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dc.contributor.advisorHanousek, Jan
dc.creatorŽlábková, Dana
dc.date.accessioned2018-10-02T16:54:50Z
dc.date.available2018-10-02T16:54:50Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/20.500.11956/13995
dc.description.abstractThe basic concern of any empirical work is to employ statistical data that correspond to the notion of the theoretical variables in the model. The problems and economic consequences connected with the measurement of selected economic variables are the focus of this thesis. It consists of three chapters that in succession analyze the issues associated with the measurement of economic growth, multi-factor productivity and capital input into production. The first chapter looks into the differences among the growth rates of GDP per capita based on data from the three most commonly used databases, namely International Financial Statistics, World Development Indicators and Penn World Table. Using a wide international dataset, we find significant differences in the growth rates that are mainly due to the adjustment for cross-country comparability of GDP per capita levels. Importantly, these differences are correlated with the level of development. We replicate six recent studies of growth determinants and find their results sensitive to the choice of data. The second chapter analyses the sensitivity of calculated multi-factor productivity (MFP) growth to assumptions of growth accounting, concentrating on the measurement of quantity, composition and the respective shares of labor and capital inputs, and...en_US
dc.languageEnglishcs_CZ
dc.language.isoen_US
dc.publisherUniverzita Karlova, Fakulta sociálních vědcs_CZ
dc.titleMeasurement of Economic Variablesen_US
dc.typedizertační prácecs_CZ
dcterms.created2007
dcterms.dateAccepted2007-09-21
dc.description.departmentCERGEcs_CZ
dc.description.facultyFaculty of Social Sciencesen_US
dc.description.facultyFakulta sociálních vědcs_CZ
dc.identifier.repId175937
dc.contributor.refereevan Ark, Bart
dc.contributor.refereeHanushek, Eric A.
dc.identifier.aleph002068367
thesis.degree.namePh.D.
thesis.degree.leveldoktorskécs_CZ
thesis.degree.disciplineEconomicsen_US
thesis.degree.disciplineEkonomiecs_CZ
thesis.degree.programEkonomické teoriecs_CZ
thesis.degree.programEconomic Theoryen_US
uk.faculty-name.csFakulta sociálních vědcs_CZ
uk.faculty-name.enFaculty of Social Sciencesen_US
uk.faculty-abbr.csFSVcs_CZ
uk.degree-discipline.csEkonomiecs_CZ
uk.degree-discipline.enEconomicsen_US
uk.degree-program.csEkonomické teoriecs_CZ
uk.degree-program.enEconomic Theoryen_US
thesis.grade.csProspěl/acs_CZ
thesis.grade.enPassen_US
uk.abstract.enThe basic concern of any empirical work is to employ statistical data that correspond to the notion of the theoretical variables in the model. The problems and economic consequences connected with the measurement of selected economic variables are the focus of this thesis. It consists of three chapters that in succession analyze the issues associated with the measurement of economic growth, multi-factor productivity and capital input into production. The first chapter looks into the differences among the growth rates of GDP per capita based on data from the three most commonly used databases, namely International Financial Statistics, World Development Indicators and Penn World Table. Using a wide international dataset, we find significant differences in the growth rates that are mainly due to the adjustment for cross-country comparability of GDP per capita levels. Importantly, these differences are correlated with the level of development. We replicate six recent studies of growth determinants and find their results sensitive to the choice of data. The second chapter analyses the sensitivity of calculated multi-factor productivity (MFP) growth to assumptions of growth accounting, concentrating on the measurement of quantity, composition and the respective shares of labor and capital inputs, and...en_US
uk.file-availabilityV
uk.publication.placePrahacs_CZ
uk.grantorUniverzita Karlova, Fakulta sociálních věd, CERGEcs_CZ
thesis.grade.codeP


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