Contextual factors usually assume an important role in determining firms' productive efficiencies. Nevertheless, identifying them in a regression framework might be complicated. The problem arises from the efficiencies being correlated with each other when estimated by Data Envelopment Analysis...

We study inference for the local innovations of It\^o semimartingales. Specifically, we construct a resampling procedure for the empirical CDF of high-frequency innovations that have been standardized using a nonparametric estimate of its stochastic scale (volatility) and truncated to rid the...

Financial advisors commonly recommend that the investment horizon should be rather long in order to benefit from the "time diversification". In this case, in order to choose the optimal portfolio, it is necessary to estimate the risk and reward of several alternative portfolios over a long-run...

I propose a nonparametric iid bootstrap procedure for the empirical likelihood, the exponential tilting, and the exponentially tilted empirical likelihood estimators that achieves sharp asymptotic refinements for t tests and confidence intervals based on such estimators. Furthermore, the...

This paper proposes bootstrap methods for the realized bipower variation and the Barndorff-Nielsen and Shephard (2006a) test for jumps. These results enable inference for the realized bipower variation in the presence of jumps in prices. Both the i.i.d and the WILD bootstrap are shown to...

This paper studies inference for the realized Laplace transform (RLT) of volatility in a fixed‐span setting using bootstrap methods. Specifically, since standard wild bootstrap procedures deliver inconsistent inference, we propose a local Gaussian (LG) bootstrap, establish its first‐order...

We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually. A direct test of the joint null hypothesis may not be possible with standard methods when the total number of...

We consider testing for correct specification of a nonparametric instrumental variable regression. In this ill-posed inverse problem setting, the test statistic is based on the empirical minimum distance criterion corresponding to the conditional moment restriction evaluated with a Tikhonov...

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...