Machine Learning Analysis of the Relationship Between Foreign Direct Investment, Innovation, and High-Tech Exports in Uzbekistan

dc.contributor.authorPhD Gafurova Azizaxon Fatixovna
dc.date.accessioned2026-03-03T20:50:18Z
dc.date.issued2026-02-25
dc.description.abstractThe aim of the following study is to investigate the relationship between foreign direct investment (FDI), high-tech exports and participation in innovation activities in Uzbekistan during 2008, 2024. We’ve constructed a synthetic IPI using macroeconomic indicators and firm-level data from the B-READY, and estimated traditional OLS as well as RandomForest and Extreme Gradient Boosting Classifier models to predict drivers of IPI. The evidence indicates that both inward FDI and growth of high-tech export are positively and significantly associated with innovation. The machine learning models expose non-linearities and confirm the dominance of FDI as a key driver.
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dc.identifier.urihttps://geniusjournals.org/index.php/ejhge/article/view/7350
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/117958
dc.language.isoeng
dc.publisherGenius Journals
dc.relationhttps://geniusjournals.org/index.php/ejhge/article/view/7350/6049
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0
dc.sourceEurasian Journal of History, Geography and Economics; Vol. 52 (2026): EJHGE; 4-10
dc.source2795-7659
dc.subjectforeign direct investment
dc.subjectinnovation
dc.subjecthigh-technology exports
dc.titleMachine Learning Analysis of the Relationship Between Foreign Direct Investment, Innovation, and High-Tech Exports in Uzbekistan
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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