scholarly journals Benford’s Law Application: Case of Elections in Sri Lanka

2020 ◽  
Author(s):  
Richmond Sam Quarm ◽  
Richmond Sam-Quarm
Keyword(s):  
Sri Lanka ◽  
Political Parties ◽  
Presidential Election ◽  
Benford’S Law ◽  
Third Place ◽  
Benford's Law ◽  
Data Points ◽  
The Mean ◽  
Election Fraud ◽  
Election Results

Sri Lanka, like many developing countries has been involved in a circle of allegations of election fraud. Usually these claims are pronounced more by losing parties. This study uses Benford’s law, a law of probability distribution of digits, to investigate whether the election fraud claims might have merit. A sample in this study is made of 808 election data. This data comes from the 2010 Presidential election for representatives from three major political parties and from 2010 General Election data. All of the data points were obtained through reliable government sources, two of which are, the Department of Elections website of Sri Lanka, and the National News Paper statistics (2010). The study contrasts the distribution of the first digit of election results against the Benford’s Law benchmark. After obtaining the results, we organize the data and find median, mean, mode and standard deviation. The preliminary results showe that the data does not align with Benford’s law predictions. In other words, it shows that the data does not follow the law where the mean is larger than the median and there is a positive skewness then it likely follows a Benford’s distribution. The distribution of the first digit of actual data for three parties disagrees with Benford's law. This misalignment is more pronounced for the winning party than for the second and third place parties, respectively. We, therefore, look forward to run the data through several critical analyses and observing if there shall be any fraud or manipulation in numbers.

scholarly journals Benford’s Law Application: Case of Elections in Sri Lanka

2020 ◽  
Vol 3 (4) ◽  
Author(s):  
Agim Kukeli ◽  
◽  
Hettiyadura Shehan Karunaratne ◽  
Keyword(s):  
Sri Lanka ◽  
Political Parties ◽  
Presidential Election ◽  
Benford’S Law ◽  
Third Place ◽  
Benford's Law ◽  
Data Points ◽  
The Mean ◽  
Election Fraud ◽  
Election Results

Sri Lanka, like many developing countries has been involved in a circle of allegations of election fraud. Usually these claims are pronounced more by losing parties. This study uses Benford’s law, a law of probability distribution of digits, to investigate whether the election fraud claims might have merit. A sample in this study is made of 808 election data. This data comes from the 2010 Presidential election for representatives from three major political parties and from 2010 General Election data. All of the data points were obtained through reliable government sources, two of which are, the Department of Elections website of Sri Lanka, and the National News Paper statistics (2010). The study contrasts the distribution of the first digit of election results against the Benford’s Law benchmark. After obtaining the results, we organize the data and find median, mean, mode and standard deviation. The preliminary results showe that the data does not align with Benford’s law predictions. In other words, it shows that the data does not follow the law where the mean is larger than the median and there is a positive skewness then it likely follows a Benford’s distribution. The distribution of the first digit of actual data for three parties disagrees with Benford's law. This misalignment is more pronounced for the winning party than for the second and third place parties, respectively. We, therefore, look forward to run the data through several critical analyses and observing if there shall be any fraud or manipulation in numbers.

scholarly journals Benford’s Law Application: Case of Elections in Sri Lanka

2020 ◽  
Author(s):  
Richmond Sam Quarm ◽  
Mohamed Osman Elamin Busharads
Keyword(s):  
Sri Lanka ◽  
Political Parties ◽  
Presidential Election ◽  
Benford’S Law ◽  
Third Place ◽  
Benford's Law ◽  
Data Points ◽  
The Mean ◽  
Election Fraud ◽  
Election Results

Sri Lanka, like many developing countries has been involved in a circle of allegations of election fraud. Usually these claims are pronounced more by losing parties. This study uses Benford’s law, a law of probability distribution of digits, to investigate whether the election fraud claims might have merit. A sample in this study is made of 808 election data. This data comes from the 2010 Presidential election for representatives from three major political parties and from 2010 General Election data. All of the data points were obtained through reliable government sources, two of which are, the Department of Elections website of Sri Lanka, and the National News Paper statistics (2010). The study contrasts the distribution of the first digit of election results against the Benford’s Law benchmark. After obtaining the results, we organize the data and find median, mean, mode and standard deviation. The preliminary results showe that the data does not align with Benford’s law predictions. In other words, it shows that the data does not follow the law where the mean is larger than the median and there is a positive skewness then it likely follows a Benford’s distribution. The distribution of the first digit of actual data for three parties disagrees with Benford's law. This misalignment is more pronounced for the winning party than for the second and third place parties, respectively. We, therefore, look forward to run the data through several critical analyses and observing if there shall be any fraud or manipulation in numbers.

scholarly journals Comment on “Benford's Law and the Detection of Election Fraud”

2011 ◽  
Vol 19 (3) ◽  
pp. 269-272 ◽  
Author(s):  
Walter R. Mebane
Keyword(s):  
Careful Analysis ◽  
Benford’S Law ◽  
Simulation Exercise ◽  
Strategic Actions ◽  
Significant Digit ◽  
Benford's Law ◽  
The Mean ◽  
Election Fraud ◽  
Open Question

“Benford's Law and the Detection of Election Fraud” raises doubts about whether a test based on the mean of the second significant digit of vote counts equals 4.187 is useful as a test for the occurrence of election fraud. The paper mistakenly associates such a test with Benford's Law, considers a simulation exercise that has no apparent relevance for any actual election, applies the test to inappropriate levels of aggregation, and ignores existing analysis of recent elections in Russia. If tests based on the second significant digit of precinct-level vote counts are diagnostic of election fraud, the tests need to use expectations that take into account the features of ordinary elections, such as strategic actions. Whether the tests are useful for detecting fraud remains an open question, but approaching this question requires an approach more nuanced and tied to careful analysis of real election data than one sees in the discussed paper.

Can Vote Countsʼ Digits and Benfordʼs Law Diagnose Elections?

Benford's Law ◽  
2015 ◽  
Author(s):  
Walter R. Mebane,
Keyword(s):  
United States ◽  
Political Parties ◽  
Strategic Behavior ◽  
The United States ◽  
Benford’S Law ◽  
Conditional Mean ◽  
Benford's Law ◽  
Election Fraud

This chapter illustrates how the conditional mean of precinct vote counts' second digits can respond to strategic behavior by voters in response to the presence of a coalition among political parties. The digits in vote counts can help diagnose both the strategies voters use in elections and nonstrategic special mobilizations affecting votes for some candidates. The digits can also sometimes help diagnose some kinds of election fraud. The claim that deviations in vote counts' second digits from the distribution implied by Benford's law is an indicator for election fraud, generally fails for precinct vote counts. This chapter shows that such tests routinely fail in data from elections in the United States, Germany, Canada and Mexico, countries where it is usually thought that there is negligible fraud.

scholarly journals Was there any widespread fraud in 2020 presidential election? What does Benford's Law say?

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Deeya Datta ◽  
David Banks
Keyword(s):  
Presidential Election ◽  
Forensic Analysis ◽  
Benford’S Law ◽  
Large Set ◽  
Donald Trump ◽  
Comprehensive Investigation ◽  
Electoral Fraud ◽  
Benford's Law ◽  
Election Fraud ◽  
Basic Statistical Analysis

Fair elections free of any interference are integral tenets of any functioning democracy, and widespread election fraud is undoubtedly a serious threat to a free republic. While instances of electoral fraud are much more prevalent in countries with illiberal democracies, the U.S has recently faced such an accusation. Although he was unable to provide any concrete evidence, the former U.S. President Donald Trump accused his opponent, Joe Biden, now president, of electoral fraud after the presidential election. Fortunately, election forensics are often successful in investigating the validity of such fraud allegations. In this paper, I applied Benford’s law, a rule that should stand up to any large set of natural numbers, such as un-tampered electoral data. Using this law and basic statistical analysis of votes of U.S. counties for candidates of the two major parties, I completed a forensic analysis to investigate Mr. Trump’s allegation. My comprehensive investigation does not find any evidence supporting his allegation.

Mexico: New Democracy with Old Parties?

Politics ◽  
2003 ◽  
Vol 23 (3) ◽  
pp. 172-180
Author(s):  
Carlos E. Casillas ◽  
Alejandro Mújica
Keyword(s):  
Political Parties ◽  
Presidential Election ◽  
Party System ◽  
Historical Perspective ◽  
Contemporary History ◽  
Systematic Analysis ◽  
Political Events ◽  
Before And After ◽  
Election Results ◽  
New Democracy

Mexico's 2000 presidential election was one of the most important political events in the nation's contemporary history. The victory of the National Action Party (PAN) and Vicente Fox, the first ‘non-official’ candidate ever to win a Mexican presidential election, surprised both local and world observers. This article comprises four parts. Part I very briefly places the election in historical perspective. In Part II, each of the three front-runners in the contest is profiled. Part III includes a systematic analysis of the general election results by constituencies or other territorial units, and features tabulated data. Part IV addresses the development of political parties and the party system before and after the elections.

Chile coalition crisis hints at new Pinera presidency

2016 ◽  
Keyword(s):  
Political Parties ◽  
Presidential Election ◽  
Pole Position ◽  
Content Type ◽  
Fertile Ground ◽  
Election Results ◽  
The Government ◽  
The Impact ◽  
Consistent Support ◽  
Actual Size

Significance Albeit expected, that defeat has widened divisions within its centre-left coalition and between the administration and its political parties. The election results put the centre-right opposition in the pole position to win the next presidential election in November 2017. Impacts The impact of the election outcome on the mood in government parties far exceeds the actual size of their defeat. High abstention is a criticism of both main coalitions and suggests potentially fertile ground for populism. Without consistent support from its own parties, it will be difficult for the government to pass promised reforms.

Complementing Benfordʼs Law for Small N: A Local Bootstrap

Benford's Law ◽  
2015 ◽  
Author(s):  
Boudewijn F. Roukema
Keyword(s):  
Presidential Election ◽  
Presidential Elections ◽  
Benford’S Law ◽  
Frequency Test ◽  
General Behavior ◽  
Benford's Law ◽  
Bootstrap Model ◽  
Small N

This chapter analyzes the initially published results of the 2009 Iranian presidential elections. It applies a small N statistical first-digit frequency test that is as nonparametric as possible in a way that leaves no doubt regarding “how close” the observed system should be to a Benford's law limit. The approach this chapter studies is a local bootstrap model, designed to closely mimic the data in a way that should statistically reproduce its first-digit distributions, given some simple hypotheses about the general behavior of the system. This method was calibrated on several presidential-election first rounds from before 2009 and applied to the 2009 Iranian election.

Violence and Election Fraud: Evidence from Afghanistan

2012 ◽  
Vol 43 (1) ◽  
pp. 53-75 ◽  
Author(s):  
Nils B. Weidmann ◽  
Michael Callen
Keyword(s):  
Random Sample ◽  
Presidential Election ◽  
Visual Inspection ◽  
Local Variation ◽  
Internal Conflict ◽  
Electoral Process ◽  
Empirical Results ◽  
Election Fraud ◽  
Election Results ◽  
The Relationship

What explains local variation in electoral manipulation in countries with ongoing internal conflict? The theory of election fraud developed in this article relies on the candidates’ loyalty networks as the agents manipulating the electoral process. It predicts (i) that the relationship between violence and fraud follows an inverted U-shape and (ii) that loyalty networks of both incumbent and challenger react differently to the security situation on the ground. Disaggregated violence and election results data from the 2009 Afghanistan presidential election provide empirical results consistent with this theory. Fraud is measured both by a forensic measure, and by using results from a visual inspection of a random sample of the ballot boxes. The results align with the two predicted relationships, and are robust to other violence and fraud measures.

scholarly journals A Bayesian Approach for Validation of Election Results

2020 ◽  
Vol 27 (2) ◽  
pp. 22-31
Author(s):  
R.K. Ogundeji ◽  
J.N. Onyeka-Ubaka
Keyword(s):  
Political Parties ◽  
Bayesian Approach ◽  
Bayesian Methods ◽  
Presidential Election ◽  
Presidential Elections ◽  
Empirical Bayes ◽  
Posterior Probability ◽  
Election Process ◽  
Credible Intervals ◽  
Election Results

Election process and results in many countries have resulted in both political and economic instability of that country. Fair and credible election process and results must be evidence-based and statistical proven. This study employed a Bayesian procedure for the validation of election results. Based on Nigerian 2011 and 2015 presidential election results, Bayesian credible intervals were obtained to assess the credibility of Nigeria presidential election results. The study explores Bayesian methods using a Bayesian model called beta-binomial conjugate model to compute posterior probability of electoral votes cast and confirm if these votes are within Bayesian credible intervals. The results obtained showed that election outcomes for the two major political parties in Nigeria 2011 presidential election are not within Bayesian credible bounds while 2015 presidential election results are within computed Bayesian credible bounds. Also, in contrast to frequentist approach, applied Bayesian methodology exhibited smaller variance which is an indication that Bayesian approach is more efficient. Thus, for election to be fair, credible and acceptable by the electorates, Bayesian approach can be used to validate electoral process and results. Keywords: Bayesian Methods, Bayesian Credible Intervals, Beta-Binomial Model, Empirical Bayes, Nigeria Presidential Elections.

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