Two Essays on Premarital Cohabitation and Divorce

Publication Year:
2013
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Repository URL:
http://hdl.handle.net/1969.1/151959
Author(s):
Liu, Chia-Hua
Tags:
Premarital cohabitation; Marital Instability; Nested logit model
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thesis / dissertation description
This dissertation studies the effect of premarital cohabitation on women?s propensity to divorce and women?s divorce risk. The dissertation focuses on various selection issues in a woman?s decision to start a relationship and the form of the relationship, and to dissolve or continue the relationship. The 1995, 2002, and 2006-2010 waves of the National Survey of Family and Growth (NSFG) are used. The sample sizes are 10,847, 7,643, and 12,279 women aged 15 to 44 living in households in the United States in 1995, 2002, and 2006-2010, respectively. The dissertation finds that premarital cohabitation has no effect on women?s propensity to divorce and women?s divorce risk. Sorting into marriage according to level of religiosity generates the variations among the same levels of religiosity between cohabiting and non-cohabiting couples. The variations can explain the positive correlation between premarital cohabitation and divorce. In absence of the information on both the wife?s and the husband?s level of religiosity, this dissertation suggests and estimates a selection model. Three different empirical approaches all suggest that living together before marriage does not lead to divorce. Findings of positive correlation between premarital cohabitation and divorce in the previous literature could be attributed to omitted variable bias or sample selection bias Overall the rising in cohabitation cannot explain the rise and the fallen in divorce rates. However, the prevalence of cohabitation will induce a thick ?cohabitation? market, and hence improve the quality of cohabiting matches through lowering search costs and increasing the turnover rates of cohabitation. As a result, the correlation between premarital cohabitation and divorce is expected to negative and significant on the basis of newly released survey data such as the 2011-2015 wave of the NSFG.