Monte Carlo simulation of vote counts from Nigeria presidential elections

Abstract

This study was designed to examine the application of Monte Carlo simulation to analyse vote counts from the 2011 and 2015 presidential elections in Nigeria. The study adopted a simulation approach and the data were simulated using the R programming language. The actual and simulated data were analysed using frequency and percentage distribution as well as Spearman Rank Correlation tests. Findings revealed that the vote counts for People's Democratic Party (PDP) and Congress for Progressive Change (CPC) in the 2011 presidential elections as well as vote counts for All Progressives Congress (APC) and PDP in the 2015 presidential elections do not conform to the distributional pattern of the respective simulated vote counts. A manipulation-free data generating process is expected to produce vote counts that are close to a random distribution. The study recommends the use of forensic analysis by the Independent National Electoral Commission (INEC) for future electoral reform in Nigeria.

Anomalies in Nigeria Presidential Election Data and the Way Forward

“…Monte Carlo analysis is a general term that refers to research that employs random numbers, usually in the form of a computer simulation [43]. The Monte-Carlo approach has been specifically adopted in detecting suspicious electoral data [44,45]. The focus is on deviation of distributional patterns of actual data from the simulated data.…”

Security and preservation of election data in Nigeria in the fourth industrial revolution

“…Similarly, Ojukwu, Mazi and Maduekwe (2019) noted that the 2019 general election was marred by vote manipulations and has credibility deficit. Scholars have also conducted studies on the possibility of the application of election forensics to detect irregular patterns and fraud in Nigeria electoral data (Beber and Scacco, 2008;Tunmibi and Olatokun 2020;Tunmibi and Olatokun 2021).…”