Abstract:
he ;111(IY, siTirmin(t from .1W)0 to 2022, scrutinized the impact of Foreign Direct Investment (FD1)
on agriculture productivity in Tanzania. Employing time series data and a sample of 33 observations, the research aimed to dissect both short-run dynamics and the enduring relationship between FD1
and agriculture productivity. Preliminary analyses ensured data integrity, confirming normal
distribution post-descriptive statistics and stationary variables through the ADF unit root test. The
ARDL bound test demonstrated a long-run equilibrium between variables. Noteworthy findings
unveiled a positive, significant relationship between FDI inflows and agriculture value added, suggesting a 1-unit surge in FDI leads to a 0.701-unit spike in agriculture productivity in the long
run. The overall model, statistically significant with a low probability of F-statistic (0.0000), boasted
high predictive power (adjusted R-squared at 74.4%). The ECM results, with a significant negative
sign, confirmed co-integration, indicating a 0.66 percent correction in deviations from long-term
growth in agriculture value added within the following year. Granger causality tests underscored a
b•-directional causalrelationship between FDI and agriculture in Tanzania, suggesting a reciprocal
influence. This comprehensive study contributes valuable insights into the nuanced dynamics of
FDI's impact on Tanzania's agriculture sector. The study recommends that, Policymakers should
implement strategies to create an investment-friendly environment, offering incentives and
removing barriers to encourage sustained FD
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