A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU)

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dc.contributor.advisorVan Walbeek, Corneen_ZA
dc.contributor.advisorSimons, Maryen_ZA
dc.contributor.authorDurham, Kate Saranneen_ZA
dc.date.accessioned2014-09-15T07:26:50Z
dc.date.available2014-09-15T07:26:50Z
dc.date.issued2007en_ZA
dc.descriptionIncludes bibliographical references (p. 69-73).en_ZA
dc.description.abstractThis thesis draws attention to the complexities involved in forecasting economic indicators. A literature review examines the general use of forecasts, errors within forecasts and various methods of analysing the accuracy of forecasts. The focus of this paper is on the testing and measuring of forecast accuracy within the Economist Intelligence Unit Country Forecasts, in particular the forecast accuracy of GOP and Inflation. This is carried out through the assessment of four a priori hypotheses 1) High Income Country Forecasts are consistently more accurate than those forecasts made for countries in the Low Income Category. 2) The accuracy of forecasts decreases the more distant the forecast horizon becomes, therefore Current-Year (t) Forecasts will outperform One-Year-Ahead (t+1) Forecasts. 3) The EIU Forecasts outperform No-Change-Forecasts as measured by the Theil's U-Statistic. 4) The EIU can forecast turning points better than a Random Probability method of forecasting can. The Tests used to evaluate the above hypotheses are the Root Mean Squared Error (RMSE), Theil U-Statistic and Turning Point Directional Analysis. The conclusion reached by this thesis is that the accuracy of forecasts decreases the more distant the forecast horizon becomes, therefore it can be said that Current-Year (t) Forecasts will outperform One-Year-Ahead (t+1) Forecasts. Additionally, the EIU Forecasts do outperform No-Change-Forecasts as measured by the Theil's U-Statistic. Therefore the EIU can forecast turning points better than a Random Probability method of forecasting can. Finally, this thesis concludes that there is little evidence to suggest that High Income Country Forecasts are consistently more accurate than those forecasts made for countries in the Low Income Category.en_ZA
dc.identifier.apacitationDurham, K. S. (2007). <i>A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU)</i>. (Thesis). University of Cape Town ,Faculty of Humanities ,Department of Political Studies. Retrieved from http://hdl.handle.net/11427/7466en_ZA
dc.identifier.chicagocitationDurham, Kate Saranne. <i>"A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU)."</i> Thesis., University of Cape Town ,Faculty of Humanities ,Department of Political Studies, 2007. http://hdl.handle.net/11427/7466en_ZA
dc.identifier.citationDurham, K. 2007. A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU). University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Durham, Kate Saranne AB - This thesis draws attention to the complexities involved in forecasting economic indicators. A literature review examines the general use of forecasts, errors within forecasts and various methods of analysing the accuracy of forecasts. The focus of this paper is on the testing and measuring of forecast accuracy within the Economist Intelligence Unit Country Forecasts, in particular the forecast accuracy of GOP and Inflation. This is carried out through the assessment of four a priori hypotheses 1) High Income Country Forecasts are consistently more accurate than those forecasts made for countries in the Low Income Category. 2) The accuracy of forecasts decreases the more distant the forecast horizon becomes, therefore Current-Year (t) Forecasts will outperform One-Year-Ahead (t+1) Forecasts. 3) The EIU Forecasts outperform No-Change-Forecasts as measured by the Theil's U-Statistic. 4) The EIU can forecast turning points better than a Random Probability method of forecasting can. The Tests used to evaluate the above hypotheses are the Root Mean Squared Error (RMSE), Theil U-Statistic and Turning Point Directional Analysis. The conclusion reached by this thesis is that the accuracy of forecasts decreases the more distant the forecast horizon becomes, therefore it can be said that Current-Year (t) Forecasts will outperform One-Year-Ahead (t+1) Forecasts. Additionally, the EIU Forecasts do outperform No-Change-Forecasts as measured by the Theil's U-Statistic. Therefore the EIU can forecast turning points better than a Random Probability method of forecasting can. Finally, this thesis concludes that there is little evidence to suggest that High Income Country Forecasts are consistently more accurate than those forecasts made for countries in the Low Income Category. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU) TI - A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU) UR - http://hdl.handle.net/11427/7466 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/7466
dc.identifier.vancouvercitationDurham KS. A critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU). [Thesis]. University of Cape Town ,Faculty of Humanities ,Department of Political Studies, 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/7466en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Political Studiesen_ZA
dc.publisher.facultyFaculty of Humanitiesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherPolitics, Philosophy and Economicsen_ZA
dc.titleA critical analysis of the accuracy of the country forecasts as prepared by the Economist Intelligence Unit (EIU)en_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMPhilen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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