|This Ph.D.-level course covers a number of nonlinear modeling environments and techniques that are used in econometric analysis. The class builds heavily on material developed in 41902, and it is strongly recommended that students have taken 41902 or equivalent before enrolling in this course. Some topics that will be covered are (i) estimating and forecasting using basic time series models (ARMA, VAR, and GARCH), (ii) discrete choice models (probit, logit, multinomial choice); (iii) limited dependent variable modles (censored regression, truncated regression, selection models); (iv) basic nonparametric estimation.|
|Journal articles and book chapters will be used in this course. A few references that may be useful are Greene Econometric Analysis, Hayashi Econometrics, Wooldridge Econometric Analysis of Cross Section and Panel Data, and Angrist and Pischke Mostly Harmless Econometrics.|
|Based on a project, midterm, final, and problem sets.|
|Business 41901 and 41902.
Description and/or course criteria last updated: 06/12
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