Foreign direct investment and industrialization in Tanzania admixture time series forecast analysis 1960 – 2020

dc.contributor.authorKitole, Felician A & Utouh Harold
dc.date.accessioned2024-04-15T09:45:17Z
dc.date.available2024-04-15T09:45:17Z
dc.date.issued2023
dc.descriptionAn article presented to economics, finance, business and industry Journal
dc.description.abstractThis paper examines and forecasts the impact of foreign direct investment (FDI) on industrialization and industrial performance in Tanzania by using World Bank data spanning 1960 to 2020. The admixture time series analysis of Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) has been extensively explored in order to provide accurate estimation. The need to examine FDI inflows is enormously based on domestic macroeconomic parameters that are stuck in many developing countries, including Tanzania, implying that FDI is necessary for growth and development now and in the future. According to the findings, FDI granger causes industrialization, and the more the sector thrives, the more granger causes FDI inflow. In the long run, FDI has a significant impact on Tanzanian industrialization growth, whereas the exchange rate (EXR) has a significant impact on industrialization growth in the short run. The study recommends the Bank of Tanzania to take appropriate measures to control poor-performing economic parameters such as the exchange rate, inflation, and the improvement of the money market in order to enhance capital availability and accessibility.
dc.description.sponsorshipPrivate
dc.identifier.citationAPA
dc.identifier.issnhttps://doi.org/10.1080/13504851.2023.2211324
dc.identifier.urihttps://scholar.mzumbe.ac.tz/handle/123456789/597
dc.language.isoen
dc.publisher Economics, finance, business and industry Journl
dc.subjectIndustrialization
dc.subjectForeign direct investiment
dc.subjectVector error correction model
dc.subjectVector autoregressive.
dc.titleForeign direct investment and industrialization in Tanzania admixture time series forecast analysis 1960 – 2020
dc.typeArticle
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