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dc.contributor.advisor Piyatilake, ITS
dc.contributor.author Karunarathne, AWSP
dc.date.accessioned 2024-08-08T05:45:16Z
dc.date.available 2024-08-08T05:45:16Z
dc.date.issued 2023
dc.identifier.citation Karunarathne, A.W.S.P. (2023). Modelineg Sri Lankan GDP using macroeconomic indicators [Master’s theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/22636
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22636
dc.description.abstract Economics mainly divided into two parts, namely microeconomics and macroeconomics. Microeconomics study the individuals and business decisions while macroeconomics look at the decisions of county and government. That is, macroeconomics helps to understand the economy as a whole. Macroeconomic indicators are the key reflectors of the economic status of a country. Therefore, macroeconomic indicators have a notable role in sustaining the economic sustainable growth of a country. This study aimed at analyzing the relationships between macroeconomic indicators and the economic growth of Sri Lanka. Nineteen macroeconomic indicators were extracted from the Central Bank of Sri Lanka reports. The data were collected for the period of 1976-2018 from the World Bank website. This research mainly uses principal component analysis (PCA) in determining the existing patterns/similarities between the selected macroeconomic indicators. PCA method is specially applied because the selected macroeconomic variables were highly correlated. Forward regression analysis has been carried out to fit models with the use of identified principal components to determine the most prominent macroeconomic indicators which impact on Gross Domestic Product (GDP) and to identify the most reliable indicators which has the highest predictive power on GDP. The extracted two principal components (PCs) highly resemble the government activities and the human capital involved with the economy respectively. GDP can be predicted using the above said two PCs with a R-squared value of 99.74% which shows a high reliable predictive power. As this study focuses on large number of macroeconomic indicators it is very much essential in identifying the most prominent indicators among them. Therefore, as a novel concept Grey Relational Analysis (GRA) was constructed in ranking the selected macroeconomic indicators. Inflation, official exchange rate, and exports of goods and services have taken the first three rankings respectively, indicating that the government and responsible parties should pay more attention to avoid future economic recessions and to develop a sustainable economy. en_US
dc.language.iso en en_US
dc.subject MACROECONOMIC INDICATORS en_US
dc.subject PCA en_US
dc.subject FORWARD REGRESSION ANALYSIS en_US
dc.subject GREY RELATIONAL ANALYSIS en_US
dc.subject MATHEMATICS- Dissertation en_US
dc.subject FINANCIAL MATHEMATICS - Dissertation en_US
dc.title Modelineg Sri Lankan GDP using macroeconomic indicators en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MSc in Financial Mathematics en_US
dc.identifier.department Department of Mathematics en_US
dc.date.accept 2023
dc.identifier.accno TH5221 en_US


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