Explaining and Forecasting Results of the Self-sufficiency Project

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Abstract:This paper models the Self-Sufficiency Project (SSP), a controlled randomized experiment concerning welfare. The model of household behavior includes stochastic labor market skill, job opportunities, and value of non-labor market time. All the variation within and between treatment groups, jurisdictions (provinces), demographic groups, and sub-experiments is derived from four underlying sources: policy variation, endogenous selection into the experimental samples, the SSP treatments themselves, and different mixtures over 4 underlying types. Using the variation within the treatment group is quantitatively important for identifying the complex model: Efficient GMM the parameters are estimated precisely and variation within the treatment group is much more important for identification than either variation within the control group or between treatment and control groups. The model tracks the primary moments well within sample and out-ofsample except for under-estimating the difference in the entry sample. Predictions of the estimated model are computed for different welfare reform experiments. The details of the design are critical for interpretation of the results and it appears that the small SSP+ treatment may have longer lasting impacts than the an in-sample impact analysis would suggest.JEL Classification: I3, C9, J0, C5

Welfare Dependence and Self-Control: An Empirical Analysis

“…The point estimate of the discount factor is smaller at 0.426, but the standard error is much larger at 0.439. This is consistent with Ferrall (2012), who finds that the standard error of the discount factor becomes very large if only the data moments within the control group are used. 67 However, unlike Ferrall (2012), the standard errors of other coefficients in the model do not increase substantially.…”

“…If the model is time-consistent, as in Magnac and Thesmar (2002), 20 In the labor literature, few studies have used exogenous policy variations to form exclusion restrictions that identify the discount factor. In Ferrall (2012), treatment group members in the Self-Sufficiency Project (SSP) will be eligible for a wage subsidy if they can find a full-time job and go off income assistance within one year following random assignment. Differences in behavior between the control and treatment groups within that period allow the discount factor to be recovered.…”

“…The above approach shares some similarities with Lise et al (2005) and Todd and Wolpin (2006), in which the treatment group is used as a validation sample for a structural model that is estimated on the control group sample. It is also related to Attanasio et al (2011) andFerrall (2012), who assess the importance of control-treatment policy variations to the predictive performance of structural models. Keane and Wolpin (2007) use Texas as a holdout sample to validate the structural model in Keane and Wolpin (2010).…”

“…This study adds to the growing literature of the estimation and validation of dynamic structural models using data from policy experiments (e.g., Lise et al (2005), Todd and Wolpin (2006), Attanasio et al (2011), Ferrall (2012). It contributes to the literature of dynamic structural models of welfare reform in the United States and Europe (e.g., Swann (2005), Keane and Wolpin (2010), Chan (2013), Blundell et al (2013)).…”

Life-cycle and intergenerational effects of child care reforms

“…We discuss the properties of our approach relative to the full structural approach, which jointly estimates the production function with a behavioral model. Closely related to our paper is a recent important paper by Bernal (2008), who estimates a dynamic model of maternal employment and child care decisions using data 5 In recent years, progress has been made in synergizing the methodological approaches undertaken by reduced-form and structural studies (e.g., Todd and Wolpin (2006), Attanasio, Meghir, and Santiago (2011), Ferrall (2012) on policy experiments; Kaboski and Townsend (2011), Chan (2013) and Blundell, Dias, Meghir, and Shaw (2016) on large-scale reforms). from the National Longitudinal Survey of Youth (NLSY79).…”