COURSE ID: D-EF10B LANGUAGE:

APPLIED PANEL DATA ANALYSIS IN STATA

Panel data analysis 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. Special attention will also be given to the interpretation and presentation of results. At the end of the course, it is expected that participants are able to implement independently the methodologies and techniques acquired during the three day workshop.

The workshop opens with an optional introductory one day course (Module A) to the statistical package Stata, during which participants will be provided with an overview of the necessary Stata commands and tools to enable them to: a) carry out data analysis, data management, importing and export of different data formats and the creation of graphs in Stata; and b) actively participate in the applied empirical Lab sessions during the course of the Panel Data workshop.

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.

MODULE A Introduction to Stata: Familiarity with PCs and a working knowledge of English.

MODULE B Panel Data Analysis: Participants are required to have a good working knowledge of the OLS regression model and the statistical software Stata.

MODULE A: INTRODUCTION TO STATA

SESSION I: INTRODUCTION – GETTING STARTED

Stata’s GUI
File types in Stata
Working interactively in Stata
Saving output: the log file
Interrupting Stata
Loading Stata databases
The Log Output File
Saving databases in Stata
Exiting the software

 

SESSION II: PRELIMINARY DATA ANALYSIS

A preliminary look at the data: describe, summarize commands
Abbreviations in Stata
Stata’s syntax
Summary statistics
Statistical Tables: table, tabstat and tabulate commands

 

SESSION III: DATA MANAGEMENT

Renaming variables
Selecting or eliminating variables
The count command
sort command
Creating sub-groups: the prefix by
Creating new variables: generate
Operators in Stata
The command assert
Missing values in Stata
Modifying variables: replacerecode
Creating Labels: variable labels and value labels
Creating dummy variables

 

SESSION IV: IMPORTING DATA FROM SPREADSHEETS

Import Excel and Export Excel commands
The insheet and outsheet commands
Importing in SPSS Files
Issues to watch out for when importing data

Missing values
String variables
Date variables

Redefining missing values
destring command
tostring command
Dealing with “messy” strings

 

SESSION V: GRAPHICS – A BRIEF INTRODUCTION

Stata’s syntax for two way graphs
Saving and exporting graphs
Useful graph commands
Personalizing a graph
Stata’s Graph Editor

 

APPENDIX A: USEFUL TO KNOW

 

APPENDIX B: MORE ADVANCED ISSUES (time permitting)

do files
Merging data bases
e-class and r-class variables
collapse command
preserve command
restore command

 

 

MODULE B: PANEL DATA ANALYSIS IN 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

Random-effect models
Correlated effects modelled as group means
Partial effects

Logit panel data models: logit, xtlogit

Random effects
Correlated effects (conditional logit)

Poisson panel data models: poisson, xtpoisson

Random effects
Correlated effects (conditional poisson)

The workshop will be held from the 15th to 18th of October 2018 in Beirut at the

University of Sciences and Arts in Lebanon (USAL)
Faculty of Management, Finance, and Economics (FMFE)
Airport Road, Ghobeiry, Beirut, Lebanon

 

 

MODULE A Introduction to Stata (1 day)
Students*: € 150.00
Academic: € 350.00
Non-Profit/Public Research Centres: € 425.00
Commercial: € 525.00

 

MODULE B Panel Data Analysis (3 days)
Students*: € 735.00
Academic: € 1225.00
Non-Profit/Public Research Centres: € 1513.00
Commercial: € 1800.00

 

MODULES A + B (4 days)
Students*: € 835.00
Academic: € 1525.00
Non-Profit/Public Research Centres: € 1888.00
Commercial: € 2275.00

 

*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.

 

REGISTRATION DEADLINE

Individuals interested in attending this workshop must return their completed registration forms either by email (training@tstat.eu) or by fax (+39 0864 206014) to TStat by the 15th of September 2018.


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The workshop opens with an optional introductory one day course (Module A) to the statistical package Stata, during which participants will be provided with an overview of the necessary Stata commands and tools to enable them to: a) carry out data analysis, data management, importing and export of different data formats and the creation of graphs in Stata; and b) actively participate in the applied empirical Lab sessions during the course of the Panel Data workshop.