The analysis of nonstationary time series using regression, correlation and cointegration with an application to annual mean temperature and sea level

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. Finally we analyse some data on annual mean temperature and sea level, by applying the cointegrated vector autoregressive model, which explicitly takes into account the nonstationarity of the variables.

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Year of publication:	2010-10-15
Authors:	Johansen, Søren
Institutions:	School of Economics and Management, University of Aarhus
Subject:	Regression correlation cointegration \| model based inference \| likelihood inference \| annual mean temperature \| sea level

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Extent:	application/pdf
Series:	CREATES Research Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	2 pages long
Classification:	C32 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008680680