Hussain, Anwar Hussain and Farid, Asif Farid and Hussain, Shah Hussain and Iqbal, Sajid Iqbal (2011): The Future of Budgetary Allocation to Sports Sector in Pakistan: Evidences from Autoregressive Integrated Moving Average Model. Published in: Journal of Managerial Sciences , Vol. 5, No. 2 (2011): pp. 111-124.
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Abstract
The study forecast Public Sector Development Program (PSDP) allocation to sports sector upto 2020 in Pakistan, utilizing time series secondary data ranging from 1988 to 2010, taken from official documents of the Ministry of Sports, Islamabad. For the analysis of the data, descriptive statistics and Autoregressive Integrated Moving Average (ARIMA) model has been applied. The findings revealed that there existed extreme fluctuations in these allocations during 1988-2010, showing uncertainty in these allocations. Further, the allocation to sports sector in PSDP will be Rs.120.082 million, Rs.124.113 million, Rs.128.349 million and Rs.134.711 million in 2013, 2015, 2017 and 2020 respectively. It is recommended that there should be a sustained growth in these allocations so as to remove the uncertainty component. There should be public private partnership in the sports sector of Pakistan which will not only improve the projects life in sports sector but will also add to incurring operation and maintaining costs of the schemes after its construction.
Item Type: | MPRA Paper |
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Original Title: | The Future of Budgetary Allocation to Sports Sector in Pakistan: Evidences from Autoregressive Integrated Moving Average Model |
English Title: | The Future of Budgetary Allocation to Sports Sector in Pakistan: Evidences from Autoregressive Integrated Moving Average Model |
Language: | English |
Keywords: | Budgetary Allocation, Sports Sector, Autoregressive Integrated Moving Average Model |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes |
Item ID: | 41979 |
Depositing User: | ANWAR HUSSAIN |
Date Deposited: | 22 Oct 2012 13:07 |
Last Modified: | 28 Sep 2019 16:52 |
References: | Avīze, N. R. (2010). Cutting sports expenditures worsens quality of life. Retrieved from http://www.eurotopics.net/en/archiv/results/archiv_article/ARTICLE71129-Cutting-sports-expenditures-worsens-quality-of-life on June 8, 2010. Baade, R. A. (2003). Evaluating Subsidies for Professional Sports in the United States and Europe: A Public-Sector Primer. Oxford university press. 19(4): 585-597. Bairner A. (2009). Sports, Intellectuals and Public Sociology Obstacles and Opportunities. International Review for the Society of Sports. 44:115-130. Barclay, J. (2009). Predicting The Costs And Benefits Of Mega-Sporting Events: Misjudgment Of Olympic Proportions? Economic Affairs. 29(2): 62–66. Box, G. and Jenkins, G. (1970). Time series analysis: Forecasting and control, San Francisco: Holden-Day. Brandt, J.A and D.A. Besslet (1981). Composite forecasting: An application with U.S. hog prices. American Journal of Agriculture Economics. 63(1): 135-140. Dickey, D. A. and Pantula, S. (1987). Determining the Order of Differencing in Autoregressive Processes, Journal of Business and Economic Statistics. 5: 455-61. Diebold, F.X. (2001) Elements of Forecasting. Thomson Learning, Australia. Dielman, T. E. (1986). A Comparison of Forecasts from Least Absolute Value and Least Squares Regression, Journal of Forecasting. 5: 189-95. Dimitrov, D., C. Helmmenstein, A. Kleissner, B. Moser, J. Schindler.(2006). Die makrookonomischen Effekte des Sports in Europa, Study im Auftrag des Bundeskanzleramts, Sektion Sports, Wein. Dougherty, C. (1992). Introduction to Econometrics, Oxford University Press, Oxford. Economic Research Service, USDA. Retrieved from http://www.ers.usda.gov/Briefing/wheat/wheatsupplyuse.htmOn May 18, 2010. European Commission Brussele (2007). White Paper on Sports, present by the European Commission. Retrieved from http://ec.europa/sport/white-paper/whitepaper8_en.htm on January 14, 2011. Friedman,M. T and D. L. Andrews. (2011). The Built Sport Spectacle and the Opacity Of Democracy. International Review for the Sociology of Sport.46(2): 181-204. Gujarati, D.N. and Dawn C. P. (2009). Basic Econometrics. Intl. McGraw-Hill. Jagemann H. (2003). Sports and Environment: Ways Towards Achieving the Sustainable Development of Sp[orts.Conference by the 4th Pierre de Coubertin School Forum Arenzano (MUVITA). Malcolm, O. N. (2003). Tourism Maturity and Demand: Jamaica. Work paper, Research Services Department, Research and Economic Programming Division, Bank of Jamaica. Molina, A. R E. A. M. Arroyave and R. J. M. Callejas. (2010). The Economic Salience of Sports inColombia: A Satellite Accounts Methodology. Lecturas de Economía. 72: 141-168. Nachane, D. M. (2006). Econometrics Theoretical Foundations And Empirical Perspectives. Oxford university press, New Delhi. Pierre de Coubertin (1863-1937), French Pedagogue and Historian, Founder of the Modern Olympic Games. Pindyck, R. S. and D. L. Rubefeild. (1981). Econometric Models and Economic Forecasts. McGraw-Hill Inc. Schwarz, G. (1978). Estimating the Dimension of a Model, Annals of Statistics 6: 461-4. Siegfried, J.and A. Zimbalist(2002). A Note on the Local Economic Impact of Sports Expenditures. Journal of Sports Economics. 3(4): 361-366. Studenmund, A. H. and H. J. Cassidy (1987). USINF Econometrics: A Practical Guide. Little, Brown and Company, Toranto. Stock, J. H. and Watson, M. W. (2006). Introduction to Econometrics 2nd edn., Addison Wesley Upper Saddle River, NJ. Syed, Z. H. (January 2011). Review of sports year 2010-VI. The News |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/41979 |