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dc.contributor.authorSusan K., Matheka
dc.contributor.authorEtyang, Martin
dc.date.accessioned2023-07-17T07:51:38Z
dc.date.available2023-07-17T07:51:38Z
dc.date.issued2023
dc.identifier.citationK., M., & Etyang, M. (2023). Government Infrastructure Spending and Economic Growth in Kenya: An Autoregressive Distributed Lag Model Approach. International Journal of Economics, 8(1), 1–29. https://doi.org/10.47604/ijecon.1780en_US
dc.identifier.urihttps://doi.org/10.47604/ijecon.1780
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/26244
dc.descriptionArticleen_US
dc.description.abstractPurpose: Since independence, the Government of Kenya has pursued many objectives, one being economic growth. Over the previous few many years, government expenditure has been developing faster than the GDP growth. Infrastructure, one of the components of public spending, has also experienced tremendous growth in government spending and development, which has not been directly reflected in the GDP growth rate. Following such situation, it calls for analyzing the impact that government infrastructure expenditure has on economic growth in Kenya with a focal point on three sectors beneath infrastructure that the public sector spends closely on; transport, energy and fuel, and Information Communication and Technology (ICT). The study's overall objective is to find out the effects of government spending on the three sampled sectors of government infrastructure on economic growth in Kenya and then draw policy implications from the findings. The specific objectives were; to investigate the effect of transport infrastructure expenditure on economic growth in Kenya, to examine the effect of energy & fuel infrastructure expenditure on economic growth in Kenya, and to examine the effect of ICT infrastructure expenditure on economic growth in Kenya. Further, Bounds F-test to cointegration as well as the Autoregressive Distributed Lag Model (ARDL) were used to realize the objectives. Methodology: The data was collected covered 1990 – 2020 for the three sectors of infrastructure: transport, energy & fuel, and ICT. Several tests on the time series data were carried out on the secondary data obtained, after which (ARDL) was employed in analysing the data. Findings: The outcome showed that government expenditure on transport, energy, fuel, and ICT infrastructure sectors affected economic growth either in the short or the long run. Based on the ECM regression findings, the long-run regression outcome revealed that expenditure on energy and fuel promotes economic growth. On the contrast, the findings showed that government expenditure on transport and ICT sectors exhibited a negative effect on GDP growth rate. Public expenditure on transport and ICT infrastructure sectors positively impacted economic growth in the short term, while the energy and fuel sectors exhibited a negative impact on GDP. Other control variables inclusive of trade openness and FDI showed either a positive or negative effect on economic growth either in long or short run. Inflation, particularly, exhibited a negative effect on GDP in the long run, in addition to within the short run. Unique Contribution to Theory, Practice and Policy: Based on the empirical findings, this study validates the Keynesian theory which stipulates that public expenditure positively contributes to economic growth. Based on this theory, public expenditure is an exogenous factor capable of being applied as a policy instrument in promoting economic growth.en_US
dc.language.isoenen_US
dc.publisherIPRJBen_US
dc.subjectInfrastructureen_US
dc.subjectSpendingen_US
dc.subjectEconomic Growthen_US
dc.subjectARDLen_US
dc.titleGovernment Infrastructure Spending and Economic Growth in Kenya: An Autoregressive Distributed Lag Model Approachen_US
dc.typeArticleen_US


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