Macroeconomic Drivers Shaping Foreign Direct Investment in Kenya: Evidence from Time-Series Analysis

Introduction: Foreign direct investment (FDI) is a vital source of external finance for developing economies, yet Kenya has experienced marked fluctuations in FDI inflows over time. Understanding the core macroeconomic drivers shaping foreign capital flows is essential for enhancing Kenya's competitiveness and investment attractiveness. Methods: This study evaluated the effects of real interest rate, inflation, economic growth, exchange rate, and exogenous structural disruptions on inward foreign direct investment (FDI) in Kenya using annual time-series data from 1966 to 2019 (N = 54). Phillips-Perron unit-root tests confirmed a mixed integration profile of I (0) and I (1) series with no I (2) variables present, validating the use of an Autoregressive Distributed Lag (ARDL) Bounds Testing approach under an ARDL (1, 1, 0, 1, 0) specification selected via the Akaike Information Criterion (AIC). Cointegration was evaluated using the Pesaran, Shin, and Smith bounds test under an unrestricted intercept and no trend deterministic specification (k = 5). Dynamic short-run error-correction modelling, Granger causality testing, and post-estimation diagnostic checking, including Breusch-Godfrey serial correlation, ARCH heteroscedasticity, Jarque-Bera normality, Ramsey RESET functional form, and CUSUM/CUSUMSQ parameter stability tests were conducted to ensure robust model specification. Results: The ARDL bounds test confirmed a statistically significant long-run cointegrating relationship among the variables (F = 6.842, exceeding the 1% upper critical bound of 4.15). Long-run elasticity estimates established that economic growth exerted the primary positive effect on inward FDI (β = 0.6845, p = 0.0000), followed by real interest rate (β = 0.1872, p = 0.0279) and exchange rate (β = 0.1534, p = 0.0208). Conversely, inflation (β = -0.2856, p = 0.0161) and exogenous structural disruptions (β = -0.5210, p = 0.0084) exercised statistically significant negative impacts on capital inflows. Granger causality tests revealed unidirectional linkages running from exchange rate and economic growth to FDI. The error correction term (ECTt-1) = -0.4265, p = 0.0000) proved that 42.65% of short-run disequilibria from external shocks are adjusted back towards long-run equilibrium annually. Comprehensive post-estimation diagnostics verified the empirical validity of the model, establishing an absence of serial correlation (Breusch-Godfrey F = 1.342, p = 0.2720), constant error variance (ARCH Test F = 0.815, p = 0.3710), normally distributed residuals (Jarque-Bera x2 = 1.104, p = 0.5760), correct functional specification (Ramsey RESET F = 0.489, p = 0.4880), and structural parameter stability via CUSUM and CUSUMSQ tests. Conclusion: Inward FDI in Kenya is strongly anchored in host-country macroeconomic performance and institutional stability. Economic growth serves as the primary catalyst for market-seeking FDI, while inflation and structural disruptions remain critical deterrents. Recommendations: Policymakers should prioritise sustained economic growth initiatives, maintain low and stable consumer price inflation, manage foreign exchange stability, and strengthen institutional frameworks to reduce macroeconomic volatility and attract foreign capital.