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The authors are Assistant Professor of Finance, Faculty of Management, McGill University, Montreal, and Deputy Division Chief, European I Department, respectively. The paper builds on earlier work by Mark Griffiths. The authors would like to thank Carlo Cottarelli, Peter Doyle, Malcolm Knight, Dan Nyberg, and Robert Sierhej for helpful comments. They would also like to thank Witold Skrok for providing the data on administered prices and David Maxwell for research assistance. Any remaining errors are the authors’ responsibility.
In fact, Wozniak (1998), using a modeling framework suggested by Ball and Mankiw, has estimated that the large administered price increases associated with transition in Poland produced substantial upward inflationary pressures between 1989 and 1997. Pujol and Griffiths (1996) also find evidence of this effect.
The last panel in Figure 3 depicts an index of the thirteen government affected goods and service prices weighted together by their respective weights in the CPI (and rebased).
In the past, headline and underlying inflation have differed in transition economies both in the short-run and over longer periods of time, so focusing on underlying inflation as a policy target would have been difficult. As administered prices, excise tax rates, etc., approach world prices and rates, it is likely that the two inflation concepts will move more together in the future. This should allow underlying inflation to play a more important policy target role.
The McNeilly and Schiesser-Gachnang (1998) approach raises the issue of rebalancing in the case of trimmed-weighted means. In the standard trimmed-means case the rebalancing simply consists of dividing by N-T instead of N. But when working with weighted means the trimming needs to consider whether trimming should be done with respect to number of observations (probability mass) or weighted number of observations (weighted probability mass). As an example, should one remove 4 out of 16 observations (categories) each time—or rather 25 percent of the weights? In either case the new mean must be properly rebalanced. McNeilly and Schiesser-Gachnang remove 4 categories in each month but do not seem to rebalance the index for reasons that are not clear.
Not surprisingly, the different inflation measures are quite correlated. Headline CPI is most highly correlated with the 20 percent trimmed inflation (0.90), followed by median inflation (0.83), and lastly, private-sector inflation (0.76).
These outliers reflects a change of government at the time and large expected changes in administered prices.
This is probably because both the unemployment rate and CPI inflation in Poland have been falling monotonically for most of the 1990s and labor markets have not yet reached equilibrium.
When the unemployment rate (lur) was added to the four multivariate models of inflation (one for each of the four definitions of inflation), it always entered with an economically nonsensical positive coefficient
These out-of-sample forecasts were produced using the “chain” method, whereby the VAR equations for each right-hand-side variable are used to produce period ahead forecasts, which then are used to produce forecasts of the relevant left-hand side inflation measure. That is, the methodology assumes no additional information beyond what was known at the start of the out-of-sample forecast period (i.e., June 1997).