Now showing 1 - 10 of 14
  • Publication
    Econometric causality
    (University College Dublin. Geary Institute, 2008-12-15)
    This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper contrasts the Neyman–Rubin model of causality with the econometric approach.
  • Publication
    Identification of treatment effects using control functions in models with continuous, endogenous treatment and heterogeneous effects
    (University College Dublin. Geary Institute, 2008-12-15) ; ; ;
    We use the control function approach to identify the average treatment effect and the effect of treatment on the treated in models with a continuous endogenous regressor whose impact is heterogeneous. We assume a stochastic polynomial restriction on the form of the heterogeneity but, unlike alternative nonparametric control function approaches, our approach does not require large support assumptions.
  • Publication
    Taking the easy way out : how the GED testing program induces students to drop out
    (University College Dublin. Geary Institute, 2008-12-15) ; ;
    We exploit an exogenous increase in General Educational Development (GED) testing requirements to determine whether raising the diffculty of the test causes students to finish high school rather than drop out and GED certify. We find that a six point decrease in GED pass rates induces a 1.3 point decline in overall dropout rates. The effect size is also much larger for older students and minorities. Finally, a natural experiment based on the late introduction of the GED in California reveals, that adopting the program increased the dropout rate by 3 points more relative to other states during the mid-1970s.
  • Publication
    Early childhood intervention : rationale, timing, and efficacy
    (University College Dublin, Geary Institute, 2007-01) ; ; ;
    This paper provides a brief review of the economic rationale for investing in early childhood. It discusses the optimal timing of intervention, with reference to recent work in developmental neuroscience, and asks how early is early? It motivates the need for early intervention by providing an overview of the impact of adverse factors during the antenatal and early childhood period on outcomes later in life. Early childhood interventions, even poorly designed ones, are costly to implement, therefore it is vital that interventions are well-designed if they are to yield high economic and social returns. The paper therefore presents a set of guiding principles for the effectiveness of early intervention. It concludes by presenting a case for a new study of the optimal timing of interventions.
  • Publication
    The economics and psychology of inequality and human development
    (University College Dublin. Geary Institute, 2009-03-09) ;
    Recent research on the economics of human development deepens understanding of the origins of inequality and excellence. It draws on and contributes to personality psychology and the psychology of human development. Inequalities in family environments and investments in children are substantial. They causally affect the development of capabilities. Both cognitive and noncognitive capabilities determine success in life but to varying degrees for different outcomes. An empirically determined technology of capability formation reveals that capabilities are self-productive and cross-fertilizing and can be enhanced by investment. Investments in capabilities are relatively more productive at some stages of a child's life cycle than others. Optimal child investment strategies differ depending on target outcomes of interest and on the nature of adversity in a child's early years. For some configurations of early disadvantage and for some desired outcomes, it is efficient to invest relatively more in the later years of childhood than in the early years.
  • Publication
    Schools, skills, and synapses
    (University College Dublin. Geary Institute, 2008-12-15)
    This paper discusses (a) the role of cognitive and noncognitive ability in shaping adult outcomes, (b) the early emergence of differentials in abilities between children of advantaged families and children of disadvantaged families, (c) the role of families in creating these abilities, (d) adverse trends in American families, and (e) the effectiveness of early interventions in offsetting these trends. Practical issues in the design and implementation of early childhood programs are discussed.
  • Publication
    The identification & economic content of ordered choice models with stochastic thresholds
    (University College Dublin. Geary Institute, 2007-07-16) ; ;
    This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with different stopping times. We establish conditions for nonparametric identification. We interpret the ordered choice model as a special case of a general discrete choice model and as a special case of a dynamic discrete choice model.
  • Publication
    Measuring Investment in Human Capital Formation: An Experimental Analysis of Early Life Outcomes
    (University College Dublin. School of Economics, 2013-08) ; ; ; ;
    The literature on skill formation and human capital development clearly demonstrates that early investment in children is an equitable and efficient policy with large returns in adulthood. Yet little is known about the mechanisms involved in producing these long-term effects. This paper presents early evidence on the nature of skill formation based on an experimentally designed, five-year home visiting program in Ireland targeting disadvantaged families - Preparing for Life (PFL). We examine the impact of investment between utero to 18 months of age on a range of parental and child outcomes. Using the methodology of Heckman et al. (2010a), permutation testing methods and a stepdown procedure are applied to account for the small sample size and the increased likelihood of false discoveries when examining multiple outcomes. The results show that the program impact is concentrated on parental behaviors and the home environment, with little impact on child development at this early stage. This indicates that home visiting programs can be effective at offsetting deficits in parenting skills within a relatively short timeframe, yet continued investment may be required to observe direct effects on child development. While correcting for attrition bias leads to some changes in the precision of estimates, overall the results are quite similar.
  • Publication
    The viability of the welfare state
    (University College Dublin. Geary Institute, 2009-03-09)
  • Publication
    Instrumental variables in models with multiple outcomes : the general unordered case
    (University College Dublin. Geary Institute, 2008-12-15) ; ;
    This paper develops the method of local instrumental variables for models with multiple, unordered treatments when treatment choice is determined by a nonparametric version of the multinomial choice model. Responses to interventions are permitted to be heterogeneous in a general way and agents are allowed to select a treatment (e.g. participate in a program) with at least partial knowledge of the idiosyncratic response to the treatments. We define treatment effects in a general model with multiple treatments as differences in counterfactual outcomes that would have been observed if the agent faced different choice sets. We show how versions of local instrumental variables can identify the corresponding treatment parameters. Direct application of local instrumental variables identifies the marginal treatment effect of one option versus the next best alternative without requiring knowledge of any structural parameters from the choice equation or any large support assumptions. Using local instrumental variables to identify other treatment parameters requires either large support assumptions or knowledge of the latent index function of the multinomial choice model.