The contribution of this paper is three-fold. Firslty, a characterisation of the sub-hypotheses comprising the seasonal unit root hypothesis is presented which provides a precise formulation of the alternative hypotheses against which regression-based seasonal unit root tests test. Secondly, it...

Swaps are one of the major innovations of the 80s but there are little empirical studies on interest rates swaps (IRS), especially on European markets. To understand how swap pricing works, we estimate IRS valuation models for the French swap market. On one hand, from the market value of the...

This paper builds upon the existing literature on tests of the full hypothesis of deterministic seasonality in a univariate time-series process against the alternative of unit root behaviour at some or all of the zero and seasonal frequencies. Under the assumption of independent Gaussian errors...

A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken "directly" from the observed data. The procedure is useful when one wants to summarize the test results for several time...

This paper compares the power in small samples of different tests for conditional heteroscedasticity. Two new tests, based on neural networks, are proposed: the main interest in them arises from the fact that they do not require the exact specification of the conditional variance under the...

Non parametric and parametric estimation for the spectral density of a stationary process is a well-known topic, except when the spectrum vanishes for some frequency. Indeed, for this frequency, the limit law degenerates, and traditional inference no longer applies. The paper introduces non...

It is well-known that traditional inference do not apply when the spectral density of a stationary process vanishes for some frequency. This paper examines some properties of several new non parametric tests of this hypothesis which have been recently proposed by Lacroix (1999). These tests...

In this paper, new noncausality tests built on a general nonlinear framework are proposed and their performance studied by a Monte Carlo experiment and a variety of nonlinear artificial series. Two of these test are based on a Taylor expansion of the nonlinear model around a given point in a...

In many, if not most, econometric applications, it is impossible to estimate consistently the elements of the white-noise process or processes that underlie the DGP. A common example is a regression model with heteroskedastic and/or autocorrelated disturbances,where the heteroskedasticity and...

In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes.