Ambiguity aversion under maximum-likelihood updating

Maximum likelihood updating (MLU) is a well-known approach for extending static ambiguity sensitive preferences to dynamic set-ups. This paper develops an example in which MLU induces an ambiguity averse maxmin expected utility (MEU) decision-maker to (i) prefer a bet on an ambiguous over a risky urn and (ii) be more willing to bet on the ambiguous urn compared to an (ambiguity neutral) subjective expected utility (SEU) decision-maker. This is challenging since prior to observing (symmetric) draws from the urns, the MEU decision-maker (in line with the usual notion of ambiguity aversion) actually preferred the risky over the ambiguous bet and was less willing to bet on the ambiguous urn than the SEU decision-maker. The identified switch in betting preferences is not due to a violation of dynamic consistency or consequentialism. Rather, it results from MLU's selection of extreme priors, causing a violation of the stability of set-inclusion over the course of the updating process

Learning under Ambiguity - A Note on the Belief Dynamics of Epstein and Schneider (2007)

Epstein and Schneider (2007) develop a framework of learning under ambiguity, generalizing maxmin preferences of Gilboa and Schmeidler (1989) to intertemporal settings. The specific belief dynamics in Epstein and Schneider (2007) rely on the rejection of initial priors that have become implausible over the learning process. I demonstrate that this feature of ex-post rejection of theories gives rise to choices that are in sharp contradiction with ambiguity aversion. Concrete, the intertemporal maxmin decision-maker equipped with such belief dynamics prefers, under prevalent conditions, a bet in an ambiguous urn over the same bet in a risky urn. I offer two modifications of their framework, each of which is capable of avoiding this anomaly

Strategic Conflicts on the Horizon: R&D Incentives for Environmental Technologies

Technological innovation is a key strategy for tackling environmental problems. The required R&D expenditures however are substantial and fall on self-interested countries. Thus, the prospects of successful innovation critically depend on innovation incentives. This paper focuses on a specific mechanism for strategic distortions in this R&D game. In this mechanism, the outlook of future conflicts surrounding technology deployment directly impacts on the willingness to undertake R&D. Apart from free-riding, a different deployment conflict with distortive effects on innovation may occur: Low deployment costs and heterogeneous preferences might give rise to 'free-driving'. In this recently considered possibility (Weitzman 2012), the country with the highest preference for technology deployment, the free-driver, may dominate the deployment outcome to the detriment of others. The present paper develops a simple two stage model for analyzing how technology deployment conflicts, free-riding and free-driving, shape R&D incentives of two asymmetric countries. The framework gives rise to rich findings, underpinning the narrative that future deployment conflicts pull forward to the R&D stage. While the outlook of free-riding unambiguously weakens innovation incentives, the findings for free-driving are more complex, including the possibility of super-optimal R&D and incentives for counter-R&D

Precision requirements in pesticide risk assessments: Contrasting value-of-information recommendations with the regulatory practice in the EU

Pesticides, while rendering immense agricultural benefits, potentially entail risks to human health and the environment. To limit these risks, market approval of a pesticide is typically conditional on an extensive risk assessment demonstrating its safety. The associated testing procedures, often involving significant numbers of animals, however are not only costly; as has become apparent from recent discussions about the active substance glyphosate, testing is often incapable of providing definitive answers on concerns like human carcinogenicity. An important regulatory task, whether explicitly acknowledged or not, is hence to decide what level of remaining uncertainty is deemed acceptable in making the final market approval decision. Economic principles suggest a value-of-information (VoI) approach for this informational task. After presenting the basics of the VoI framework, this paper analyzes the actual regulatory practice in the EU's pesticide approval process, pointing out the defaults and substance-specific procedures that shape the precision of the European Food Safety Authority's (EFSA) risk assessment and hence the level of knowledge under which the European Commission decides on the approval of substances. The comparison between theory and practice uncovers substantial deviations, providing valuable insights for restructuring the risk assessment guidelines

Informativeness of Experiments for MEU - A Recursive Definition

The well-known Blackwell's theorem states the equivalence of statistical informativeness and economic valuableness. Celen (2012) generalizes this theorem, which is well-known for subjective expected utility (SEU), to maxmin expected utility (MEU) preferences. We demonstrate that the underlying definition of the value of information used in Celen (2012) is in contradiction with the principle of recursively defined utility. As a consequence, Celen's framework features dynamic inconsistency. Our main contribution consists in the definition of a value of information for MEU preferences that is compatible with recursive utility and thus respects dynamic consistency

Risk Assessment under Ambiguity: Precautionary Learning vs. Research Pessimism

Agencies charged with regulating complex risks such as food safety or novel substances frequently need to take decisions on risk assessment and risk management under conditions of ambiguity, i.e. where probabilities cannot be assigned to possible outcomes of regulatory actions. What mandates should society write for such agencies? Two approaches stand out in the current discussion. One charges the agency to apply welfare economics based on expected utility theory. This approach underpins conventional cost-benet analysis (CBA). The other requires that an ambiguity-averse decision-rule - of which maxmin expected utility (MEU) is the best known - be applied in order to build a margin of safety in accordance with the Precautionary Principle (PP). The contribution of the present paper is a relative assessment of how a CBA and a PP mandate impact on the regulatory task of risk assessment. In our parsimonious model, a decision maker can decide on the precision of a signal which provides noisy information on a payoff-relevant parameter. We find a complex interplay of MEU on information acquisition shaped by two countervailing forces that we dub 'Precautionary Learning' and 'Research Pessimism'. We find that - contrary to intuition - a mandate of PP rather than CBA will often give rise to a less informed regulator. PP can therefore lead to a higher likelihood of regulatory mistakes, such as the approval of harmful new substances

Five Essays in the Economics of Climate Engineering, Research, and Regulation under Uncertainty

This thesis revolves around two of the most prominent strategies for tackling environmental problems. One is technological innovation with a focus on Climate Engineering technologies, mostly Solar Radiation Management (SRM) (Crutzen 2006; Keith 2013). The other is regulatory decision-making under fundamental uncertainty. Research and learning are intimately linked with both strategies, thus playing a connecting role in this dissertation. Methodologically, this thesis takes a theoretical approach, combining modern environmental economics with recent developments in decision theory and the literature on regulation. The first part of this thesis advances the current state of knowledge on technological solutions to environmental problems, taking Climate Engineering technologies as an illustration. The focus here is on the implications of specific strategic conflicts on the incentives to develop SRM technologies with costly R&D. The two dimensions of strategic conflict analyzed are the intergenerational conflict among generations when the generation providing the technology for a future generation anticipates that the way the technology will be used is different from its own preferred profile (“The Intergenerational Transfer of Solar Radiation Management Capabilities and Atmospheric Carbon Stocks”) and the intragenerational conflict among countries that have different preferences for the amount of global cooling (“Free rider vs. free driver – R&D incentives for environmental technologies”). The findings can be summarized as follows: First, the intergenerational strategic conflict that results if a current generation cannot stipulate the specific use of SRM technologies can give rise to a rich set of outcomes in terms of R&D decision and abatement efforts, including the ban of SRM, abatement collapse, but also the development of SRM accompanied by an increase in abatement efforts in order to nudge future generation towards a specific use of the technology. Second, the anticipation of strategic conflicts between countries can give rise to suboptimal low or suboptimal high investments in R&D, depending on whether the expected strategic conflict in the deployment profile of the Climate Engineering technology is a standard free-rider or a free-driver conflict; the latter occurs if one country chooses high levels of SRM and thus imposes an externality on other countries (Weitzman 2012). The second part of this thesis focuses on regulatory decisions under uncertainty for which the standard expected utility framework is inadequate. This may happen if the matter of regulation involves complex processes or novel substances and thus requires a description of knowledge that goes beyond a unique probability distribution formulation. A well-known alternative are multiple prior models (static and dynamic axiomatizations were provided by Gilboa and Schmeidler 1989 and Epstein and Schneider 2003/2007, respectively). The third and fourth paper in this thesis overcome shortcomings in the existing decision-theoretic literature on multiple prior by establishing a consistent notion of the value of information (“Informativeness of Experiments for MEU – A Recursive Definition”) and well-behaved learning dynamics (“Learning Under Ambiguity – A Note on the Belief Dynamics of Epstein and Schneider (2007)”) for maxmin expected utility (MEU) preferences, a well-established ambiguity averse decision rule widely used to model precaution (Vardas and Xepapadeas 2010; Heal and Millner 2013). These decision-theoretical contributions stand for themselves, but also build the ground for the main paper in this part (“Information acquisition under Ambiguity – Why the Precautionary Principle may keep us uninformed”). This paper connects learning and technology choices by focusing on regulatory settings like the approval of a new pesticide in which ambiguous scientific knowledge can be reduced by the regulator by means of (costly) research, for instance with animal testing. In decision-theoretic terms, this paper analyzes active learning under ambiguity and is, to our knowledge, the first model to do so. We find a complex and surprising interplay of the maxmin rule and the research behavior of the regulator: Our results suggest that, despite its notion of precaution, the maxmin rule often leads to an underinvestment in research relative to a standard expected utility regulation, giving rise to a counterintuitive increase in erroneous regulatory decisions (for instance the approval of harmful pesticides). Jointly, the five papers in this thesis contribute to theoretical environmental economics by furthering our knowledge on the role of learning when science is uncertain, on the role of technologies, and on the interplay between technological solutions and uncertainty

The Intergenerational Transfer of Solar Radiation Management Capabilities and Atmospheric Carbon Stocks

Solar radiation management (SRM) technologies are considered one of the likeliest forms of geoengineering. If developed, a future generation could deploy them to limit the damages caused by the atmospheric carbon stock inherited from the current generation, despite their negative side effects. Should the current generation develop these geoengi-neering capabilities for a future generation? And how would a decision to develop SRM impact on the current generation's abatement efforts? Natural scientists, ethicists, and other scholars argue that future generations could be more sanguine about the side effects of SRM deployment than the current generation. In this paper, we add economic rigor to this important debate on the intergenerational transfer of technological capabilities and pollution stocks. We identify three conjectures that constitute potentially rational courses of action for current society, including a ban on the development of SRM. How-ever, the same premises that underpin these conjectures also allow for a novel possibility: If the development of SRM capabilities is sufficiently cheap, the current generation may for reasons of intergenerational strategy decide not just to develop SRM technologies, but also to abate more than in the absence of SRM

Strategic implications of counter-geoengineering: clash or cooperation?

Solar geoengineering has received increasing attention as an option to temporarily stabilize global temperatures. A key concern is that heterogeneous preferences over the optimal amount of cooling combined with low deployment costs may allow the country with the strongest incentive for cooling, the so-called free-driver, to impose a substantial externality on the rest of the world. We analyze whether the threat of counter-geoengineering technologies capable of negating the climatic effects of solar geoengineering can overcome the free-driver problem and tilt the game in favour of international cooperation. Our game-theoretical model of countries with asymmetric preferences allows for a rigorous analysis of the strategic interaction surrounding solar geoengineering and counter-geoengineering. We find that counter-geoengineering prevents the free-driver outcome, but not always with benign effects. The presence of counter-geoengineering leads to either a climate clash where countries engage in a non-cooperative escalation of opposing climate interventions (negative welfare effect), a moratorium treaty where countries commit to abstain from either type of climate intervention (indeterminate welfare effect), or cooperative deployment of solar geoengineering (positive welfare effect). We show that the outcome depends crucially on the degree of asymmetry in temperature preferences between countries

Modelling the butterfat crystallisation process

Milk fat exhibits seasonal variations in composition and properties which are undesirable for many subsequent applications. Thus techniques are sought to process dairy products in order to achieve a consistent quality. A brief introduction to milk fat presents its most important particularities, especially composition, seasonal variations, solid fat content, crystalisation and polymorphism. The differential scanning calorimetry (DSC) analysis allows to estimate the solid fat content. Different methods have been developed to estimate more and more precisely the solid fat content which is certainly an important parameter in the description of the textural properties of butterfat. The industrial crystallisation process is modelled on the basis of pilot plant data. That model allows to approach the particular temperature profile in the scraped surface heat exchangers and to give a first explanation of the involved phenomena