Climate Change Impact on Togo’s Agriculture Performance: A Ricardian Analysis Based on Time Series Data

This paper applies Ricardian approach to measure the effect of climate change on agriculture performance in Togo using time series data from the period 1971-2004. The study examines the relationship between net farm revenue and climate variables. Net farm revenue is regressed on climate and other variables. The findings show that there exists a non linear relationship between agricultural added value and recorded precipitations during the cropping period. More specifically, relatively high precipitation seems to have positive impact on net farm income during the rainy seasons. Marginal impacts are mostly in line with the Ricardian model, showing marginally increasing precipitation during rainy season would increase net farm income, but reduce by the square terms of this season. Other variables such as ratio of irrigated farm land and farm labour are found to have positive impact on net farm value but not agricultural machinery. Climate change impact simulations reveal that changes in climate attributes will reduce agricultural added value per hectare by a value ranging from 7.11% in 2025 climate scenario to 15.24% in 2050 climate scenario. In terms of GDP, climate change will cost Togo a proportion between 2.84 and 6 percent. Conclusively, the impact of climate change on agriculture seems to be varied with the temperature and precipitation in different seasons. Climate change impacts are driven by decreases in precipitations implies that adaptation efforts should target more drought-resistant crop varieties and technologies.Keywords: Climate change, Agricultural Added Value, Ricardian analysis, Tog