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Government Revenue Forecasting in Nepal

Author

Listed:
  • T. P. Koirala Ph.D.

    () (Nepal Rastra Bank)

Abstract

This paper attempts to identify appropriate methods for government revenues forecasting based on time series forecasting. I have utilized level data of monthly revenue series including 192 observations starting from 1997 to 2012 for the analysis. Among the five competitive methods under scrutiny, Winter method and Seasonal ARIMA method are found in tracking the actual Data Generating Process (DGP) of monthly revenue series of the government of Nepal. Out of two selected methods, seasonal ARIMA method albeit superior in terms of minimum MPE and MAPE criteria. However, the results of forecasted revenues in this paper may vary depending on the application of more sophisticated methods of forecasting which capture cyclical components of the revenue series. The prevailing forecasting method based particularly on growth rate method extended with discretionary adjustment of a number of updated assumptions and personal judgment can create uncertainty in revenue forecasting practice. Therefore, the methods recommended here in this paper help in reducing forecasting error of the government revenue in Nepal.

Suggested Citation

  • T. P. Koirala Ph.D., 2012. "Government Revenue Forecasting in Nepal," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 24(2), pages 47-60, October.
  • Handle: RePEc:nrb:journl:v:24:y:2012:i:2:p:47-60
    as

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    File URL: http://www.nrb.org.np/ecorev/pdffiles/vol24-2_art4.pdf
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    References listed on IDEAS

    as
    1. Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
    2. Auerbach, Alan J., 1999. "On the Performance and Use of Government Revenue Forecasts," National Tax Journal, National Tax Association;National Tax Journal, vol. 52(4), pages 765-782, December.
    3. Stephan Danninger, 2005. "Revenue Forecasts as Performance Targets," IMF Working Papers 05/14, International Monetary Fund.
    4. Annette J Kyobe & Stephan Danninger, 2005. "Revenue Forecasting—How is it done? Results from a Survey of Low-Income Countries," IMF Working Papers 05/24, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Data generating process; forecast bias; seasonal pattern; under-or-over estimationh; government revenue; seasonality;

    JEL classification:

    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • O23 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Fiscal and Monetary Policy in Development

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