- The objective of this course is to provide students with the basic knowledge of econometrics. Studies will learn the linear regression model theory and its applications in economics or management or finance.
- to know how the research questions can be solved using econometrics
- to learn how to calculate linear regression coefficients
- to know how to interpret coefficients of the linear regression model
- to know Gauss-Markov Theorem
- to be able to detect heteroscedasticity problem
- to learn how to calculate multivariable regression coefficients
- be able to detect the multicollinearity problem
- to be aware of the consequences of the omitted variable bias
- be able to interpret interaction effects and squared terms
- be able to export STATA outputs to MS Word
- to know what we have to write in econometric research
- IntroductionStudents learn what econometrics is. In addition, we discuss typical research questions are used in econometric studies. Finally, we consider basic problems with data management.
- The Linear Regression Model: an OverviewThis topic is about the OLS estimator. We study why we use OLS estimator. Moreover, we consider the population and sample regression. In addition, we learn how to calculate linear regression coefficients and interpret the results.
- The Gauss-Markov Theorem.This topic is about assumptions of the linear regression model. We discuss why these assumptions are important for the model. In addition, we consider what if the homoscedasticity assumption cannot be held in our study.
- Multiple Regression AnalysisThis topic considers the problem of the omitted variable. The possible solution to this problem is to use the variable (or proxy) that has been omitted in the model before. Thus, we turn to the multivariate regression model. We discuss how to calculate coefficients of the multivariable model and learn one of the most common problems of these models: multicollinearity.
- Multiple Regression Analysis: testsIn this topic we discuss how to verify if the multivariable model shows reliable results. We consider several basic tests that we use in the multivariable regression model.
- Relaxing the Assumptions of the Classical ModelIn this topic we discuss a real empirical reseach to show how the linear regression models works in practice. We discuss the problem of endogeneity and some other typical problems. In addition, what we have to write in an empirical research report.
- Stock, J. H., & Watson, M. W. (2015). Introduction to Econometrics, Update, Global Edition (Vol. Updated third edition). Boston: Pearson Education. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1419285
- An introduction to modern econometrics using Stata, Baum, C., 2006
- Brooks,Chris. (2019). Introductory Econometrics for Finance. Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.cup.cbooks.9781108422536
- Using Stata for principles of econometrics, Adkins, L.C., 2011