Residual Diagnostic Plots for Checking for Model Mis-Specification in Time Series Regression

Richard Fraccaro, Rob Hyndman and Alan Veevers

No 267485, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper considers residuals for time series regression. Despite much literature on visual diagnostics for uncorrelated data, there is little on the autocorrelated case. In order to examine various aspects of the fitted time series regression model, three residuals are considered. The fitted regression model can be checked using orthogonal residuals; the time series error model can be analysed using marginal residuals; and the white noise error component can be tested using conditional residuals. When used together, these residuals allow identification of outliers, model mis-specification and mean shifts. Due to the sensitivity of conditional residuals to model mis-specification, it is suggested that the orthogonal and marginal residuals be examined first.

Keywords: Productivity Analysis; Research and Development/Tech Change/Emerging Technologies; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 23
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/267485/files/monash-255.pdf (application/pdf)
https://ageconsearch.umn.edu/record/267485/files/monash-255.pdf?subformat=pdfa (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267485

DOI: 10.22004/ag.econ.267485

Access Statistics for this paper

More papers in Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().