Modeling and forecasting of Saudi Arabia revenue and expenditure data

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dc.contributor.advisor Rahamataullaha Imana, E. Eica. Ema.
dc.contributor.author Alrweili, Hleil Aed
dc.date.accessioned 2015-05-14T12:24:59Z
dc.date.available 2015-05-14T12:24:59Z
dc.date.issued 2015-05-02
dc.identifier.uri http://cardinalscholar.bsu.edu/handle/123456789/199544
dc.description.abstract Saudi Arabia is one of the richest countries in the world, but its economy heavily depends on oil. In my research my prime objective was to predict the expenditure pattern of Saudi Arabia in terms of oil and total revenue. We considered six variables here. Current, capital and total expenditure are considered as response and oil, other and total revenue are considered as explanatory variables. This can be done by regression method. The commonly used least squares method heavily depends on normality and other standard assumptions. For this reason we consider distribution free nonparametric and robust regression methods. Since this is a time series data this prediction can also be done using ARIMA models. In our study we evaluate the prediction obtained by different regression and time series methods (OLS from classical regression, LMS from robust regression, LOWESS from nonparametric regression and AR(1) from ARIMA time series models) by cross validation technique. Our results suggest that current, capital and total expenditure of Saudi Arabia can be predicted in the best possible way when we consider the oil revenue/total revenue as the predictor and use the nonparametric LOWESS method to generate forecasts. en_US
dc.description.sponsorship Department of Mathematical Sciences
dc.description.tableofcontents Modeling and fitting of data using classical, robust and nonparametric regression methods -- Forecasting with ARIMA models -- Evaulation of forecasts by regression and time series methods using cross validation.
dc.subject.lcsh Revenue -- Saudi Arabia -- Mathematical models.
dc.subject.lcsh Tax revenue estimating -- Saudi Arabia.
dc.subject.lcsh Box-Jenkins forecasting.
dc.subject.other Saudi Arabia -- Appropriations and expenditures -- Mathematical models.
dc.subject.other Saudi Arabia -- Appropriations and expenditures -- Forecasting.
dc.title Modeling and forecasting of Saudi Arabia revenue and expenditure data en_US
dc.description.degree Thesis (M.S.) en_US
dc.identifier.cardcat-url http://liblink.bsu.edu/catkey/1784569


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  • Master's Theses [5293]
    Master's theses submitted to the Graduate School by Ball State University master's degree candidates in partial fulfillment of degree requirements.

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