Numerical standard error (NSE) is an estimate of the standard deviation of a simulation result if the simulation experiment were to be repeated many times. We review standard methods for computing NSE, and perform a Monte Carlo experiments to compare their performance in the case of high/extreme...

This paper investigates the finite sample properties of the widely-used Gibbons, Ross, Shanken (1989) (GRS) test in the presence of both conditional correlation and conditional heteroskedasticity. It finds that the GRS test exhibits serious size distortions resulting in potentially misleading...

There is a growing literature on unit root testing in threshold autoregressive models. This paper makes two contributions to the literature. First, an asymptotic theory is developed for unit root testing in a threshold autoregression, in which the errors are allowed to be dependent and...

We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The first step consists in estimating the...

We propose a test for the key identification and estimation conditions in Regression Discontinuity (RD) designs. We characterize the set of sharp testable implications of the RD assumptions, for which the proposed test is uniformly valid under a class of distributions, is consistent against all...

HAC estimators are known to produce test statistics that reject too frequently in finite samples. One neglected reason comes from using the OLS residuals when constructing the HAC estimator. If the regression matrix contains high leverage points, such as from outliers, then the OLS residuals...

This study proposes a multivariate test for linear factor asset pricing models when the number of assets, N, is larger than the time dimension of returns, T. We extend the exact test proposed by Gibbons et al. (1989) to obtain a nonsingular covariance matrix with fewer estimation errors in the...

NSE is an R package for computing the numerical standard error (NSE), an estimate of the standard deviation of a simulation result if the simulation experiment were to be repeated many times. The package provides a set of wrappers around several R packages, which give access to more than thirty...

Efficient computational algorithms for bootstrapping linear regression models with clustered data are discussed. For OLS regression, a new algorithm is provided for the pairs cluster bootstrap, and two algorithms for the wild cluster bootstrap are compared. One of these is a new way to express...