Government tax revenue, expenditure, and debt in sri lanka: A vector autoregressive model analysis

dc.contributor.authorUthayakumar, S.S.
dc.contributor.authorSelvamalai, T.
dc.date.accessioned2022-01-21T06:03:32Z
dc.date.accessioned2022-06-29T07:16:44Z
dc.date.available2022-01-21T06:03:32Z
dc.date.available2022-06-29T07:16:44Z
dc.date.issued2016
dc.description.abstractThe study has applied Vector Autoregressive (VAR) Model of times series econometric techniques to examine the relationship between government tax revenue, expenditure and debt in Sri Lanka from 1950 to 2015. The data were gathered from Annual Report of Central Bank of Sri Lanka, 2015. The study was found several interesting results. Results of variance decomposition analysis concluded that impact of the external shock on forecast error in tax can be negligible but it can be negligible in the case of government expenditure and debt. Further, the impact of the own shock on forecast error in all cases cannot be negligible. The results of impulse response function concluded that responses of the system to standard deviation shock in a single variable were meaning full only in the short-run (up to five periods). The results of Granger Causality test concluded that government tax revenue did Grange cause government expenditure and debt in Sri Lanka not vice versa at 5% significant level. And there was a uni-directional causal relation from government expenditure to debt at 5% significant level. Further, at 10% significant level, there was a bi-directional Granger Causality between government tax revenue and debt in Sri Lanka.en_US
dc.identifier.issn2279-2406
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/5140
dc.language.isoenen_US
dc.publisherUniversity of Jaffnaen_US
dc.subjectTaxen_US
dc.subjectExpenditureen_US
dc.subjectDebten_US
dc.subjectVector autoregressive (VAR) modelen_US
dc.subjectImpulse response functionen_US
dc.titleGovernment tax revenue, expenditure, and debt in sri lanka: A vector autoregressive model analysisen_US
dc.typeArticleen_US

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