This study investigates the determinants of medium-term revenue forecast errors across eight developed countries: the United States, the United Kingdom, Germany, Ireland, Hong Kong, New Zealand, Australia, and Canada. By examining two- and three-year revenue forecasts, this study applies the Kenneth Holden–David Peel test to identify forecast biases and employs panel regression models to assess the economic factors influencing forecast accuracy. The findings indicate that inflation, GDP growth, and budget balance rules are positively associated with forecast errors, whereas unemployment, population growth, and the number of fiscal rules mitigate these errors. Panel estimates reveal that fiscal structure-related variables are not only statistically significant but also economically meaningful determinants of medium-term revenue forecast errors. The results underscore the persistent challenges in achieving accurate revenue forecasts and highlight the necessity for improved forecasting methodologies to enhance fiscal policy effectiveness and resource allocation. Strengthening forecasting frameworks can contribute to more reliable revenue projections, reducing fiscal uncertainty and supporting sound economic decision making.
Kara et al. (Sun,) studied this question.
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