H. (2000). Nonstationary Panel Data Analysis: an Overview of Some Recent Developments. Econometric Reviews, 19(3), 263-286, https://doi.org/10.1080/07474930008800473 Go to original source...
  29. Pryor, F. L. (2012). Determinants of the Size of the Nonprofit Sector. The European Journal of Comparative Economics, 9(3), 337-348.
  30. Roland, A. B., Valentinov, V., Buchenrieder, G. (2010). Nonprofit Extension in Rural Cameroon: A Study of Demand and Supply Determinants. International Journal of Social Economics, 37(5), 391-399, https://doi.org/10.1108/03068291011038972 Go to original source...
  31. Salamon, L. M., Sokolowski, S. W., Anheier, H. K. (2000). Social Origins of Civil Society: An Overview. Working Papers of the Johns Hopkins Comparative Nonprofit Sector Project.
  32. Schwenger, D., Straub, T., Borzillo, S. (2014). Non-governmental Organizations: Strategic Management for a Competitive World. The Journal of Business Strategy, 35(4), 11-19, https://doi.org/10.1108/jbs-11-2013-0105 Go to original source...
  33. Steinberg, R. (2006). Economic Theories of Nonprofit Organizations, in Powel, W.W., Steinberg, R., eds., The Nonprofit Sector: A Research Handbook. 2nd ed., New Haven, CT: Yale University, pp. 117-139. Go to original source...
  34. UNDP (2016). United Nations Development Programme. Available at: http://www.undp.org
  35. Valentinov, V. (2008). The Economics of Nonprofit Organization: In Search of an Integrative Theory. Journal of Economic Issues, 42(3), 745-761, https://doi.org/10.1080/00213624.2008.11507177 Go to original source...
  36. Valentinov, V. (2009). Managerial Nonpecuniary Preferences in the Market Failure Theories of Nonprofit Organization. International Journal of Social Economics, 36(1/2), 81-92, https://doi.org/10.1108/03068290910921208 Go to original source...
  37. WB (2016). World Bank Open Data. The World Bank. Available at: http://databank.worldbank.org/data/home.aspx
  38. Weinblatt, J. (1992). Do Government Transfers Crowd Out Private Transfers to Nonprofit Organizations? The Israeli Experience. International Journal of Social Economics, 19(2), 60-66, https://doi.org/10.1108/eum0000000000482 Go to original source...
  39. WHO (2016). Global Health Observatory (GHO) data. World Health Organisation. Available at: http://www.who.int/gho/database/en

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY NC ND 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.