Long-Run Causality, with an Application to International Links Between Long-Term Interest Rates
AbstractIn 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 knwoledge 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, conditionally 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.
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Bibliographic InfoPaper provided by Banque de France in its series Working papers with number 53.
Length: 24 pages
Date of creation: 1998
Date of revision:
Cointegration ; Forecasts ; Interest Rate;
Other versions of this item:
- Bruneau, Catherine & Jondeau, Eric, 1999. " Long-Run Causality, with an Application to International Links between Long-Term Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 545-68, November.
- C. Bruneau & E. Jondeau, 1997. "Long-run causality, with an application to international links between long-term interest rates," THEMA Working Papers 97-26, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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