NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

NBER Publications by Salvador Navarro

Contact and additional information for this authorAll papers and publicationsWorking Papers onlyWorking Papers with publication info

Working Papers and Chapters

July 2007The Identification and Economic Content of Ordered Choice Models with Stochastic Thresholds
with Flavio Cunha, James J. Heckman: t0340
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.
October 2005Dynamic Discrete Choice and Dynamic Treatment Effects
with James J. Heckman: t0316
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.
January 2005Separating Uncertainty from Heterogeneity in Life Cycle Earnings
with Flavio Cunha, James J. Heckman: w11024
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.

Contact and additional information for this authorAll papers and publicationsWorking Papers onlyWorking Papers with publication info

 
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