# Regulating Misinformation

• “Cancer cured with soothing balmy oils.” Appeal to Reason
• “According to this repeated nationwide survey, more doctors smoke Camels than any other cigarette.” – TV ad
• Regarding patent medicine sold at the end of the nineteenth century: “…the medicines were ineffectual. Some of the syrups contained as much as 80 per cent alcohol; many of the tonics used cocaine and morphine. Some of the medicines destroyed health, and make drunkards and dope addicts out of their users.” Weinberg and Weinberg (2006) The Muckrackers.

False advertising has been a problem since the beginning of commerce. Deliberately misleading messages lead consumers to purchase products which they do not need or ones which may even harm them. In the 2006 NBER Working Paper “Regulating Misinformation,” Edward Glaeser and Gergely Ujhelyi create a theoretical model to examine what are the optimal governmental strategies to combat misinformation.

Previous economic analyses have often espoused laissez faire polices. These studies would claim that misleading information is either ineffective because the wisdom of the masses will prevail or because the government is an poor arbiter of what exactly is defined as misinformation. Still, companies spend millions of dollars on misinformation advertising campaigns (see Zyprexa rep post) so they must be at least somewhat effective in changing popular opinion.

Model

Glaeser and Ujhelyi create a theoretical model using an Cournot-style oligarchical setting. Total quantity, Q(P), is equal to N(a-c-P)/a. There are N number of people who receive benefits from the product and there are J number of equally sized firms. The variable c is equal to the individuals expected health cost of using the product which can be erroneous. This perceived cost, c is equal to the true cost, c0, minus an error term, ε (c=c0). Using the formulas for solving Nash equilibrium, we can see that each firm will produce q=N(a-c)/[a(J+1)] quantity of the good. On an industry-wide level, we find:

• Q(ε)=JN(a-c)/[a(J+1)] = J*q
• P(ε)=(a-c)/(J+1)
• Π(ε)=JN(a-c)2/[a(J+1)2]

We see that the cross derivative QεJ>0 because more firms increase their output in response to higher demand caused by the increase in misleading information transmitted to consumers.

Looking at the mathematics, the authors suggest that misinformation may actually be welfare enhancing if there are other market imperfections. For instance, in the case of monopoly, price is raised and thus the quantity consumed in a monopolistic environment is below the optimal level. With false advertising under monopoly, the authors argue, the equilibrium quantity could move closer to the socially optimal level.

The authors assume advertising is a public good on the industry level. Proposition 3 of the paper claims the following: 1) total advertising expenditure increases with market size, 2) total advertising expenditure decreases with the true health-cost, c0; and 3) total advertising expenditure decreases with the number of firms. Conclusions (1) and (2) are relatively self-explanatory. Conclusion number (3) is sensible since it implies that as competition rises, misinformation falls. “This is the classic example of the free rider problem. All firms benefit by confusing consumers about the costs of the product, but if there are too many firms, they will fail to invest in this industry-level public good.”

Conclusions

The authors conclusions are as follows:

1. Misinformation may not be socially inefficient (as in the case of monopoly). Further “misinformation is more likely to be welfare reducing when prices are closer to marginal costs than in a more monopolistic setting.”
2. When advertising only misinforms, a tax on advertising or an equivalent quantity control (e.g.: Pure Food and Drug Act of 1906) is optimal.
3. Counter-advertising by the government is ineffectual because the government much incur costs to air the advertising and the government actions may lead to increased industry level advertising.

The health care industry is one where people pay large amounts of money for accurate information (e.g.: correct diagnoses, assessment of physician or hospital quality, etc.) and other individuals pay large amount of money to breed misinformation (e.g.: false advertising for pharmaceuticals). Understanding the role of information in the health care industry is very important. While the paper analyzed here is only theoretical – it does not give any empirical evidence to back up its mathematics – and the analysis only pertains to information problems with regards to advertising, the study is a step in the right direction towards helping society understand the role of information in the medical field.