Panel Data Econometrics: theory and applications
THE COURSE IS DELIVERED IN ONLINE MODE.
If the conditions of the ongoing COVID 19 pandemic allow it, the course will be also delivered in presence. Participants may express thier preference upon acceptance
Bertinoro, 12 - 17 July 2021
Maria Elena Bontempi University of Bologna, Department of Economics
Strada Maggiore 45
Maria Elena Bontempi, University of Bologna
Roberto Golinelli, University of Bologna
Irene Mammi, University of Venezia Ca' Foscari
Programs are conditional to the recruitment of a minimum of 15 participants
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, analyzed 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, heteroscedasticity, the introduction of dynamics and the role of unit roots.
(1) Static panels. Understanding the clustered data structure. Dealing with endogeneity (simultaneity, measurement errors). Methods: handling unobserved heterogeneity; variance decomposition at two or more levels; correlated random effects and correlated random slopes; instrumental variables (IV) in panel data models; unbalanced panels and selection bias. Guided hands-on session on the topics.
(2) Dynamic panels. Nickell’s bias, 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.
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 data-sets and the programming files to make applied econometrics will be provided during the lectures in Bertinoro. But 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 Stata already installed on them. Any Stata version from 12 to 15 is ok!
Venue and timetables
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.
Fees and Enrollment
* Online Course
- Students, new graduated students, PhD students and temporary university staff: 340 euro
- University staff: 450 euro
- Others: 1500 euro
* Course in Bertinoro
- Students, new graduated students, PhD students and temporary university staff: 690€
- University staff: 800€
- Others: 2300€
Fee includes: accommodation breakfast and lunch (starting from Sunday evening).
If participants do not need any accomodation during the course, please send an email to email@example.com to request a reduced fee and we will apply a cost reduction of 100€.
In case of enrollment in two or more courses, for a maximum of three, Student and Staff participants are entitled to a discount of 100 euros on each course. Other participants are entitled to a discount of 300 euros on each course.
Renounce and refund:
To submit a renounce request, please send an email to firstname.lastname@example.org.
You can give up immediately after the notification of acceptance or later.
After the payment, you can submit your renounce up to one week (7 days) from the beginning of the course (within the terms for refund) and ask for a refund with motivated reasons (health reasons to be documented, for study purposes or personal reasons). We will refund your fee with a deduction for administrative and organization costs: 150 Euro for the course in presence, 100 Euro for online course.
Over the terms for refund (less of 7 days from the beginning of the course) you need to motivate your request (as indicated above), which will be submitted to SIdE President.
Application Deadline: May 18th, 2021
Notification of acceptance will be posted by the 21th May, 2021
Deadline for Fee Payment is June 7th, 2021
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- For travel and accommodation: Monica Michelacci (firstname.lastname@example.org), phone: +39 0543446500.