Contributions published at Department of Economics (Florian Scheuer)

Deficits in neural processing of reward have been described in both bipolar disorder (BD) and schizophrenia (SZ), but it remains unclear to what extent these deficits are caused by similar mechanisms. Efficient reward processing relies on adaptive coding which allows representing large input spans by limited neuronal encoding ranges. Deficits in adaptive coding of reward have previously been observed across the SZ spectrum and correlated with total symptom severity. In the present work, we sought to establish whether adaptive coding is similarly affected in patients with BD. Twenty-five patients with BD, 27 patients with SZ and 25 healthy controls performed a variant of the Monetary Incentive Delay task during functional magnetic resonance imaging in two reward range conditions. Adaptive coding was impaired in the posterior part of the right caudate in BD and SZ (trend level). In contrast, BD did not show impaired adaptive coding in the anterior caudate and right precentral gyrus/insula, where SZ showed deficits compared to healthy controls. BD patients show adaptive coding deficits that are similar to those observed in SZ in the right posterior caudate. Adaptive coding in BD appeared more preserved as compared to SZ participants especially in the more anterior part of the right caudate and to a lesser extent also in the right precentral gyrus. Thus, dysfunctional adaptive coding could constitute a fundamental deficit in severe mental illnesses that extends beyond the SZ spectrum.

In many markets, firms make their products complex through add-on features, thus making them difficult to evaluate and compare. Does this product obfuscation lure buyers into buying overpriced products, and if so, why does competition not eliminate this practice? More generally, under which conditions can sellers enforce stable obfuscation levels in a competitive environment such that they can increase their profits at the buyers’ expense? We show – based on competitive experimental markets – that add-ons that merely complicate the products render obfuscation quite fragile because buyers display an aversion against complex products. However, if add-ons are surplus-enhancing, sellers can mitigate competition via obfuscation which generates substantial profits and persistent dispersion in headline and add-on prices. Sellers anticipate that obfuscation limits the buyers’ depth and breadth of search, and they exploit this by hiding unattractive product features. Therefore, even the best product in the market is priced above marginal cost and buyers persistently fail to find the best product in the market such that inferior products have a good chance of being traded. We also identify the causal impact of obfuscation opportunities on profits and price dispersion because if we remove obfuscation opportunities, overall prices quickly converge to marginal cost. Thus, surplus-enhancing obfuscation opportunities cause persistent price dispersion, facilitate stable profits and reduce buyers’ share of the surplus.

Die öffentliche Wahrnehmung der Ökonomik stimmt häufig nicht mit der Realität überein. Die Wirtschaftswissenschaft von heute ist weder ideologisch noch verschlossen, sondern stark empirisch und evidenzbasiert ausgerichtet. Patentrezepte indes liefert sie nicht.

We combined established emotion regulation and dietary choice tasks with fMRI to investigate behavioral and neural associations in self-regulation across the two domains in human participants. We found that increased BOLD activity during the successful reappraisal of positive and negative emotional stimuli was associated with dietary self-control success. This cross-task correlation was present in medial and lateral prefrontal cortex as well as the striatum. In contrast, BOLD activity during the food choice task was not associated with self-reported emotion regulation efficacy. These results suggest that neural processes utilized during the reappraisal of emotional stimuli may also facilitate dietary choices that override palatability in favor of healthfulness. In summary, our findings indicate that the neural systems supporting emotion reappraisal can generalize to other behavioral contexts that require reevaluation of rewarding stimuli and outcomes to promote choices that conform with the current goal.

This paper proposes a procedure for assessing sensitivity of inferential conclusions for functionals of sparse high-dimensional models following model selection. The proposed procedure is called targeted undersmoothing. Functionals considered include dense functionals that may depend on many or all elements of the highdimensional parameter vector. The sensitivity analysis is based on systematic enlargements of an initially selected model. By varying the enlargements, one can conduct sensitivity analysis about the strength of empirical conclusions to model selection mistakes. We illustrate the procedure's performance through simulation experiments and two empirical examples.

The widespread use of markets leads to unprecedented material well-being in many societies. We study whether market interaction, as a side effect, erodes moral values. In an influential paper, Falk and Szech (2013) provide experimental data that seem to suggest that “market interaction erodes moral values.” Although we replicate their main treatment effect, we show that additional treatments are necessary to corroborate their conclusion. These treatments reveal that playing repeatedly, and not market interaction, causes the erosion of moral values. Our paper thus shows that neither Falk and Szech's data nor our data support the claim that markets erode morals.

The world trading system is a very complicated network comprised of shipping routes that link many connecting ports or nodes. In such a networked setting, the economics of regulation is challenging because the efficiency of a networked system depends on both the set of active nodes (ports) and the volume of activity flowing through its links (trade). In this Kühne Impact Series, I discuss how a standard environmental policy such as taxing carbon emissions may have the unintended consequence of lowering overall network efficiency. As a result environmental policies need to be designed carefully whenever network interaction effects are large. When they are large and positive, as seems to be the case, then the optimal carbon tax is below the marginal social cost of carbon.

In this Kühne Impact Series, we focus on the distributional effects of climate action. We simulate the distributional effects of a global carbon tax – the optimal economic policy tool in the fight against climate change – with or without international redistribution schemes. Our main result is that the economic costs of climate action are disproportionately borne by poor countries, but that realistic cross-country transfers could remedy this inequality. For example, annual North-South transfers of an average $200 per person would suffice to equalize the economic costs of climate action.

In this Kühne Impact Series we provide a historical perspective on globalizationʼs contribution to climate change, and the historical role of trade in bringing us closer to (or further away from) a sustainable world. We introduce the Sustainable Globalization Index (SGI) that tracks the worldʼs progress towards a Sustainable Globalization scenario. The SGI reveals that globalization has historically diverged from a sustainable pattern of trade until the Great Recession, but is now on a converging trend. The comparison in the recent period suggests that the (green) future of trade and logistics involves more trade from and to the economic North, more intraregional trade, and a shift of trade flows in favor of energy and raw materials and away from agricultural goods.

In this Kühne Impact Series, we continue our effort to understand the role of international trade in the fight against climate change. Our main contribution is to introduce the concepts of environmental comparative advantage and environmental gains from trade. Our main point is that the environmental gains from trade are large so that trade plays a crucial role in the fight against climate change.

Adopting clean energy technology is crucial for reducing emissions and achieving global climate goals. In this Kühne Impact Series, we shed light on the importance of global diffusion of clean technology through international trade. In particular, we highlight China’s expansion in the solar energy sector and its role in bringing down the cost of solar energy worldwide. Our main result is that international trade and globally integrated value chains have dramatically reduced the global average cost of renewable technologies. Keeping markets open to trade is essential for enabling a low-carbon energy transition as it ensures that all countries benefit from the lower cost of clean energy technologies. Moreover, we highlight three potential challenges that represent considerable vulnerabilities for the global diffusion of clean technology: (i) the current geographical concentration in global supply chains, (ii) the US-China and EU-China “Solar Trade War,” and (iii) the global slowdown in high-quality solar energy inventions.

The annual adverse effects of pollution are on the order of 10% of world GDP. Many approaches are used or have been proposed to control the growing pollution problem, but none of them allows for efficient pollution control in settings in which the marginal cost of pollution is increasing and polluters are better informed than regulators about the costs of abatement. We propose a simple primary market mechanism, True-Cost Pay as Bid, that implements efficient pollution control and does not depend on how much information the regulators have about the abatement costs.

Increasing inequality and associated egalitarian sentiments have put redistribution on the political agenda. In this paper, we take advantage of Swiss direct democracy, where people voted several times on strongly redistributive policies in national plebiscites, to study the link between social preferences and a behaviorally validated measure of support for redistribution in a broad sample of the Swiss population. Using a novel nonparametric Bayesian clustering algorithm, we uncover the existence of three fundamentally distinct preference types in the population: predominantly selfish, inequality averse and altruistic individuals. We show that inequality averse and altruistic individuals display a much stronger support for redistribution, particularly if they are more affluent. In addition, we show that previously identified key motives underlying opposition to redistribution – such as the belief that effort is an important driver of individual success – play no role for selfish individuals but are highly relevant for other-regarding individuals. Finally, while inequality averse individuals display strong support for policies that primarily aim to reduce the incomes of the rich, altruistic individuals are considerably less supportive of these policies. Thus, knowledge about the qualitative properties of social preferences and their distribution in the population also provides insights into which preference type supports specific redistributive policies, which has implications for how policy makers may design redistributive packages to maximize political support for them.