1. Introduction 2 -- Start using Gretl and R 3 -- Basic Material 4 -- Hypothesis testing 5 -- Simple linear regression 6 -- Multiple regression 7 -- Regression using dummy variables 8 -- Non linear models 9 -- Time series analysis 10 -- Other statistical tools.

An MLE of the unknown parameters of co integrating vectors is presented for systems in which some variables exhibit higher orders of integration, in which there might be deterministic components, and in which the co integrating vector itself might involve variables of differing orders of...

A number of recent studies have attempted to test propositions concerning "long runt" economic relationships by means of frequency-domain time series techniques that concentrate attention on low frequency co-movements of variables.The present paper emphasizes that many of these propositions...

We develop a sequence of tests for specifying the cointegrating rank of, possibly fractional, multiple time series. Memory parameters of observables are treated as unknown, as are those of possible cointegrating errors. The individual test statistics have standard null asymptotics, and are...

Fractional cointegration is viewed from a semiparametric viewpoint as a narrow-band phenomenon at frequency zero. We study a narrow-band frequency domain least squares estimate of the cointegrating vector, and related semiparametric methods of inference for testing the memory of observables and...

The concept of cointegration has principally been developed under the assumption that the raw data vector zt is I(1) and the cointegrating residual et is I(0), but is also of interest in more general, including fractional, circumstances, where zt is stationary with long memory and et is...

We provide a new asymptotic theory for local time density estimation for a general class of functionals of integrated time series. This result provides a convenient basis for developing an asymptotic theory for nonparametric cointegrating regression and autoregression. Our treatment directly...