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TRUE STATE DEPENDENCE IN MONTHLY WELFARE PARTICIPATION:A NONEXPERIMENTAL ANALYSIS
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Abstract
This paper provides an empirical evaluation of true state dependence in welfare participation
using unique administrative data from California that is measured at the monthly frequency,
which coincides with the welfare eligibility period and so is free of time aggregation bias. The
analysis uses first- and second-order dynamic conditional logit models that non-parametrically
control for permanent unobserved heterogeneity to test for state dependence in welfare behavior.
The second-order model also absorbs individual-specific first-order Markov chains, and provides
a more robust test for state dependence in high frequency data. The results using the first-order
model show substantial first-order state dependence in monthly welfare participation. Absorbing
heterogeneous first-order effects, the hypothesis of no second-order state dependence is also
easily rejected. This suggests that past welfare participation predicts future participation, given
unrestricted effects of both the present state and unobserved heterogeneity, and provides
substantive evidence of duration dependence at the individual level.Binary response panel data, state dependence, unobserved heterogeneity, initialconditions, conditional logit models