The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration
Contemporary Economics, Vol. 6, No. 2, pp. 40-57, 2012
18 Pages Posted: 25 Nov 2012
Date Written: 2012
Abstract
There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods.
Keywords: regression, correlation, cointegration, model based inference, likelihood inference
JEL Classification: C32
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Specification Analysis of Affine Term Structure Models
By Qiang Dai and Kenneth J. Singleton
-
Specification Analysis of Affine Term Structure Models
By Qiang Dai and Kenneth J. Singleton
-
By Andrew Ang and Monika Piazzesi
-
By Andrew Ang and Monika Piazzesi
-
By John H. Cochrane and Monika Piazzesi
-
Expectation Puzzles, Time-Varying Risk Premia, and Dynamic Models of the Term Structure
By Qiang Dai and Kenneth J. Singleton
-
Expectation Puzzles, Time-Varying Risk Premia, and Dynamic Models of the Term Structure
By Qiang Dai and Kenneth J. Singleton
-
Expectation Puzzles, Time-Varying Risk Premia, and Dynamic Models of the Term Structure
By Qiang Dai and Kenneth J. Singleton
-
Expectation Puzzles, Time-Varying Risk Premia, and Dynamic Models of the Term Structure
By Qiang Dai and Kenneth J. Singleton