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Will you marry me? It depends (on the business cycle)

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Abstract

This paper studies the relationship between the business cycle and the marriage rate, using a panel data of 30 European countries for 1991 to 2018. Our results point to a pro-cyclical behavior of marriage rates, which holds after controlling for country-level observed and unobserved characteristics. We detect possible different responses of the marriage rate to the business cycle, after considering a wide range of country-level regulation affecting couples (taxation, property division, informal relationship regulations, and reproduction). Our findings suggest an important role of the cost/gain of marriage versus cohabitation/singlehood. Supplemental analysis reveals gender differences in the relationship between the business cycle and the marriage rate, depending on the previous legal marital status of the individuals. We provide additional evidence on the consequences of the pro-cyclical response of marriage rate by exploring variations in the stock of married/unmarried individuals. Results show a clear negative association between the business cycle and the stock of married individuals, but no negative response is found for the stock of those living as unmarried couples.

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Notes

  1. Sorted alphabetically, the countries included in our analysis are: Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom.

  2. Information collected from Busardò et al. 2014; Commission on European Family Law (http://ceflonline.net/country-reports-by-jurisdiction/); and the Ministry for Social Dialogue Consumer Affairs and Civil Liberties of Malta (info. on Cohabitation Law).

  3. This is not a minor issue, since the percentage of couples who resort to medical treatments related to infertility and assisted reproductive technology has dramatically increased (Kocourkova et al. 2014; Leridon and Slama 2008).

  4. As we have defined above, the CMR is the ratio of the number of marriages during the year to the average population in that year, expressed per 1000 inhabitants.

  5. We have used data for unemployment rates from different sources, such as the Organization for Economic Co-operation and Development (OECD) and the National Estimates, finding no differences in the results.

  6. The unemployment rate as a proxy of the business cycle can also be problematic. According to Schaller (2013), this is the best indicator to capture the business cycle, although it presents some weaknesses: it can understate the magnitude of economic downturns by failing to incorporate discouraged workers.

  7. We use as main variable of interest the total unemployment rate, but also the total female and total male unemployment rates in alternative estimates. Results are quite similar.

  8. Country-specific quadratic time trends have also been included as a robustness check. Results do not change.

  9. In the rest of the analysis, we only include country-specific linear trends, although results are unchanged when adding quadratic trends.

  10. We replicate every estimate using the CMR in logarithm as dependent variable, and conclusions do not change.

  11. We replicate every estimate using this estimator (that considers the population “at risk” of getting married), and conclusions do not change. However, since we lose almost 49% of the observations, we use the CMR as our main marriage indicator.

  12. We use the Ravn-Uhlig rule to determine the smoothing parameter, considering that we use annual data.

  13. Changes in the number of observations are due to the availability of information on those proxies of the business cycle dynamics.

  14. We do not show the estimations for the cyclical components of both variables of interest because of space constraints, but results are available upon request.

  15. Germany is also excluded from the analysis, since its current territory was part of both former territories.

  16. Source: The World Factbook of the CIA.

  17. Fifteen countries joined the European Union during the sample period: in 1995 (Austria, Finland and Sweden), in 2004 (Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovak Republic and Slovenia), and in 2007 (Bulgaria and Romania).

  18. Eighteen countries adopted the common currency during the sample period: in 1999 (Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Portugal and Spain), in 2001 (Greece), in 2007 (Bulgaria and Slovenia), in 2008 (Cyprus and Malta), in 2009 (Slovak Republic), and in 2011 (Estonia).

  19. We do not have information for all countries, nor for the entire period. For this reason, the number of observations changes in Table 9.

  20. Data come from the U.N. Statistics Division and Eurostat. Data on men and women by previous marital status (divorced, single, and widowed) have been linearly completed by the authors to avoid gaps, except for those countries to which it has not been possible to apply this technique. Results without the linear interpolation are maintained.

  21. Of course, in the literature we can find other papers that study other determinants of the transition into and out of marriage, such as family laws (González-Val and Marcén 2012a; 2012b; 2017; 2018b; Stevenson and Wolfers 2007), parenthood (Bellido et al. 2016; Steele et al. 2005), welfare reforms (Bitler et al. 2004), demographic factors such as gender ratios or ethnicity (Angrist 2002; Bulcroft and Bulcroft 1993; Manning and Smock 2002) and even medical advances (Goldin and Katz 2002; Marcén 2015). All appear to affect the transition into and out of marriage.

  22. Data for each country can be consulted at: https://ec.europa.eu/eurostat/fr/web/products-eurostat-news/-/DDN-20180809-1?inheritRedirect=true&redirect=%2Feurostat%2Ffr%2Fhome.

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Acknowledgements

The authors acknowledge the comments and suggestions of two anonymous referees and those of the editor, all of whom helped us to improve the quality of this work.

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  1. Universidad de Zaragoza, Zaragoza, Spain

    Héctor Bellido & Miriam Marcén

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  1. Héctor Bellido
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Correspondence to Héctor Bellido.

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Appendix

Appendix

Tables 16–18

Table 16 Crude marriage rate and unemployment rate differences (replication of baseline estimates)
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Table 17 Crude marriage rate and youth unemployment rates (replication of baseline estimates)
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Table 18 Married by previous marital status per 1000 (Columns (1)–(3): men; Columns (4)–(6): women)
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Bellido, H., Marcén, M. Will you marry me? It depends (on the business cycle). Rev Econ Household 19, 551–579 (2021). https://doi.org/10.1007/s11150-020-09493-z

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