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Stochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysis

dc.contributor.authorYasar, Nermin
dc.contributor.authorID230528tr_TR
dc.date.accessioned2024-04-25T07:32:34Z
dc.date.available2024-04-25T07:32:34Z
dc.date.issued2021
dc.departmentÇankaya Üniversitesi, Meslek Yüksek Okulu, Dış Ticaret Bölümüen_US
dc.description.abstractThis paper analyses the stochastic pattern of health care spending for 188 countries around the world which are categorized into four groups based on the World Bank income categories. The main motivation of this ar-ticle is to evaluate whether the stochastic features of total health care expenditure varies if decomposed into private and public health care consumption. To achieve this goal, in addition to conventional empirical methods, latterly de-veloped panel stationarity approaches are employed for both linear and nonlinear regression processes. Our results demonstrate that allowing for cross-section dependency between series and nonlinearity in the estimation process may lead to more often rejection of the null hypothesis of unit root for all series in panel data set.en_US
dc.identifier.citationYasar, N. (2021). "Stochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysis", Review of Economics and Finance, Vol.19, pp.264-270.en_US
dc.identifier.doi10.55365/1923.X2021.19.27
dc.identifier.endpage270en_US
dc.identifier.issn19237529
dc.identifier.startpage264en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12416/7932
dc.identifier.volume19en_US
dc.language.isoenen_US
dc.relation.ispartofReview of Economics and Financeen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectHealth Care Consumptionen_US
dc.subjectHeterogeneous Panel Unit Rooten_US
dc.subjectNonlinearityen_US
dc.subjectPanel Cross Section Dependenceen_US
dc.subjectPanel Unit Root Testen_US
dc.titleStochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysistr_TR
dc.titleStochastic Pattern of Health Care Spending: Evidence From Nonlinear Panel Data Analysisen_US
dc.typeArticleen_US
dspace.entity.typePublication

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