Effect of Climate Change on Maize Productivity in Kenya: A Vector Error Correction Model

Abstract

As Much As Agriculture Is The Major Catalyst For Any Nation’s Economy, It Relies Heavily On Rainfall, Which Has Changed In Terms Of Rainfall Patterns. SSA Countries (97%) Rely On Rain Fed Agriculture. These Countries’ Populations Remain Vulnerable To Climate Change. This Study Sought To Analyze The Effect Of Climate Change Of Maize Productivity VECM. A Production Function Was Used Where The Most Commonly Used Weather Indicators, Which Are Precipitation; Temperature Averages And CO2 Concentration Were Incorporated. Unit Roots Were Done Using The Augmented Dickey-Fuller Test And Cointegration By Johansen Cointegration Test, Where Variables Were Found To Be Cointegrated. Temperature, Temperature Squared, CO2 And CO2 Squared Were Found To Be Statistically Significant. From The ECM Results, Rainfall Squared, Temperature And Carbon Dioxide Squared Had A Positive (Direct) And Significant Effect On Maize Output Respectively (P-Value 0.000, 0.011, 0,034< 0,05). Rainfall, Temperature Squared And Carbon Dioxide Had A Negative (Indirect) Significant Effect On Maize Output Respectively (P-Value 0.000, 0.014, 0.002< 0.05). It Is Recommended That The Government To Seriously Use The Metrological Departments To Monitor The Key Indicators Of The Climate So As To Advice The Stakeholders Accordingly. Key Words: Error Correction Models (ECM, Cointegration -------------------------------------------------------------------------