Abstract
This chapter discusses the viability of gross domestic product (GDP) per capita in purchasing power parity as an indicator of economic development and well-being and estimates the factors which diminish its ability to represent the level of life. Firstly, we theoretically outline the factors that might be undermining GDP per capita’s ability to serve as a measurement of well-being and debate other development indicators. Subsequently, we confront GDP per capita with the most well-known development indicator – Human Development Index (HDI) – and calculate the deviations between those two indicators. To empirically evaluate the potential limitations of GDP in measuring development, we regress the development-GDP gaps on an array of economic, social and political variables employing a broad panel dataset and modified fixed effects estimators. The results reveal that factors such as income inequality and level of economic freedom cause negative gap between development and GDP; the size of shadow economy has positive impact on deviation of HDI from GDP levels, while certain sociocultural factors such as higher fertility rates and alcohol consumption have negative effect on the dependent variable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
As a rule, in purchasing power parity.
- 2.
In this chapter, we use the terms “development,” “well-being” and “level of life” as defined by the modern development economics: a multidimensional concept which embodies the aspects that are of direct or indirect impact on the quality of human life, such as health, income and education (Syrovatka, 2008). Therefore, for the purpose of simplicity, these terms may be viewed as synonymous.
- 3.
Which were started by one of the inventors of the GDP: Simon Kuznets often stated that the criticism stems from the fact that GDP became employed in a fashion it had never been meant to – according to him, GDP was developed to measure and compare the individual countries’ productive capacities and cannot serve as a technique to evaluate economic development and well-being (Sagar and Najam, 1998).
- 4.
With the exact computation of grey economy’s size still posing a problem even for middle-income countries (Bala, 2013).
- 5.
As simple as it gets, those limits may be approximately collapsed into two spheres: one deals with the quantitative issues that GDP per capita fails to include, while the other relates to the points that are of qualitative nature and cannot be included into the accounting monetary indicator.
- 6.
Which are supported by a handful of relatively popular “happiness indexes” of too lax or too complicated methodology, which aim at quantifying the quality of life without turning to economic framework of GDP (Stiglitz et al., 2009).
- 7.
- 8.
It refers to the inklings of undemocratic regimes deliberately overvaluing their economic indicators due to ideological or propagational needs (Syrovatka, 2008).
- 9.
Or its most trendy iteration, adjusted net national income, which is the GNI minus natural resources depletion and fixed capital amortization (Lange et al., 2017).
- 10.
See Lange et al. (2017) for the concrete methodology of these approaches.
- 11.
Which is calculated using mean years of schooling and expected years of schooling (Klasen, 2018).
- 12.
Albeit some may argue that its components are directly affected by the institutions and therefore may be viewed as fairly representative in terms of this matter (Syrovatka, 2008).
- 13.
List and description of all the variables, descriptive statistics and correlation table available upon request.
- 14.
For idiosyncratic error εi,t in fixed-effects and random-effects models, we consider assumptions E(εi,t| di,t, Wit, Sit, Zit ) = 0, \( Var\left({\varepsilon}_{i,t}|{d}_{i,t},{\boldsymbol{W}}_{it},{\boldsymbol{S}}_{it},{\boldsymbol{Z}}_{it}\ \right)= Var\left({\varepsilon}_{i,t}\right)={\sigma}_{\varepsilon}^2 \) in all time periods t, Cov(εi,t, εi,s| di,t, Wit, Sit, Zit ) = 0 for all t ≠ s and for fixed-effects ideally also \( \left({\varepsilon}_{i,t}|{d}_{i,t},{\boldsymbol{W}}_{it},{\boldsymbol{S}}_{it},{\boldsymbol{Z}}_{it}\ \right)\sim N\left(0,{\sigma}_{\varepsilon}^2\right) \).
- 15.
In contrast with estimates included in GDP figures by the national statistical offices, proxy estimated by Medina and Schneider (2019) offers uniform methodology and thus universally comparable values.
- 16.
GDP excess is equal to zero in case of GDP per capita being below 75,000 dollars. Amount exceeding this limit value causes proportionately higher GDP excess variable.
References
Arellano, M. (1987). Computing robust standard errors for within group estimators. Oxford Bulletin of Economics and Statistics, 49, 431–434. https://doi.org/10.1111/j.1468-0084.1987.mp49004006.x
Atkinson, G., & Marlier, A. C. (2015). Monitoring the evolution of income poverty and real incomes over time (CASE Papers, 2015(188)). Centre for Analysis of Social Exclusion. Available at: http://eprints.lse.ac.uk/103979. Accessed 1 Feb 2021.
Bala RM (2013) Limits of gross domestic product in characterizing economic welfare. EBEEC Conference Papers, 2013(5), Istanbul: 5th International Conference on the Economics of Balkan and Eastern Europe Countries in the Changed World (pp. 133–142). Available at: https://www.researchgate.net/publication/263652456_Limits_of_Gross_Domestic_Product_in_characterizing_economic_welfare. Accessed 27 Jan 2021.
Baltagi, B., & Chang, Y. J. (1994). Incomplete panels: A comparative study of alternative estimators for the unbalanced one-way error component regression model. Journal of Econometrics, 62(2), 67–89. https://doi.org/10.1016/0304-4076(94)90017-5
Clapp, J., & Sen, A. (1999). Development as freedom. International Journal, 55(1), 160–178. https://doi.org/10.2307/40203469
Costanza, R., Hart, M., Posner, S., & Talberth, J. (2009). Beyond GDP: The need for new measures of progress (The Pardee Papers, 2009(4)). Pardee Center for the Study of the Longer-Range Future. Available at: https://www.bu.edu/pardee/files/documents/PP-004-GDP.pdf. Accessed 2 Feb 2021.
Dasgupta, P. (1990). Well-being and the extent of its realisation in poor countries. The Economic Journal, 100(400), 1–32. https://doi.org/10.2307/2234181
Deb, S. (2015). Gap between GDP and HDI: Are the rich country experiences different from the poor? Paper for the IARIW-OECD Special Conference: “Whither the SNA”, Paris: OECD Conference. Available at: http://old.iariw.org/papers/2015/deb.pdf. Accessed 27 Jan 2021.
Dynan, K., & Sheiner, L. (2018). GDP as a measure of economic well-being (Hutchins Center Working Paper 2018(43)). Hutchin Center on Fiscal and Monetary Policy. Available at: https://www.brookings.edu/research/gdp-as-a-measure-of-economic-well-being. Accessed 11 Feb 2021.
Giannetti, B. F., Agostinho, F., Almeida, C. M. V. B., & Huisingh, D. (2015). A review of limitations of GDP and alternative indices to monitor human wellbeing and to manage eco-system functionality. Journal of Cleaner Production, 87, 11–25. https://doi.org/10.1016/j.jclepro.2014.10.051
Hopkins, M. (1991). Human development revisited: A new UNDP report. World Development, 19(10), 1469–1473. https://doi.org/10.1016/0305-750x(91)90089-z
Hudakova, J. (2017). Relationship between gross domestic product and human development index. In 4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2017. Modern Science – Economics and Tourism (pp. 665–672). https://doi.org/10.5593/sgemsocial2017/14/s04.087
Kahneman, D., & Deaton, A. (2010). High income improves evaluation of life but not emotional well-being. Proceedings of National Academy of Sciences, 107(38), 16489–16493. https://doi.org/10.1073/pnas.1011492107
Klasen, S. (2018). Human development indices and indicators: A critical evaluation (UNDP Background Paper). UNDP Human Development Report Office. Available at: http://hdr.undp.org/en/content/human-development-indices-and-indicators-critical-evaluation. Accessed 23 Feb 2021.
Lange, G. M., Wodon, Q., & Carey, K. (2017). The changing wealth of nations 2018: Building a sustainable future. World Bank. https://doi.org/10.1596/978-1-4648-1046-6
Medina L and Schneider FG (2019) Shedding light on the shadow economy: A global database and the interaction with the official one. CESifo Working Paper No. 7981. Available at: https://ssrn.com/abstract=3502028. Accessed 2 Mar 2021.
Nolan, B., Roser, M., & Thewissen, S. (2018). GDP per capita versus median household income: What gives rise to the divergence over time and how does this vary across OECD countries? Review of Income and Wealth, 65(3), 465–494. https://doi.org/10.1111/roiw.12362
Osberg, L., & Sharpe, A. A. (2001). Comparisons of Trends in GDP and Economic Well-being – The Impact of Social Capital (International Symposium Report, 2001) (pp. 310–351). Organization for Economic Co-operation and Development. Available at: https://www.oecd.org/innovation/research/1824740.pdf. Accessed 27 Jan 2021.
Sagar, A., & Najam, A. (1998). The human development index: A critical review. Ecological Economics, 25(3), 249–264. https://doi.org/10.1016/S0921-8009(97)00168-7
Stiglitz, J., Sen, A., & Fitoussi, J. P. (2009). The measurement of economic performance and social progress revisited: Reflections and overview. Sciences Po Publications 2009(33). Available at: https://ideas.repec.org/p/spo/wpmain/infohdl2441-5l6uh8ogmqildh09h4687h53k.html. Accessed 24 Jan 2021.
Swamy, P. A. V. B., & Arora, S. S. (1972). The exact finite sample properties of the estimators of coefficients in the error components regression models. Econometrica, 40(2), 261–275. https://doi.org/10.2307/1909405
Syrovatka, M. (2008). Jak (ne)měřit kvalitu života – kritické pohledy na index lidského rozvoje. Mezinárodní vztahy, 43(1), 9–37. Available at: https://www.development.upol.cz/uploads/dokumenty/Syrovatka_HDI.pdf. Accessed 3 Feb 2021).
Teker, S., & Guner, A. (2016). Whether development indices affect economic growth: A cross-country analysis. Procedia Economics and Finance, 38(2016), 340–346. https://doi.org/10.1016/S2212-5671(16)30206-4
UNDP (United Nations Development Programme). (2020). HDR 2020 technical notes. Available at: http://hdr.undp.org/sites/default/files/hdr2020_technical_notes.pdf. Accessed 19 Feb 2021.
Acknowledgments
The work on this chapter was funded by the internal grant of Prague University of Economics and Business #F1/03/2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Dědeček, R., Dudzich, V. (2022). Causes of Limitations of GDP Per Capita as an Indicator of Economic Development. In: Procházka, D. (eds) Regulation of Finance and Accounting. ACFA ACFA 2021 2020. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-99873-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-99873-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-99872-1
Online ISBN: 978-3-030-99873-8
eBook Packages: Economics and FinanceEconomics and Finance (R0)