It aims to provide the basic theoretical and operational concepts to the student about Linear Econometric Models of cross-section data.The course will cover estimation and inference principles, the mathematical (algebraic properties) of the Ordinary Least Square methods, simple and multiple linear regression models, tests for functional form and omitted variables, in addition to heteroskedasticity and weighted least squares.It will also emphasize the nature of residuals and analyze many of the inspection and tests of goodness-of-fit and influential measures by means of residuals.
Wooldridge Econometrics Data Software And DataThe empirical part of the course will be based on the R software and data from Wooldridge (2016).I expect that students read the suggested literature specific to linear econometrics, including the basic texts on mathematical econometrics, probability, and statistical inference, as well participate in the data laboratory classes. At the end of the course I expect students to be able to manipulate cross-section data in R and apply the methods to specific areas of interest in Demography, Geography, Sociology, Economics, and Health Studies. Class 4 Solution to Computer Exercises (Chapter 2 Wooldridge). Class 4 Frisch-Waugh-Lovell and Orthogonal Partitioned Regression Theorems (Simulation). ![]() ![]() Class 6 Solution to Computer Exercises (Chapter 4 Wooldridge). Class 7 Solution to Computer Exercises (Chapter 6 Wooldridge). Class 8 Solution to Computer Exercises (Chapter 7 Wooldridge). Chapter 7 Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables. Trivedi Regression Analysis of Count Data, Cambridge University Press, 1998.
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