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Section II

Data collection

The data for inflation and unemployment values were colleted from the Economist Intelligence Unit (EIU) for each individual country. For inflation, the percentage of consumer price inflation (CPI) was taken, since this is the headline value of inflation that central banks tend to target. For unemployment, the total percentage unemployment rate was used, since it was the most commonly used and an aggregate of the unemployment statistics. Other studies[1] have suggested using capacity utilisation to monitor the output or unemployment gap, but since this study primarily concerns an investigation into the Phillip’s curve relationship, unemployment was chosen.

Due to the lack of more frequent data for the 1980’s, yearly values were used in Section III.A for comparing the experience of the 1980’s and 1990’s for each individual country. The original idea was to carry out a cross section for all the OECD countries in order to maximise the number of observations for the regression, but the wide variance of unemployment and inflation values between countries rendered the test inaccurate. Testing for an aggregate Phillips curve of highly industrialised countries is not yet possible yet, given the lack of convergence of real variables – particularly in the 1980’s. Therefore, despite the lack of observations, OLS regression tests were carried out for the individual countries, utilising each decade as a subsample. Given that data was available for the period 1980-2004 it was decided to split this period into two, so that rather than studying each decade, the subsamples chosen are in fact 1980-1992 and 1993-2004.

For Section III.B, since quarterly data from the EIU dataset was available for the 1990’s, this was used to increase the number of observations and accuracy of the regression. Data for the NAIRU estimates were collected from the OECD dataset. Since values were only available for the years 1990,1995,1999, and 2003, the values in between had to be interpolated for a smooth transition between the years with estimates. Although this reduces the validity of the test, it was pursued because the natural rate is believed to move gradually, and thus interpolation seemed a fair method of replicating this. For this section, since the unemployment gap was being measured by regressing Unemployment minus NAIRU (U-NAIRU) on Inflation, it was possible to carry out both an aggregate cross-section regression and an individual country regression. This is because using the unemployment gap accounts for differing positions of NAIRU values for each respective country.

The countries chosen for the analyses had to meet three criteria:

- They are in the OECD, and thus highly industrialised

- They had to have their NAIRU value estimated

- Countries with the majority of inflation values above 20% were ignored since this study is concerned with observing what occurs under low inflation values.

As a result, the countries analysed were: Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Greece, Italy, Ireland, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom (UK), and United States of America (US).

Data Description

Tables II.1 and II.2 represent a summary of the data used in this study, and are complemented by Figures A.1 and A.2 in the appendix which are time series line graphs showing the unemployment and inflation experiences of each country.

Table II.1

Table II.2

The data has been split into the subsamples representing the two periods studied in order to analyse average changes. Of notable interest is the lower inflation mean for the period 1993-2004, falling from 6.76 in 1980-1992 to 2.25. This can be largely attributed to the increasing devotion that policy makers have paid toward maintaining low and stable inflation, especially with many of these countries switching to inflation targeting and/or central bank independence in the 1990’s, starting with New Zealand in 1989. In addition to a significantly reduced mean, the mean variance of inflation has also dropped for these countries. This solidifies the proposition that lower average inflation is accompanied by lower inflation volatility.

There has been less movement in the unemployment data between the two periods, with aggregate average unemployment rising very little from 7.64 to 7.74. Whilst this aggregate suggests little movement, it is slightly misleading given that some countries experienced significant falls and others experienced significant increases of unemployment. Australia, Belgium, Portugal, New Zealand, Canada, Denmark, Ireland, Netherlands, UK and US have experienced a fall in average unemployment, with the latter six experiencing a fall of more than 1%. Even small changes of average unemployment should be considered important because these subsamples cover twelve years each, and thus the differences between the periods are unlikely to be of a cyclical nature, but rather a change of structural unemployment. The other countries suffered increases of average unemployment, particularly dramatic are the increases of at least 3% for Finland, Greece, Sweden and Switzerland. Little can be said of the changing variance of unemployment (rising from 3.02 to 4.31), except that 1993-2004 experienced a slightly larger fluctuation of unemployment rates.