# Panel Data Methods and Factor Models with EViews

Cass Business School 2 days (21st October 2019 - 14th November 2019) EViews Advanced, Intermediate
Delivered by: Professor Stephen Hall, School of Business, University of Leicester
Econometrics, Factor Models, Forecasting, Panel Data

### Overview

This two-day course will explore two important topics in Econometrics; Panel Data estimation and the use of factor models in economic forecasting and analysis.

This course will acquaint the student with modern panel data techniques including their use for standard stationary panels, dynamic panels and the broad area of non stationary panels. By the end of the two day course the participants should be able to; understand the structure of a panel data set and know the two ways to define such data sets in E-VIEWS. Estimate fixed and random effect models and construct Hausman tests between the two formulations. Conduct standard hypothesis tests. Understand the importance of stationarity for panels and use panel stationarity test. Test cointegration for a panel.

Factor analysis allows us to concentrate the important information contained in a large number of data series into a relatively small number of artificial factors which may be used for various purposes. Factor analysis begins with the single factor model which is estimated in state space form using the Kalman filter. It progresses to the multifactor models using principal components. It then combines these two into the dynamic facto model. These techniques are becoming increasingly important as we move into a world of ‘Big’ data.

### DAY 1

Session 1&2

• Panel lecture I
• Simple Panels
• Least squares dummy variable
• Testing hypothesis
• Setting up a panel in E-VIEWS using a pool
• Setting up a panel using the panel approach
• Performing a pooled regression in E-VIEWS
• Fixed effect estimation in E-VIEWS
• Random effects estimation in E-VIEWS

Session 3&4

• Brief Introduction to Stationarity and cointegration
• The importance of Non-stationarity for Panel Estimation
• Stationarity testing in the Panel Context
• Testing for Cointegration

### DAY 2

Session 1&2

• The intuition behind factor models
• The various versions of factor models
• Brief introduction to state space models and the Kalman Filter
• The single factor state space model
• The static multiple factor model using principal components
• The dynamic factor model

Session 3&4

• The static multiple factor model using principal components
• The dynamic factor model
• Scree plots and selecting the number of factors
• Practical examples of factor analysis
• Factor augmented VARs

1. Baltagi B. ‘Econometric Analysis of Panel Data’, Wiley
2. Stock and Watson ‘Dynamic Factor Models’ Oxford Handbook of Economic Forecasting, eds Clements M.P. and Hendry D.F.
3. Diebold F. ‘Big Data, Dynamic Factor Models for Macroeconomic Measurement and Forecasting’ in Dewatripont M, Hansen L.P. and Turnovsky(eds) Advances in Economics and Econometrics. 2003.

Learning Ratio: 40% theory, 20% demonstration and 40% practical

### DAILY TIMETABLE (subject to minor changes)

TimeSession / Description
08:45 - 09:15 Arrival & Registration
09:30 - 11:00 Session 1
11:00 - 11:15 Morning break
11:15 - 12:45 Session 2
12:45 – 13.45 Lunch
13:45 - 15:15 Session 3
15:15 - 15:30 Tea/coffee break
15:30-17:00 Session 4

### Prerequisites

Intermediate level knowledge of econometrics. Familiarity with EViews fundamentals (built-in functions) is required.

• Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
• Additional discounts are available for multiple registrations.
• Cost includes course materials, lunch and refreshments.
• Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. (Alternatively, laptops can be hired for a fee of £10.00 (ex. VAT) per day).
• If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
• Payment of course fees required prior to the course start date.
• Registration closes 5-calendar days prior to the start of the course.
• 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
• 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
• No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of delegates is restricted. Please register early to guarantee your place.