The Uncertainty Evaluation of Tax Revenue Forecast in Iran, Using Fan Chart

Document Type : Original Article

Authors

Economic and Administrative Faculty, University of Mazandaran, Babolsar, Iran

Abstract

In this research, we tried to analyze the forecast error of the tax revenue forecasting in Iran using the Fan chart method. In this regard, using data during the period of 1974-2016 and Bayesian linear regression model, Iran’s tax revenue be forecasted and its uncertainty is derived from uncertainty in correlated macroeconomic variables. Internalizing subjective assessments of the macro variables, the tax revenue forecast skewness be obtained. In most cases, the uncertainty of macro variables’ are based on their historical standard deviation. However, in the present study, we allow the uncertainty of macro variables to be adjusted subjectively, if there is a reason to be less or more uncertain than their historical standard deviations. A subjective balance of risk assessment, that whether the distributions are symmetric or non symmetric, is also used. The results show that the fan chart method has high efficiency in depicting the forecast uncertainty of tax revenue and can be used in the budget preparation and Formulation in Iran.

Keywords

References

Akhbari, M., (2009). Extracting Uncertainty Bands (Fan Charts) of Inflation Forecasts in 2007, Economic Research and Policy Department, Central Bank of the Islamic Republic of Iran.
Allan, C. M., (1965).Fiscal Marksmanship 1951-63. Oxford Economic Papers, 17(2): 317-327.
Arbabian, S, Ghasemy M. R., Vafaei V., (2012). Investigation Budgetary Forecast Error in Iran during (1965-2008). Economic Development Research. 2 (7): 51-68.
Asher, M. G., (1978). Accuracy of Budgetary Forecasts of Central Government, 1967-68 to 1975-76. Economic and Political Weekly, 13(8): 423-432.
Babaei, H., (1999). Government Budgeting in Iran (from theory to policiy), The Commerce Printing & Publishing Company.
Bhattacharya, B. B., Kumari, A., (1988). Budget Forecasts of Central Government Revenue and Expenditure: A Test of Rational Expectation. Economic and Political weekly, 23(26): 1323-1327.
 Blix, M., (1998). Forecasting Swedish Inflation with a Markov Switching VAR", Working Paper No. 65, SverigesRiksbank.
Blix, M., Sellin, P., (1998).Uncertainty Bands for Inflation Forecasts, Mimeo, SverigesRiksbank.
Boyd, D. J., Dadayan, L., (2014). State Tax Revenue Forecasting Accuracy.The Public Policy Research Arm of the State University of New York, Revenue Forecasting, September.19 (2): 122- 143.
Camilleri, G., Vella, K., (2015). Interpolating Forecast Errors for Assessing Uncertainty in Macroeconomic Forecasts: An Analysis for Malta.Economic Policy Department, 18(1): 122-136.
Chakrabarty, T. K., Varghese, W., (1982). Government of India's Budget Estimation: An Analysis of the Error Components. RBI Occasional Papers, 175-190.
Chakraborty, L, S., Sinha, D., (2008). Budgetary Forecasting in India: Partitioning Errors and Testing for Rational Expectations. MPRA Paper, University Library of Munich, Germany, 7538.
Cogley, T., Morozov, S., Sargent, T. J., (2005). Bayesian Fan Charts for U.K. Inflation: Forecasting and Sources of Uncertainty in an Evolving Monetary System, Journal of Economic Dynamics and Control, 29: 1893-1925.
Cornec, M. (2010). Constructing a conditional GDP fan chart with an application to French business survey data. 30th CIRET Conference, New York.
Cronin, D., Dowd, K., (2013). Fiscal Fan Charts: A Tool for Assessing Member States'(Likely?) Compliance with EU Fiscal Rules.Fiscal Studies, 34(4): 517-534.
Davis, J. M., 1980. Fiscal Marksmanship in the United Kingdom, 1951–78.The Manchester School, 48(2): 187-202.
Glosov, M., King, J., (2002).Tax Revenue Forecasts in IMF-Supported Programs.IMF Working Paper, 2: 236-252.
Henry, J., De Cos, P. H., Momigliano, S., (2008). The Impact of Government Budgets on Prices: Evidence from Macroeconometric Models. Journal of Policy Modeling, 30(1), 123-143.
John, S., (1982). The Three-parameter Two-piece Normal Family of Distributions and its Fitting”, Communications in Statistical Theory and Methods, 11(8): 879-885.
Julio, J, M., (2006). The Fan Chart: The Technical Details of the New Implementation. Borradores de Economia, No. 468.
Lawrence, M. J., Edmundson, R. H., O’Connor, M. J., (1985). An Examination of the Accuracy of Judgemental Extrapolation of Time Series, International Journal of Forecasting 1:14-25.
Mihaela, Simionescu, (2014). Fan chart or Monte Carlo simulations for assessing the uncertainty of inflation forecasts in Romania?, Economic Research, 27(1): 629–644.
Mihaela, Simionescu., (2014). Fan chart or Monte Carlo simulations for assessing the uncertainty of inflation forecasts in Romania?, Economic Research-EkonomskaIstraživanja, 27:1, 629-644, DOI: 10.1080/1331677X.2014. 970453
 Mitchell, J., Hall, S. G., (2005). Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’Charts of Inflation.Oxford Bulletin of Economics and Statistics, 67(s1): 995-1033.
Novo, A., Pinheiro, M., (2003).Uncertainty and Risk Analysis of Macroeconomic Forecasts: Fan Charts Revisited.Banco de Portugal, Economic Research Department.18(2), 43- 65.
Plesko, G. A., (1988). The Accuracy of Government Forecasts and Budget Projections.National Tax Journal, 41(4): 483-501.
Sanders, N. R., Ritzman, L. P., (1999).Judgemental Adjustments of Statistical Forecasts. In: Armstrong, J. S. (ed), Principles of Forecasting. Kluwer Academic Publishers, Norwell.
Sen Gupta, A., (2007). Determinants of Tax Revenue Efforts in Developing Countries.IMF Working Papers, 1-39.
Simionescu, M., (2015). The Accuracy of General Government Balance Forecasts In Romania. CES Working Papers, (1): 167-178.
Tay, A, S., Wallis, K, F., (2000). Density Forecasting: A Survey. Journal of Forecasting, 19: 235- 254.
International Journal of New Political Economy
Volume 1, Issue 1 - Serial Number 1
January 2020
Pages 44-56

Files

History

  • Receive Date: 12 May 2019
  • Accept Date: 26 August 2019
  • First Publish Date: 01 January 2020

Share

How to cite

Statistics