In last night’s presidential debate, there were many often contradictory facts and figures thrown out by both candidates. With so many numbers being presented to the public, it is sometimes hard to distinguish what is fact, what is fiction, and how to critically think about the issues. Is That a Fact author Mark Battersby brings this up in Chapter 5 in his discussion on mythical numbers and the dangers of misinformation.
Politics and Mythical Numbers
Numbers play a powerful role in public debate and governmental decision making and are often given a degree of credibility and significance that they simply do not deserve. While it is commendable to attempt to base decisions on “facts,” one should not rely on mythical or even “soft” numbers as if they were well-established facts.
A current example of a debate centring on a “mythical number” is the controversy over whether individuals in third-world countries are receiving any benefit from globalization. Globalization skeptics often mention that the per-capita income of people in impoverished countries is about a dollar day, while some economists argue that it is closer to two dollars a day.  My first reaction is that this is a difference not worth arguing about—either amount is terrible.
Though the misery of much of the third world is undeniable, the quality of income data cannot support such debates about precise numbers. Deeply impoverished countries, whose governments are often in disarray, do not have the necessary means or inclination to collect reliable data. And even with reliable data, the comparisons across cultures and differing monetary regimes would make the comparisons daunting. As Reddy and Pogge note in the abstract to a recent article,
[The World Bank] … employs a concept of purchasing power “equivalence” that is neither well defined nor appropriate for poverty assessment. These difficulties are inherent in the Bank’s “money-metric” approach and cannot be credibly overcome without dispensing with this approach altogether. In addition, the Bank extrapolates incorrectly from limited data and thereby creates an appearance of precision that masks the high probable error of its estimates. 
While it is understandable that the World Bank and other world institutions would like to put precise values on the state of the world, they should recognize the real limitation of their ability to do so. Once we start using these
numbers as if they were precise measurements, we have slipped into the world of mythical numbers.
Nevertheless, many significant political decisions are based on unreliable data. A well-known example is the CIA’s use of very misleading economic data from the former Soviet Union, which led the CIA to miss the impending economic collapse of that country. This misinformation was used to encourage military spending to defend against the (collapsing) Soviet “menace.” 
 Benjamin Friedman, “Globalization: Stiglitz’s Case,” The New York Review of Books, August 15,2002, http://www.nybooks.com/articles/15630.
 Sanjay Reddy and Thomas Pogge, “How Not to Count the Poor,” in Joseph Stiglitz, Sudhir Anand, and Paul Segal (eds.), Debates on the Measurement of Global Poverty (Oxford: Oxford University Press, 2010), 42–85.
 Paul Craig Roberts, “My Time with Soviet Economics,” The Independent Review 7.2 (2002): 259–64, http://www.independent.org/pdf/tir/tir_07_2_roberts.pdf.