Courses

Course Overview

Prof. Sébastien Laurent, Aix-Marseille University

Panel data econometrics has developed rapidly over the last decades.

Longitudinal data are more and more available to researchers and methods to analyse these data are in high demand from scholars from different fields.

The course offers a comprehensive overview on panel data methods with Stata, covering static and dynamic linear models.

Each session briefly introduces the different methodologies, discussing strengths and weaknesses with a focus on the interpretation of the results.

By the end of the two-day on-line course, participants should be able to prepare panel data for the analysis with Stata, choose the relevant model, get the parameter estimates and interpret the results.

Presented By: Dr. George Naufal (Texas A&M University)

Time series data are nowadays collected for several phenomena in social and empirical sciences. Initially collected at year or quarter level, time series data are now used by marketing analytics, financial technology, and other fields in which data are collected at much smaller intervals (daily, hourly and even by the minute).

This course focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data and provides an introduction to the theoretical foundation of time series models alongside a practical guide to the use of time series analysis techniques implemented in Stata 16. The course is based on the textbook by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata, Stata Press Publication.

Presented by Dr. Malvina Marchese

This course is for economists, econometricians and applied researchers who want to go even further in EViews by coding something that is not implemented in the existing routines such as long memory GARCH models or Value at Risk. In addition, one may wish to make life easier and to ask EViews to perform some repetitive tasks. This is where EViews Programming starts. The goal of this training course is to make life easier, namely to do things with only a small investment instead of learning a completely new language.

This course will be running online, as a Zoom webinar.

Presented by Prof. Lorenzo Trapani (University of Nottingham)

Course Timetable: 10am - 12pm & 2pm - 4pm

The course offers an intermediate/advanced level overview of stationary VARs, cointegrated VARs and the VECM, and an introduction to Structural VARs (SVARs). It is a mixture, with equivalent weights, of methodology and practice, and each session is complemented by a data example. The SVAR part is also based on discussing several examples which are commonly encountered in macroeconometrics and monetary economics.

The course is aimed at practitioners and applied researchers in general who wish to either have a comprehensive introduction to the practical use of VARs and their variants, or a more rigorous understanding of these tools.

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

Our web-based Time Series Analysis and Forecasting with EViews course provides a complete introduction to time series modelling and forecasting with EViews. It provides a good and practical understanding of a wide range of time series models used in various fields, including macroeconomics and financial applications with a strong background in forecasting.

This course is an essential step for any more advanced courses in forecasting such as the Midas Touch or Regime Switching models in EViews.

Overview

Course Timetable: 10am - 12pm & 2pm - 4pm

Risk modelling is about modelling and quantification of risk. For the financial industry, the cases of credit-risk quantifying potential losses due to either bankruptcy of debtors, or market-risks quantifying potential losses due to negative fluctuations of a portfolio's market value are of particular relevance.

The aim of this course is to offer a comprehensive introduction to risk modelling and forecasting with EViews 12. The course offers one introductory day on risk modelling and forecasting via parametric methods and then builds on it to discuss the econometrics methods for stress testing, Value at Risk and fundamental measures of risk.

Presented By: Dr. Giovanni Cerulli

This course will provide participants with the essential tools, both theoretical and applied, for a proper use of modern micro-econometric methods for policy evaluation and causal counterfactual modelling under both assumptions of “selection on observables” and “selection on unobservables”. The course will cover these approaches: Regression adjustment (parametric and nonparametric), Matching (on covariates and on propensity score), Reweighting and Double-robust methods, and Difference-in-differences methods.

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

At times of great uncertainty for financial markets, this course provides participants with an understanding of the time series methods involved in modelling and forecasting financial markets volatilities. Participants will learn how to build, estimate and assess alternative models of volatility of financial time series. Each concepts will be explained from an econometric perspective and by means of many examples and applications in EViews

Presented by Jennifer L. Castle, Jurgen A. Doornik and David F. Hendry.

Running 2.00pm —5.30pm GMT

The course provides an introduction to the theory and practice of econometric modelling of climate variables in a non-stationary world. It covers the modelling methodology, implementation, practice and evaluation of climate economic models.

The framework, its basic concepts and implications will be explained for modelling evolving processes that are also subject intermittently to outliers and structural breaks. Applications to empirical climate time series will demonstrate the approach. The Climate Econometrics international webinar by Zack Miller will be included on Tuesday 16.

Join us for the 23rd Dynamic Econometrics Conference following this Spring School, 18th - 19th March 2021.

Course Timetable: 10am - 12pm & 2pm - 4pm (London time)

Presented by Dr. Malvina Marchese

Panel data econometrics has developed rapidly over the last decades.

Longitudinal data – both with a large number of units tracked for a short period and with a relative small number of units for a long time - are more and more available to researchers and methods to analyse these data are in high demand from scholars from different fields.

The course offers a comprehensive overview on panel data econometrics with EViews, covering linear models with exogenous and endogenous variables, static and dynamic linear models. All the traditional static and dynamic econometric techniques are discussed (fixed effect, random effect, GMM, GLS) together with some more advanced topics, such as serial correlation, stationarity and cointegration. The focus of the course is applied and all the topics are demonstrated in EViews using micro and macro panel data sets.

Presented By: Dr. Malvina Marchese (CASS Business School, London)

Course Timetable: 10am - 12pm & 2pm - 4pm

Our web-based 'Introduction to Panel Data Analysis with Stata' course provides an overview of the most-used panel data techniques and is ideal for the beginner/intermediate-level user who wants to learn how to implement panel data estimation with Stata commands.

Presented by Dr. Giovanni Cerulli

Course Timetable: 10am - 12pm & 2pm - 4pm (London time)

This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value from rows of large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.