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Author and presenter Barban, Nicola; Dondena Centre, Università Bocconi; Centre for Population Studies, Ageing and Living Conditions programme, Umea <strong>University</strong> Title Sequence analysis and causality. The effect of age at retirement on health using Swedish register data Abstract Life expectancy is increasing steadily in developed countries. Governments are seeking to increase the proportion of elderly people in paid employment to balance the ratio of employed people over dependent ones. This led to a considerable debate about the timing of retirement and its influence on health: is early retirement good or bad for your health? Several studies have shown that retirement at younger age has adverse effects on health (e.g., Westerlund and al. 2010, Hult and al., 2010). However, selection into retirement may obscure the effect of retirement on health. The individual decision to retire can be influenced by previous health trajectory, marital status and widowhood, social relations with relatives and work career. Moreover, the transition to retirement has become blurred, and the actual range of retirement age has expanded, making the transition “longer and fuzzier” (Kohli and Rein 1991; Han and Moen,1999). As a result, retirement is becoming more “destandardized” and “deinstitutionalized” (Guillemard and Rein 1993, Guillemard and van Gunsteren 1991) with people anticipating retirement entering periods of inactivity or reducing their labor supply. Starting from this theoretical framework, we develop a new matching approach to investigate the causal effect of age at retirement on later health outcomes. Standard matching estimators (Rosembaum and Rubin 1985) based on propensity score pair each treatment participant with a single (or multiple) non-treated participant based on a set of observed characteristics. However, we claim that selection into treatment can be affected by the trajectories of a set of observed characteristics before treatment. For this reason, using sequence analysis with Optimal Matching (OM) (Abbott, 1995), we develop a matching procedure based on the trajectory before treatment. Our method use an extension of nearest neighborhood matching estimator using OM distances. In this way we matched individuals with the most similar trajectory
efore retirement. We identify four different sources of selection into retirement: health trajectory, partnership trajectory, work career and family support history. We combine the four trajectories with a standard propensity score and develop a complex measure of dissimilarity among individuals. We use Swedish register data and we restrict the analysis to the cohort of people born in Sweden during 1935. Our measure of outcome is the average days of hospitalization from retirement to age 71. We conduct separate analysis for different ages at retirement focusing on retirement between age 60 and 65. Our preliminary results confirm that early retirement is associated with poorer health outcomes. Once we control for selection issues the negative effect of retirement is negligible except for men and women who retire at age 60.
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The ASA Spring Methodology Conferen
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Friendships under study were formed
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the interplay of social background
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greatly inefficient. Only very few
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Data We use matched employer-employ
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Page 43 and 44: Presenter Engel, Uwe; Dept. of Soci
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Page 83 and 84: Presenter Morren, Meike; Tilburg Sc
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Page 87 and 88: Presenter Kankaraš, Miloš; Dept.
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