The paper studies the interaction between aggregation and persistence pertaining to skip sampling of stock variables as well as temporal aggregation of flow variables for the generalized fractional processes. We show that, for skip sampling, the long memory feature at the zero frequency can...

This paper extends the classical work of bipower variation by allowing the return process to be autocorrelated. We propose a method of estimating the return volatility when the price process is described by a fractal Brownian motion with jumps.

We proposed a method to estimate extreme conditional quantiles by combining quantile GARCH model of Xiao and Koenker (2009) and extreme value theory (EVT) approach. We first estimate the latent volatility process using the information of intermediate quantiles. We then apply EVT to the tail...

I provide the nonparametric identification of nonlinear dynamic panel data models. I relax the assumption of covariate evolution in Shiu and Hu (2013) by the results of Hu and Shum (2012). The assumptions include first-order Markov assumptions and a restriction on the evolution of the covariate.

This paper proposes a model selection criterion for models defined by a set of moment conditions that are possibly nonsmooth and discontinuous. The model selection criterion is based on an asymptotically unbiased approximation of the Kullback–Leibler Information Criterion (KLIC), using the...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, ‘partial mean’ plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A...

We propose a method to generate flexible mixture distributions that are useful for estimating models such as the mixed logit model using simulation. The method is easy to implement, yet it can approximate essentially any mixture distribution. We test it with good results in a simulation study...

We analyse statistical inference for top income shares in finite samples. The asymptotic inference performs poorly even in large samples. The standard bootstrap tests give some improvement, but can be unreliable. The semi-parametric bootstrap approach is accurate in moderate and larger samples.

In this paper we extend the FMLS-based CUSUM cointegration test (Xiao and Phillips, 2002) for testing the smooth time-varying cointegration null hypothesis. For this purpose we use Chebyshev time polynomials to specify time-varying coefficients under the null. We derive the limiting distribution...

We examine the performance of nonlinear instrumental variable (NIV) unit root tests using various recursive detrending methods. We find that the NIV unit root tests using the recursive detrending method of Chang (2002) are the most powerful. They are more powerful than OLS based DF tests.