Cointegration

About: Cointegration is a research topic. Over the lifetime, 17130 publications have been published within this topic receiving 506215 citations.

Investigating the relationship between gold and silver prices

Abstract: This paper analyses the long-run relationship between gold and silver prices. The three main questions addressed are: the influence of a large bubble from 1979:9 to 1980:3 on the cointegration relationship, the extent to which by including error-correction terms in a non-linear way we can beat the random walk model out-of-sample, and the existence of a strong simultaneous relationship between the rates of return of gold and silver. Different efficient single-equation estimation techniques are required for each of the three questions and this is explained within a simple bivariate cointegrating system. With monthly data from 1971 to 1990, it is found that cointegration could have occurred during some periods and especially during the bubble and post-bubble periods. However, dummy variables for the intercept of the long-run relationships are needed during the full sample. For the price of gold the non-linear models perform better than the random walk in-sample and out-of-sample. In-sample non-linear models for the price of silver perform better than the random walk but this predictive capacity is lost out-of-sample, mainly due to the structural change that occurs (reduction) in the variance of the out-of-sample models. The in-sample and out-of-sample predictive capacity of the non-linear models is reduced when the variables are in logs. Clear and strong evidence is found for a simultaneous relationship between the rates of return of gold and silver. In the three type of relationships that we have analysed between the prices of gold and silver, the dependence is less out-of-sample, possibly meaning that the two markets are becoming separated. © 1998 John Wiley & Sons, Ltd.

Long-Run Causality, with an Application to International Links between Long-Term Interest Rates

Abstract: In this paper we give a precise definition of long-run causality in a multivariate non-stationary, possibly cointegrated, framework. A variable is said to be causal for another in the long run if knowledge of the past of the former improves long-run predictions of the latter. In a VAR framework, we show that long-run non-causality can be easily tested with a Wald statistics, conditionnally on the cointegration rank. The methodology is used to study long-run causal links between US, German, and French long-term interest rates from January 1990 to June 1997.

Short- and Long-Run Electricity Demand Elasticities at the Subsectoral Level: A Cointegration Analysis for German Manufacturing Industries

Abstract: In this paper we use multivariate cointegration analysis to estimate electricity demand elasticities at the subsectoral industry level. This enables us to reap the benefits of lower heterogeneity within the electricity-consuming sectors investigated and of retaining additional information otherwise blurred by aggregation. The annual data set used covers eight subsectors of the German economy for the period 1970-2007. By employing a cointegrated VAR model specification and accounting for structural breaks we find cointegration relationships for five of the eight subsectors studied. The long-run elasticities range between 0.70 and 1.90 for economic activity and between –0.52 and zero for the price of electricity. The short-run elasticities are estimated by single-equation error-correction modeling and found to be between 0.17 to 1.02 for economic activity and –0.57 to zero for electricity price. Granger-causality tests indicate that in the long term causality runs from both economic activity and electricity price to electricity consumption, while Granger-causality from electricity price and electricity consumption to economic activity is detected in only two subsectors. Electricity price is found to be Granger-caused neither in the long nor the short run. Finally, an impulse response analysis yields plausible results confirming the usefulness of the approach adopted.