Modeling the Effect of Climate Change and Economic Growth on food Security Indicators in Ghana
Sampson Twumasi-Ankrah1, Wilhemina Adoma Pels2, Dennis Kankam Danquah3, Doris Arthur4
1Sampson Twumasi-Ankrah*, Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, PMB UPO.
2Wilhemina Adoma Pels, Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
3Doris Arthur, Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
4Dennis Kankam Danquah, Department of Mathematical Sciences, University of Mines and Technology, Tarkwa, Ghana.
Manuscript received on May 16, 2020. | Revised Manuscript received on May 21, 2020. | Manuscript published on June 10, 2020. | PP: 909-917 | Volume-9 Issue-8, June 2020. | Retrieval Number: B7265129219/2020©BEIESP | DOI: 10.35940/ijitee.B7265.069820
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Hunger is on the rise in almost all sub-regions of Africa, where the prevalence of undernourishment has reached levels of 22.8 percent in sub-Saharan Africa. Therefore, the purpose of this study is to examine the effect of economic growth and climatic factors on food security in Ghana using different functional forms of regression analysis. Annual secondary data on food security indicators, gross domestic product, CO2 , rainfall and temperature spanning from 1999 to 2017 were obtained from the Food and Agricultural Organization (FAO) and World Bank websites. The principal component analysis and regression method were used to reduce the dimensionality of the variable and model the effect of economic growth and climatic factors on food security in Ghana respectively. The dimensions of food availability, stability and utilization were reduced from 5, 6 and 9 variables to 2 variables respectively. However, the dimension of food accessibility was reduced from 3 variables to 1 variable. Food Security Index (FSI) was constructed for each of the food security indicators, and competing models were fitted to the data. It was observed that, GDP has a positive effect on food accessibility, availability, stability and utilization. However, temperature negatively affects food accessibility and stability but a positive effect on food utilization. Rainfall has a negative effect on food stability and CO2 has a negative effect on food availability, stability and utilization.
Keywords: Food Security, Principal Component Analysis, Food Security Index, and Regression
Scope of the Article: Software Economics