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Government Revenue Forecasting in Nepal

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  • T. P. Koirala Ph.D.

    ()
    (Nepal Rastra Bank)

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    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.

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    File URL: http://www.nrb.org.np/ecorev/pdffiles/vol24-2_art4.pdf
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    Bibliographic Info

    Article provided by Nepal Rastra Bank, Research Department in its journal NRB Economic Review.

    Volume (Year): 24 (2012)
    Issue (Month): 2 (October)
    Pages: 47-60

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    Handle: RePEc:nrb:journl:v:24:y:2012:i:2:p:47-60

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    Related research

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

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    1. Annette Kyobe & Stephan Danninger, 2005. "Revenue Forecasting," IMF Working Papers 05/24, International Monetary Fund.
    2. Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
    3. Auerbach, Alan J., 1999. "On the Performance and Use of Government Revenue Forecasts," National Tax Journal, National Tax Association, vol. 52(n. 4), pages 765-82, December.
    4. Stephan Danninger, 2005. "Revenue Forecasts As Performance Targets," IMF Working Papers 05/14, International Monetary Fund.
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