Human existence faces a series of catastrophic risks at a global level, including pandemics, climate catastrophes, or nuclear and bioterrorism. It is widely recognized that mitigating these risks include important social choices (such as, reducing economic growth), incentive design and coordination, and innovation (Nordhaus, 2019). Amongst these, innovation is particularly appealing. While the other two simply solve an externality by internalizing the costs of climate impact, innovation can directly reduce the risks, adapt to new changes, or stop them all-together. At the center of this promise stands the option of connecting innovators to climate problems, and learning who and when do they care about them. Yet, to date, little evidence exist on this topic. The purpose of this paper is to use a novel pre-registered experiment to understand the ways in which innovators display interest around several parameters of catastrophic risks, by focusing specifically on the risk of climate change.
We will perform a randomized control trial sending messages to a series of high profile innovators to get them to click to learn more about the MIT Solve challenge related to climate change. In these messages, we will vary use a two-by-two design where we include a phrase around the human cost of global warming. We will vary the time of this cost (i.e., framed as a present or future cost), and its magnitude in terms of the estimated number of human lives affected. This will allow us to separate two fundamental parameters of the human 'preferences' for solving global catastrophes, namely time preferences and the magnitude effect.
Our study will use two samples, innovators and non-innovators. The innovator sample will be individuals who have been approved by the US government for a Small Business Innovation Research grant (SBIR) or a Small Business Technology Transfer grant (STTR) in recent years. These represent highly innovative technologies that the US government agencies directly provide financial support for the subsequent development. The grantees include the inventor (principal investigator) and the manager (business contact) at each firm, who are listed publicly on the SBIR website by the U.S. government from which we have downloaded the data. We intend to email these individuals messages using one of four treatments. We will then track outcome variables reflective of their interest such as: a) whether they click, b) how long do they stay in the Solve website, and c) whether they eventually submit an application. The non-innovator sample will be a general population sample in the U.S. This sample will be recruited through Amazon Mechanical Turk and paid market price to see one of four treatment messages and respond with their interest by clicking and answering a survey questionnaire.
We expect to find that, on average, individuals discount catastrophic risks that are further into the future, and that they will be more interested as the magnitude of the risk increases. We are also interested in the heterogeneous treatment effects across different types of individuals, namely inventors, managers, and inventor-managers in the innovator sample as well as general populations in the non-innovator sample.