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144
The Evidence on Credit Constraints in PostSecondary Schooling
 Economic Journal
"... This paper examines the family income–college enrolment relationship and the evidence on credit constraints in postsecondary schooling. We distinguish short run liquidity constraints from the long term factors that promote cognitive and noncognitive ability. Long run factors crystallised in ability ..."
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Cited by 188 (25 self)
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This paper examines the family income–college enrolment relationship and the evidence on credit constraints in postsecondary schooling. We distinguish short run liquidity constraints from the long term factors that promote cognitive and noncognitive ability. Long run factors crystallised in ability are the major determinants of the family income schooling relationship, although there is some evidence that up to 8 % of the total US population is credit constrained in a short run sense. Evidence that IV estimates of the returns to schooling exceed OLS estimates is sometimes claimed to support the existence of substantial credit constraints. This argument is critically examined. This paper interprets the evidence on the relationship between family income and college attendance. Fig. 1 displays aggregate time series college participation rates for 18–24 year old American males classified by their parental income. Parental income is measured in the child’s late adolescent years. There are substantial differences in college participation rates across family income classes in each year. This pattern is found in many other countries; see the essays in Blossfeld and Shavit (1993). In the late 1970s or early 1980s, college participation rates start to
Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond
 IZA DISCUSSION PAPER NO.1700
, 2005
"... ..."
Dynamic Discrete Choice and Dynamic Treatment Effects
, 2005
"... This paper considers semiparametric identification of structural dynamic discrete choice models and models for dynamic treatment effects. Time to treatment and counterfactual outcomes associated with treatment times are jointly analyzed. We examine the implicit assumptions of the dynamic treatment m ..."
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Cited by 135 (30 self)
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This paper considers semiparametric identification of structural dynamic discrete choice models and models for dynamic treatment effects. Time to treatment and counterfactual outcomes associated with treatment times are jointly analyzed. We examine the implicit assumptions of the dynamic treatment model using the structural model as a benchmark. For the structural model we show the gains from using cross equation restrictions connecting choices to associated measurements and outcomes. In the dynamic discrete choice model, we identify both subjective and objective outcomes, distinguishing ex post and ex ante outcomes. We show how to identify agent information sets.
Separating uncertainty from heterogeneity in life cycle earnings, the 2004 Hicks Lecture. Oxford Economic Papers 57
"... This paper develops and applies a method for decomposing cross section variability of earnings into components that are forecastable at the time students decide to go to college (heterogeneity) and components that are unforecastable. About 60 % of variability in returns to schooling is forecastable. ..."
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Cited by 96 (22 self)
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This paper develops and applies a method for decomposing cross section variability of earnings into components that are forecastable at the time students decide to go to college (heterogeneity) and components that are unforecastable. About 60 % of variability in returns to schooling is forecastable. This has important implications for using measured variability to price risk and predict college attendance.
2006): “Child Care Choices and Childrens Cognitive Achievement: The Case of Single Mothers
"... We evaluate the effect of childcare vs. maternal time inputs on child cognitive development using the single mothers from the National Longitudinal Survey of Youth (NLSY79). To deal with nonrandom selection of children into childcare, we exploit the (plausibly) exogenous variation in welfare policy ..."
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Cited by 72 (4 self)
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We evaluate the effect of childcare vs. maternal time inputs on child cognitive development using the single mothers from the National Longitudinal Survey of Youth (NLSY79). To deal with nonrandom selection of children into childcare, we exploit the (plausibly) exogenous variation in welfare policy rules facing single mothers. In particular, the 1996 Welfare Reform, and earlier State level policy changes, generated substantial increases in their work/childcare use. Thus, we construct a comprehensive set of welfare policy variables, and use them (along with local demand conditions) as instruments to estimate child cognitive ability production functions. Because welfare rules are complex, we need many variables to characterize them. Thus, we face a “many instrument problem ” (i.e., 2SLS severely biased toward OLS). We deal with this problem both by using LIML, and by using factor analysis to condense the instrument set. Results from the two approaches are very similar, and quite different from OLS. Using LIML along with factor analysis of the instruments leads to an efficiency gain (i.e., smaller standard errors) relative to using LIML alone.
Instrumental variable treatment of nonclassical measurement error models.
 Econometrica,
, 2008
"... Abstract While the literature on nonclassical measurement error traditionally relies on the availability of an auxiliary dataset containing correctly measured observations, we establish that the availability of instruments enables the identification of a large class of nonclassical nonlinear errors ..."
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Cited by 64 (18 self)
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Abstract While the literature on nonclassical measurement error traditionally relies on the availability of an auxiliary dataset containing correctly measured observations, we establish that the availability of instruments enables the identification of a large class of nonclassical nonlinear errorsinvariables models with continuously distributed variables. Our main identifying assumption is that, conditional on the value of the true regressors, some "measure of location" of the distribution of the measurement error (e.g. its mean, mode or median) is equal to zero. The proposed approach relies on the eigenvalueeigenfunction decomposition of an integral operator associated with specific joint probability densities. The main identifying assumption is used to "index" the eigenfunctions so that the decomposition is unique. We propose a convenient sievebased estimator, derive its asymptotic properties and investigate its finitesample behavior through Monte Carlo simulations.
Causal inference in statistics: An Overview
, 2009
"... This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all ca ..."
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Cited by 61 (12 self)
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This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interventions, (also called “causal effects ” or “policy evaluation”) (2) queries about probabilities of counterfactuals, (including assessment of “regret, ” “attribution” or “causes of effects”) and (3) queries about direct and indirect effects (also known as “mediation”). Finally, the paper defines the formal and conceptual relationships between the structural and potentialoutcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both.
Selection Bias, Demographic Effects, and Ability Effects in Common Value Auction Experiments
 American Economic Review
, 2007
"... We find clear demographic and ability effects on bidding in common value auction experiments as inexperienced subjects with higher (lower) SAT/ACT scores are less (more) likely to bankrupt than those with middle level scores, inexperienced women suffer far more from the winner’s curse than do men, a ..."
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Cited by 45 (10 self)
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We find clear demographic and ability effects on bidding in common value auction experiments as inexperienced subjects with higher (lower) SAT/ACT scores are less (more) likely to bankrupt than those with middle level scores, inexperienced women suffer far more from the winner’s curse than do men, and economics and business majors substantially overbid relative to other majors. There are strong selection effects in bid estimates for both inexperienced and experienced subjects which, although they are not identified using standard econometric techniques, are identified through our experimental treatment effects. Ignoring these selection effects is most misleading for inexperienced bidders, as the biased estimates indicate much slower learning and adjustment to the winner’s curse for individual bidders than do the unbiased estimates. JEL classification: C9, D44, C24, J16. Key words: common value auction experiments, selection effects, econometric methods, gender and ability effects.