We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or sub-sampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests have asymptotic sizes that are exactly equal to the nominal level uniformly...

We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or subsampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests have asymptotic sizes that are exactly equal to the nominal level uniformly...

This paper makes several important contributions to the literature about non- parametric instrumental variables (NPIV ) estimation and inference on a structural function h 0 and functionals of h 0 .First,wederivesup-normconvergence rates for computationally simple sieve NPIV (series two-stage...

This paper makes several important contributions to the literature about nonparametric instrumental variables (NPIV) estimation and inference on a structural function h0 and its functionals. First, we derive sup-norm convergence rates for computationally simple sieve NPIV (series 2SLS)...

This paper proposes two simple and new specification tests based on the use of an orthogonal series for a considerable class of cointegrated time series models with endogeneity and nonstationarity. The paper then establishes an asymptotic theory for each of the proposed tests. The first test is...

The stochastic inequality test is an exact non-parametric test that can be used to infer whether values in one random sample tend to be higher than in another. In addition it can be used to derive a confidence interval around an intuitive measure of effect size that is readily interpretable...

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from...

In this paper, we consider some specification testing problems in nonlinear time series models with nonstationarity. We propose using a nonparametric kernel test for specifying whether the regression function is of a known parametric nonlinear form. The power function of the proposed...

This paper deals with nonparametric inference for second order stochastic dominance of two random variables. If their distribution functions are unknown they have to be inferred from observed realizations. Thus, any results on stochastic dominance are influenced by sampling errors. We establish...

This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of an Itô semi-martingale, which is discretely observed over a fixed time horizon. We construct a minimax-optimal test to discriminate different smoothness classes of the...