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An Analysis of Tax Revenue Forecast Errors - WP 07/02

1  Background

In each of the last three years, the New Zealand Treasury has published a report analysing the performance of its macroeconomic, tax and fiscal forecasts. These reports can be found at In particular, Treasury forecasts have persistently underestimated actual tax flows over the past six years. Why this should be and what the sources of error are, form the background for this study where the primary objectives are to better determine the major sources of tax revenue forecast errors and to identify the potential for methodological improvements.

The study builds on and complements Schoefisch (2005) which focussed on the Treasury's general tax forecasting methods and processes rather than specific forecasting models and methodology. Schoefisch (2005) noted that a study (Mühleisen, Danninger, Hauner, Krajnyák, and Sutton, 2005) published by the International Monetary Fund (IMF) showed that the Treasury's tax forecasting performance compared well with the performances of government agencies in other countries over the period 1995 to 2003. It would seem that New Zealand is not unique in terms of persistent underestimation of tax, and we are aware of similar reviews undertaken in Australia, Canada and the United Kingdom that also address these issues. Some of these reviews have not yet been published, but others have, including O'Neill (2005) which reviews Canadian federal fiscal forecasting. In general, the literature on tax forecasting seems to be sparse and largely the preserve of official government agencies or organisations such as the IMF. In addition to those already cited, some relatively recent examples of this literature are Basu, Emmerson and Frayne (2003), who examine United Kingdom corporate tax forecasts by the Institute for Fiscal Studies, London, and Rich, Bram, Haughwout, Orr, Rosen and Sela (2005) who use regional economic indices to forecast tax revenues for New York. Further publications are listed in the references of the publications already mentioned.

The Treasury's tax forecasts are based on rating up past tax revenues by growth rates in related macroeconomic variables such as gross domestic product (GDP) which also need to be forecast. Included in the 2003 and 2004 forecast performance reports was an attempt to disaggregate each one-year-ahead Budget total tax forecasting error into a macroeconomic component and a tax component. Separating out the two sources of forecast error allows one to test the proposition that the tax forecasts might still be too low even in the case of a perfect macroeconomic forecast. For total tax, part of the forecast error was attributed to errors in the forecasts of nominal GDP, with the remaining portion being attributed to the tax forecasting process. In both the 2003 and 2004 analyses, there was insufficient evidence to determine whether the proposition was true.

Nevertheless, these analyses suggested that errors in nominal GDP forecasts were making a considerable contribution to errors in the tax forecasts. However, the Treasury does not explicitly use nominal GDP to forecast total tax. Rather, forecasts of various macroeconomic variables are used to forecast each of the component tax types and the forecasts of the tax types are then aggregated into a total tax forecast.

Schoefisch (2005) noted these earlier attempts to split the tax forecast errors into macroeconomic and tax components and recommended that resources should be directed towards analysing the relative contributions of macroeconomic and tax errors to the total tax error for the various tax types (PAYE, GST, company tax, etc). This is a primary objective of the analysis presented in this report.

A review of the Treasury's tax forecasting processes and methods is given in Section 2 and a general class of models is proposed in Section 3 that encompasses these methods. In Section 4, one of the simplest of these models is adopted as a benchmark model where tax revenue is expressed as a product of a tax ratio and a suitable macroeconomic variable that can be regarded as a proxy for the tax base. Using this model, expressions for suitable forecast error decompositions are also derived. Individual tax revenue forecast errors are first decomposed into component errors due to forecasting the underlying macroeconomic driver used as the tax-base proxy, and a component due to forecasting the tax ratio. The tax ratio is then further disaggregated into a component error due to forecasting the tax ratio trend and random error. The latter provides a measure of the best accuracy that can be achieved using the benchmark models adopted.

Using these decompositions, an analysis was undertaken of historical data from 1995 to 2005 where a discussion of the data and adjustments applied is given in Section 5. Results and discussion of the analysis are given in Section 6 with conclusions presented in Section 7. As noted by Schoefisch (2005), the overriding purpose of this analysis is to enhance the understanding of key deficiencies in forecast performance and provide a base for other research projects designed to improve forecast quality.

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