An Introduction to Panel Data using EViews

Panel data econometrics is a vital tool for modern researchers seeking to model complex, longitudinal data structures. With the widespread availability of panel datasets across economics, finance, and policy research, the demand for rigorous, yet accessible, methods has never been greater.

This two-day online course provides a comprehensive introduction to panel data modelling using EViews 14, covering both static and dynamic linear models with exogenous and endogenous variables. Participants will engage with core econometric techniques—including fixed and random effects, GLS, and GMM estimators—while learning how to diagnose issues such as serial correlation and apply appropriate solutions. A strong applied focus ensures that concepts are reinforced through real-world micro and macro datasets in hands-on EViews sessions. By the end of the course, participants will be able to conduct their own panel data research proficiently using EViews 14.

What You’ll Learn

• Understand the strengths and challenges of panel data compared to cross-sectional and time series analysis, particularly in controlling for unobserved heterogeneity and improving estimation efficiency.

• Learn to estimate static panel models in EViews 14, including fixed effects and random effects, with a focus on robust inference techniques to address issues like heteroskedasticity and autocorrelation.

• Explore advanced methods for dynamic panel models, including the Arellano-Bond and Blundell-Bond estimators, and develop intuition for when and how to apply them.

• Gain hands-on experience with real-world applications of panel data models—such as evaluating the determinants of bank risk-taking in European financial systems—ensuring practical readiness for applied research.

This course is ideal for researchers, analysts, and policymakers looking to build a strong foundation in panel data econometrics using EViews 14. It combines rigorous theoretical insights with practical application, guiding participants through the essential methodologies for analysing both micro and macro longitudinal data.

Each session is carefully structured to demystify complex concepts—such as exogeneity, endogeneity, and serial correlation—while offering hands-on experience in estimating and comparing static and dynamic panel models. Whether you're refining your empirical strategy or expanding your software toolkit, this course equips you with the applied skills and confidence to conduct advanced panel data research with EViews.

• Comprehensive coverage of both static and dynamic panel data models using EViews 14

• Step-by-step guidance on fixed effects, random effects, GMM, and GLS estimators

• Introduction to advanced techniques including Arellano-Bond and Blundell-Bond estimators

• Robust inference methods to address serial correlation, heteroskedasticity, and endogeneity

• Real-world applications using macro and micro panel datasets

• Practical sessions designed to build confidence in EViews-based analysis

• Q&A session to address participant-specific research challenges

• Suitable for academic researchers, policy analysts, and data-driven professionals in economics and finance

This course is ideal for economists, applied researchers, and policy analysts who work with longitudinal or panel data and want to deepen their understanding of econometric modelling. It is also well-suited to postgraduate students and academics in economics, finance, and related social sciences who are looking to build practical skills in using EViews for empirical research. While no prior experience with EViews is necessary, a basic familiarity with linear regression and time series analysis will help participants get the most out of the course.

• 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.
• 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.
• 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.