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.
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.
a b s t r a c tWe measure the connectedness in EMU sovereign market volatility between April 1999 and January 2014, monitoring stress transmission and identifing episodes of intensive spillovers from one country to the others. We first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period using a framework recently proposed by Diebold and Yilmaz (2014). Second, we use a dynamic analysis to evaluate the net directional connectedness for each country and apply panel model techniques to investigate its determinants. Finally, we examine the time-varying behaviour of net pair-wise directional connectedness at different stages of the recent sovereign debt crisis.
Our research aims to analyze the possible existence of Granger-causal relationships in the behavior of public debt issued by peripheral member countries of the European Economic and Monetary Union (EMU), with special emphasis on the recent episodes of crisis triggered in the eurozone sovereign debt markets since 2009. With this goal in mind, we make use of a database of daily frequency of yields on 10-year government bonds issued by five EMU countries (Greece, Ireland, Italy, Portugal and Spain), covering the entire history of the EMU from its inception on 1 January 1999 until 31 December 2010. In the first step, we explore the pair-wise Granger-causal relationship between yields, both for the whole sample and for changing subsamples of the data, in order to capture the possible time-varying causal relationship. This approach allows us to detect episodes of significant increase in Granger-causality between yields on bonds issued by different countries. In the second step, we study the determinants of these episodes, analyzing the role played by different factors, paying special attention to instruments that capture the total national debt (domestic and foreign) in each country.
scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.