This paper proposes a score-driven model for filtering time-varying causal parameters through the use of instrumental variables. In the presence of suitable instruments, we show that we can uncover dynamic causal relations between variables, even in the presence of regressor endogeneity which...

Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least squares estimation of cointegrating regressions between nonstationary and/or long memory stationary variables where the...

A unified theory of estimation and inference is developed for an autoregressive process with root in (-∞, ∞) that includes the stationary, local-to-unity, explosive and all intermediate regions. The discontinuity of the limit distribution of the t-statistic outside the stationary region and...

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.