Abstract
Was the steep rise in U.S. Divorce rates from the late 1960's through the early 1980's due to the state-by-state, sweeping changes in laws governing divorce? And if so, what accounts for the decline and leveling off of divorce rates since then? Peters [1986] and Friedberg [1998] provided early conflicting answers. Both Wolfers [2006] and Gold [2008] proposed reconciliations. This study embeds the implications of dynamic optimization models of marriage and divorce (e.g., Rasul [2006]) into a model for state panel data, thereby bridging the gap between structural and difference in difference methods. In particualar we allow current divorce rates to be a¤ected not only by current divorce laws, but also by past divorce laws as embodied in the divorce proclivities of cohorts married under earlier legal regimes. By constructing a wait-time index of the cost of divorce, we collapse the three dimensions of divorce laws (whether or not no-fault grounds are available, whether or not the law is unilateral, and the length of minimum wait times, if available) into just two, the cost of divorce and whether or not laws are unilateral. The model exploits the relative sizes of marriage cohorts to capture the indirect effects of divorce law on sorting into marriage. We proxy these relative sizes with a simple characterization of the age distribution relative to age at marriage. Preliminary results indicate that the structure necessary for the wait time index to work can be seen in the data. They also show that the addition of marriage cohort effects into a state panel data model has the potential to dramatically affect estimated expected divorce rates under various legal regimes. All previous models for state panel data can be cast as special cases of ours and differences across studies could be due to omitted variable bias. Finally, our marriage-cohort model for state panel data also provides a straightforward parametric test of the Coase theorem.
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