Causality between transport infrastructure and economic growth in Kenya

Research output: Contribution to journalArticlepeer-review

Abstract

The study investigated the relationship between transport infrastructure investments and economic growth in Kenya, using annual time-series data from 1975 to 2023. An autoregressive distributed lag (ARDL) estimation method was used. The study reveals a unidirectional causality from road and rail investments to GDP, indicating that these sectors drive short-run economic growth. A bidirectional relationship exists between port infrastructure, gross capital formation, labor, and GDP, suggesting mutual reinforcement, while no short-run causality is observed between air transport and GDP. The short-run dynamics further show that infrastructure investments, capital formation, and structural breaks are key determinants of growth. In the long run, the results confirm a stable equilibrium association, where port infrastructure, capital formation, labor, and structural reforms contribute positively and significantly to sustaining economic growth. The study recommends that Kenya should sustain investment in road, rail, and port infrastructure, alongside capital formation and labor development, to stimulate both short-term and long-term economic growth. At the same time, implementing structural reforms and efficiency-enhancing strategies will help ensure that these investments yield lasting and inclusive development gains.

Original languageEnglish
Pages (from-to)38-47
Number of pages10
JournalTransport Economics and Management
Volume4
DOIs
Publication statusPublished - Dec 2026

Keywords

  • Causality
  • Co-integration
  • Economic Growth
  • Transport Infrastructure

ASJC Scopus subject areas

  • Transportation
  • Economics, Econometrics and Finance (miscellaneous)
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management

Fingerprint

Dive into the research topics of 'Causality between transport infrastructure and economic growth in Kenya'. Together they form a unique fingerprint.

Cite this