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Short-Term Fiscal Projections Using Forecast Combination Approach

Author

Listed:
  • Roman S. Leukhin

    (Economic Expert Group, Moscow 109012, Russia; Financial Research Institute, Moscow 127006, Russian Federation)

Abstract

In this paper the author compares a number of methods to forecast corporate income tax revenues in the next quarter: autoregressive integrated moving average, exponential smoothing, linear regression, naïve forecast, and combination approaches. Results show that the increase of the time period for the next quarter forecast error calculation leads to the increase of errors for individual models and arithmetic mean, and the decrease for combination approaches which consider forecast errors in previous periods. Linear regression with the MOEX Russia Index as explanatory variable provides the lowest error for the next quarter forecast for 5- and 10-quarter periods. The forecast combination approach, what takes into account the forecast error in previous 4 quarters, provides the best result for a period of 15 quarters, what is explained by diversification of forecast errors. This method can be successfully used for corporate income tax revenue projections and possibly for other budget revenues.

Suggested Citation

  • Roman S. Leukhin, 2019. "Short-Term Fiscal Projections Using Forecast Combination Approach," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 9-21, June.
    • Handle: RePEc:fru:finjrn:190301:p:9-21
    DOI: 10.31107/2075-1990-2019-3-9-21
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    References listed on IDEAS

    as
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    4. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    fiscal forecast; forecast combination; forecast accuracy; tax revenues; corporate income tax;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • H20 - Public Economics - - Taxation, Subsidies, and Revenue - - - General

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