Abstract
In this paper, we examine the role of the business cycle in divorce. To do so, we use a panel of 29 European countries covering the period from 1991 to 2012. We find the unemployment rate negatively affects the divorce rate, pointing to a pro-cyclical evolution of the divorce rate, even after controlling for socio-economic variables and unobservable characteristics that can vary by country, and/or over time. Results indicate that a one-percentage-point increase in the unemployment rate involves almost 0.025 fewer divorces per thousand inhabitants. The impact is small, representing around 1.2 % of the average divorce rate in Europe during the period considered. Supplementary analysis, developed to explore a possible non-linear pattern, confirms a negative relationship between unemployment and divorce in European countries, with the inverse relationship being more pronounced in those countries with higher divorce rates.
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Notes
“Hard Times in Spain Force Feuding Couples to Delay Divorce,” The New York Times, http://www.nytimes.com/2012/12/18/world/europe/hard-times-in-spain-force-feuding-couples-to-delay-divorce.html?pagewanted=all&_r=1&.
Due to problems with the availability of data on the divorce rate, we could not include in the analysis the following European countries: Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Georgia, Kosovo, Liechtenstein, Malta, Moldova, Monaco, Montenegro, Russia, San Marino, Serbia, Turkey, and Ukraine. The FYR of Macedonia was also excluded from the analysis, following the suggestions of two anonymous referees, as Macedonia can be considered to be an outlier in this analysis. The unemployment rate of Macedonia is considerably higher (more than twice) than that of the other European countries, with a rate near 30 % in all periods considered, and the divorce rate is half of that in the other countries. In any case, we also repeated the analysis including the FYR of Macedonia, and the results did not change substantially.
Although there may be some concerns about the use of the crude divorce rate, it is worth noting that other papers that contain information about both the crude divorce rate and the total divorce rate did not find differences in their results (see González-Val and Marcén 2012a and Marcén 2015). Those authors showed that both rates behave in the same manner.
The Ireland divorce rate was excluded from that figure because divorce was not allowed in that country until the 1990s. The Family Law Act that regulates divorce was passed in 1996, although the act was not in force until 1997. The rest of the countries introduced divorce many years earlier. All of the analysis presented in this work was repeated without Ireland, and the results did not change.
Robust standard errors clustered by country. All specifications include country fixed effects, year fixed effects, and country-specific linear and quadratic time trends. We repeated all of the analysis with/without all these controls, with/without population weights and with/without clustering the standard errors, and the results did not vary.
In the case of Ireland, data on divorce is only available since 1997 because divorce was not allowed before that date. As mentioned above, our findings do not change when Ireland is excluded from the sample.
It is also arguable that if the number of divorced individuals increases, the demand for housing could also increase when divorcees do not move in with a new partner. In this setting, a rise in the number of divorced individuals could drive changes in unemployment rates through an increase in the number of workers in the building sector. However, changes in the building sector take time because it is not easy to build a new house or building in a few days (projects, licenses are hard to obtain, etc.); thus, an impact of the divorce rate on the contemporaneous unemployment rate would be unlikely. It would be more likely to detect changes in the renting of houses, which normally demands fewer workers than the construction sector. From those arguments, it would be unlikely to observe variations in the contemporaneous unemployment rate caused by changes in the divorce rates, mitigating previous concerns.
We have tested the robustness of all our results to the inclusion of the male unemployment rate and our results are not affected.
We re-ran all of the analysis excluding each country, one at a time, and excluding those countries that exhibit the highest and the lowest unemployment and divorce rates. The results did not change substantially.
No data were available for the whole period in the cases of Croatia, Estonia, Latvia, Lithuania, Slovakia, and Slovenia. For consistency, we repeated the analysis without those countries. The results did not vary.
We recognize that changes in these variables may drive unemployment and divorce rates. Although this issue can be problematic, it is comforting that adding or deleting all of these variables does not affect our conclusions concerning the relationship between divorce and unemployment rates.
Observations are not available for the whole sample. For this reason, we repeated the analysis with only that sample (column (4) of Table 5), and our results are the same.
We have repeated the estimates by including/excluding those countries that introduced reforms related to the separation period during the period considered, and the results are maintained.
We take into account the divorce law reforms that occurred during the period considered to calculate our estimates.
The magnitude of the effect varies a little, especially in the case of joint custody reform, but this result should be interpreted with caution because we are considering all reforms pertaining to joint custody, not only those related to joint physical custody.
This analysis was repeated including more lags. We obtained the same results.
The local polynomial provides a smoother fit for the divorce rate to a polynomial form of the unemployment rate, via locally-weighted least squares. We used the lpolyci command in STATA with the following options: local mean smoothing, a Gaussian kernel function to calculate the locally-weighted polynomial regression, and a bandwidth determined by Silverman’s rule-of-thumb.
Moreover, quantile regressions are invariant to monotonic transformations of the dependent variable, such as logarithms.
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Acknowledgments
The authors acknowledge financial support from the Spanish Ministerio de Economía y Competitividad (ECO2012-34828, ECO2013-45969-P and ECO2013-41310-R projects), the DGA (ADETRE research group), and FEDER. This paper was partly written while the authors were visiting the Department of Economics, ISEG-Universidade de Lisboa, whose support and hospitality are gratefully acknowledged. The visits were funded by Santander Universidades (Becas Iberoamérica Jóvenes Profesores e Investigadores y Alumnos de Doctorado 2015). Earlier versions of this paper were presented at the 55th Congress of the European Regional Science Association (Lisbon, 2015) and at the 55th Annual Meeting of the Western Regional Science Association (Big Island, 2016), with all the comments made by participants being highly appreciated. Finally, suggestions and observations received from two anonymous referees and the editor (Prof. Shoshana Grossbard) have also significantly improved the version originally submitted. All remaining errors are ours.
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González-Val, R., Marcén, M. Divorce and the business cycle: a cross-country analysis. Rev Econ Household 15, 879–904 (2017). https://doi.org/10.1007/s11150-016-9329-x
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DOI: https://doi.org/10.1007/s11150-016-9329-x