Econometrics 1

Leerdoelen

At the end of this course, students will be able to:

• Specify the linear regression model (in matrix notation) with standard assumptions;
• derive the LS estimators, their properties and the related t and F-tests;
• analyse the quality of the LS estimators and the related t and F-tests in relation to the model specification and assumptions and possible errors in them;
• give the model specification in case of nonlinear, interaction or categorical effects (including parameter instability) and apply tests for such effects;
• adjust the LS method in case of invalid model assumptions (heteroscedasticity, autocorrelation and endogeneity) and apply specifications tests for such cases;
• correctly apply and interpret diagnostic tests for checking underlying assumptions in the model;
• apply econometric techniques to economic data using specialized computer software.

Inhoud

In this course the multiple regression model is developed with applications, in particular, to cross sectional data. The treatment makes extensive use of matrix algebra and multivariate statistical theory. Discussed are: the classic linear regression model, standard assumptions, properties of the LS estimators, fit, consequences of omitted or redundant variables, partial regression, multicollinearity, linear restrictions, prediction, asymptotic properties and variable transformations, dummy variables, test for parameter stability, test for normality, heteroscedasticity, serial correlation, endogeneity of explanatory variables and instrumental variables. Applications and simulations are carried out with the software packages EViews and Matlab.

Aanbevolen voorkennis

This course has no formal entry requirements, except valid enrollment. Yet, it is indispensable to have sufficient knowledge of statistics and linear algebra. The reason not to demand specific courses as formal entry requirements is to avoid exclusion of students who just did not pass one of the relevant preparatory courses. This course builds on a series of courses and makes use of the knowledge gained there. It is recommended that students have ready knowledge of:

Probability Theory and Statistics 1,

Probability Theory and Statistics 2

Probability Theory and Statistics 3

Mathematics 2: Linear Algebra

Mathematics 3: Linear Algebra and Unconstrained Optimization

Mathematics 4:Multivariable Analysis and Constrained Optimization

Introduction Econometrics

For minor students requirements set by the program director must be met.

Verplichte voorkennisWerkvorm

In weeks 1 to 6 there are weekly two two-hour lectures, one two-hour tutorial and one mandatory two-hour computer lab. The computer labs include weekly mandatory computer/theory tests. The computer tests are one-time only and cannot be retaken.

The exact dates of the sessions can be seen in UvA Timetable.