Transcription of Lecture 3 Discrete Choice Models
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Lecture 3 Discrete Choice Models
RS Lecture 171 Lecture 3 Discrete Choice ModelsLimited Dependent VariablesDiscrete Dependent Variable Continuous dependent variableTruncated/Censored Regr. ModelsDiscrete Choice Models (DCM)Duration (Hazard)ModelsTruncated,Censored To date we have implicitly assumed that the variable yiis a continuous random variable. But, the CLM does not require this assumption! The dependent variable can have discontinuities. For example, it can be Discrete or follow counts. In these cases, linearity of the conditional expectations is unusual. Different types of discontinuities generate different Models :RS Lecture 17 From Frances and Paap (2001)With limited dependent variables, the conditional mean is rarelylinear. We need to use adjusted Models . Limited Dependent VariablesLimdep: Discrete Choice Models (DCM) We usually study Discrete data that represent a decision, a Choice . Sometimes, there is a single Choice .
-store expenditures, labor force participation, income below poverty line. •Censored variables: Values in a certain range are all transformed to/grouped into (or reported as) a single value.-hours worked, exchange rates under Central Bank intervention. Note: Censoring is essentially a defect in the sample data. Presumably,
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