A dataset does not speak for itself, and model assumptions can drive results just as much as the data. Limited transparency about model assumptions creates a problem of asymmetric information between analyst and reader. This chapter shows how we need better methods for robust results.

Multiverse analysis is not simply a computational method but also a philosophy of science. In this chapter we explore its core tenets and historical foundations. We discuss the foundational principle of transparency in the history of science and argue that multiverse analysis brings social science back into alignment with this core founding ideal. We make connections between this framework and multiverse concepts developed in cosmology and quantum physics.

In chapter 7, Releasing the BIS credit (May 29 - June 5), the BIS credit of 150 million schilling is released to the ANB as a moratorium is averted and a guarantee. Meantime, the issue of an Austrian government loan, re-emerges and it becomes clear that the French may not be able to or wanting to take the lead in organizing the loan. In Basel, the BIS is getting ready for the upcoming board and governors’ meeting, where the decision about another credit to the ANB will have to be discussed. Rodd prepares several notes and a plan for the meeting.

Chapter 8 delves into the complexities introduced by asymmetric information, where some contestants possess more information than others, or neither of the contestants has complete information about the characteristics of the others. The chapter examines contests in which the true common value of the prize may be unknown to certain contestants, such as an incumbent having a better understanding of the value of office than a challenger, or a current resource owner having more information about its true value than potential entrants. It also examines situations where no contestant has complete information about the value assigned for each contestant to the prize, such as companies competing to develop a new product or technology. Each company knows its own valuation of the potential market but does not know the competitor’s valuation. The chapter also analyzes the existence and properties of equilibrium and other related questions, such as the following: How do outcomes in complete and incomplete information scenarios compare? Should a well-informed planner disclose information to maximize total effort in a contest involving both informed and uninformed contestants?

Human minds are particularly biased when processing information in digital environments. Behavioral economics has highlighted many cognitive biases that afflict our economic decision making. We may choose people like ourselves for important jobs or we may focus on irrelevant characteristics. We may also focus on recent, available information because our brains interpret that as more relevant for the current situation, whereas, optimally, we might benefit from a deeper dive into collecting more representative or comprehensive data and analyzing it appropriately. Even the way information is presented influences whether we believe it. Designers of digital content and experiences need to be aware of and account for such biases when engaging users.

Online marketplaces have permeated many aspects of our lives, as we use them to procure goods and services of all sorts, and many have relied on them during the COVID-19 lockdowns. Both sides of the market must feel comfortable trusting each other for online marketplaces to thrive, and for that, they need to have safeguards that alleviate the problems caused by asymmetric information. In this chapter I explain how feedback and reputation systems work in practice, and how they support ecommerce in online marketplaces. It starts by covering the theory behind reputation mechanisms and how they support more efficient trade, followed by descriptions of the actual working of typical online feedback and reputation systems. A survey of empirical findings from a host of papers is presented that explore how reputation works in actual online marketplaces, and how these relate to the theory. I then highlight some of the shortcomings of feedback systems and offer some suggestions and considerations for the future design of feedback and reputation systems that can augment their effectiveness.

Chapter 3 lays out the book’s central theory as well as the theory’s observable implications. It argues that powerful producers seek to use their privileged knowledge of the risks and benefits of their products (and regulators’ dependence on that knowledge) to systematically push their own out-of-patent products and those of generic sellers off the market via regulation, in favor of more expensive, patented alternatives. Producers accomplish this first by strategically revealing negative information about out-of-patent products as a means of convincing regulators that these products require stricter regulations. Second, producers support regulatory institutions that require existing products to be reevaluated under a precautionary standard, meaning that failure to prove an existing product is safe leads to the assumption it is dangerous. These precautionary institutions help innovative producers eliminate out-of-patent products more systematically, allowing them to acquire stricter standards not via the provision of damaging information, which carries some reputational risks, but through the withholding of favorable information. This chapter also lays out expectations for where we might expect these precautionary institutions to be adopted, given the distribution of preferences across countries, and it shows why such precautionary institutions should tend to be supported by developed countries and opposed by developing ones. Finally, the chapter argues that because international standard-setters ought to be susceptible to the same sorts of information problems as domestic regulators, and given the distribution of national power within these organizations, we can expect international standard-setters to replicate the precautionary institutional preferences of their wealthier members. We can additionally expect this to create the same tendency on the part of international standard-setters to arbitrarily impose stricter standards on more affordable products, despite the fact that this creates trade barriers that disadvantage poorer members and that directly conflict with these standard-setters’ stated mission.

Chapter 1 provides an introduction to the book. Motivating the book with examples of various regulatory barriers to agricultural trade that have proven particularly contentious, this chapter asks what might explain these barriers and whether we should expect current international solutions to resolve them. The chapter provides a brief overview of the book’s argument regarding how producers leverage private information to acquire the sorts of regulatory barriers that the opening examples describe. In addition, it previews the book’s main contribution and gives a brief chapter outline.

This chapter sets the stage for the remainder of the book by providing a broad overview of the sorts of information asymmetries that exist between producers of potentially dangerous products and those who are tasked with regulating them. Leveraging insights from a diverse set of industries -- aerospace, direct-to-consumer products, pharmaceuticals, and industrial chemicals -- and spanning a wide range of countries, this chapter establishes the surprising degree to which regulators not only are at a disadvantage relative to firms when it comes to acquiring information about product risk but also, as a result, depend on firms to be the primary source of information required to regulate. The chapter then investigates the conditions under which this might allow producers to influence the timing and direction of regulatory change. After establishing the pervasiveness of information asymmetries and dependencies at the domestic level, as well as the resulting opportunities for regulatory bias, the chapter demonstrates why we should expect the very same information asymmetries and biases to be replicated and even exacerbated at the international level.

After establishing why people migrate, in this chapter we turn to an investigation of how migrants economically re-engage with their homeland. Specifically, we explore how migrants facilitate flows of international financial capital. We argue that migrants, because they possess critical knowledge about investment opportunities in their homelands, help international investors overcome information asymmetries which drives both portfolio and foreign direct investment into their homelands. Our empirical analyses leverage a wide range of data on migrant stocks and portfolio and foreign direct investment to test our argument. We find that migrants are key to explaining international capital flows, especially in environments where formal political institutions that protect property rights are absent or weak.