This article examines the impact of the boundary specification problem upon the estimation of spatial autoregressive models within an instrumental variable (IV) framework. We show the usual IV estimator remains consistent and asymptotically normal, but incurs an asymptotic bias of order...

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...

We highlight a subtle identification problem that afflicts models for non-negative data in which the conditional expectation is specified as the product of a logit and an exponential function. The results are illustrated with an empirical model for medical expenditures.

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.

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...

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

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 paper provides evidence of a negative association between macroeconomic uncertainty and the cross sectional dispersion of investment rate for a panel of Japanese manufacturing firms. We show that an increase in uncertainty leads to the narrowing of the cross section dispersion of investment...

This paper illustrates that the generalized propensity score method can easily be applied with multiple continuous endogenous treatment variables. Consistency proofs carry over straightforwardly to this general case, and the approach is shown to work well in finite samples with various...