Benford’s Law and its Applicability in the Forensic Analysis of Electoral Results
Keywords:
ley de Benford, análisis de fraude electoral, modelos basados en agentes, preferencias políticas, elecciones mexicanas de 2006Abstract
This article analyses the viability of Benford’s Law in the forensic study of the detection of electoral frauds. According to this law, the initial digits of a set of numbers follow a logarithmic distribution as long as the data has not been disturbed. Implementation of this law in socioeconomic data —or in other types of data— depends on the presence of a two-fold randomized process: events of a distribution, and probability distributions selected from a reduced group. Through agent-based models, it is demonstrated that this law does not offer a robust test to distinguish between clean elections and elections that have been manipulated. In the model-in-question, partisan preferences are modified by means of social transmission and the parameters are calibrated with data from the Mexican 2006 elections.
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