We propose a simple test on structural change in long-range dependent time series. It is based on the idea that the test statistic of the standard CUSUM test retains its asymptotic distribution if it is applied to fractionally differenced data. We prove that our approach is asymptotically valid...

We propose a family of self-normalized CUSUM tests for structural change under long memory. The test statistics apply non-parametric kernel-based fixed-b and fixed-m long-run variance estimators and have well-defined limiting distributions that only depend on the long-memory parameter. A Monte...

This paper proposes a residual based cointegration test with improved power. Based on the idea of Hansen (1995) and Elliott & Jansson (2003) in the unit root testing case, stationary covariates are used to improve the power of the residual based Augmented Dickey Fuller (ADF) test. The asymptotic...

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional...

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

We propose a new way to conduct multiple hypothesis testing in economics research. Our framework allows for correlation among tests and incomplete data, both of which are prevalent in economic meta-analysis. Our simulations show that that our method is able to produce the correct p-value cutoff...

Large-scale inference has become increasingly popular in financial economics. I explore an empirical Bayes approach to large-scale multiple testing. The proposed approach bases its inference on the posterior probability that the null is true given the observed data. It provides a convenient way...

Local asymptotic power advantages are available for testing the null hypothesis that the slope coefficient is zero in regressions of y(t+k)-y(t) on x(t) for k 1 where the x(t) and the change in y(t) are I(0) series. The advantages of these long-horizon regression tests accrue in a linear...

Lobato and Robinson (1998) develop semiparametric tests for the null hypothesis that a series is weakly autocorrelated, or I(0), about a constant level, against fractionally integrated alternatives. These tests have the advantage that the user is not required to specify a parametric model for...