TStat’s Introduction to Micrcoeconometrics workshop offers participants an applied and theoretical introduction to the principle methodologies implemented in the analysis of microeconomic data. More specifically, the course focuses on linear regression techniques, instrumental variable analysis and GMM estimators, qualitative dependent variable models (the Logit and Probit estimators) and the issue of censoring and sample selection (the Tobit model). Although the course is entitled “Introduction to Microeconometrics”, the techniques developed throughout the courses are easily implemented in a variety of research contexts, in both public health and the social sciences, where micro data is becoming increasingly more available.
The Workshop opens with an optional one day introductory course (Module A) to the statistical package Stata, during which participants will be provided with the necessary tools to enable them to use Stata independently and actively participate in the applied empirical Lab sessions during the course of the 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 course, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques.
Researchers and professionals working in biostatistics, economics, epidemiology, finance, psychology, social and political sciences needing to acquire the necessary statistical requisites required to independently conduct empirical analysis using micro data.
Introductory knowledge of econometrics and/or statistics.
MODULE A: STATA IN JUST ONE DAY!
SESSION I: INTRODUCTION GETTING STARTED
File types in Stata
Working interactively in Stata
Saving output: the log file
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
Statistical Tables: table, tabstat and tabulate commands
SESSION III: DATA MANAGEMENT
Selecting or eliminating variables
The count command
Creating sub-groups: the prefix by
Creating new variables: generate
Operators in Stata
The command assert
Missing values in Stata
Modifying variables: replace, recode
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
Reading in Text Data Files
Issues to watch out for when importing data
Redefining missing values
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
Useful to know
APPENDIX B: MORE ADVANCED ISSUES (TIME PERMITTING)
Merging data bases
e-class and r-class variables
MODULE B: INTRODUCTORY ECONOMETRICS
DAY 1: THE LINEAR REGRESSION MODEL
SESSION I: ORDINARY LEAST SQUARES (OLS) ESTIMATION
OLS Estimation in Stata
SESSION II: QUALITATIVE EXPLANATORY VARIABLES
OLS estimation in the presence of qualitative explanatory variables
Including factor variables in the estimation process
Fixed-effect panel-data models
DAY 2: ENDOGENEITY AND INSTRUMENTAL VARIABLES ESTIMATORS
SESSION I: INSTRUMENTALS VARIABLES ESTIMATORS
Endogeneity and bias in OLS estimators
Instrumental variables and GMM estimators
Implementation in Stata
SESSION II: TESTS AND ROBUSTNESS
Testing for exogeneity
Tests of over-identifying restrictions
Testing for weak instruments
Tests and robustness in Stata
DAY 3: LIMITED DEPENDENT VARIABLE MODELS
SESSION I: BINARY DEPENDENT VARIABLE
Binary outcome models
Goodness of fit and specification tests
Implementation in Stata
SESSION II: CENSORED AND SELECTION MODELS
Implementation in Stata
Mostly Harmless Econometrics: An Empiricist’s Companion, Joshua D. Angrist e Jorn-Steffen Pischke (2008) Princeton University Press.
Microeconometrics Using Stata, Colin Cameron and Pravin K. Trivedi (2010) Stata Press.
The course will be held in Florence from the 26th to the 29th August 2019.
Una-Louise BELL – TStat Training
Giovanni BRUNO – Bocconi University
MODULES A and B (4 days)
Students*: € 1485.00
Academic: € 1755.00
Non-Profi t/Public Research Centres: € 1935.00
Commercial: € 2115.00
MODULE B (3 days)
Students*: € 1115.00
Academic: € 1318.00
Non-Profi t/Public Research Centres: € 1450.00
Commercial: € 1587.00
*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-Profi t/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: i) teaching materials (copies of lecture slides, databases and Stata routines used during the summer school; ii) a temporary licence of Stata valid for 30 days from the day before the beginning of the school; iii) half board accommodation (breakfast, lunch and coffee breaks) in a single room at the CISL Studium Centre or equivalent (4 nights for Modules A and B, 3 nights for Module B). Participants requiring accommodation the night of the final day of the school, are requested to contact us as soon as possible.
To maximize the usefulness of this summer school, 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 summer school must return their completed registration forms by email (firstname.lastname@example.org) to TStat by the 1st August 2019.
TStat’s Introduction to Micrcoeconometrics workshop offers participants an applied and theoretical introduction to the principle methodologies implemented in the analysis of microeconomic data. More specifically, the course focuses on linear regression techniques, instrumental variable analysis and GMM estimators, qualitative dependent variable models (the Logit and Probit estimators) and the issue of censoring and sample selection (the Tobit model).