Abstract

Agriculture plays a dominant role in West African economy. For example, agriculture employs more than half of the labour force in most countries in the subregion, as well as contributes 15 per- cent to the subregion’s total GDP (OECD/FAO 2016). Additionally, agriculture is a vital source of livelihood in the rural areas. Thus, the state of agriculture in the subregion is central to the challenge of eradicating poverty and ensuring food security. Previous studies (e.g., Schlenker & Lobell (2010), Blanc (2012)) that have analysed the relationship between climate change and agriculture in the subregion treat countries as spatially independent of one another: but as observed by Kumar (2011), the values of agricultural variables are, in reality, also defined by conditions in neighbouring countries. Furthermore, the error terms could be serially correlated which may bias the true variance-covariance matrix, and hence the t -statistics if not corrected. This paper, therefore, uses updated panel data (1970-2014), as well as location-specific weather observations to examine the effect of climate change on agricultural production in Western Africa while simultaneously control- ling for several types of spatial effects using the spatial Durbin model (SDM). The SDM model controls for three sources of spatial interactions - in the outcome variable, the covariates and errors. Our preliminary results and no evidence of spatial dependence in the outcome variable, but in the regressors and error terms.

Presenters

Lotanna Emediegwu
Lecturer in Economics, Economics, Policy and International Business, Manchester Metropolitan University, Manchester, United Kingdom

Details

Presentation Type

Focused Discussion

Theme

Human Impacts and Impacts on Humans

KEYWORDS

Agriculture, Climate, Spatial, Africa

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