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dc.contributor.authorTsaurai, Kunofiwa
dc.contributor.authorNdou, Adam
dc.date.accessioned2019-04-03T10:08:28Z
dc.date.available2019-04-03T10:08:28Z
dc.date.issued2019
dc.identifier.issn1508-2008
dc.identifier.urihttp://hdl.handle.net/11089/27368
dc.description.abstractThis study investigated the impact of infrastructure and human capital development on economic growth in transitional economies. It also explored whether the interaction between infrastructural and human capital development enhanced economic growth in the transitional economies. Although the literature is awash with studies which investigated the separate impact of infrastructure and human capital development on economic growth, no study that the author is aware of has so far explored whether the interaction between infrastructure and human capital development enhances economic growth. The study mainly used a dynamic panel generalised methods of moments (GMM) approach by Arellano and Bond (1995), a framework that takes into account the dynamic nature of economic growth data and addresses the endogeneity issues normally associated with economic growth regression functions. Panel data analysis approaches such as pooled ordinary least squares (OLS), and fixed and random effects were used for comparison purposes and robustness tests. According to the dynamic GMM framework, the interaction between infrastructure and human capital development improved economic growth in transitional economies, in line with theoretical and empirical predictions. Random effects and pooled OLS show that the interaction between infrastructural and human capital development had a deleterious effect on economic growth, whilst according to the fixed effects approach, the interaction between these two variables had an insignificant positive influence on economic growth in transitional economies. Considering that the results from a dy34 Kunofiwa Tsaurai, Adam Ndou namic panel GMM are considered to be more accurate due to the approach’s ability to address the endogeneity problem and the dynamic nature of economic growth data, the current study recommends that transitional economies should implement policies that improve human capital development in order to enhance infrastructural development’s ability to influence economic growth. Future studies should investigate not just one (human capital development), but all the conditional factors which must be in place before economic growth advantages triggered by infrastructure development are realised.en_GB
dc.description.abstractW niniejszym opracowaniu poddano analizie wpływ rozwoju infrastruktury i kapitału ludzkiego na wzrost gospodarczy w gospodarkach przechodzących proces transformacji. Zbadano również, czy interakcje między rozwojem infrastruktury a rozwojem kapitału ludzkiego przyczyniły się do wzrostu gospodarczego w tych gospodarkach. Mimo że literatura przedmiotu obejmuje wiele opracowań, poświęconych zbadaniu odrębnego wpływu rozwoju infrastruktury i rozwoju kapitału ludzkiego na wzrost gospodarczy, to jednak żadne ze znanych autorowi badań nie było poświęcone próbie kapitału ludzkiego sprzyjają wzrostowi gospodarczemu. W badaniu wykorzystano głównie uogólnione metody momentów (dynamic panel GMM) autorstwa Arellano i Bonda (1995), które uwzględniają dynamiczny charakter danych dotyczących wzrostu gospodarczego i rozwiązują problemy endogeniczności normalnie związane z funkcjami regresji wzrostu gospodarczego. Metody analizy danych panelowych, takie jak metoda najmniejszych kwadratów (pooled OLS) oraz metody z efektami stałymi i losowymi zostały użyte do celów porównawczych i przeprowadzenia testów odporności. Zgodnie z dynamicznym podejściem opartym na uogólnionych metodach momentów (GMM), interakcje między rozwojem infrastruktury a rozwojem kapitału ludzkiego przyczyniły się do zwiększenia wzrostu gospodarczego w gospodarkach przechodzących transformację, zgodnie z przewidywaniami teoretycznymi i empirycznymi. Metoda z efektami losowymi i metoda najmniejszych kwadratów (pooled OLS) pokazują, że interakcje między rozwojem infrastruktury a rozwojem kapitału ludzkiego miały szkodliwy wpływ na wzrost gospodarczy, natomiast zgodnie z metodą z efektami stałymi interakcje między tymi dwiema zmiennymi miały niewielki pozytywny wpływ na wzrost gospodarczy w gospodarkach przechodzących transformację. Biorąc pod uwagę, że wyniki otrzymane metodą uogólnionych momentów (GMM) są uważane za dokładniejsze ze względu na możliwość uwzględnienia problemu endogeniczności i dynamiczny charakter danych dotyczących wzrostu gospodarczego, z niniejszego badania wynika zalecenie, aby gospodarki przechodzące transformację wdrożyły polityki, które wspierają rozwój kapitału ludzkiego w celu zwiększenia zdolności rozwoju infrastruktury do wpływania na wzrost gospodarczy. Przyszłe badania powinny obejmować nie tylko jeden (rozwój kapitału ludzkiego), ale wszystkie warunki, które muszą być spełnione aby rozwój infrastruktury mógł przyczynić się do osiągnięcia korzyści ekonomicznych.pl_PL
dc.language.isoenen_GB
dc.publisherWydawnictwo Uniwersytetu Łódzkiegoen_GB
dc.relation.ispartofseriesComparative Economic Research. Central and Eastern Europe; 1
dc.rightsThis work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.en_GB
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0en_GB
dc.subjecthuman capitalen_GB
dc.subjectinfrastructure transitional economiesen_GB
dc.subjectdynamic GMMen_GB
dc.subjectkapitał ludzkipl_PL
dc.subjectinfrastrukturapl_PL
dc.subjectgospodarki przechodzące transformacjępl_PL
dc.subjectmetoda uogólnionych momentów (dynamic GMM)pl_PL
dc.titleInfrastructure, Human Capital Development and Economic Growth in Transitional Countriesen_GB
dc.title.alternativeInfrastruktura, rozwój kapitału ludzkiego i wzrost gospodarczy w krajach przejściowychpl_PL
dc.typeArticleen_GB
dc.page.number33-52
dc.contributor.authorAffiliationSouth Africa, Pretoria, Risk Management and Banking, Department of Finance, University of South Africa
dc.contributor.authorAffiliationSouth Africa, Pretoria, Risk Management and Banking, Department of Finance, University of South Africa
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dc.contributor.authorEmailtsaurk@unisa.ac.za
dc.contributor.authorEmailendouaa@unisa.ac.za
dc.identifier.doi10.2478/cer-2019-0003
dc.relation.volume22en_GB
dc.subject.jelF43
dc.subject.jelJ24
dc.subject.jelO18
dc.subject.jelP20


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