[Abstract]: Traditional technology adoption models identified ‘perceived ease of use’ and ‘perceived usefulness’ as the dominating factors for technology adoption. However, recent studies in healthcare have indicated that these two factors are not always reliable on their own and other...

Pretesting for exogeneity has become a routine in many empirical applications involving instrumental variables (IVs) to decide whether the ordinary least squares (OLS) or the IV-based method is appropriate. Guggenberger (2010) shows that the second-stage t-test – based on the outcome of a...

This note studies the asymptotic validity of bootstrapping the test of overidentifying restrictions under many/many weak instruments and heteroskedasticity. We show that the wild bootstrap consistently estimates the null limiting distributions of a jackknife overidentification statistic under...

Under a framework with a small number of clusters but large numbers of observations per cluster for instrumental variable (IV) regression, we show that an unstudentized wild bootstrap test based on IV estimators such as the two-stage least squares estimator is valid as long as the instruments...

In this note, for the case that the disturbances are conditional homoskedastic, we show that a properly re-scaled residual bootstrap procedure is able to consistently estimate the limiting distribution of a series estimator in the partially linear model even when the number of regressors is of...

Pretesting for exogeneity has become a routine in many empirical applications involving instrumental variables (IVs) to decide whether the ordinary least squares (OLS) or the two-stage least squares (2SLS) method is appropriate. Guggenberger (2010) shows that the second-stage t-test – based on...

Pretesting for exogeneity has become a routine in many empirical applications involving instrumental variables (IVs) to decide whether the ordinary least squares (OLS) or the two-stage least squares (2SLS) method is appropriate. Guggenberger (2010) shows that the second-stage t-test – based on...

Pretesting for exogeneity has become a routine in many empirical applications involving instrumental variables to decide whether the ordinary least squares or the two-stage least squares (2SLS) method is appropriate. Guggenberger (2010) shows that the second-stage t-test – based on the outcome...

Bootstrap procedures based on instrumental variable (IV) estimates or t-statistics are generally invalid when the instruments are weak. The bootstrap may even fail when applied to identification-robust test statistics. For subvector inference based on the Anderson-Rubin (AR) statistic, Wang and...

Pretesting for exogeneity has become a routine in many empirical applications involving instrumental variables (IVs) to decide whether the ordinary least squares (OLS) or the two-stage least squares (2SLS) method is appropriate. Guggenberger (2010) shows that the second-stage t-test– based on...