Posted on SSRN April 28, 2020; last accessed November 17, 2020. Published in Econ Lett 2020;196(109973) .
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Trust in the reported data of contagious diseases in real time is important for policy makers. Media and politicians have cast doubt on Chinese reported data on COVID-19 cases. We find Chinese confirmed infections match the distribution expected in Benford’s Law and are similar to that seen in the U.S. and Italy and thus find no evidence of manipulation. Policy makers in the rest of the world should trust the Chinese data and formulate policy accordingly.
Bibtex:
@misc{,
AUTHOR = {Christoffer Koch and Ken Okamura},
TITLE = {Benford's Law and COVID-19 Reporting},
YEAR = {2020},
MONTH = {April 28},
URL = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3586413&download=yes},
}
Reference Type: Journal Article
Subject Area(s): Computer Science