Panel data contains information on many cross-sectional units, which are observed at regular intervals across time. Panel data, by its very nature, can be highly informative regarding dynamic effects across different units and thus they are increasingly used in econometrics, financial analysis, medicine and the social sciences. This introductory course offers participants the opportunity to acquire the necessary theoretical background and the applied skills to enable them to: i) independently employ micro panel data techniques to their own research topics, and ii) to understand and evaluate micro panel data analyses published in the academic literature. The course focuses on the techniques adopted for the analysis of stationary panel data sets, including fixed and random effects models; hypothesis testing; the violations of the basic assumptions of regression analysis; unbalanced panels; instrumental variable estimation techniques and non-linear panel data models.
In common with TStat’s training philosophy, each individual session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the workshop, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques.
The Panel data workshop is of particular interest to Master and Ph.D. Students, researchers in public and private research centres and professionals working in the following fields: Agricultural Economics, Economics, Finance, Management, Public Health, Political Sciences and the Social Sciences seeking to acquire the “introductory” applied and theoretical toolset to enable them to undertake independent empirical research using panel data.
Participants are required to have a good working knowledge of the OLS regression model and the statistical software Stata.
SESSION I: INTRODUCTION
Panel data: definition
Panel data: benefits for estimation and inference
SESSION II: LINEAR PANEL DATA MODELS WITH EXOGENOUS VARIABLES
One-way and two-way fixed effect estimators: xtreg, fe
Random Effects Estimators: xtreg, re; xtmixed
SESSION III: LINEAR PANEL DATA MODELS WITH EXOGENOUS VARIABLES: ROBUST INFERENCE
Robust covariance estimators
The first-difference estimator
Testing for non i.i.d. errors
Testing Random Effects against Fixed Effects: hausman
SESSION IV: LINEAR PANEL DATA MODELS WITH ENDOGENOUS VARIABLES
General aspects of IV and GMM
Estimators with strictly exogenous IV
Fixed and Random Effect IV Estimators: xtivreg
Hausman and Taylor’s estimator: xthtaylor
Dynamic panel data estimators: xtabond
SESSION V: NON-LINEAR PANEL DATA MODELS
The incidental parameter problem in non-linear models
Probit panel data models: probit, xtprobit
Correlated effects modelled as group means
Logit panel data models: logit, xtlogit
Correlated effects (conditional logit)
Poisson panel data models: poisson, xtpoisson
Correlated effects (conditional poisson)
The course will be held in Frankfurt am Main from the 26th to the 28th June 2019.
Students*: € 735.00
Academic: € 1225.00
Non-Profit/Public Research Centres: € 1513.00
Commercial: € 1800.00
*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.
Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.
Please note that a non-refundable deposit of €100.00 for students and €200.00 for Academic, Non-Profit/Public Research Centres and Commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 15. Places will be allocated on a first come, first serve basis.
Course fees cover: teaching materials (handouts, Stata do files and datasets to used during the course), a temporary licence of Stata valid for 30 days from the beginning of the workshop, light lunch and coffee breaks.
To maximize the usefulness of this workshop, we strongly recommend that participants bring their own laptops with them, to enable them to actively participate in the empirical sessions.
Individuals interested in attending this workshop must return their completed registration forms by email (email@example.com) to TStat by the 6th June 2019.
This introductory workshop offers participants the opportunity to acquire the necessary theoretical background and the applied skills to enable them to: i) independently employ micro panel data techniques to their own research topics, and ii) to understand and evaluate micro panel data analyses published in the academic literature. The workshop focuses on the techniques adopted for the analysis of stationary panel data sets, including fixed and random effects models; hypothesis testing; the violations of the basic assumptions of regression analysis; unbalanced panels; instrumental variable estimation techniques and non-linear panel data models.