Human mating behaviour continues to have significant influences on both individuals and society as a whole. Various economic theories have been applied in an attempt to interpret and model human mate choice decisions; however, arguably the most common is that of assortative mating (or homogamy) (Pencavel, 1998).
If you need assistance with writing your essay, our professional essay writing service is here to help!
Though there are numerous qualities considered by individuals when searching for a potential partner, this paper will focus on the two most common and economically relevant: education and income, and their impact on human mating behaviour. Research demonstrates that educational homogamy is dominant in the marriage market, as education is often associated with social ranking and intelligence, which positively impact mate value (Correia, 2003). Additionally, given income and wealth are strongly correlated with educational attainment, it is expected that economic assortment is also prevalent (Kalmijn, 1994). Wealth is also known to be a factor that increases an individuals’ attractiveness (Sterelny & Fitness, 2003).
The underlying neoclassical economics framework supporting most assortative mating research is the theory of preferences in a marriage market (Schwartz, 2013). It suggests that individuals compete with each other to find their preferred mate, however, face constrained opportunities e.g. laws and cultural norms (Becker,1974). Individuals are assumed to be rational and self-interested utility maximisers and should therefore, search for the highest utility payoff available in a mate. Consequently, people favour partners with education levels and income that are equivalent or higher than their own (Whyte & Torgler, 2017).
However, the nature of such competition in the marriage market varies with changes in social norms; more specifically, the role of women in society. In traditional sex roles a strong gender division of labour exists, causing men and women to specialize in ‘breadwinning’ and ‘homemaking’, respectively. As a result, there is an exchange between male economic resources and female resources in other domains, e.g. high-class backgrounds and physical attractiveness (Becker, 1981; Stevens, Owens, & Schaefer, 1990).This is due to the income discrepancies between genders in the labour market, providing men with a comparative advantage in paid labour and lowering the opportunity cost of working for women. Consequently, a women’s time is used more productively when spent on domestic labour (Kalmijn, 1994).
Conversely, as gender roles become more homogenous, this exchange becomes less prominent (Kalmijn, 1994). With gender equality on the rise, Australia has experienced a rapid increase of approximately 20 percent in female labour force participation over the past four decades and the participation gap between male and females has reduced by more than 70 percent (refer to Figure 1). As a result, dual-income households have become increasingly more common (ABS, 2019).
Figure 1: Labour Force Participation Rate
Concurrent with this increase in female labour force participation, Australia has also seen changes in the nature of females’ work. During the Baby Boom, married women’s contribution to the household budget was at a historical low and females commonly only worked as a means to supplement their husband’s temporarily low income (Janssens, 1997). However, in modern times, females’ field of work have increasingly begun to reflect independent career choices (Kalmijn, 1994).
Additionally, since the 1960s, there has been an increase in higher educational attainment among females, with women representing 58.4 percent of students in higher education and out-numbering men in completion rates (WGEA,2019).
Based on these societal changes, numerous academics have concluded that education and economic resources have become key characteristics in partner selection for men now too, just as it always has been for females (Davis, 1984; Mare, 1991). Since these traits have become more symmetrical between males and females, the Australian marriage market has seen a rise in educational and income-based assortment (Worner, 2006).
It has been argued that increased assortative mating on an educational and income basis, can have significant social and economic implications, particularly on income distribution and fertility (Worner, 2006; Bratsberg et al., 2018; Nomes & Bavel, 2016).
Microeconomic theories propose that higher education and income could lead to either a positive income effect on fertility, as childrearing is costly, or a negative substitution effect, since higher salaries imply greater opportunity costs for having children (Kravdal & Rindfuss, 2008). However, given a gender wage gap exists and expectations of involvement in domestic labour and childrearing differ, these effects of educational attainment and income on fertility significantly vary between genders (Becker, 1981). As a result, it is important to analyse the issue on a couple-level, rather than individual. When these substitution and income effects between partners balance, an efficient family model is achieved and is subsequently conducive to fertility. Therefore, a couple would be conducive to childbearing when an imbalance of earning potential (traditionally in favour of the male) exists(Becker, 1981).
Figure 2: Total Fertility Rate
This was evident after World War II when Australia experienced a peak of 3.548 percent in birth rates (as seen in Figure 2) (ABS, 2013). This rapid increase can be attributed to the strong sexual division of labour and prevailing gender roles during this era (Janssens,1997).
Our academic experts are ready and waiting to assist with any writing project you may have. From simple essay plans, through to full dissertations, you can guarantee we have a service perfectly matched to your needs.
However, with increases in female labour force participation, the division of labour is diverging from traditional sex roles and economically homogamous couples have become increasingly more prevalent. These pairings likely face lower fertility rates than traditional hypergamous couples, due to higher opportunity costs given the reduced gender wage gap caused by increased job opportunities and higher educational attainment for women (Mulligan & Rubinstein, 2008). This is further supported by timing effects as higher educational attainment is generally associated with delays in parenthood and low fertility, especially for women (Nomes & Bavel, 2016). As fecundity declines with age, an earlier transition into marriage and childbearing is correlated with greater amounts of offspring (Berrington et.al, 2015). Figure 2 clearly demonstrates this decline, as total fertility fell to 1.9 percent in 2012 since its peak in 1961(ABS, 2013).
It should be noted however, that for highly educated, and thus wealthy, homogamous couples, the opportunity cost of having children may be smaller as their household income may be enough to outsource childcare (Nomes & Bavel, 2016).
Additionally, where both partners are of low education levels, although they experience lower opportunity costs for having children, their limited income and thus parental investment resources may negatively affect their fertility levels. However, such negative effects are potentially offset as individuals with lower educational attainment are likely to marry earlier and value quantity over quality in terms of offspring (Becker & Lewis, 1974).
Overall, each combination of education and income between partners could lead to a different result for marital fertility and therefore, the impact of assortative mating on fertility is difficult to measure. However, educational and income homogamy is generally found to have negative associations with a couple’s fertility due to higher opportunity costs i.e. a stronger substitution effect (Becker 1991).
Given total fertility rate and its position relative to the replacement level is strongly correlated with a nation’s future productivity and economic development, the decline in fertility rates poses a serious macroeconomic problem for Australia. Although reduced fertility is found to induce improvements in labour force participation, education, and economic growth, when it falls below replenishment rate countries face population decline and aging populations (Ashraf & Weil, 2013).
Since 1976, Australia’s total fertility rate has been below the replenishment rate. Consequently, there have been insufficient amounts of young people entering the workforce to offset the numbers that are leaving (ABS,2013) (ABS,2009). Therefore, retirement age has since increased, as a decade ago only 9 per cent of people aged 65 and over were employed, whereas this increased to 13 per in 2016 (ABS,2017). This has impacted labour productivity, as an older workforce is a found to be less productive and the older consumers’ consumption patterns may shift capital and labour towards industries with higher labour to output shares e.g. health care. This poses the issue of slowing economic growth for Australia (Parliamentary Budget Office, 2019).
Assortative mating by income and education not only impacts fertility, but also income and wealth distribution (Schwartz, 2013). Over the past two decades there has been increased concern regarding increased income inequality in Australia, with Australia’s Gini coefficient at 0.34, compared to an OECD average of 0.32 (ABS, 2019). As indicated in figure 3, households in the highest quantile have an income of almost five times that of the lowest. Clearly, the disparity in earnings has widened over time, with steady increases between 1981 and 2007 and a drastic upsurge during the Global Financial Crisis (GFC) (ABS, 2019).
Figure 3: Income Distribution (1994-2018)
Australian Bureau of Statistics (ABS). (2019, July 12). Household Income and Wealth, Australia, 2017 18. Retrieved from: https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6523.02017-18?OpenDocument
Such levels of inequality result in societal segregation, since people in lower income brackets participate less in society as they struggle to attain a socially acceptable living standard. Economic growth also weakens as resources are concentrated among a single group and disadvantaged individuals cannot effectively participate in paid labour, or acquire the skills to do so (University of New South Wales, 2018).
The increasing economic and educational resemblance of spouses has contributed to this rising income inequality, as the number of couples with both high or both low-earning partners has increased (Gonalons-Pons & Schwartz, 2017). Several studies have shown that countries with greater income inequality and returns to schooling have higher levels of educational homogamy (Dahan & Gavairia, 2001; Torche , 2010). This interpretation is supported by the microeconomic theory mentioned earlier, as people face greater opportunity costs when ‘marrying down’ in countries with higher inequality (Schwartz, 2013).
Furthermore, increases in Australia’s residential segregation between higher and lower household income further aggravates educational and income homogamy as individuals are restricted from meeting potential mates in different income brackets (University of Melbourne, 2018). As a result, likelihood of intermarriage and individuals’ economic mobility decreases (Schwartz, 2013).
While these changes in mate choice preferences and their implications on income distribution clearly affect today’s adults, there may also be significant impacts on the educational and economic outcomes of later generations. Due to intergenerational transmission, future generations may experience a rise in inequality, consequently reducing economic and social mobility (Kremer, 1997; Fernandez & Rogerson, 2001). Studies show that the socioeconomic status of parents is highly correlated with a child’s educational success and income potential (Björklund & Salvanes, 2010). Therefore, increased educational/income assortment exacerbates inequality among future generations and may even dampen a nation’s long-run economic growth (Greenwood et al., 2014).
To summarize, it is clear that the increase in educational homogamy was largely driven by increases in labour participation rates and higher educational attainment among females (Kalmijn, 1994). Literature to date suggests that this rise in assortative mating by education and income has exacerbated Australia’s income inequality and decline in fertility rates (Nomes & Bavel, 2016) (Schwartz, 2013). However, the proportion of change attributed to assortative mating is difficult to measure, as the trends seen may also be due to other contributing factors. Thus, further research is required to fully assess the implications of homogamy on fertility and income equality.
- Australian Bureau of Statistics (ABS). (2019, July 12). Household Income and Wealth, Australia, 2017-18. Retrieved from https://www.abs.gov.au/household-income
- Ashraf, Q. H., & Weil, D. N. (2013). The Effect of Fertility Reduction on Economic Growth. Population and Development Review, 39(1), 97-130.
- Australian Bureau of Statistics (ABS). (2009, January 16). Australian Labour Market Statistics, Jan 2009. Retrieved from https://www.abs.gov.au/ausstats/abs@.nsf/0/36EDBADC29D261FECA25776100150592?OpenDocument
- Australian Bureau of Statistics (ABS). (2013, October 24). Births, Australia, 2012. Retrieved from Australian Bureau of Statistics : https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3301.02012?OpenDocument
- Australian Bureau of Statistics (ABS). (2017, December 18). Retirement and Retirement Intentions, Australia, July 2016 to June 2017. Retrieved from https://www.abs.gov.au/ausstats/abs@.nsf/products/FA701E410A126C43CA2573D700161420
- Australian Bureau of Statistics (ABS). (2019, July). Labour Force, Australia, Jul 2019. Retrieved from https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6202.0Jul%202019?OpenDocument
- Becker, G. S. (1974). A theory of marriage. In T. W. Schultz, Economics of the Family: Marriage, Children, and Human Capital (pp. 299-351). Chicago: University of Chicago Press.
- Becker, G. S. (1981). A Treatise on Family. Cambridge, Massachusetts: Harvard University Press.
- Becker, G. S., & Lewis, G. H. (1974). Interaction between Quantity and Quality of Children. National Bureau of Economic Research, 81-90.
- Berrington, A., Stone, J., & Beaujouan, E. (2015). Educational differences in timing and quantum of childbearing in britain: A study of cohorts born 1940-1969. Demographic Research, 33, 733-764.
- Björklund, A., & Salvanes, K. (2010). Education and family background: Mechanisms and policies. IDEAS Working Paper Series. Retrieved from http://search.proquest.com/docview/1698468998/
- Blau, F. D., Brummund, P., & Liu, Y.-H. A. (2013). Erratum to Trends in Occupational Segregation by Gender 1970-2009: Adjusting for the Impact of Changes in the Occupational Coding System. Demography, 50(2), 493-494. doi:https://doi.org/10.1007/s13524-013-0198-0
- Bratsberg, B., Markussen, S., Rauum, O., Roed, K., & Rogeberg, O. (2018). Trends in Assortative Mating and Offspring Outcomes. Norway: IZA Institute of LAbor Economics.
- Correia, H. R. (2003). Higher Male Educational Hypergamy: Evidence from Portugal. Journal of Biosocial Science, 35(2), 303313. doi:https://doi.org/10.1017/S0021932003003031
- Dahan, M., & Gavairia, A. (2001). Sibling correlations and intergenerational mobility in Latin America. Economic Development and Cultural Change, 49, 537-554.
- Davis, K. (1984). Wives and Work: Consequences of the Sex Role Revolution. Population and Development Review, 10, 397-417.
- Fernandez, R., & Rogerson, R. (2001). Sorting and Long-Run Inequality. Quarterly Journal of Economics, 116, 1305-1341.
- Gonalons-Pons, P., & Schwartz, C. R. (2017). Trends in Economic Homogamy: Changes in Assortative Mating or the Division of Labor in Marriage? Demography, 54(3), 985-1005. doi:https://doi.org/10.1007/s13524-017-0576-0
- Greenwood, J., Guner, N., Kocharkov, G., & Santos, C. (2014). Marry Your Like: Assortative Mating and Income Inequality. American Economic Review, 104(5), 348-353.
- Janssens, A. (1997). The Rise and Decline of the Male Breadwinner Family? An Overview of the Debate. International Review of Social History, 42(S5), 1-23. doi:https://doi.org/10.1017/S0020859000114774
- Kalmijn, M. (1994). Assortative Mating by Cultural and Economic Occupational Status. American Journal of Sociology, 100, 422-452.
- Kravdal, O., & Rindfuss, R. R. (2008). Changing Relationships between Education and Fertility: A Study of Women and Men Born 1940 to 1964. American Sociological Review, 73(5), 854-873.
- Kremer, M. (1997). How much does sorting increase inequality? Quarterly Journal of Economics, 112, 115-139.
- Mare, R. D. (1991). Five Decades of Educational Assortative Mating. American Sociological Review, 56, 15-32.
- Mulligan, C., & Rubinstein, Y. (2008). Selection, investment, and women’s relative wages over time. Quarterly Journal of Economics, 123, 1061-1110.
- Nomes, E., & Bavel, J. V. (2016). Marital Fertility and Educational Assortative MAting Before, During anf After the Baby Boom in Belgium. Centre for Sociological Research, University of Leuven.
- Parliamentary Budget Office. (2019). Australia’s Ageing Population. Commonwealth of Australia.
- Pencavel, J. (1998). Assortative mating by schooling and the work behavior of wives and husbands. The American Economic Review, 88(2), 326-329.
- Schwartz, C. R. (2013). Trends and Variation in Assortative Mating: Causes and Consequences. Annual Review of Sociology, 39, 451-470.
- Stevens, G., Owens, D., & Schaefer, E. C. (1990). Education and Attractiveness in Marriage Choices. Social Psychology Quarterly, 53, 62-70.
- Torche , F. (2010). Educational assortativemating and economic inequality: a comparative analysis of three Latin American Countries. Demography, 47, 481-502.
- University of Melbourne. (2018). Improving housing affordability. Retrieved from Parliament of Australia: https://www.aph.gov.au/Parliamentary_Business/Committees/House/ITC/DevelopmentofCities/Report/section?id=committees%2Freportrep%2F024151%2F25689#footnote9target
- University of New South Wales. (2018). Inequality in Australia 2018. Strawberry Hills, NSW: Australian Council of Social Service. Retrieved from https://www.acoss.org.au/wp-content/uploads/2018/07/Inequality-in-Australia-2018_Factsheet.pdf
- Whyte, S., & Torgler, B. (2017). Things change with age: Educational assortment in online dating. Personality and Individual Differences, 109, 5-11.
- Workplace Gender Equality Agency (WGEA). (2019, August 9). Higher education enrolments and graduate labour market statistics. Retrieved from Australian Government: https://www.wgea.gov.au/data/fact-sheets/higher-education-enrolments-and-graduate-labour-market-statistics
- Worner, S. M. (2006). The Effects of Assortative Mating on Income Inequality: A Decompositional Analysis. Canberra: The Australian National University.