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
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page. teacher profile teaching materials
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page. teacher profile teaching materials
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page. teacher profile teaching materials
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page. teacher profile teaching materials
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page. teacher profile teaching materials
The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
Stock J.H. and Watson M.W., Introduction to Econometrics, Global edition, 4th Edition, 2020, Pearson.
Programme
The main official statistical surveys: data collection methods and interpretation of the resulting statistics. In particular: consumer prices, industrial production, labour force, household consumption, income and living conditions, the Survey on Household Income and Wealth, and national accounts.The main indicators used to summarize economic data: index numbers (simple and composite) and measures of concentration. The main data transformations applied before publication to ensure meaningful comparisons over time: calendar adjustment, seasonal adjustment, and chain-linking. Moving averages for estimating the underlying trend.
Introduction to econometrics. Simple and multiple linear regression: the ordinary least squares (OLS) method, measures of goodness of fit, homoskedasticity and heteroskedasticity. Nonlinear regression models. Panel data regression models. Regression models with a binary dependent variable.
Introduction to the use of the R software environment for empirical data analysis using the methods introduced in the theoretical part of the course.
A detailed course syllabus and additional teaching materials are available on the course Moodle page.
Core Documentation
Lecture notes prepared by the instructor are available on the course Moodle page.Press releases, information notes, and statistical bulletins (Istat – Bank of Italy).
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 is recommended but not compulsory.Type of evaluation
The exam consists of a written test held in the computer lab (“Piazza telematica”), with a maximum duration of two hours. The test includes both theoretical and practical questions and requires the use of the software introduced during the course. Therefore, during the exam, students are not allowed to consult books or notes, nor are they allowed to use a calculator. The written test normally consists of three questions, each divided into specific sub-questions. The oral exam is optional. However, the instructor may require a mandatory oral interview if there are elements that raise doubts about the correctness of the written exam performance. Some sample exam papers from previous years are available on the course Moodle page. Each week, usually at the end of the last lecture of the week, a Moodle quiz consisting of multiple-choice questions on the topics covered during the previous week will be made available. Participation in the quizzes is not compulsory and does not affect eligibility to take the final exam; however, participation allows students to earn a bonus that will be added to the final exam grade. Students who participate in all quiz sessions and answer all questions correctly will receive a 2-point bonus. Other students will receive a proportional score based on the total number of correct answers provided. Two midterm tests are scheduled during the teaching period. The format and assessment procedures of these tests will be specified at the beginning of the semester and described in a file available among the teaching materials on the course Moodle page.