Panel Data Econometrics: theory and applications

Bertinoro, 1-7 September 2024



Maria Elena Bontempi  
University of Bologna, Department of Economics, Piazza Scaravilli 2, 40126 Bologna  



Maria Elena Bontempi, University of Bologna
Roberto Golinelli, University of Bologna
Irene Mammi, University of Venezia Ca' Foscari


The maximum number of allowed participants in presence is 50.


Basic knowledge of econometrics to a level comparable with Introductory Econometrics SIDE course.
Examples of reference are represented by:
** Verbeek M. (2017), A guide to Modern Econometrics, 5th ed, Wiley, Ch. 1, 2, 3, 4, 5, 6  or
** Wooldridge J. M. (2020), Introductory Econometrics, a Modern Approach, 7th ed., Cengage, Ch. 1-6, 8-9, 15

Reference textbooks for the course:
**Wooldridge J. M (2010), Econometric Analysis of Cross-Section and panel Data, 2nd ed, Cambridge Mass.: MIT Press, Ch. 10- and 11 (panel), Ch. 7 (SUR)
**Handouts, readings and further material will be provided before the beginning of the course and during the lectures.


Course outline, objectives and learning outcomes
Nowadays panel datasets, intended as both time-series cross-sectional data (CSTS) and multilevel data with observations at higher- and lower-levels, permeate the empirical research on many topics, going from classical economics towards behavioral and political economy. The aim of the course is to provide an overview, both methodological and applied, of econometric models for panel data, where observations are available at least at two dimensions. During the course, to ease the comprehension and to introduce important topics, N will indicate individuals (cross-sections) and T will denote temporal periods (time-series). The first part of the course relates to micro panel data (where N is larger than T). After introducing the classical fixed and random effects models with emphasis to their pros and cons, we will discuss about endogeneity of explanatory variables, intended both as correlation with individual heterogeneity (the heterogeneity bias) and as correlation with idiosyncratic shocks (due to simultaneity, measurement errors, dynamics). The instrumental variables estimator, such as the Generalized Method of Moments (GMM), is at the core of this part. The second part of the course relates to macro panel data (where T is larger than N). The main issues will be non-stationarity and cointegration, analysed and discussed in the light of parameters’ heterogeneity and cross correlated effects. At each step of the course, the methodologies will be accompanied by hands-on empirical applications with an econometric software. At the end of the course, participants will be able to critically evaluate the empirical literature based on panel data, and to model and estimate their own issue of interest, according to the problems at hand: static versus dynamic approaches, heterogeneity and clustering, exogeneity versus endogeneity of covariates, GMM, unit roots and long/short run relationships.


Schedule of the course:

0) Crash course: OLS, GLS, IV, heteroskedasticity, the introduction of dynamics and the role of unit roots into the empirical models’ specification.

(1) Static panels. Understanding the data structure and the role of unobserved heterogeneity. The decomposition of the total variability at two or more levels, and the heterogeneity bias. Methods: fixed, random, and correlated effects. Guided hands-on session on the topics.

(2) Dynamic panels. Understanding endogeneity. Instrumental variables (IV) in panel data models, and the problem of overfitting and weak instruments. Methods: alternative data transformations; first-differences and IV, GMM-DIF, -LEV, -SYS estimators, the principal components analysis applied to the set of instruments. Guided hands-on session on the topics.

(3) Heterogeneous panels. ARDL specification and Pesaran’s poolability. Methods: Mean-Group (MG) and Pooled-MG estimators; demeaning and cross-correlated effects. Guided hands-on session on the topics.

(4) Non-stationary panels. Integration and cointegration. Methods: first- and second-generation unit roots tests; Pedroni and Westerlund cointegration tests; PANIC and PANICCA. Guided hands-on session on the topics.


Hands-on Sessions

Theoretical lectures are associated with working sessions; during them you will receive the suggestions needed to use an econometric software and to run your own empirical analysis. The statistical analysis will be done using Stata and help for new Stata users will be given during the lectures (it is worth to be stressed that the course is not about Stata, but it is on Panel Data Econometrics, and Stata is just a tool, like any other econometric package able to manage panel data). The datasets and the programming files to make applied econometrics will be provided during the lectures in Bertinoro. Please remember that in Bertinoro we do not have, and we cannot provide Stata software installation files or the Stata licence. So, if you would interactively use Stata during the lectures, you must have Stata pre-installed on your laptop before coming to Bertinoro. Any Stata version from 12 to 15 is ok!



Participants will use their laptops with the software STATA already installed on them. Any STATA version from 12 on is ok! Important remark: the course is not about STATA, but on Panel Data Econometrics. STATA is just a tool, like any other econometric package able to manage panel data. Moreover, in Bertinoro we do not have, and we cannot provide, STATA installation files and licenses. To actively interact during the lectures and the hands-on sessions, we strongly suggest that you have STATA pre-installed on your laptop before coming to Bertinoro



The certificate of attendance  will be based on one final “take-home in Bertinoro” exam. The assignment will contain an empirical exercise, covering the issues faced during the lectures, to be performed by using the econometric software and your understanding of the taught theoretical issues. Working in groups is strongly encouraged to improve exchanges of views, but each of you must submit an individual take-home exam.


Venue and timetables

Each Module requires a full-time attendance and participation is not compatible with other jobs at the same time (e.g. preparation of other exams). The Module will last one week and will be held in the University Residential Centre, Via Frangipane 6, 47032 Bertinoro (FC). Participants will be hosted in the Centre guest quarters, (as an exception, in case of reduced availability of rooms in the Centre, they will be accommodated in local hotels). Lectures and tutorials will be in English, with the following schedule: Monday to Friday: lectures 9:00-13:00, 15:00-17:00 individual hands-on sessions: 17:00-19:00. Saturday: lectures 9:00-13:00. .