Skip to main content
Log in

The Financial Burden of Having Children and Fertility Differentials Across Development and Life Stages: Evidence from Satisfaction Data

  • Research Paper
  • Published:
Journal of Happiness Studies Aims and scope Submit manuscript


Comparing the financial burden of having children across countries accompanies various types of measurement issues. The present study employs financial satisfaction to overcome the measurement issues and examines how the financial burden of having children differs across development stages. The challenge in this approach lies in detecting the impact of having children on financial satisfaction. To address this challenge, we focus our attention on the peculiar movement of satisfaction in the financial domain of life, which is measured by standardizing financial satisfaction by overall life satisfaction, and perform regression analyses using World and European Integrated Values Survey. The results show that the negative impact of having an additional child on satisfaction becomes particularly greater in the financial domain as income increases and total fertility rate (TFR) decreases. The results also indicate that having children offers a sense of financial security to the elderly in high TFR countries while this is not the case in lower TFR countries. These results support the general idea that the heavier financial burden of having children is a major cause of fertility decline and provide policy implications to find a way out of extremely low fertility.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others


  1. Examples of socioeconomic factors that are potentially responsible for the fertility decline include mortality decline (Ehrlich and Lui 1991; Kalemli-Ozcan 2002, 2003; Nerlove 1974; Soares 2005), technological progresses (Galor and Weil 1996, 2000), the empowerment of women (de la Croix and Vander Donckt 2010; Diebolt and Perrin 2013; Eswaran 2002; Komura 2013), the establishment of social security systems (Ehrlich and Kim 2007), and a decline in relative costs of leisure goods (Galindev 2011).

  2. For example, in the Leibenstein’s framework, in which the benefits of children are separated into consumption, labor, and old-age security utilities, the importance of labor utility and, later, security utility decreases with economic development (Leibenstein 1957). Similarly, in the value-of-children approach pioneered by Hoffman and Hoffman (1973), in which the psychological benefits of children are separated into nine categories, including economic utility, the importance of specific values differs across culture, countries, and development stages (e.g., Bulatao 1979a, b; Kağitçibaşi 1982; Kağitçibaşi and Ataca 2015; Nauck and Klaus 2007). Especially, economic utility decreases with economic development. Furthermore, Campbell and Bedford (2009) showed that in traditional societies, where psychological barriers exist, such as non-evidence-based restrictive medical rules and misinformation that prevent women from restricting the number of children, the removal of these barriers lead to a reduction in fertility. This suggests that the cost of restricting the number of children is perceived larger in traditional societies than in industrialized societies. These studies demonstrate that the perception of the role and value of children changes with economic development and affects fertility behavior.

  3. Here, we use happiness and life satisfaction interchangeably.

  4. See, e.g., Hamermesh (2004) for the issues using subjective data for regression analyses.

  5. As argued in Stanca (2012), “in the absence of longitudinal data or appropriate instruments, relatively little can be done to address endogeneity.” Given this constraint, Stanca (2012) added the ideal number of children to explanatory variables as a proxy for unobserved individual characteristics. Our approach would potentially be a promising method to handle endogeneity in the SWB studies and deserves further research.

  6. Our preliminary analyses also could not reject the endogeneity of the ideal number of children for regressing financial satisfaction.

  7. Indeed, unobserved individual heterogeneity discussed above is one prominent example of omitted variables.

  8. For the details of the database, see Inglehart et al. (2000).

  9. China is omitted as its one-child policy may influence the regression results in unexpected ways.

  10. The outlier is Nigeria.

  11. Exceptions are found in some years in Bangladesh, Taiwan, India, Vietnam, and Turkey.

  12. The regression model can be presented as

    (1) \(SFS = \alpha CHILD + {\mathbf{x}}\mathcal{\beta } + u\)

    (2) \(CHILD = \gamma IDEAL + {\mathbf{x}}\mathcal{\delta } + v\)where \({\mathbf{x}}\) is a vector of control variables including a constant, α, \(\mathcal{\beta }\), γ, and \(\mathcal{\delta }\) are corresponding coefficients, and \(u\) and \(v\) are error terms.

  13. Excluding respondents that scored financial and overall life satisfaction equally does not change the results in any meaningful manner. Neither does only using recent data (Waves 3–5).

  14. It is worth noting that these results do not necessarily mean that children are net financial contributors to parents in an absolute monetary term even in high TFR countries.

  15. With respect to control variables, we obtain three interesting results. First, the coefficients of income class are always significantly positive. This is consistent with expectation. Second, the sex dummy becomes significantly negative only in low and very low TFR countries, likely pointing to a substantial financial load among mothers in these countries. Third, the coefficients of education are significantly positive only in high TFR countries, demonstrating the importance of education as an economic activity in less developed countries. As for other variables, further research is required to fully understand their impacts.

  16. Although insignificant, the coefficient of CHILD is quite large in absolute value at young age in low TFR countries. This potentially reflects a tight financial constraint at young age.

  17. Fertility has recently increased in several countries in which fertility used to be extremely low. This could potentially be due to the decline in the financial burden of parenthood in these countries, as suggested by the present study. However, the data set in this study contains data up to the year 2008, and thus the present findings are not directly applicable for examining the recent upward trend in fertility.

  18. Instead of ln(SFS), we can also use the difference of FS and LS as the dependent variable. However, the results do not change in any meaningful way.


  • Becchetti, L., Ricca, E. G., & Pelloni, A. (2013). The paradox of children and life satisfaction. Social Indicators Research, 111(3), 725–751.

    Article  Google Scholar 

  • Becker, G. S. (1960). An economic analysis of fertility. In G. B. Roberts (Ed.), Demographic and economic change in developed countries (pp. 209–240). New York: Columbia University Press.

    Google Scholar 

  • Bulatao, R. A. (1979a). On the nature of the transition in the value of children. Honolulu: East-West Center.

    Google Scholar 

  • Bulatao, R. A. (1979b). Further evidence of the transition in the value of children. Honolulu: East-West Center.

    Google Scholar 

  • Campbell, M., & Bedford, K. (2009). The theoretical and political framing of the population factor in development. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1532), 3101–3113.

    Article  Google Scholar 

  • Cracolici, M. F., Giambona, F., & Cuffaro, M. (2014). Family structure and subjective economic well-being: Some new evidence. Social Indicators Research, 118, 433–456.

    Article  Google Scholar 

  • de la Croix, D., & Vander Donckt, M. (2010). Would empowering women initiate the demographic transition in least developed countries? Journal of Human Capital, 4(2), 85–129.

    Article  Google Scholar 

  • Demoussis, M., & Giannakopoulos, N. (2008). Analysis of domain satisfactions: evidence from a panel of Greek women. Journal of Socio-Economics, 37(4), 1347–1362.

    Article  Google Scholar 

  • DePianto, D. E. (2011). Financial satisfaction and perceived income through a demographic lens: Do different race/gender pairs reap different returns to income? Social Science Research, 40(3), 773–783.

    Article  Google Scholar 

  • Diebolt, C., & Perrin, F. (2013). From stagnation to sustained growth: The role of female empowerment. American Economic Review, 103(3), 545–549.

    Article  Google Scholar 

  • Easterlin, R. A. (2006). Life cycle happiness and its sources intersections of psychology, economics, and demography. Journal of Economic Psychology, 27(4), 463–482.

    Article  Google Scholar 

  • Ehrlich, I., & Kim, J. (2007). Social security and demographic trends: Theory and evidence from the international experience. Review of Economic Dynamics, 10(1), 55–77.

    Article  Google Scholar 

  • Ehrlich, I., & Lui, F. (1991). Intergenerational trade, longevity, and economic growth. Journal of Political Economy, 99(5), 1029–1059.

    Article  Google Scholar 

  • Eswaran, M. (2002). The empowerment of women, fertility, and child mortality: Towards a theoretical analysis. Journal of Population Economics, 15(3), 433–454.

    Article  Google Scholar 

  • Ferrer-i-Carbonell, A., & Gerxhani, K. (2011). Financial satisfaction and (in) formal sector in a transition country. Social Indicators Research, 102(2), 315–331.

    Article  Google Scholar 

  • Ferrer-i-Carbonell, A., & Van Praag, B. M. (2003). Income satisfaction inequality and its causes. Journal of Economic Inequality, 1(2), 107–127.

    Article  Google Scholar 

  • Galindev, R. (2011). Leisure goods, education attainment and fertility choice. Journal of Economic Growth, 16(2), 157–181.

    Article  Google Scholar 

  • Galor, O., & Weil, D. N. (1996). The gender gap, fertility, and growth. American Economic Review, 86(3), 374–387.

    Google Scholar 

  • Galor, O., & Weil, D. N. (2000). Population, technology, and growth: From Malthusian stagnation to the demographic transition and beyond. American Economic Review, 90(4), 806–828.

    Article  Google Scholar 

  • Hamermesh, D. S. (2004). Subjective outcomes in economics. Southern Economic Journal, 71(1), 2–11.

    Article  Google Scholar 

  • Hank, K., & Wagner, M. (2013). Parenthood, marital status, and well-being in later life: Evidence from SHARE. Social Indicators Research, 114(2), 639–653.

    Article  Google Scholar 

  • Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054.

    Article  Google Scholar 

  • Hansen, T. (2012). Parenthood and happiness: A review of folk theories versus empirical evidence. Social Indicators Research, 108(1), 29–64.

    Article  Google Scholar 

  • Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271.

    Article  Google Scholar 

  • Hoffman, L. W., & Hoffman, M. L. (1973). The value of children to parents. In J. T. Fawcett (Ed.), Psychological perspective on population (pp. 19–76). New York: Basic Book.

    Google Scholar 

  • Inglehart, R., et al. (2000). World values surveys and European values surveys, 1981–1984, 1990–1993, and 1995–1997. Ann Arbor, MI: ICPSR.

    Google Scholar 

  • Kağitçibaşi, Ç. (1982). Old-age security value of children cross-national socioeconomic evidence. Journal of Cross-Cultural Psychology, 13(1), 29–42.

    Article  Google Scholar 

  • Kağitçibaşi, Ç., & Ataca, B. (2015). Value of children, family change, and implications for the care of the elderly. Cross-Cultural Research, 49(4), 374–392.

    Article  Google Scholar 

  • Kalemli-Ozcan, S. (2002). Does the mortality decline promote economic growth? Journal of Economic Growth, 7(4), 411–439.

    Article  Google Scholar 

  • Kalemli-Ozcan, S. (2003). A stochastic model of mortality, fertility, and human capital investment. Journal of Development Economics, 70(1), 103–118.

    Article  Google Scholar 

  • Komura, M. (2013). Fertility and endogenous gender bargaining power. Journal of Population Economics, 26(3), 943–961.

    Article  Google Scholar 

  • Lee, R. (2013). Intergenerational transfers, the biological life cycle, and human society. Population and Development Review, 38(s1), 23–35.

    Article  Google Scholar 

  • Leibenstein, H. (1957). Economic backwardness and economic growth. New York: Wiley.

    Google Scholar 

  • López-Pérez, B., & Wilson, E. L. (2015). Parent–child discrepancies in the assessment of children’s and adolescents’ happiness. Journal of Experimental Child Psychology, 139, 249–255.

    Article  Google Scholar 

  • Nauck, B., & Klaus, D. (2007). The varying value of children empirical results from eleven societies in Asia, Africa and Europe. Current Sociology, 55(4), 487–503.

    Article  Google Scholar 

  • Nelson, S. K., Kushlev, K., & Lyubomirsky, S. (2014). The pains and pleasures of parenting: When, why, and how is parenthood associated with more or less well-being? Psychological Bulletin, 140(3), 846.

    Article  Google Scholar 

  • Nerlove, M. (1974). Household and economy: toward a new theory of population and economic growth. Journal of Political Economy, 82(2), 200–218.

    Article  Google Scholar 

  • Newman, C., Delaney, L., & Nolan, B. (2008). A dynamic model of the relationship between income and financial satisfaction: Evidence from Ireland. Economic and Social Review, 39(2), 105–130.

    Google Scholar 

  • Nomaguchi, K. M. (2012). Parenthood and psychological well-being: Clarifying the role of child age and parent–child relationship quality. Social Science Research, 41(2), 489–498.

    Article  Google Scholar 

  • Ogawa, N., Mason, A., Chawla, A., Matsukura, R., & Tung, A. C. (2009). Declining fertility and the rising cost of children: what can NTA say about low fertility in Japan and other Asian countries? Asian Population Studies, 5(3), 289–307.

    Article  Google Scholar 

  • Oyama, M. (2006). Measuring cost of children using equivalence scale on Japanese panel data. Applied Economics Letters, 13(7), 409–415.

    Article  Google Scholar 

  • Panopoulou, G., & Tsakloglou, P. (1999). Fertility and economic development: theoretical considerations and cross-country evidence. Applied Economics, 31(11), 1337–1351.

    Article  Google Scholar 

  • Peiro, A. (2006). Happiness, satisfaction and socio-economic conditions: Some international evidence. Journal of Socio-Economics, 35(2), 348–365.

    Article  Google Scholar 

  • Penn, D. (2009). Financial well-being in an urban area: an application of multiple imputation. Applied Economics, 41(23), 2955–2964.

    Article  Google Scholar 

  • Plagnol, A. C. (2011). Financial satisfaction over the life course: The influence of assets and liabilities. Journal of Economic Psychology, 32(1), 45–64.

    Article  Google Scholar 

  • Pollmann-Schult, M. (2014). Parenthood and life satisfaction: Why don’t children make people happy? Journal of Marriage and Family, 76(2), 319–336.

    Article  Google Scholar 

  • Rojas, M. (2007). A subjective well-being equivalence scale for Mexico: Estimation and poverty and income-distribution implications. Oxford Development Studies, 35(3), 273–293.

    Article  Google Scholar 

  • Soares, R. R. (2005). Mortality reductions, educational attainment, and fertility choice. American Economic Review, 95(3), 580–601.

    Article  Google Scholar 

  • Stanca, L. (2012). Suffer the little children: Measuring the effects of parenthood on well-being worldwide. Journal of Economic Behavior & Organization, 81(3), 742–750.

    Article  Google Scholar 

  • Umberson, D., Pudrovska, T., & Reczek, C. (2010). Parenthood, childlessness, and well-being: A life course perspective. Journal of Marriage and Family, 72(3), 612–629.

    Article  Google Scholar 

  • Van Praag, B. M., Frijters, P., & Ferrer-i-Carbonell, A. (2003). The anatomy of subjective well-being. Journal of Economic Behavior & Organization, 51(1), 29–49.

    Article  Google Scholar 

  • Van Praag, B. M., Romanov, D., & Ferrer-i-Carbonell, A. (2010). Happiness and financial satisfaction in Israel: Effects of religiosity, ethnicity, and war. Journal of Economic Psychology, 31(6), 1008–1020.

    Article  Google Scholar 

  • Vera-Toscano, E., Ateca-Amestoy, V., & Serrano-Del-Rosal, R. (2006). Building financial satisfaction. Social Indicators Research, 77(2), 211–243.

    Article  Google Scholar 

  • Zhang, J., & Zhang, J. (2004). How does social security affect economic growth? Evidence from cross-country data. Journal of Population Economics, 17(3), 473–500.

    Article  Google Scholar 

Download references


We wish to thank Joshua Goldstein, Carl Mason, Movshuk Oleksandr, and anonymous referees for their helpful comments. Any remaining errors are our own. This study is supported by Grant-in-Aid for Scientific Research from JPSS in Japan (No. 263880243, 24730221). Part of this research was conducted at the University of California, Berkeley, at the University of Philippine, Diliman, and at Mage Nishikoku.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Junji Kageyama.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 3733 kb)



1.1 Descriptive Statistics, List of Countries, and Country-specific Means

See Tables 5 and 6.

Table 5 Descriptive statistics
Table 6 List of countries and country-specific means

1.2 Validity of Regression Results

1.2.1 Endogeneity Test

We perform the over-identification test (Hansen 1982) by adding an instrument, “importance in life: friends” for high and middle TFR countries, and “the importance in life: politics” for low and very low TFR countries. The results are presented in Table 7. As Hansen’s J-statistic demonstrates, all instruments can be treated as exogenous.

Table 7 Regression results (dependent variable: SFS. Categorized by TFR)

1.2.2 OLS versus IV

To assess the severity of the endogeneity bias, we estimate the same model with OLS. The results, presented in Table 8, show that the difference in the coefficients between IV and OLS estimations is significant for high TFR countries, suggesting that the endogeneity bias is more severe for high TFR countries. Performing the Wu–Hausman test (Hausman 1978), we obtain the results supporting the use of IV at the 1 % level for high TFR countries, and at the 15 % level for low and very low TFR countries. Thus, for comparing the results across various TFR levels, the IV method provides more consistent results.

Table 8 Regression results (dependent variable: SFS. categorized by TFR)

1.2.3 Robustness

To further assess the robustness of the estimation results, we regress the logarithm of SFS, which is technically a more accurate measure than SFS itself. We used SFS in the main analysis because the interpretation of estimated coefficients is more intuitive and because it can sufficiently reduce the endogeneity bias.

To see the logic behind the use of the logarithm of SFS, assume that financial satisfaction, FS, takes a log-linear form such that

$$\ln \left( {FS} \right) = a_{FS} CHILD + {\mathbf{xb}}_{{{\mathbf{FS}}}} + \theta_{FS} + \varepsilon_{FS}$$

where \(\theta_{FS}\) and \(\varepsilon_{FS}\) are respectively the unobserved individual characteristics and the usual error term and where \(\alpha_{FS}\) and \({\mathbf{b}}_{{{\mathbf{FS}}}}\) are coefficients. In reality, however, \(\theta_{FS}\) is unobservable and the error term in the regression equation contains not only \(\varepsilon_{FS}\) but also \(\theta_{FS}\). Thus, as discussed in Sect. 2, CHILD and the error term in the regression equation correlate with each other, and the estimated coefficient of CHILD becomes biased. Using IDEAL as the instrument does not solve the issue because IDEAL is also subjective data and expected to correlate with \(\theta_{FS}\).

Assume also that life satisfaction, LS, takes the same functional form. Then, by taking the difference, the logarithm of SFS can be written as

$$\ln \left( {SFS} \right) = \ln \left( {FS} \right) - \ln \left( {LS} \right) = \left( {a_{FS} - a_{LS} } \right)CHILD + {\mathbf{x}}\left( {{\mathbf{b}}_{{{\mathbf{FS}}}} - {\mathbf{b}}_{{{\mathbf{LS}}}} } \right) + \left( {\theta_{FS} - \theta_{LS} } \right) + \varepsilon$$

where \(\varepsilon = \varepsilon_{FS} - \varepsilon_{LS}\). Thus, by regressing ln(SFS), we can take the difference between \(\theta_{FS}\) and \(\theta_{LS}\), both of which share the same individual characteristics, and substantially reduce the endogeneity bias. In addition, this method allows us to use IDEAL as the instrument to further control the endogeneity bias.Footnote 18

Table 9 presents the regression results for the financial burden over the life course. The estimated results share the same characteristics as the ones presented in Table 4. Generally speaking, the results are, as expected, more robust than regressing SFS itself. In high TFR countries, the coefficient of CHILD increases with parent’s age. In middle TFR countries, it again turns from negative to positive at the late middle age whereas it is now insignificant even at the 10 % level at any age. In low TFR countries, while the coefficient becomes significant at a young age, it dips again at the late middle age with a higher level of significance. These results point to the robustness of the results of the present study.

Table 9 Regression results (dependent variable: ln(SFS). categorized by TFR and Age)

1.3 Data Sources

EVS (2011). “European Values Study 1981–2008, Longitudinal Data File.” GESIS Data Archive, Cologne, Germany, ZA4804 Data File Version 2.0.0 (2011-12-30) DOI:10.4232/1.11005.

WVS (2009). “World Value Survey 1981–2008 official aggregate v.20090902, 2009.” World Values Survey Association ( Aggregate File Producer: ASEP/JDS Data Archive, Madrid, Spain.

Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer (2013). “The Next Generation of the Penn World Table.” available for download at

UN (2013). “World Population Prospects, The 2012 Revision.” available for download at

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kageyama, J., Matsuura, T. The Financial Burden of Having Children and Fertility Differentials Across Development and Life Stages: Evidence from Satisfaction Data. J Happiness Stud 19, 1–26 (2018).

Download citation

  • Published:

  • Issue Date:

  • DOI: