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A Practical Comparison of the Bivariate Probit and Linear IV Estimators

This paper presents asymptotic theory and Monte-Carlo simulations comparing maximum-likelihood bivariate probit and linear instrumental variables estimators of treatment effects in models with a binary endogenous treatment and binary outcome. The t...

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Bibliographic Details
Main Authors: Chiburis, Richard C., Das, Jishnu, Lokshin, Michael
Language:English
Published: 2012
Subjects:
ASYMPTOTIC DISTRIBUTION
BOOTSTRAP
CONFIDENCE INTERVALS
CRITICAL VALUE
CRITICAL VALUES
DEGREES OF FREEDOM
DEVELOPMENT RESEARCH
DISTRIBUTION FUNCTION
DUMMY VARIABLE
ECONOMETRICS
ENDOGENOUS REGRESSORS
EQUATION SYSTEM
ERROR
ERROR TERMS
ESTIMATORS
EXHIBITS
GOODNESS OF FIT
HYPOTHESIS TESTING
INSTRUMENTAL VARIABLES
INSTRUMENTAL VARIABLES ESTIMATION
KURTOSIS
LIMITED DEPENDENT VARIABLE
LIMITED DEPENDENT VARIABLES
LOG-LIKELIHOOD FUNCTION
LOGISTIC REGRESSION
MATRIX
MAXIMUM LIKELIHOOD
MEAN SQUARE
0 HYPOTHESIS
NUMBER OF OBSERVATIONS
PREDICTION
PROBABILITIES
PROBABILITY
PUBLIC SERVICES
RANDOM VARIABLES
REGRESSION MODEL
RESEARCH WORKING PAPERS
RESEARCHERS
SAMPLE SIZE
SCIENCES
SIMULATION
SIMULATIONS
SKEWNESS
SMALL SAMPLE
STANDARD DEVIATION
STANDARD ERRORS
STANDARD NORMAL DISTRIBUTION
STATA
STATISTICAL SOFTWARE
STRUCTURAL PARAMETERS
T-TESTS
TECHNIQUES
TEST STATISTIC
VALIDITY
Online Access:http://www-wds.worldbank.org/external/default/main?menuPK=64187510&pagePK=64193027&piPK=64187937&theSitePK=523679&menuPK=64187510&searchMenuPK=64187283&siteName=WDS&entityID=000158349_20110317174628
http://hdl.handle.net/10986/3368

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