Advanced Panel Data Analysis with Stata

Advanced Panel Data Analysis with Stata

This advanced two-day online course explores non-linear panel data models and panel cointegration using Stata. Participants will gain hands-on experience estimating complex models and interpreting outputs through guided exercises.

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360,00 GBP
Gwarancja bezpiecznej i pewnej realizacji transakcji
–
2 Days
Online
Stata

Overview

As data-driven research becomes more sophisticated, the ability to work with complex longitudinal datasets is a vital skill for economists, social scientists, and policy analysts. Panel data methods, especially at an advanced level, allow researchers to model dynamic behaviour, control for unobserved heterogeneity, and produce more accurate empirical findings.

 

This two-day, interactive online seminar offers a deep dive into Advanced Panel Data Analysis using Stata, ideal for researchers who are already familiar with the basics of panel econometrics and want to build on that foundation. Through a combination of lectures and hands-on coding exercises, participants will explore advanced non-linear models, panel cointegration, and quantile regression techniques. The course emphasises both conceptual understanding and practical implementation in Stata.

Course Aims & Objectives
  • Deepen understanding of advanced econometric methods for panel data.
  • Introduce estimation techniques for non-linear models such as probit, logit, Tobit, and selection models.
  • Provide tools for addressing incidental parameter problems and cointegration in panel settings.
  • Enable participants to apply advanced Stata techniques confidently in their own research.
Key Skills Acquired

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

  • Estimate and interpret non-linear panel models (probit, logit, Tobit, selection, and count models).

  • Perform diagnostic testing and model validation in Stata.

  • Apply panel quantile regression and unit root tests for panels with large N and T.

  • Understand and implement panel cointegration techniques.

Learning Outcomes
  • Technical Expertise: Learn advanced econometric tools for non-linear and cointegrated panel data using Stata.
  • Applied Skills: Gain hands-on experience estimating models and interpreting Stata outputs.
  • Analytical Ability: Develop skills to choose appropriate models for specific research questions.
  • Research Readiness: Equip yourself with advanced techniques applicable to academic, policy, and industry research.
Course Structure

Format: Two-day online seminar
Daily Sessions: 10:00–12:00 & 14:00–16:00 (BST)
Q&A: 1-hour concluding session on Day 2

Total contact time: 8 hours of instruction + 1 hour Q&A

Agenda

Day 1:

Session 1: Binary Panel Models & Estimation Challenges

  • Introduction to non-linear panel models

  • The incidental parameter problem in estimation

  • Probit Panel Models

    • Definition and motivation

    • Estimation techniques in Stata

    • Diagnostic tests and interpretation of output

  • Logit Panel Models

    • Definition and estimation in Stata

    • Handling incidental parameter problems

    • Output diagnostics and interpretation

Session 2: Tobit, Selection, and Count Models

  • Tobit Models

    • Definition and context for use

    • Estimation in Stata

    • Diagnostic testing and interpretation

  • Selection Models

    • Model specification and estimation in Stata

    • Output diagnostics

  • Introduction to Count Models

    • Basic definitions and applications

Day 2:

Session 1: Count Models & Quantile Regression

  • Count Models (continued)

    • Estimation in Stata

    • Model diagnostics and output interpretation

  • Panel Quantile Regression Models

    • Definition and applications

    • Estimation techniques in Stata

    • Diagnostic checks and interpreting results

Session 2: Unit Roots & Panel Cointegration

  • Panel Data with Large N and T

    • Challenges and model considerations

  • Tests for Unit Roots in Panel Data

    • Introduction and implementation

  • Introduction to Panel Cointegration

    • Conceptual overview and relevance

    • Application examples

Prerequisites

There are no specific prerequisites to attend the course but we reccomend viewing the below pre-course reading

Reccomended Reading
 
  • An introductory level of Stata helps but is not necessary
  • A good knowledge of the topics presented in the course: panel data analysis in Stata is required

Course Timetable

Subject to minor changes
Day Morning Session Afternoon Session
Day One 10am-12pm (London time) 2pm-4pm (London time)
Day Two 10am-12pm (London time) 2pm-4pm (London time)

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