The purpose and applications of Econometrics; kinds of problems addressed by econometrics; the link between economic theory, mathematics, and statistics; review of regression model essentials (assumptions, parameter estimates, goodness-of-fit); univariate and multivariate ordinary least squares; addressing problems due to heteroskedasticity, autocorrelation, multicollinearity, specification errors; dummy independent and dummy dependent variables; binary and multinomial probit and logit models; models of count data (poisson and negative binomial models); limited dependent variable models (tobit model); sample selection bias, selectivity problem, Heckit (Heckman model), self selection, double huddle model, matching estimators (propensity score matching); endogenous and exogenous variables; reduced form equations; identification problem; estimation of simultaneous equations (maximum likelihood and two-stage least squares); recursive models; seemingly unrelated regressions equations. objectives :
By the end of the course students should:-