This paper investigates how conditional quantiles of a given distribution relate to each other. Given two conditional quantiles estimated nonparametrically, we investigate their relation by linking them through a parametric transformation. Asymptotic normality of the associated parameter vector...

This paper proposes unit root tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adaptive estimation using...

We provide an argument for the limitation of Edgeworth expansions to many commonly used statistics in the weak instrument framework. However, we show that Edgeworth expansions hold for approximately similar tests regardless of the identification conditions. Finally, we consider simulation...

The aim of this paper is to give a formal definition and consistent estimates of the extremes of a population. This definition relies on a threshold value that delimits the extremes and on the uniform convergence of the distribution of these extremes to a Pareto type distribution. The tail...

Being able to correctly characterise an observed time series into its separate difference stationary and trend stationary regimes, should they exist, has important implications for effective model building and forecasting in economics and finance. Existing ratio-based statistics test the null...

In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) tests. The first involves testing for the inclusion of a non-linear regressor and the second involves testing of a linear regressor against the alternative of a non-linear regressor. We report the...

This paper considers an important practical problem in testing time-series data for nonlinearity in mean. Most popular tests reject the null hypothesis of linearity too frequently if the the data are heteroskedastic. Two approaches to redressing this size distortion are considered, both of which...

It is a well accepted fact that stock returns data are often contaminated by market microstructure effects, such as bid-ask spreads, liquidity ratios, turnover, and asymmetric information. This is particularly relevant when dealing with high frequency data, which are often used to compute model...

Understanding and forecasting financial time series depend crucially on identifying any non-linearity which may be present. Recent developments in tests for non-linearity very commonly display low power, most likely because of over-smoothing and discarding pertinent information. In this...

This paper investigates whether Japanese banks had been following herd behavior in the domestic loan market from 1975 through 2002. Applying the technique developed by Lakonishok, Shleifer, and Vishny (LSV) (1992, J. of Fin. Econ.) to the data of loans outstanding to different types of...