1. The impact of job loss on family dissolution Silvia Mendolia, Denise Doiron School of Economics, University of New South Wales Introduction Objectives  To examine the impact of job loss on the probability of divorce.  To further our understanding of possible transmission channels:  Financial stress from the negative income shock both on immediate and future expected income.  Psychological shocks.  Additional information on individual traits and downward revision of expectations on future value of match. (This effect does not apply in the case of exogenous job losses). Policy implications Policies aimed at reducing the earnings’ shock from job losses may alleviate the first 2 impacts but they will be less effective if the latter effect is the main one. Data and Method Data  Family history data from the BHPS, a combination of retrospective histories and panel information.  Sample: Couples in which men are aged between 16-65 (7,500 couples). Analysis Results  Job losses affect family dissolution through more than one channel: a negative income shock imposes stress on the relationship (redundancies) and new information is revealed regarding the value of the match (dismissals). Note: Standard error in parentheses. Sample size: 40,662 observations. + significant at 10%; * significant at 5%; ** significant at 1%. The baseline hazard linearly depends on years of marriage in this specification of the model. Similar results are found with other specifications. Coefficients are transformed to relative risk format. Standard errors are similarly transformed.  The longer the partners have been together, the smaller the divorce probability: the hazard rate decreases over time.  Household non labour income decreases the probability of family dissolution.  The probability of divorce increases with the number of dependent children in the household.  Differences in age between partners (>8 years) increase the probability of divorce. Separate estimation is conducted on the stock and flow samples (partnerships that begin before/after the start of the survey):  Older couples are more likely to divorce after a redundancy. They are more affected by the income shock.  Younger couples are more likely to divorce after a dismissal as the signalling effect is more important. Conclusion and extensions  Job loss may affect marital stability through multiple channels.  Further results include the analysis of:  Long term unemployment and repeated job loss  Income groups  Interactions between job loss and age of children Estimation method Discrete time proportional hazards models h ij = 1-exp{-exp{X ij ’β + λ j }} i=1,…..N, j=1,….T i  h is the hazard rate: the probability of divorce at duration j conditional on the marriage having survived until j-1.  X includes job losses, education levels, income, number of children and other exogenous characteristics.  λ j is the baseline hazard which may depend on the duration j. Various specifications of λ j are estimated.  Specifications of h containing unobserved time- invariant individual-specific effects (modeled as Gamma distributed) are also estimated. Flow and stock samples of marriages are treated separately to check for selection effects. Literature  Most of the previous literature focuses on the costs of job loss in terms of future employment probabilities and lost earnings.  In these papers, family composition is ignored or treated as exogenous.  A few studies have looked at the impact of job loss on divorce. (Kraft, 2001, Charles and Stephens, 2004 and Eliason, 2004). To date results on the presence of such effects are inconsistent. Economic models of divorce  Mostly derived from the pioneering work of Becker (1973, 1974).  The family is an expected utility maximizing unit.  Two general causes for separation:  Meeting of a new partner with expected joint utility greater than the current match.  “Surprises” may change initial expectations about the partner’s characteristics or alter the value of the partnership. Variables  Involuntary job losses are separated by type:  Redundancies are used as measures of exogenous job loss and capture psychological and negative earning shocks.  Dismissals are likely to be endogenous due to common omitted variables. The impact of dismissals will capture effects from the negative earnings shocks and possibly a signaling impact.  Temporary job endings may have some signaling effect due to the marginal labour market attachment usually associated with these jobs and to the fact that the employment contract was not renewed.  To minimize the likelihood of measurement error we also separate redundancies by industry and consider only those in declining employment as exogenous. Exp. Coeff. Dismissal3.09 (1.11)** Redundancy1.48 (0.35) + Temporary job ended2.09 (0.60)** Household income0.82 (0.09) + Number of children1.14 (0.05)** Difference in education level0.98 (0.11) Difference in age > 8 years1.33 (0.20) +