2024/01/24 by Lethani Ndwandwe, James Allison, Ndwandwe, Lethani +5
Agricultural and Biological Sciences · Economics, Econometrics and Finance · #Agricultural risk and resilience #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Monetary Policy and Economic Impact
paper · pdf · doi:10.48550/arxiv.2401.13777
openalex publication_date 2024/01/24 · openalex created_date 2024/01/27 · openalex updated_date 2026/07/28
We propose new goodness-of-fit tests for the Pareto type I distribution. These tests are based on a multiplicative version of the memoryless property which characterises this distribution. We present the results of a Monte Carlo power study demonstrating that the proposed tests are powerful compared to existing tests. As a result of independent interest, we demonstrate that tests specifically developed for the Pareto type I distribution substantially outperform tests for exponentiality applied to log-transformed data (since Pareto type I distributed values can be transformed to exponentiality via a simple log-transformation). Specifically, the newly proposed tests based on the multiplicative memoryless property of the Pareto distribution substantially outperform a test based on the memoryless property of the exponential distribution. The practical use of tests is illustrated by testing the hypothesis that two sets of observed golfers' earnings (those of the PGA and LIV tours) are realised from Pareto distributions.