Economic Statistics II

Course objectives

The main objective of the course is to provide students with the main tools to analyse time series in economics and finance, to make forecasts and to evaluate them. Knowledge and understanding. After attending the course, students will be able to describe, interpret and forecast economic time series, distinguishing seasonal, short-term, and long-term fluctuations. Applying knowledge and understanding. After attending the course, the students will know the main statistical tools to analyse temporal dependent data, and will be able to implement the analysis on real time series through statistical software. Making judgements. Students will increase not only their theoretical skills but also their critical curiosity in reading real recent economic phenomena. Communication skills. Students, through discussions in the classroom and exercises, will acquire tools for critical analysis of empirical evidence and communication skills. Learning skills. Students learn methods of analysis that will allow them to critically read an economic report.

Channel 1
ROBERTO ZELLI Lecturers' profile

Program - Frequency - Exams

Course program
Economic data and sources 1. Economomic data 2. Statistical sources 3. Data transformations 4. Deflating procedures of monetary aggregates Exploratory analysis of time series 1. Decomposition of a time series 2. The regression method 3. Moving averages 4. Seasonally adjustment 5. Exponential smoothing and forecast evaluation ARMA models 1. Autoregressive models 2. Moving average models 3. ARIMA models 4. Box-Jenkins procedure 5. Forecasting with ARIMA models Further topics 1. Problems with sasonal adjustments 2. Seasonal ARIMA 3. Deterministic vs stochastic trend 4. Modelling volatility of financial time series
Prerequisites
It is suggested to have basic knowledge in Statistics, Probability, Linear Algebra, Economics and Economic Statistics.
Books
T. Di Fonzo e F. Lisi, “Serie storiche economiche”, Carocci Editore, 2005. Suggested for specific topics: P.H. Franses, D. van Dijk, A. Opschoor, “Time Series Models for Business and Economic Forecasting”, second edition, Cambridge University Press, 2014. J. Hamilton, “Time Series Analysis”, Princeton University, 1994. R.J. Hyndman, G. Athanasopoulos, “Forecasting: Principles and Practice”, OTexts, 2014, http://otexts.com/fpp/
Teaching mode
Lectures include presentation of statistical methods, empirical applications and exercises.
Frequency
Attending the course is strongly suggested but not compulsory.
Exam mode
Students have to seat for (a) a written exam where they have to solve and interpret simple exercises; (b) an oral exam.
Bibliography
Suggeriti per specifici argomenti: P.H. Franses, D. van Dijk, A. Opschoor, “Time Series Models for Business and Economic Forecasting”, second edition, Cambridge University Press, 2014. J. Hamilton, “Econometria delle serie storiche”, Monduzzi Editore, 1995. R.J. Hyndman, G. Athanasopoulos, “Forecasting: Principles and Practice”, OTexts, 2014, http://otexts.com/fpp/
Lesson mode
Lectures include presentation of statistical methods, empirical applications and exercises.
  • Lesson code1035300
  • Academic year2024/2025
  • CourseStatistics, Economics, Finance and Insurance
  • CurriculumEconomia e finanza
  • Year3rd year
  • Semester1st semester
  • SSDSECS-S/03
  • CFU9
  • Subject areaStatistico, statistico applicato, demografico