Econometric Evaluation of Socio-Economic Programs

Econometric Evaluation of Socio-Economic Programs by Giovanni Cerulli provides an excellent introduction to estimating average treatment effects from observational data. This book provides thorough introductions to the models and estimators implemented in teffects, etregress, and etpoisson and provides many examples using these commands and some similar commands written by the author.

After presenting an overview of the topic, the book delves into methods based on conditional independence. Next, it considers methods that drop conditional independence, thereby allowing for endogenous treatment effects. Finally, the book covers more advanced topics, including local average treatment effects and regression-discontinuity designs.

The author provides a nice mix of intuition, mathematics, and Stata examples. Professors, graduate students, and researchers will find this book useful in the classroom and for self-study in preparation for research projects.

AN INTRODUCTION TO THE ECONOMETRICS OF PROGRAM EVALUATION

 

Introduction
Statistical Setup, Notation, and Assumptions

Identification Under Random Assignment
A Bayesian Interpretation of ATE Under Randomization
Consequences of Nonrandom Assignment and Selection Bias

Selection on Observables and Selection on Unobservables

Selection on Observables (or Overt Bias) and Conditional Independence Assumption
Selection on Unobservables (or Hidden Bias)
The Overlap Assumption

Characterizing Selection Bias

Decomposing Selection Bias

The Rationale for Choosing the Variables to Control for
Partial Identification of ATEs: The Bounding Approach
A Guiding Taxonomy of the Econometric Methods for Program Evaluation
Policy Framework and the Statistical Design for Counterfactual Evaluation
Available Econometric Software
A Brief Outline of the Book

References

 

METHODS BASED ON SELECTION ON OBSERVABLES

 

Introduction

Regression-Adjustment

Regression-Adjustment as Unifying Approach Under Observable Selection
Linear Parametric Regression-Adjustment: The Control-Function Regression
Nonlinear Parametric Regression-Adjustment
Nonparametric and Semi-parametric Regression-Adjustment

Matching

Covariates and Propensity-Score Matching
Identification of ATEs Under Matching
Large Sample Properties of Matching Estimator(s)
Common Support
Exact Matching and the “Dimensionality Problem”
The Properties of the Propensity-Score
Quasi-Exact Matching Using the Propensity-Score
Methods for Propensity-Score Matching
Inference for Matching Methods
Assessing the Reliability of CMI by Sensitivity Analysis
Assessing Overlap
Coarsened-Exact Matching

Reweighting

Reweighting and Weighted Least Squares
Reweighting on the Propensity-Score Inverse-Probability
Sample Estimation and Standard Errors for ATEs

Doubly-Robust Estimation
Implementation and Application of Regression-Adjustment
Implementation and Application of Matching

Covariates Matching
Propensity-Score Matching
An Example of Coarsened-Exact Matching Using cem

Implementation and Application of Reweighting

The Stata Routine treatrew
The Relation Between treatrew and Stata 13’s teffects ipw
An Application of the Doubly-Robust Estimator

References

 

METHODS BASED ON SELECTION ON UNOBSERVABLES

 

Introduction
Instrumental-Variables

IV Solution to Hidden Bias
IV Estimation of ATEs
IV with Observable and Unobservable Heterogeneities
Problems with IV Estimation

Selection-Model

Characterizing OLS Bias within a Selection-Model
A Technical Exposition of the Selection-Model
Selection-Model with a Binary Outcome

Difference-in-Differences

DID with Repeated Cross Sections
DID with Panel Data
DID with Matching
Time-Variant Treatment and Pre-Post Treatment Analysis

Implementation and Application of IV and Selection-Model

The Stata Command ivtreatreg
A Monte Carlo Experiment
An Application to Determine the Effect of Education on Fertility
Applying the Selection-Model Using etregress

Implementation and Application of DID

DID with Repeated Cross Sections
DID Application with Panel Data

References

 

LOCAL AVERAGE TREATMENT EFFECT AND REGRESSION-DISCONTINUITY-DESIGN

 

Introduction
Local Average Treatment Effect

Randomization Under Imperfect Compliance
Wald Estimator and LATE
LATE Estimation
Estimating Average Response for Compliers
Characterizing Compliers
LATE with Multiple Instruments and Multiple Treatment

Regression-Discontinuity-Design

Sharp RDD
Fuzzy RDD
The Choice of the Bandwidth and Polynomial Order
Accounting for Additional Covariates
Testing RDD Reliability
A Protocol for Practical Implementation of RDD

Application and Implementation

An Application of LATE
An Application of RDD by Simulation

References

Author: Giovanni Cerulli
ISBN-13: 978-3-662-46404-5
©Copyright: 2015 Springer
Versione e-Book disponibile

Econometric Evaluation of Socio-Economic Programs by Giovanni Cerulli provides an excellent introduction to estimating average treatment effects from observational data. This book provides thorough introductions to the models and estimators implemented in teffects, etregress, and etpoisson and provides many examples using these commands and some similar commands written by the author.