Some information is beneficial; it makes people’s lives go better. Some information is harmful; it makes people’s lives go worse. Some information has no welfare effects at all; people neither gain nor lose from it. Under prevailing executive orders, federal agencies must investigate the welfare effects of information by reference to cost-benefit analysis. Federal agencies have (1) claimed that quantification of benefits is essentially impossible; (2) engaged in “breakeven analysis”; (3) projected various endpoints, such as health benefits or purely economic savings; and (4) relied on private willingness to pay for the relevant information. All of these approaches run into serious objections. With respect to (4), people may lack the information that would permit them to make good decisions about how much to pay for (more) information; they may not know the welfare effects of information. Their tastes and values may shift over time, in part as a result of information. These points suggest the need to take the willingness-to-pay criterion with many grains of salt, and to learn more about the actual effects of information, and of the behavioral changes produced by information, on people’s experienced well-being.
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For an important decision upholding a refusal to quantify benefits, on the ground that quantification was not feasible, see Investment Co. Institute v. Commodity Futures Trading Commission (U.S. Court of Appeals for the D.C. Circuit 2013). In the context of disclosure, the leading decision is National Association of Manufacturers v. SEC (U.S. Court of Appeals for the D.C. Circuit 2014), which upheld against arbitrariness review a regulation that would require disclosure of the use of “conflict minerals”:
An agency is not required “to measure the immeasurable,” and need not conduct a “rigorous, quantitative economic analysis” unless the statute explicitly directs it to do so. Here, the rule’s benefits would occur half-a-world away in the midst of an opaque conflict about which little reliable information exists, and concern a subject about which the Commission has no particular expertise. Even if one could estimate how many lives are saved or rapes prevented as a direct result of the final rule, doing so would be pointless because the costs of the rule—measured in dollars—would create an apples-to-bricks comparison. Despite the lack of data, the Commission had to promulgate a disclosure rule.
Quoting Investment Co. Institute v. Commodity Futures Trading Commission (U.S. Court of Appeals for the D.C. Circuit 2013).
For a useful discussion in an especially controversial area, see Levy et al. (2016).
For example, according to the U.S. Environmental Protection Agency and U.S. Department of Transportation (2011), speaking of new fuel economy labels:
The agencies recognize that Executive Order 13563 directs agencies “to use the best available techniques to quantify anticipated present and future benefits as accurately as possible.” In this context, however, quantitative information is not available, and the agencies have therefore chosen instead to continue with a qualitative assessment of benefits. It is difficult to develop a good baseline for the fleet using the existing label, partly because the existing label is not designed to incorporate advanced technology vehicles. It is even more difficult to develop a comparison for the fleet with the new labels, because the effects of label designs on vehicle purchases are not known. Thus, any assessment of quantitative effects of label design on vehicle sales involves a great deal of speculation. The agencies believe that informed choice is an end in itself, even if it is hard to quantify; the agencies also believe that the new labels will provide significant benefits for consumers, including economic benefits, though these benefits cannot be quantified at this time.
In short, “The primary benefits associated with this rule are associated with improved consumer decision-making resulting from improved presentation of information. At this time, EPA and NHTSA do not have data to quantify these impacts” (U. S. Environmental Protection Agency & U.S. Department of Transportation 2011).
The defining work here comes from W. Kip Viscusi. See Viscusi (2018); many people draw on his research. See, e.g., Thomson and Monje (2015) explaining, “On the basis of the best available evidence, this guidance identifies $9.4 million as the value of a statistical life.” See also Sunstein (2014), providing the underlying theory and a discussion of how “agencies . . . assign monetary values to the human lives that would be saved by a proposed regulation.”
See Loureiro et al.’s (2006, p. 263) finding that “on average, consumers are willing to pay close to 11% above the initial price to obtain cookies with nutritional labelling.” Further, “Consistent with prior expectations, our results also indicate a difference between the [willingness-to-pay] of individuals suffering from diet-related health problems (estimated mean 13%) and those who do not suffer any diet-related health problems (estimated mean 9%)” (Loureiro et al. 2006, p. 249).
In the words of the FDA (2014, p. 64),
To our knowledge, Abaluck (2011) is the only study that translates the potential effect of increasing nutrition information on consumption into estimates of welfare gains using willingness-to-pay based on revealed preferences (Ref. 43). This study uses the variation in nutrition information generated by Nutrition Labeling and Education Act (NLEA) as a method to determine how changes in individuals’ beliefs about nutrient content affect consumption decisions. The differential changes in nutrition information across food categories, measured in units of calories per gram, allow the study to identify a general model of food demand as a function of nutrient characteristics that accounts for the total daily diet, prior beliefs about nutrient content, and preferences, including willingness to substitute across food categories.
As before, however, the willingness-to-pay criterion may run into normative objections, even from the standpoint of welfare. See generally Bronsteen et al. (2015) raising questions about willingness to pay in view of people’s occasional failure to know what will promote their welfare.
See U.S. Food and Drug Administration (2011) noting the longer lifespans, fewer cancers and diseases, as well as increased property and monetary values of non-smokers. See also U.S. Department of Labor (2016) requiring that employees have access to OSHA logs, and U.S. Environmental Protection Agency and U.S. Department of Transportation (2011) explaining, “The agencies believe that informed choice is an end in itself, even if it is hard to quantify; the agencies also believe that the new labels will provide significant benefits for consumers, including economic benefits, though these benefits cannot be quantified at this time.” Finally, see U.S. Food and Drug Administration (2014, p. 11) explaining, “The final rule may also assist consumers by making the long-term health consequences of consumer food choices more salient and by providing contextual cues of food consumption.”
See U.S. Court of Appeals for the D.C. Circuit (2015) explaining, “The Commission was ‘unable to readily quantify’ the ‘compelling social benefits’ the rule was supposed to achieve: reducing violence and promoting peace and stability in the Congo,” quoting U.S. Securities and Exchange Commission (2012).
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Robert Walmsley University Professor, Harvard University. In some places, this essay draws on Cass R. Sunstein, On Mandatory Labeling, With Special Reference to Genetically Modified Foods, 165 U. Pa. L. Rev. 1043 (2017). I am grateful to Hunt Allcott, Oren Bar-Gill, George Loewenstein, and Tali Sharot for valuable discussions, Ralph Hertwig and W. Kip Viscusi for excellent comments, Andrew Heinrich and Cody Westfall for superb research assistance. Thanks too to audiences at Carnegie-Mellon University, Microsoft, New York University, and Vanderbilt University for terrific suggestions.
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Sunstein, C.R. Ruining popcorn? The welfare effects of information. J Risk Uncertain 58, 121–142 (2019). https://doi.org/10.1007/s11166-019-09300-w
- Behavioral economics
- Willingness to pay
- Hedonic forecasting errors
- Welfare effects
- Information avoidance
- Present bias
- Information disclosure