Value of Science 201: Monetizing the Value of Information

When people use information to make decisions, we can determine the value of that information by characterizing differences in socioeconomically meaningful outcomes across two worlds: one in which the improved information is available to decisionmakers and one in which the improved information is not available. This idea forms the foundation of the VALUABLES impact assessment framework we learned about in the previous, 100-level Value of Science explainer series. In some cases, these differences in outcomes can be described in nonmonetary terms. When recreational managers used satellite data to inform advisories and closures at Utah Lake as a harmful algal bloom (HAB) impacted the water in 2017, for example, we noted that no people were exposed to this potentially toxic bloom. If managers had not used the satellite data, an estimated 400 people would have gotten sick. Here, the value of the HAB information is expressed as 400 averted illnesses.

In many cases, we also can describe differences in outcomes in monetary terms, a topic we will discuss in more detail in this explainer. In the HAB example, the researchers were able to restate the social benefits associated with the 400 averted illnesses by calculating the health-care costs associated with treating the illnesses. They found that these avoided health-care costs were worth approximately $370,000. Thus, the $370,000 figure represents a monetized estimate of the value of the satellite data that were used to manage the 2017 HAB in Utah Lake.

This type of economic analysis is called cost of illness, and economists have developed many other tools to monetize the value of information. Expressing value in monetary terms can be particularly helpful for an apples-to-apples comparison of the benefits of scientific information and the cost of producing it, which often is already expressed in monetary terms. Monetization also can help us prioritize across scientific projects that have very different kinds of societal benefits. For example, the benefits of a satellite-based decision support tool that improves human health outcomes, and the benefits of a tool that helps reduce deforestation, would be very difficult to compare directly. Monetizing the value of the outcomes in these two applications—the human health improvements and the avoided deforestation—can help us determine which application is more socially beneficial.

Monetizing benefits is a complex and well-studied topic. Although it is beyond the scope of this explainer to provide a full treatment of monetization, we provide a brief summary of methods used to monetize impacts. We also list some benefit categories that are commonly associated with improvements in satellite information, some examples of monetized estimates within those categories, and links to references for further reading.

As we discussed in Value of Science 101, projects, programs, and policies that produce new information can yield societal benefits when the information is used to make decisions. We describe these benefits as the improvements in outcomes that matter to people and the environment. Scientists can quantify these benefits using tools from the field of economics.

The method used to monetize a benefit depends on whether it has market value. As discussed in Value of Science 103, goods and services that are sold in markets carry prices that reflect a balance between the costs of producing those goods and services and what people are willing to pay for them. These market prices are a good indicator of the value of benefits associated with the good or service. Thus, when market prices are available for the good or service that is tied to the outcome of the decision, the monetized value of the improvement in outcomes can be estimated by applying the following steps:

(1) calculate the difference in the number of units of the good or service provided in the reference case and the number of units provided in the counterfactual case, and then

(2) multiply that difference in units to the per-unit market price of that good or service.

This method is what we followed in the example described in Value of Science 103 to characterize the value of more accurate weather information for corn farmers. The benefits of that information can be expressed in terms of the additional bushels of corn produced (relative to what would have been produced without the improved weather information) multiplied by the market price of a bushel of corn.

Most environmental goods and services—such as clean air and water, biodiversity, and human health improvements—are not transacted in markets. Yet they do have value to people, and their benefits often can be characterized in monetary terms, using a range of tools that economists have developed to estimate those benefits. These tools accomplish an analytical task known as nonmarket valuation. Specifically, these tools typically relate nonmarket benefits to market goods that do have prices, and the tools fall into two categories: revealed preference and stated preference.

Revealed preference. People make decisions every day based on how they value nonmarket benefits. Consider the choice to purchase shade-grown coffee to protect rainforest biodiversity, organic products to reduce pesticide exposure, or—to borrow an example from our previous explainer series—a GPS with live traffic info to save time running errands. In all these examples, an individual’s choice to pay or not to pay for the market good (i.e, the coffee, organic product, or GPS device) tells us something about the value that the individual places on a nonmarket benefit (i.e., protection of rainforest diversity, reduction of exposure to pesticides, saving time). Economists have developed many techniques to infer people’s willingness to pay for nonmarket goods and services based on these choices. These revealed preference methods include:

• Travel cost methods. A day at the beach, a hike, a fishing trip: these experiences have value to people, even though the price of admission may be low or nonexistent. Travel cost methods assume that the price of a recreational trip is more appropriately inferred from the cost to travel there and back, including expenses and the opportunity cost of time (commonly expressed as a fixed fraction—from one-third to a whole—of a traveler’s hourly wage).
• Averting behavior method. The averting behavior method infers values for environmental quality by observing the expenditures that people make to protect themselves from perceived health threats—for instance, purchasing an air or water filter to avoid exposure to pollutants. Economists have compared these expenditures with their perceived effectiveness, or with lost time and negative health outcomes, to monetize environmental quality.
• Hedonic price methods: In hedonics, the price of a good or service is understood to reflect the composite value of its many characteristics. Hedonic pricing methods use statistical models to break down these contributions into individual values. In the area of environmental economics, common applications include those that use property values to understand people’s willingness to pay for a beautiful environment and for reduced exposure to pollution (which, in turn, can be used to understand people’s willingness to pay to reduce the risk of morbidity or mortality).

Stated preference. When no data exist to infer people’s willingness to pay for a particular good or service, economists can turn to surveys—or stated preference methods—that ask people directly how much they would pay to maintain or improve a nonmarket good (or, conversely, how much money they would accept for its loss). An important difference between the two methods is that stated preference techniques directly solicit responses about a hypothetical situation, whereas revealed preference techniques are based on observed behavior. Popular stated preference techniques include contingent valuation and choice experiment.

• Contingent valuation. A contingent valuation method typically provides survey respondents with a hypothetical government program that would reduce the likelihood of a future environmental threat, or that would influence some other change in societal outcome. The survey asks respondents what maximum amount they would be willing to pay for the program.
• Choice experiment. In contrast to direct willingness-to-pay questions, stated choice methods ask survey respondents to indicate their top choice, or to rank choices, from a range of policy scenarios.

Each of the methods we have described has its particular data requirements, strengths, and weaknesses. One way to identify which technique (or techniques) would best suit a particular impact assessment is to first look at the type of benefit you are assessing. In Table 1, we pair key benefit categories in each of NASA’s five Applied Science Program areas with commonly used methods to monetize those benefits. We also link to classic examples from the economics literature and resources for further reading. Table 2 shows other key benefit categories and methods of monetizing those benefits.

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