Skip to main navigation menu Skip to main content Skip to site footer

Absolute value and diversity of household spending: analysis on International Comparison Program (ICP) 2011 data

Abstract

Research background: This article investigates the connection between consumer?s budget growth and diversification of household spending. The main question of research is ?are there new drivers of modern processes of consumer spending's diversification, at a time when spending on food has reached the minimum share in the consumer budget.

Purpose of the article: The objective of the article is to clarify the hypothesis about the existence of a certain limit of income (and consumer spending) after which the growing of consumer?s purchasing capacity loses power of influence on spending diversity.

Methods: Theil entropy index was used for measuring the diversity of household spending. This index was defined as a sum of within-group and between-group entropy, which allows for comparing the diversification of household spending in two aggregate groups of expenditure, which were formed by the authors. The Workings? equation was used for modeling the spending entropy?s dependence on their absolute value. Two categories of household spending were regrouped (consolidated) by us through forming a group more related to the development of human economic potential (SMRHD) and less related to these processes (SLRHD). The research was done on the basis of ICP (2011) data, which covers 178 countries and refers to 2011 year ? the latest available on the moment of the article was completed.

Findings & Value added: The results obtained in this research confirmed that there is a limit of household spending?s size, beyond which further increasing of consumers? economic opportunities loses a significant impact on the diversity of consumption spending. However, the weakening of the link between size of spending and its entropy reflects impact of two qualitative differenced factors. The first is relatively much more radical decrease of spending growth influence on within-group entropy for SLRHD. The second ? is relatively much less significant decrease of entropy?s sensitivity to spending growth for SMRHD. Such results reflect the increase in the importance of "non-functional demand components", which reduces the capacity of data on functional distribution of household expenditures to characterize the extent of their diversification.

Keywords

household spending, entropy of consumption basket, consumption patterns, consumer choice, grouping of household spending categories

PDF

References

  1. Acemoglu, D., & Pischke, J.-S. (1999). The structure of wages and investment in general training. Journal of Political Economy, 107. doi: 10.3386/w6357. DOI: https://doi.org/10.1086/250071
    View in Google Scholar
  2. Yang, X., & Huang, W. (2017). Human capital investment inequality and rural-urban income gap: evidence from China. In Advances in Pacific Basin business economics and finance. Volume 5. Emerald Publishing Limited. DOI: https://doi.org/10.1108/S2514-465020170000001007
    View in Google Scholar
  3. Bleakley, H. (2010). Health, human capital, and development. Annual Review of Economics, 2. doi: 10.1146/annurev.economics.102308.124436. DOI: https://doi.org/10.1146/annurev.economics.102308.124436
    View in Google Scholar
  4. Bloom, D., & Canning, D. (2003). Health as human capital and its impact on economic performance. Geneva Papers on Risk and Insurance, 28(2). DOI: https://doi.org/10.1111/1468-0440.00225
    View in Google Scholar
  5. Boopen, S. (2006). Transport infrastructure and economic growth: evidence from Africa using dynamic panel estimates. Empirical Economics Letters, 5(1).
    View in Google Scholar
  6. Chai, A., Rohde, N., & Silber, J. (2014). Measuring the diversity of household spending patterns. Journal of Economics Surveys, 29(3). doi: 10.1111/joes. 12066. DOI: https://doi.org/10.1111/joes.12066
    View in Google Scholar
  7. Chai, A., & Moneta, A. (2012). Back to Engel? Some evidence for the hierarchy of needs. Journal of Evolutionary Economics, 1. doi: 10.3386/w6357. DOI: https://doi.org/10.1007/s00191-012-0283-3
    View in Google Scholar
  8. Chang, K., & Yung-Hsiang, Y. (2006). Economic growth, human capital investment, and health expenditure: a study of OECD countries. Hitotsubashi Journal of Economics, 47. doi: 10.15057/7644.
    View in Google Scholar
  9. Clements, K. W., & Qiang, Y. (2003). The economics of global consumption patterns. Journal of Agricultural and Applied Economics, 35.
    View in Google Scholar
  10. Clements, K. W., Wu, Y., & Zhang, J. (2005). Comparing international consumption patterns. Empirical Economics, 31(1). doi: 10.1007/s00181-005-0012-y. DOI: https://doi.org/10.1007/s00181-005-0012-y
    View in Google Scholar
  11. Clements, K. W., & Chen, D. (1996). Fundamental similarities in consumer behaviour. Applied Economics, 28(6). doi: 10.1080/000368496328498. DOI: https://doi.org/10.1080/000368496328498
    View in Google Scholar
  12. Falkinger, J., & Zweimüller, J. (1996). The cross-country Engel curve for product diversification. Structural Change and Economic Dynamics, 7. DOI: https://doi.org/10.1016/0954-349X(95)00039-P
    View in Google Scholar
  13. Feldmann, H. (2017). Economic freedom and human capital investment. Journal of Institutional Economics, 13(2). doi: 10.1017/s174413741600028x. DOI: https://doi.org/10.1017/S174413741600028X
    View in Google Scholar
  14. Leibenstein, H. (1950). Bandwagon, snob, and Veblen effects in the theory of consumers' demand. Quarterly Journal of Economics, 64(2). doi: 10.2307/ 1882692. DOI: https://doi.org/10.2307/1882692
    View in Google Scholar
  15. Lewbel, A. (2005). Modelling heterogeneity. Boston College Working Papers in Economics, 650.
    View in Google Scholar
  16. Lewbel, A. (2008). Engel curves. In New Palgrave dictionary of economics. Palgrave Macmillan. DOI: https://doi.org/10.1057/978-1-349-95121-5_525-2
    View in Google Scholar
  17. Muhammad, A., James, L. S., Jr., Meade, B., & Regmi, A. (2011). International evidence on food consumption patterns: an update using 2005 International Comparison Program Data. TB-1929. U.S. Dept. of Agriculture, Econ. Res. Serv. DOI: https://doi.org/10.2139/ssrn.2114337
    View in Google Scholar
  18. Randolph, S., Bogetic, Z., & Helfey, D. (1996). Determinants of public expenditure on infrastructure. Transportation and communication. World Bank Policy research Working Paper, 1661.
    View in Google Scholar
  19. Seale, J. L. Jr., & Regmi, A. (2006). Modeling international consumption patterns. Review of Income and Wealth, 52(4). doi:10.1111/j.1475-4991.2006.00204.x. DOI: https://doi.org/10.1111/j.1475-4991.2006.00204.x
    View in Google Scholar
  20. Theil, H. (1987). The econometrics of demand systems. In H. Theil & K.W. Klements (Eds.). Applied demand analysis: results from system-wide approaches. Cambridge, MA: Ballinger Press.
    View in Google Scholar
  21. Theil, H., & Finke, R. (1983). The consumer’s demand for diversity. European Economic Review, 23(3). DOI: https://doi.org/10.1016/0014-2921(83)90039-9
    View in Google Scholar
  22. Theil, H., Chung, C. F., & Seale J. L. (1989). International evidence on consumption patterns. JAI Press.
    View in Google Scholar
  23. Turi, K. N., Masuda, T., & Goldsmith, P. (2009). Exploiting long-term co-integration between major animal and aquatic food commodities and countries GDP for robust forecasting. Working Paper. January.
    View in Google Scholar
  24. World Bank (2015). Purchasing power parities and the real size of world economies: a comprehensive report of the 2011 International Comparison Program. Washington, DC: World Bank. doi: 10.1596/978-1-4648-0329-1. DOI: https://doi.org/10.1596/978-1-4648-0329-1
    View in Google Scholar
  25. Working, H. (1943). Statistical laws of family expenditure. Journal of the American Statistical Association, 38(221). DOI: https://doi.org/10.1080/01621459.1943.10501775
    View in Google Scholar

Similar Articles

1-10 of 108

You may also start an advanced similarity search for this article.