NEFM-Data: Input data for the Nigerian Energy-Food Model (NEFM)
Description
This Data Article houses secondary data, consisting of the available historic and current farm production data in Nigeria such as crop type, yields, prices, crop production inputs’ (e.g. labour, fertilizer, pesticide, seed, cash capital) as well as the Nigerian food consumption, ethanol demand, and international commodity (crop/food) trade (import and export) data. The data were collected from reputable online databases such as FAOSTAT, World Bank, IMF, USDA, NBS, IITA, etc., and through personal research visits to Nigerian government agencies such as Federal and State Ministries of Agricultural and Rural Development, State Agricultural Development Agency (ADP) in Nigeria, National (Nigerian) Bureau of Statistics (NBS) and others; and were assembled, screened, processed (tabulated them according to GAMS table requirements), and applied via General Algebraic Modelling System (GAMS) to analyse the Nigerian Biofuels (bioethanol production) Potential, assessing its policy impacts on domestic (Nigerian) food and energy securities, job creation, rural development, and the economy. Ndukwe Agbai Dick collected all the data, processed and applied them through GAMS to analyse the Nigerian Biofuels Potential during his PhD research studies at Newcastle University, England, between October 2010 and September, 2014. The research visit took place between March 1st and June, 2012. Research findings from the analysis of these data using GAMS have been partly documented in paper titled "Analysis of the Inherent Energy-Food Dilemma of the Nigerian Biofuels Policy using Partial Equilibrium Model: The Nigerian Energy-Food Model (NEFM)", which has been peer-reviewed and recommended for publication with major revisions in a reputable international high impact journal - Renewable and Sustainable Energy Reviews (RSER). Of course, the NEFM and results generated from it has been peer-reviewed and validated, acceptance for publication, and is now available online on the Renewable and Sustainable Energy Reviews Journal's website - a high impact and reputable international journal with impact factor of 9.184.
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Steps to reproduce
1. Literature review to identify the required analytical model to employ for your data analysis, 2. Literature review to identify data needs, 3. Data mapping to link required data with the potential sources, 4. Internet screening of reputable and relevant online databases, 5. Data evaluation to identify the relevance of data prior to data harvesting, 6. Data harvesting/download, 7. Data saving into relevant folders, 8. Data pre-processing (data screen to identify outliers, uniformity, and normal distribution), 9. Data processing (e.g. data assembling, data tabulation, charts, graphs, etc.), 10. Data incorporation and alignment to GAMS