This paper provides an updated survey of a burgeoning literature on testing, estimation and model specification in the presence of integrated variables. Integrated variables are a specific class of non-stationary variables which seem to characterise faithfully the properties of many macroeconomic time series. The analysis of cointegration develops out of the existence of unit roots and offers a generic route to test the validity of the equilibrium predictions of economic theories. Special emphasis is put on the empirical researcher's point of view.

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In this paper we provide new evidence on the hypothesis of German leadership and asymmetric performance in the EMS, in the framework of causality tests, using daily data. Given the evidence about non-linearity in financial series, we propose applying non-linear forecasting methods based on the literature on complex dynamic systems. Our analysis covers nine countries, and the sample period runs until 30 April 1998, so including the more recent events in the EMS history. A comparison of our results with those obtained from standard linear econometric techniques leads us to conclude that inference on causality based on our non-linear predictors would be preferable to that based on the standard linear approach.

This paper empirically investigates the short and the long run impact of public debt on economic growth. We use annual data from both the central and the peripheral countries of the euro area (EA) for the 1961–2013 period and estimate a production function augmented with a debt stock term by applying the Autoregressive Distributed Lag (ARDL) bounds testing approach. Our results suggest different patterns across the EA countries and tend to support the view that public debt always has a negative impact on the long-run performance of EA member states, whilst its short-run effect may be positive depending on the country.