The course has two aims: to foster the ability to interpret economic systems and their tendencies through the main economic statistics produced by the official organizations and to introduce the basic methods to analyse economic data. In particular the course covers the production of economic indicators, the basic of classical time series analysis, also to correctly perform a short-term analysis, the linear regression model and its generalizations.Theoretical concepts will be illustrated using the most recent Italian economic data. The statistical analysis will be done using the software R.
Curriculum
teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available. teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Mutuazione: 21201505 STATISTICA PER L'ECONOMIA in Economia L-33 BARBIERI MARIA MADDALENA
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available. teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available. teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available. teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available. teacher profile teaching materials
Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
Main official statistical surveys: data production and interpretation. In particular: Consumer prices, Industrial production, Labour forces, Household consumptions, Income and living conditions, Household Income and Wealth. National accounts. Main statistical indicators for economic phenomena: (simple and complex) index numbers, measures of concentration.Calendar adjusted and seasonal adjusted time series; chain-linked values. The use of moving averages to reconstruct the trend.
Introduction to econometrics. Single and multiple Linear Regression: ordinary least squares, goodness of fit, homoscedasticity and heteroscedasticity. Nonlinear regression functions. Regression with panel data. Regression with a binary dependent variable.
An introduction to the use of R for statistical analysis.
Core Documentation
Class notes (in Italian) downloadable from the Moodle space of the course.Press releases (Istat - Banca d'Italia).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Type of delivery of the course
Whole class teaching.Attendance
Attendance in classes is recommended, but not compulsory.Type of evaluation
The final exam is a written two hours closed-book and closed-note test; takes place in the Lab; consists in both analytical and computer-exercise questions. The test is usually organized in four main questions, each of them divided into a number of specific items. The oral exam is optional. In the Moodle space of the course, test papers of some previous exams are available.