Residual log-periodogram inference for long-run relationships

Log-periodogram regression in asymmetric long memory

Filtered Log-periodogram Regression of long memory processes

Filtered log-periodogram regression estimation of the fractional differencing parameter d is considered. Asymptotic properties are derived and the effect of filtering on d̂ is investigated. It is shown that the estimator by Geweke and Porter-Hudak (1983) can be improved significantly using a simple family of filters. The essential improvement is based on a binary decision that is asymptotically ...

Log-periodogram Regression of Time Series with Long Range Dependence

This paper discusses the use of fractional exponential models (Robinson (1990), Beran (1994)) to model the spectral density f(x) of a covariance stationary process when f(x) may be decomposed as f(x) = x ?2d f (x), where f (x) is bounded and bounded away from zero. A form of log-periodogram regression technique is presented both in the parametric context (i.e. f (x) is a nite order exponential ...

Bootstrapping the log-periodogram regression

Semiparametric estimation of the memory parameter in economic time series raises the problem of the small sample size and the poor approximation of the asymptotic distribution to the finite sample counterpart. This paper considers the bootstrap to improve the finite sample distribution of the popular log peridogram regression and shows that it can significantly reduce the error in the coverage ...

Reputation in Long-run Relationships

We model a long-run relationship as an infinitely repeated game played by two equally patient agents. In each period, the agents play an extensive-form game of perfect information. There is incomplete information about the type of player 1 while player 2’s type is commonly known. We show that a sufficiently patient player 1 can leverage player 2’s uncertainty about his type to secure his highes...