New extra-semestral course 5EN382- Introduction to Time Series Analysis

Faculty of Economics, Department of Economics would like to invite you to an extra-semestral course 5EN382 Chapters in Economics II.- Introduction to Time Series Analysis


Visiting Professor from University of Glasgow, senior lecturer Marco Avarucci


Department of Economics, Faculty of Economics has the honor to welcome Marco Avarucci, who will deliver a course 5EN382 Introduction to Time Series Analysis“


Course will take place from 6/11/23 to 8/11/2023, so if you want to participate, please register via INSIS in section extra-semestral courses. Registration available from 12.9. 2023.


Marco Avarucci is a Senior Lecturer in Economics at the Adam Smith Business School at the University of Glasgow. He holds a PhD in Econometrics and Empirical Economics from Tor Vergata University in Rome. He is interested in time series analysis, including factor models, panel data and volatility models. His works appeared in leading journals in Econometrics and Statistics, such as the Journal of Econometrics, Econometric Theory, and the Journal of American Statistics Association.  Before joining Glasgow, he held a position at Maastricht University and LUISS in Rome. He taught different courses on statistics and econometrics to undergraduate and postgraduate students.

Time series appear naturally with data sampled in time. Many familiar series occur in the field of economics, where we are continually exposed to daily stock market quotations, monthly inflation rates or annual GDP data. Social scientists follow population series, such as birthrates or school enrollments. Other applications of time series analysis include climatology, astronomy and medicine, to name a few.

This course aims at providing students with a set of robust and useful techniques to analyze time series, mainly in a univariate framework. Topics will include stationarity, (partial) autocorrelation functions, autoregressive moving average (ARMA) and volatility model. The application of the aforementioned techniques will be illustrated using EViews.


By the end of this course students will be able to:

  1. Select and fit the appropriate model to analyse time series data.
  2. Derive the main properties of the models used to analyse and forecast time series.
  3. Produce optimal forecasts for a given information set and forecast horizon.
  4. Model and forecast time series using statistical/econometric software.



Monday 6/11/23 9-12, 14-17, SB 208

Tuesday 7/11/23 9-12, 14-17, SB 208

Wednesday 8/11/23 9-12, 14-17, SB 208

Final exam: TBA


We are looking forward to your participation.

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New extra-semestral course 5EN382- Introduction to Time Series Analysis