CODICE CORSO: I-SS10 LINGUA: RESIDENZIALE

Econometrics for Program Evaluation: Theory and Practice using Stata, 3rd Edition

Providing effective evaluation of economic, social and medical programs has become an increasingly important requirement for both public and private institutions. This school seeks therefore, to provide participants with the requisite tools, both theoretical and applied, for the correct implementation of modern micro-econometric methods for implementing program evaluation using Stata. As such, the program has been developed to encompass both: standard statistical methods of program evaluation: regression-adjustment, matching, selection-models and difference-in-differences methodologies; and the more advanced econometric techniques: for example, instrumental variables, endogenous regression-adjustment and regression discontinuity design.

 

The school opens with an introductory one day 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. Module B (Introductory Econometrics) running from day two to four, offers participants the opportunity to acquire, or simply refresh, the econometric techniques required to follow and actively participate in the empirical sessions during the course of the week. Both Modules A and B are optionally, attendance will depend on the individual participant’s background.

 

At the end of the school participants are expected to be able to master complex evaluation design by: identifying the type of data required in their specific policy framework; evaluating which specific econometric method is more appropriate for the analysis in hand; and finally extracting policy recommendations from the obtained results. Participants should leave the course being in a position to autonomously implement, with the aid of the Stata routines utilized during the sessions, the theories and methodologies discussed during the course of the school.

 

In common with TStat’s course 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 school, 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 public and private institutions needing to undertake econometric program evaluation analysis using micro data. Although these methodologies are commonly used to evaluate policy interventions in, for example, the labour market, investment activities of enterprises, education policy, regional development, etc., they can in fact be used across a variety of studies, such as public health sector evaluation, which aim to estimate the ex-post impact of a given intervention or project on specific targets.

Introductory knowledge of econometrics and/or statistics.

MODULE A: AN INTRODUCTION TO STATA

 

SESSION I: INTRODUCTION – GETTING STARTED

Stata’s GUI

File types in Stata

Working interactively in Stata

Organizing one’s work in Stata

Help

Web resources in Stata: dowloading updates and new commands via internet

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

Constrained commands

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: 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

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 (bar, histogram, scatter)

Saving and exporting graphs

Useful graph commands

Personalizing a graph

Stata’s Graph Editor

 

APPENDIX A: USEFUL TO KNOW

 

APPENDIX B: MORE ADVANCED ISSUE (time permitting)

do files

Merging data bases

e-class and r-class variables

collapse command

preserve command

restore command

 

MODULE B: INTRODUCTORY ECONOMETRICS MODULE I

 

DAY 1: THE LINEAR REGRESSION MODEL

 

SESSION I: ORDINARY LEAST SUQARES (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

 

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

 

INTRODUCTORY ECONOMETRICS MODULE II

 

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

Tobit models

Selection models

Implementation in Stata

 

MODULE C: PROGRAM EVALUATION

 

DAY 1: ECONOMETRICS OF PROGRAM EVALUATION

 

SESSION I: INTRODUCTION TO THE ECONOMETRICS OF PROGRAM EVALUATION

Concept of conterfactual causality

Experimental and quasi-experimental settings

Non-random sampling: selection on observables and selection on unobservables

Definition of treatment effects: types of effects and potential outcome

Notation and working hypothesis: SUTVA, CIA and CMI

 

SESSION II: OVERVIEW OF THE METHODS

Available econometric methods: limits and advantages

Stata for effective program evaluation: user-written commands and the TEFFECS package

 

SESSION III: LINEAR AND NON-LINEAR REGRESSION ADJUSTMENT

The control function regression approach

Non-linear models

 

DAY 2: MATCHING AND REWEIGHTING

 

SESSION I: MATCHING

The selection on observable setting

Identification conditions for Matching

Matching in practice: tests and sensitivity analysis

Implementation in Stata

 

SESSION II: REWEIGHTING

The logic of Reweighting

Reweighting on the propensity score

Analytical and bootstrap standard errors

Implementation in Stata

 

DAY 3: INSTRUMENTAL-VARIABLES AND SELECTION MODELS

 

SESSION I: INSTRUMETAL-VARIABLES

The logic of IV

Endogeneity and consistent estimation

Types of IV methods

Implementation in Stata

 

SESSION II: ENDOGENOUS REGRESSION ADJUSTMENT

The logic of ERA

The residual control-function approach

Implementation in Stata

 

SESSION III: SELECTION MODEL (HECKIT)

Dealing with selection-on-unobservables

Heckman selection model (heckit)

Implementation in Stata

 

DAY 4: DIFFERENCE-IN-DIFFERENCES AND REGRESSION DISCONTINUITY DESIGN

 

SESSION I: DIFFERENCE-IN-DIFFERENCES (DID)

DID statistical setting

DID with longitudinal data

DID with repeated cross-section

Implementation in Stata

 

SESSION II: REGRESSION DISCONTINUITY DESIGN (RDD) (time permitting)

RDD as a local approximation of a natural experiment

Sharp RDD: setting and estimation

Fuzzy RDD: setting and estimation

Implementation in Stata

 

SESSION III: POLICY EVALUATION IN PRACTICE

Ex-post policy evaluation: logical structure and statistical design

The choice of the evaluation method

Limitations and open questions

The summer school is expected in Florence from the 26th of August to the 2nd of September 2017, from 9:00 am to 5:00 pm

 

LOCATION: CISL Studium Centre ♦ Via della Piazzola, 71 ♦ Florence

 

PARTICIPATION FOR THE ENTIRE WEEK (Modules A, B and C – 8 days)

Students*: € 1825.00
Academic: € 2763.00
Government / Nonprofi t: € 3091.00
Commercial: € 3420.00

 

MODULES A and B (4 days)
Students*: € 1060.00
Academic: € 1599.00
Government / Nonprofi t: € 1793.00
Commercial: € 1987.00

 

MODULE B (3 days)
Students*: € 815.00
Academic: € 1239.00
Government / Nonprofi t: € 1383.00
Commercial: € 1527.00

 

MODULE C (4 days)
Students*: € 1087.00
Academic: € 1652.00
Government / Nonprofi t: € 1844.00
Commercial: € 2036.00

 

*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.

 

All fees are subject to VAT (applied at the current Italian rate of 22%).

 

Please note that a non-refundable deposit of €100.00 for students and €200.00 for academic, government/nonprofit and commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 20. 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 school); ii) a temporary licence of Stata valid for 30 days from the beginning of the school; iii) half board accommodation (breakfast, lunch and coffee breaks) in a single room at the Centro Studi CISL (7 nights for entire week, 3 nights for Modules A and B, 2 nights for Module B, 3 nights for Module C). Participants requiring accommodation the day before the course beginning or the night of the final day of the school, are requested to contact us as soon as possible.

 

In order to maximize the usefulness of this workshop, we recommend that participants bring their own laptops with them, to be able to actively participate in the empirical sessions.

 

Individuals interested in attending this summer school must return their completed registration forms either by email (training@tstat.eu) or by fax (+39 0864 206014) to TStat by the 10th of August 2017.


L’iscrizione al corso dovrà avvenire tramite lo specifico modulo di registrazione e pervenire a TStat S.r.l. almeno 15 giorni prima dell’inizio del corso stesso. E’ possibile richiedere il modulo di registrazione compilando il seguente form oppure inviando una mail a formazione@tstat.it


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Autorizzo il trattamento dei dati personali ai sensi dell'articolo 13 del D.lgs. n.196/2003 - Testo completo



Providing effective evaluation of economic, social and medical programs has become an increasingly important requirement for both public and private institutions. This school seeks therefore, to provide participants with the requisite tools, both theoretical and applied, for the correct implementation of modern micro-econometric methods for implementing program evaluation using Stata. As such, the program has been developed to encompass both: standard statistical methods of program evaluation: regression-adjustment, matching, selection-models and difference-in-differences methodologies; and the more advanced econometric techniques: for example, instrumental variables, endogenous regression-adjustment and regression discontinuity design.