title: A Markov chain Monte Carlo (MCMC) methodology with bootstrap percentile estimates for predicting presidential election results in Ghana.
abstract: Although, there exists numerous literature on the procedure for forecasting or predicting election results, in Ghana only opinion poll strategies have been used. To fill this gap, the paper develops Markov chain models for forecasting the 2016 presidential election results at the Regional, Zonal (i.e. Savannah, Coastal and Forest) and the National levels using past presidential election results of Ghana. The methodology develops a model for prediction of the 2016 presidential election results in Ghana using the Markov chains Monte Carlo (MCMC) methodology with bootstrap estimates. The results were that the ruling NDC may marginally win the 2016 Presidential Elections but would not obtain the more than 50 % votes to be declared an outright winner. This means that there is going to be a run-off election between the two giant political parties: the ruling NDC and the major opposition party, NPP. The prediction for the 2016 Presidential run-off election between the NDC and the NPP was rather in favour of the major opposition party, the NPP with a little over the 50 % votes obtained.
authors.affiliation: Department of Statistics, University of Ghana, Box LG 115, Legon, Ghana.
authors.forename: Ezekiel N N
authors.initials: EN
authors.lastname: Nortey
authors.affiliation: Ghana Space Science and Technology Institute (GSSTI), Ghana Atomic Energy Commission (GAEC), Box AE 1, Atomic Kwabenya, Ghana.
authors.forename: Theophilus
authors.initials: T
authors.lastname: Ansah-Narh
authors.affiliation: Department of Political Science, University of Ghana, Legon, Ghana.
authors.forename: Richard
authors.initials: R
authors.lastname: Asah-Asante
authors.affiliation: Department of Statistics, University of Ghana, Box LG 115, Legon, Ghana.
authors.forename: Richard
authors.initials: R
authors.lastname: Minkah
keywords: Elections; Forecasting; Ghana; Markov chains; NDC; NPP; Stochastic matrix