Objectives

• Consolidate the use of statistical methods to interpret a dataset.
• Understand the underlying hypothesis of the linear regression model for cross sectional data.
• Formulate and specify econometric models to interpret economic phenomena.
• Study the properties of the ordinary least squares in small and large samples.
• Study statistical inference in the classic case and in the presence of heteroskedasticity.
• Gain familiarity in empirical applications and conceive simple econometric studies with cross sectional data using R software

Syllabus

• Introduction and the Nature of Econometrics
• The Simple Linear Regression Model
• The Multiple Linear Regression Model
• Heteroskedasticity
• Further Issues
• Multiple Regression Analysis with Qualitative Information

Bibliography

• Wooldridge, J. M., Introductory econometrics: A modern approach, 6th Edition. South-Western, Cengage Learning, 2016;
• Heiss, F., Using R for Introductory Econometrics, 1st Edition; CreateSpace (Independent publishing platform), 2016.
• Greene, W. H., Econometric analysis, 7th edition, Pearson , 2012;
• Stock, J. H and Watson, M. W, Introduction to Econometrics, 3rd. Edition, Pearson, Addison Wesley, 2011;
• Adler, J., R in a nutshell: A desktop quick reference, 1st Edition, O’Reilly Media, 2010;
• Teetor, P., R cookbook: Proven recipes for data analysis, statistics, and graphics, O’Reilly Media, 2011.