Abstract
The need to of en transform raw data is discussed and the logarithmic transformation is introduced in some detail. It is emphasised that the slope of a graph of the original data says nothing about the growth rate of the variable, since it is only from the slope of the graph of the logarithms that such information can be obtained. These ideas are illustrated by constructing alternative measures of UK inflation. Other transformations are discussed, including the famous Phillips curve, linking inflation to the inverse of the unemployment rate. Moving averages are introduced as a way of smoothing data and such ideas are extended to decomposing a time series, illustrated by decomposing retail sales into its trend, seasonal and irregular components as a prelude to seasonally adjusting the series.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Notes
A.W Phillips, ‘The relation between unemployment and the rate of change of money-wage rates in the UK, 1861–1957’, Economica 25 (1958), 283–299.
The original form of the Phillips curve used here has long been regarded as being far too simplistic and has been extended in various ways: see, for example, the ‘New Keynesian Phillips curve’ of Olivier Blanchard and Jordi Gali, ‘Real wage rigidities and the New Keynesian model’, Journal of Money, Credit and Banking 39 (2007), 35–65. A retrospective look at the Phillips curve’s place in macroeconomics is provided by Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective (MIT Press, 2009).
A useful introductory reference is Terence C. Mills, Modelling Trends and Cycles in Economic Time Series (Palgrave Macmillan, 2003).
The original reference to the Hodrick-Prescott filter, of en referred to as the H-P filter, is Robert J. Hodrick and Edward C. Prescott, ‘Postwar US business cycles: an empirical investigation’, Journal of Money, Credit and Banking 19 (1997), 1–16.
For detailed analyses of current temperature trends, see Terence C. Mills, ‘Modelling current trends in Northern Hemisphere temperatures’, International Journal of Climatology 26 (2006), 867–884; ‘Modelling current temperature trends’, Journal of Data Science 7 (2009), 89–97; ‘Skinning a cat: stochastic models for assessing temperature trends’, Climatic Change 10 (2010), 415–426; and ‘Is global warming real? Analysis of structural time series models of global and hemispheric temperatures’, Journal of Cosmology 8 (2010), 1947–1954.
Author information
Authors and Affiliations
Copyright information
© 2014 Terence C. Mills
About this chapter
Cite this chapter
Mills, T.C. (2014). Transforming Data. In: Analysing Economic Data. Palgrave Texts in Econometrics. Palgrave Macmillan, London. https://doi.org/10.1057/9781137401908_3
Download citation
DOI: https://doi.org/10.1057/9781137401908_3
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-48656-4
Online ISBN: 978-1-137-40190-8
eBook Packages: Palgrave Economics & Finance CollectionEconomics and Finance (R0)