THE COURSE "ECONOMETRICS" INTRODUCES THE BASIC CONCEPTS AND TOOLS OF QUANTITATIVE ANALYSIS RELATED TO ECONOMIC PHENOMENA. ECONOMETRICS STUDIES ECONOMIC DATA TO BOTH CHECK THEORETICAL HYPOTHESIS, ANALYSING CAUSAL RELATIONS BETWEEN VARIABLES, AND PROVIDE FORECASTS. THE MAIN OBJECTIVE IS TO PROVIDE STUDENTS WITH THE BASIC KNOWLEDGE TO, STARTING WITH A GIVEN RESEARCH QUESTION, PROPERLY ANALYSE THE DATA AND INTERPRET THE RESULTS. PRACTICAL APPLICATIONS ARE, THEN, FUNDAMENTAL.
THE COURSE FOCUSES ON: REVIEW OF BASIC STATISTICS, SIMPLE AND MULTIPLE LINEAR REGRESSION ANALYSES, BINARY AND MULTINOMIAL DEPENDENT VARIABLE MODELS. THE APPLICATION OF ECONOMETRIC TECHNIQUES IS BASED ON THE SOFTWARE R.
THE COURSE FOCUSES ON: REVIEW OF BASIC STATISTICS, SIMPLE AND MULTIPLE LINEAR REGRESSION ANALYSES, BINARY AND MULTINOMIAL DEPENDENT VARIABLE MODELS. THE APPLICATION OF ECONOMETRIC TECHNIQUES IS BASED ON THE SOFTWARE R.
Curriculum
teacher profile teaching materials
- A review of Statistics and Probability theory
- Linear Regression with One Regressor
- Regression Models with Multiple Regressors
- Regression with a Binary Dependent Variable
- Regression with a Multinomial Dependent Variable
The course guides students in implementing empirical applications with the R software
Christoph Hanck, Martin Arnold, Alexander Gerber & Martin Schmelzer, 2018, Introduction to Econometrics with R, https://econometrics-with-r.org/
Articles/book chapters provided during the course
Programme
The course focuses on the following issues:- A review of Statistics and Probability theory
- Linear Regression with One Regressor
- Regression Models with Multiple Regressors
- Regression with a Binary Dependent Variable
- Regression with a Multinomial Dependent Variable
The course guides students in implementing empirical applications with the R software
Core Documentation
James H. Stock, Mark W.Watson, 2016. Introduzione all'econometria, Pearson.Christoph Hanck, Martin Arnold, Alexander Gerber & Martin Schmelzer, 2018, Introduction to Econometrics with R, https://econometrics-with-r.org/
Articles/book chapters provided during the course
Reference Bibliography
Hideo Aizaki, Tomoaki Nakatani, Kazuo Sato, 2014, Stated Preference Methods Using R, CRC Press. A.H. Studenmund, Using econometrics: a practical guide, 2011, Pearson.Type of delivery of the course
The course includes on-line lectures and exercises to be carried out live.Attendance
Attendance is not mandatory but strongly recommended.Type of evaluation
During the COVID-19 emergency period, the final exam will be carried out in accordance with the provisions of art.1 of the Rectoral Decree no. 703 of 5 May 2020. In particular: For attending students: the final mark depends on the outcome of the oral exam (50%) and on the practical activities (exercises, data analysis, interpretation of the results, participation) carried out during the course. The oral exam consists of around 3 questions aimed at verifying the knowledge of the contents discussed during the course and the synthesis ability. For non-attending students: the final mark depends on the outcome of the oral exam. The oral exam consists of around 3 questions aimed at verifying the knowledge of the contents of the book James H. Stock, Mark W.Watson, 2016. Introduzione all'econometria, Pearson. The ability to understand and interpret the output of econometric models is required. teacher profile teaching materials
- A review of Statistics and Probability theory
- Linear Regression with One Regressor
- Regression Models with Multiple Regressors
- Regression with a Binary Dependent Variable
- Regression with a Multinomial Dependent Variable
The course guides students in implementing empirical applications with the R software
Christoph Hanck, Martin Arnold, Alexander Gerber & Martin Schmelzer, 2018, Introduction to Econometrics with R, https://econometrics-with-r.org/
Articles/book chapters provided during the course
Mutuazione: 21801893 ECONOMETRIA in Scienze delle pubbliche amministrazioni LM-63 GATTA VALERIO
Programme
The course focuses on the following issues:- A review of Statistics and Probability theory
- Linear Regression with One Regressor
- Regression Models with Multiple Regressors
- Regression with a Binary Dependent Variable
- Regression with a Multinomial Dependent Variable
The course guides students in implementing empirical applications with the R software
Core Documentation
James H. Stock, Mark W.Watson, 2016. Introduzione all'econometria, Pearson.Christoph Hanck, Martin Arnold, Alexander Gerber & Martin Schmelzer, 2018, Introduction to Econometrics with R, https://econometrics-with-r.org/
Articles/book chapters provided during the course
Reference Bibliography
Hideo Aizaki, Tomoaki Nakatani, Kazuo Sato, 2014, Stated Preference Methods Using R, CRC Press. A.H. Studenmund, Using econometrics: a practical guide, 2011, Pearson.Type of delivery of the course
The course includes on-line lectures and exercises to be carried out live.Attendance
Attendance is not mandatory but strongly recommended.Type of evaluation
During the COVID-19 emergency period, the final exam will be carried out in accordance with the provisions of art.1 of the Rectoral Decree no. 703 of 5 May 2020. In particular: For attending students: the final mark depends on the outcome of the oral exam (50%) and on the practical activities (exercises, data analysis, interpretation of the results, participation) carried out during the course. The oral exam consists of around 3 questions aimed at verifying the knowledge of the contents discussed during the course and the synthesis ability. For non-attending students: the final mark depends on the outcome of the oral exam. The oral exam consists of around 3 questions aimed at verifying the knowledge of the contents of the book James H. Stock, Mark W.Watson, 2016. Introduzione all'econometria, Pearson. The ability to understand and interpret the output of econometric models is required.