We consider LM-type tests for a unit root allowing for a break in trend at an unknown date. In addition to the minimum LM test statistic, we propose new LM-type tests based on the least squares estimator of the break date under the null. We examine asymptotic behavior under the null hypothesis...

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...

In this paper, starting from continuous-time local level unobserved components models for stock and flow data we derive locally best invariant (LBI) stationarity tests for data available at potentially irregularly spaced points in time. We demonstrate that the form of the LBI test differs...

In this paper, we propose the use of bootstrapping methods to obtain correct critical values for dating breaks. Following the procedure proposed in Banerjee, Lazarova and Urga (1998), we consider the case of estimating a system with two or more marginal processes and a conditional process....

In this paper, we consider testing marginal distributional assumptions. Special cases that we consider are the Pearson's family like the Gaussian, Student, Gamma, Beta and uniform distributions. The test statistics we consider are based on the first moment conditions derived by Hansen and...

In this paper it is shown that "classical" tests can become asymptotically inadmissible (i.e. we show that there exist uniformly better tests) if the information matrix becomes stochastic: A typical example is the augmented Dickey-Fuller test for unit roots (in case of no deterministic trend. We...

The notion of cointegration was developed by Engle and Granger (1987), and since then has been considered important in the recent development of time series econometrics. Many statistical methods have been developed for the analysis of the cointegrated systems, and several methods of estimating...

A correctly specified time series model can be used to transform the data set to obtain an i.i.d. sequence of random variables, assuming that the true parameter values are known. In reality, however, one only has an estimated model and must therefore address the sampling error associated with...

We present a general framework for testing the accuracy of Value-at-Risk (VaR) forecasts. The approach is based on the observation that violations – the days on which portfolio losses exceed the VaR – should be unpredictable. Specifically, these violations form a martingale difference...

In this paper we investigate portfolio coskewness using a quadratic market model as return generating process. It is shown that portfolios of small (large) firms have negative (positive) coskewness with market. An asset pricing model including coskewness is tested through the restrictions it...