The fundamentals of estimation and inference in the classical regression model, with applied laboratory sessions using actual economic data. Topics covered typically include: multiple linear and non-linear regression models; least squares; maximum likelihood; instrumental variables; statistical properties of estimators; asymptotic theory; restrictions; measurement error; serial correlation; heteroskedasticity; systems of equations. Weekly hours: 3 Lecture hours and 1 Practicum/Lab hoursNote: Students with credit for BPBE 860 will not receive credit for this course.
The fundamentals of estimation and inference in the classical regression model, with applied laboratory sessions using actual economic data. Topics covered typically include: multiple linear and non-linear regression models; least squares; maximum likelihood; instrumental variables; statistical properties of estimators; asymptotic theory; restrictions; measurement error; serial correlation; heteroskedasticity; systems of equations. Weekly hours: 3 Lecture hours and 1 Practicum/Lab hoursNote: Students with credit for BPBE 860 will not receive credit for this course.
