Frictions or Mental Gaps: What’s Behind the Information We (Don’t) Use and When Do We Care?

Bridging the gap: Experimental evidence on information provision and health insurance choices

Previous research has shown that individuals do not always make rational decisions when selecting their health insurance, for example, due to the existence of information frictions or mental gaps. We study the effect of specific types of information provision for decision support on health plan choices and test their potential to improve decision quality by implementing a randomized laboratory experiment. We provide personalized and generic aids, differentiate between numerical and visual decision support, and provide one or two optional formats of personalized information. We find that generic aids have no effect on health plan choices while personalized information leads to better choices as measured by several indicators of decision quality. The largest effects were observed for those who "opted in" to visualize personalized information, with immediate and lasting improvements in health insurance decisions. By reducing information frictions, our results suggest that accessible and easy-to-use tools can positively impact health insurance navigation, improve decision-making, and reduce switching costs.

Experimental Evidence on the Effectiveness of Nonexperts for Improving Vaccine Demand

We experimentally vary signals and senders to identify which combination will increase vaccine demand among a disadvantaged population in the United States-Black and White men without a college education. Our main finding is that laypeople (nonexpert concordant senders) are most effective at promoting vaccination, particularly among those least willing to become vaccinated. This finding points to a trade-off between the higher qualifications of experts on the one hand and the lower social proximity to low-socioeconomic-status populations on the other hand, which may undermine credibility in settings of low trust.

Information Avoidance and Image Concerns

A rich literature finds that individuals avoid information and suggests that avoidance is driven by image concerns. This paper provides the first direct test of whether individuals avoid information because of image concerns. We build on a classic paradigm, introducing control conditions that make minimal changes to eliminate the role of image concerns while keeping other key features of the environment unchanged. Data from 6,421 experimental subjects shows that image concerns play a role in driving information avoidance, but a role that is substantially smaller than one might have expected.

The Behavioral Foundations of Default Effects: Theory and Evidence from Medicare Part D

We show in two natural experiments that default rules in Medicare Part D have large, persistent effects on enrollment and drug utilization of low-income beneficiaries. The implications of this phenomenon for welfare and optimal policy depend on the sensitivity of passivity to the value of the default option. Using random assignment to default options, we show that beneficiary passivity is extremely insensitive, even when enrolling in the default option would result in substantial drug consumption losses. A third natural experiment suggests that variation in active choice is driven by random transitory shocks rather than the inherent attentiveness of some beneficiaries.

The Design of the RAND Health Insurance Experiment: A Retrospective

This article, prepared as part of a special issue on multiarmed experiments, describes the design of the RAND Health Insurance Experiment, paying particular attention to the choice of arms. It also describes how the results of the Experiment were used in a simulation model and, looking back, how the design might have differed, and how the results apply today, 4 decades after the Experiment was conducted.

Competition in network industries: Evidence from the Rwandan mobile phone network

This article analyzes the potential for competition policy to affect welfare and investment in a network industry. When a network is split between competitors, each internalizes less network effects, but may still invest to steal customers. I structurally estimate consumers' utility from adopting and using mobile phones, with transaction data from nearly the entire Rwandan network. I simulate the equilibrium choices of consumers and network operators. Adding a competitor earlier could have reduced prices and increased incentives to invest in rural towers, increasing welfare by the equivalent of 1% of GDP. However, forcing free interconnection can lower incentives to invest.

Can the updated nutrition facts label decrease sugar-sweetened beverage consumption?

Sugar-sweetened beverages are the primary source of added sugar consumption in the U.S, and the Food and Drug Administration recently updated the Nutrition Facts Label to communicate the amount of added sugars in manufactured food. The changes to the Nutrition Facts Label (NFL) is concurrent with some cities implementing policies that place an excise tax on sugar-sweetened beverages. While sugar-sweetened beverages taxes may be effective at changing quantity demanded, the updated NFL has the potential to shift the demand curve by decreasing friction and mental gaps associated with the communication of nutrition information. We conducted a randomized control trial using eye tracking technology to determine if the updated NFL garnered more visual attention or affected beverage choice. Participants were also exposed to an information intervention to determine if the updated NFL affected choice after receiving information about added sugars. We found that consumers were more visually attentive to nutrition information displayed by the updated NFL; however, viewing the updated label did not affect choice of beverages nor did it improve the effectiveness of the dietary information on subsequent choices.

Adopting robot lawyer? The extending artificial intelligence robot lawyer technology acceptance model for legal industry by an exploratory study

The development of artificial intelligence has created new opportunities and challenges in industries. The competition between robots and humans has elicited extensive attention among legal researchers. In this exploratory study, we addressed issues regarding the introduction of robots to the practice of legal service through a semistructured interviews with lawyers, judges, artificial intelligence experts, and potential clients. An extended robot lawyer technology acceptance model with five facets and 11 elements is proposed in this study. This model highlights two dimensions: ‘legal use’ and ‘perception of trust.’ In summary, this study provides new specific implications and exhibits three characteristics, namely, derivative, macroscopic, and instructive, in the legal services with artificial intelligence. In addition, artificial intelligence robot lawyers are being developed with some of the abilities necessary to substitute for human beings. Nevertheless, working with human lawyers is imperative to produce benefits from this type of reciprocity.