dc.description.abstract | This study sought to identify the determinants of agricultural productivity in Kenya. The study used partial factor productivity given by physical output over factor inputs. It explored inflation, real exchange rate, labour force, government expenditure and climate/rainfall as the factors determining agricultural productivity. The study utilized secondary data for the period of 1980 to 2013. The study employed Cobb-Douglas production function and ordinary least square (OLS) estimation technique as the method of analysis. The independent variables were labour force, inflation, real exchange rate, government expenditure and climate/rainfall while the dependent variable was agricultural productivity.
From the regression results, an increase of one percent in government expenditure, annual rainfall, labour force caused an increase in agricultural productivity by 0.0639032%, 0.0917103%, 0.1984402% respectively. An increase of one percent in inflation rate, exchange rate in caused a decrease in agricultural productivity by 0.0193286% and 0.405422% respectively. Overall the model is statistically significant at 5% level of significance.
The study also employed Johansen-Granger Cointegration procedures and Error Correction Model (ECM) to forecast long-run relationships and to check for short-run relationship respectively among the study variables. The long run relation highlights the negative impact of exchange rate (E) and inflation (I) on agricultural productivity (Y), while Labour force, rainfall, and government expenditure impact agricultural productivity positively.
From the results of Error Correction Model, labour, rainfall and government expenditure have a high explanatory power, as indicated by R2 of 0.9105, 0.7181 and 0.6613 respectively. Exchange rate and inflation rate have a relatively low explanatory power given by R2 of 0.3231 and 0.3204 respectively. This implies that in the short run Labour, rainfall, and government expenditure are the main determinants of agricultural productivity in Kenya. | en_US |