This paper shows the inconsistency of three forms of 2SLS estimators to illustrate the specialty of the endogeneity problem in threshold regression.

This paper proposes using the Gaussian approximation, also known as quantile coupling, to estimate a quantile model. The quantile coupling allows one to apply the standard Gaussian-based estimation and inference to the transformed data set. The resulting estimator is asymptotically normal with a...

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV...

The nonparametric identification of the local average treatment effect (LATE) hinges on the satisfaction of three instrumental variable assumptions: (1) unconfounded assignment of the instrument, (2) no average direct effect of the instrument on the outcome within compliance types (exclusion...

This paper proposes a simple method for testing whether non-compliance in experiments is ignorable, i.e., not jointly related to the treatment and the outcome. The approach consists of (i) regressing the outcome variable on a constant, the treatment, the assignment indicator, and the...

This paper assesses duration-specific treatment effects of fixed currency regimes on bilateral trade along a duration path of up to 25 years. We find that country-pairs with fixed exchange rate regimes trade more, but only after about 8 years.

This paper considers a factor-augmented regression model in the presence of structural change. We propose a two-step procedure to estimate the coefficients of explanatory variables. We show that when the number of units (N) and the number of periods (T) are large and comparable, the proposed...

This note proposes a computationally simple estimator for quantile regression in a linear model context, as an alternative to Koenker and Bassett’s (1978) algorithm. The new estimator can remedy several drawbacks associated with Powell’s (1986) censored quantile regression estimator.

This work considers the estimation of a network model with sampled networks. Chandrasekhar and Lewis (2011) show that the estimation with sampled networks could be biased due to measurement error induced by sampling and propose a bias correction by restricting the estimation to sampled nodes to...

A particular robust regression estimator has gained popularity among applied econometricians. We show that this estimator is inconsistent for the parameters of the conditional mean when the errors are skewed and heteroskedastic, and conclude that therefore its use cannot be generally recommended.