Lydia Hellrung, Matthias Kirschner, James Sulzer, Ronald Sladky, Frank Scharnowski, Marcus Herdener, Philippe Tobler, Individual differences in the mechnistic control of the dopaminergic midbrain, In: bioRxiv, No. 863639, 2019. (Working Paper)
The dopaminergic midbrain is associated with elementary brain functions, such as reward processing, reinforcement learning, motivation and decision-making that are often disturbed in neuropsychiatric disease. Previous research has shown that activity in the dopaminergic midbrain can be endogenously modulated via neurofeedback, suggesting potential for non-pharmacological interventions. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we used non-invasive modulation of the dopaminergic midbrain activity by real-time neurofeedback to examine how self-modulation capability affects transfer and correlated activation across the brain. In addition, to further elucidate potential mechanisms underlying successful self-regulation, we studied individual prediction error coding during neurofeedback training, and, during a completely independent monetary incentive delay (MID) task, individual reward sensitivity. Fifty-nine participants underwent neurofeedback training either in a veridical or inverted feedback group. Post-training activity within the cognitive control network was increased only in those individuals with successful self-regulation of the dopaminergic midbrain during neurofeedback training. Successful learning to regulate was accompanied by decreasing prefrontal prediction error signals and increased prefrontal reward sensitivity in the MID task. Our findings suggest that the cognitive control network contributes to successful transfer of the capability to upregulate the dopaminergic midbrain. The link of dopaminergic self-regulation with individual differences in prefrontal prediction error and reward sensitivity indicates that reinforcement learning contributes to successful top-down control of the midbrain. Our findings therefore provide new insights in the cognitive control of dopaminergic midbrain activity and pave the way to improving neurofeedback training in neuropsychiatric patients. |
|
Andreea O Diaconescu, Madeline Stecy, Lars Kasper, Christopher J Burke, Zoltan Nagy, Christoph Mathys, Philippe Tobler, Neural arbitration between social and individual learning systems, In: bioRxiv, No. 857862v1, 2019. (Working Paper)
Decision making often requires integrating self-gathered information with information acquired from observing others. Depending on the situation, it may be beneficial to rely more on one than the other source, taking into account that either information may be imprecise or deceiving. The process by which one source is selected over the other based on perceived reliability, here defined as arbitration, has not been fully elucidated. In this study, we formalised arbitration as the relative reliability (precision) of predictions afforded by each learning system using hierarchical Bayesian models. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and self-sampled outcomes. The number of points participants wagered on their predictions reflected arbitration: The higher the relative precision of one learning system over the other and the lower the intention volatility, the more points participants wagered on a given trial. Functional neuroimaging demonstrated that the arbitration signal was independent of decision confidence and involved modalityspecific brain regions. Arbitrating in favour of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain whereas arbitrating in favour of social information engaged ventromedial prefrontal cortex and the temporoparietal junction. These findings are in line with domain specificity and indicate that relative precision captures arbitration between social and individual learning systems at both the behavioural and neural level. |
|
Giuseppe Ugazio, Marcus Grüschow, Rafael Polania, Claus Lamm, Philippe Tobler, Christian Ruff, Neuro-computational foundations of moral preferences, In: bioRxiv, No. 801936, 2019. (Working Paper)
Moral preferences pervade many aspects of our lives, dictating how we ought to behave, whom we can marry, and even what we eat. Despite their relevance, one fundamental question remains unanswered: Where do individual moral preferences come from? It is often thought that all types of preferences reflect properties of domain-general neural decision mechanisms that employ a common “neural currency” to value choice options in many different contexts. This assumption, however, appears at odds with the observation that many humans consider it intuitively wrong to employ the same scale to compare moral value (e.g., of a human life) with material value (e.g., of money). In this paper, we directly challenge the common-currency hypothesis by comparing the neural mechanisms that represent moral and financial subjective values. In a study combining fMRI with a novel behavioral paradigm, we identify neural representations of the subjective values of human lives or financial payoffs by means of structurally identical computational models. Correlating isomorphic model variables from both domains with brain activity reveals specific patterns of neural activity that selectively represent values in the moral (in the rTPJ) or financial (in the vmPFC) domain. Thus, our findings show that human lives and money are valued in distinct neural currencies, supporting theoretical proposals that human moral behavior is guided by processes that are distinct from those underlying behavior driven by personal material benefit. |
|
Björn Lindström, Martin Bellander, Allen Chang, Philippe Tobler, David M Amodio, A computational reinforcement learning account of social media engagement, In: PsyArXiv Preprints, No. 78mh5, 2019. (Working Paper)
Social media has become the modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (“likes”), which turns the online world into a “Skinner Box” for the modern human. Yet despite such common portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. We applied a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyzed over one million posts from over 4,000 individuals on several social media platforms, using computational models based on reward reinforcement learning theory. Our results consistently show that human behavior on social media qualitatively and quantitatively conforms to the principles of reward learning. Results further reveal meaningful individual differences in social reward learning on social media, explained in part by variability in users’ tendency for social comparison. Together, these findings support the social reinforcement learning view of social media engagement and offer key new insights into this emergent mode of modern human behavior on an unprecedented scale. |
|
Hans-Joachim Voth, Sebastian Klaus Dörr, Stefan Gissler, José Luis Peydró, From finance to fascism: the real effect of Germany's 1931 banking crisis, In: CEPR Discussion Papers, No. 12806, 2020. (Working Paper)
Do financial crises radicalize voters? We study Germany's banking crisis of 1931, when two major banks collapsed and voting for radical parties soared. We collect new data on bank branches and firm-bank connections of 5,610 firms. Incomes plummeted in cities affected by the bank failures; connected firms curtailed payrolls. Nazi votes surged in locations exposed to Danatbank, led by a Jewish manager - but not in those suffering from the other bank's failure. Unobservables or pretrends do not explain the results. Danatbank's collapse boosted Nazi support, especially in cities
with deep-seated anti-Semitism, suggesting a synergy between cultural and economic channels. |
|
Hans-Joachim Voth, Guo Xu, Patronage for productivity: selection and performance in the age of sail, In: CEPR Discussion Papers, No. 13963, 2019. (Working Paper)
Patronage is a byword for poor performance, yet it remains pervasive. We study the selection effects of patronage in the world's most successful navy - the British Royal Navy between 1690 and 1849. Using newly collected data on the battle performance of more than 5,800 naval officers promoted - with and without family ties - to the top of the navy hierarchy, we find that connected promotees outperformed unconnected ones. There was substantial heterogeneity among the admirals in charge of promotions. Discretion over appointments thus created scope for "good" and "bad" patronage. Because most admirals promoted on the basis of merit and did not favor their kin, the overall selection effect of patronage was positive. |
|
Jim Malley, Ulrich Woitek, Estimated human capital externalities in an endogenous growth framework, In: CESifo Working Papers, No. 7603, 2019. (Working Paper)
To better understand the quantitative implications of human capital externalities at the aggregate level, we estimate a two-sector endogenous growth model with knowledge spill-overs. To achieve this, we account for trend growth in a model consistent fashion and employ a Markov-chain Monte-Carlo (MCMC) algorithm to estimate the model's posterior parameter distributions. Using U.S. quarterly data from 1964-2017, we find significant positive externalities to aggregate human capital. Our analysis further shows that eliminating this market failure leads to sizeable increases in education-time, endogenous growth and aggregate welfare. |
|
Nir Jaimovich, Itay Saporta-Eksten, Henry Siu, Yaniv Yedid-Levi, The macroeconomics of automation: data, theory, and policy analysis, In: Working paper series / Department of Economics, No. 340, 2020. (Working Paper)
The U.S. economy has experienced a significant drop in the fraction of the population employed in middle wage, “routine task-intensive” occupations. Applying machine learning techniques, we identify characteristics of those who used to be employed in such occupations and show they are now less likely to work in routine occupations. Instead, they are either non-participants in the labor force or working at occupations that tend to occupy the bottom of the wage distribution. We then develop a quantitative, heterogeneous agent, general equilibrium model of labor force participation, occupational choice, and capital investment. This allows us to quantify the role of advancement in automation technology in accounting for these labor market changes. We then use this framework as a laboratory to evaluate various public policies aimed at addressing the disappearance of routine employment and its consequent impacts on inequality. |
|
Marek Pycia, Peter Troyan, A theory of simplicity in games and mechanism design, In: CEPR Discussion Paper Series, No. DP14043, 2019. (Working Paper)
We introduce a general class of simplicity standards that vary the foresight abilities required of agents in extensive-form games. Rather than planning for the entire future of a game, agents are presumed to be able to plan only for those histories they view as simple from their current perspective. Agents may update their so-called strategic plan as the game progresses, and, at any point, for the called-for action to be simply dominant, it must lead to unambiguously better outcomes, no matter what occurs at non-simple histories. We use our approach to simplicity to provide characterizations of simple mechanisms in general social choice environments both with and without transfers, including canonical mechanisms such as ascending auctions, posted prices, and serial dictatorship-style mechanisms. As a final application, we explain the widespread popularity of the well-known Random Priority mechanism by characterizing it as the unique mechanism that is efficient, fair, and simple to play. |
|
G Aydogan, R Daviet, R Karlsson Linnér, Todd Anthony Hare, J W Kable, H R Kranzler, R R Wetherill, Christian Ruff, P D Koellinger, G Nave, Genetic underpinnings of risky behavior relate to altered neuroanatomy, In: bioRxiv, No. 862417, 2019. (Working Paper)
Previous research points to the heritability of risk-taking behavior. However, evidence on how genetic dispositions are translated into risky behavior is scarce. Here, we report a genetically-informed neuroimaging study of real-world risky behavior in a large European sample (N=12,675). We found negative associations between risky behavior and grey matter volume (GMV) in distinct brain regions, including amygdala, ventral striatum, hypothalamus and dorsolateral prefrontal cortex (dlPFC). Polygenic risk scores for risky behaviors, derived from a genome-wide association study in an independent sample (N=297,025), were inversely associated with GMV in dlPFC, putamen, and hypothalamus. This relation mediated ∼2.2% of the association between genes and behavior. Our results highlight distinct heritable neuroanatomical features as manifestations of the genetic propensity for risk taking.
One Sentence Summary
Risky behavior and its genetic associations are linked to lower grey matter volume in distinct brain regions. |
|
Todd Anthony Hare, Carolina Feher da Silva, Humans are primarily model-based and not model-free learners in the two-stage task, In: bioRxiv, No. 682922, 2019. (Working Paper)
Distinct model-free and model-based learning processes are thought to drive both typical and dysfunctional behaviors. Data from two-stage decision tasks have seemingly shown that human behavior is driven by both processes operating in parallel. However, in this study, we show that more detailed task instructions lead participants to make primarily model-based choices that show little, if any, model-free influence. We also demonstrate that behavior in the two-stage task may falsely appear to be driven by a combination of model-based/model-free learning if purely model-based agents form inaccurate models of the task because of misunderstandings. Furthermore, we found evidence that many participants do misunderstand the task in important ways. Overall, we argue that humans formulate a wide variety of learning models. Consequently, the simple dichotomy of model-free versus model-based learning is inadequate to explain behavior in the two-stage task and connections between reward learning, habit formation, and compulsivity. |
|
Todd Anthony Hare, Silvia Maier, Greater BOLD signal during successful emotional stimulus reappraisal is associated with better dietary self-control, In: bioRxiv, No. 542712, 2019. (Working Paper)
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 better dietary self-control. This cross-task correlation was present in medial and lateral prefrontal cortex as well as the striatum. These results suggest that neural processes related to the reappraisal of emotional stimuli may also facilitate dietary self-control. However, within the dietary self-control task itself, we did not find that prefrontal cortex (PFC) activity significantly increased with self-control success during our food choice task, in contrast to previous reports. This prompted us to conduct exploratory analyses, which revealed that BOLD activity in PFC tracks the amount of taste and healthiness at stake on each self-control challenge trial regardless of the chosen outcome. This exploratory finding also replicated in an independent dataset. We discuss the implications of this evidence that individuals track the self-control stakes in light of theories about effortful self-regulation. In addition, we discuss features of this version of the food choice task that may have reduced the need to recruit PFC to achieve self-control. In summary, our findings indicate that the neural systems supporting emotion reappraisal can generalize to other behavioral contexts that require reevaluation to conform to the current goal.
Significance statement
Reappraisal is a prominent strategy for self-regulation. Yet data to compare processes underlying the reappraisal of emotions and dietary self-control within the same individual is lacking. Here, we use two established emotion regulation and dietary choice tasks to compare both on the neural level. We found that increased BOLD activity in several brain regions including medial and lateral prefrontal cortex and striatum during the successful reappraisal of positive and negative emotional stimuli was linked to better dietary self-control. These results suggest that neural processes underlying the reappraisal of emotional stimuli may also facilitate dietary self-control. |
|
Ingo E Isphording, Ulf Zölitz, The value of a peer, In: Working paper series / Department of Economics, No. 342, 2020. (Working Paper)
This paper introduces peer value-added, a new approach to quantify the total contribution of an individual peer to student performance. Peer value-added captures social spillovers irrespective of whether they are generated by observable or unobservable peer characteristics. Using data with repeated random assignment to university sections, we find that students significantly differ in their peer value-added. Peer value-added is a good out-of-sample predictor of performance spillovers in newly assigned student-peer pairs. Yet, students’ own past performance and other observable characteristics are poor predictors of peer value-added. Peer value-added increases after exposure to better peers, and valuable peers are substitutes for low-quality teachers. |
|
Giuseppe Sorrenti, Ulf Zölitz, Denis Ribeaud, Manuel Eisner, The causal impact of socio-emotional skills training on educational success, In: Working paper series / Department of Economics, No. 343, 2020. (Working Paper)
We study the long-term effects of a randomized intervention targeting children’s socio-emotional skills. The classroom-based intervention for primary school children has positive impacts that persist for over a decade. Treated children become more likely to complete academic high school and enroll in university. Two mechanisms drive these results. Treated children show fewer ADHD symptoms: they are less impulsive and less disruptive. They also attain higher grades, but they do not score higher on standardized tests. The long-term effects on educational attainment thus appear to be driven by changes in socio-emotional skills rather than cognitive skills. |
|
Simon A Broda, Marc Paolella, Archmodels.Jl: Estimating Arch Models in Julia, In: Econometrics: Computer Programs & Software SSRN eJournal, No. 3551503, 2020. (Working Paper)
This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate ARCH-type models. This model class is the workhorse tool for modelling the conditional volatility of financial assets. Their distinguishing feature is that they model the latent volatility as a (deterministic) function of past returns and volatilities. This recursive structure results in loop-heavy code which, due to its just-in-time compiler, Julia is well-equipped to handle. As such, the entire package is written in Julia, without any binary dependencies. We benchmark the performance of ARCHModels.jl against popular implementations in MATLAB, R, and Python, and illustrate its use in a detailed case study. |
|
Christian Ewerhart, Marco Serena, On the (im-)possibility of representing probability distributions as a difference of i.i.d. noise terms, In: Working paper series / Department of Economics, No. 428, 2023. (Working Paper)
A random variable is difference-form decomposable (DFD) if it may be written as the difference of two i.i.d. random terms. We show that densities of such variables exhibit a remarkable degree of structure. Specifcally, a DFD density can be neither approximately uniform, nor quasiconvex, nor strictly concave. On the other hand, a DFD density need, in general, be neither unimodal nor logconcave. Regarding smoothness, we show that a compactly supported DFD density cannot be analytic and will often exhibit a kink even if its components are smooth. The analysis highlights the risks for model consistency resulting from the strategy widely adopted in the economics literature of imposing assumptions directly on a dfference of noise terms rather than on its components. |
|
Christian Ewerhart, Sheng Li, Imposing choice on the uninformed: the case of dynamic currency conversion, In: Working paper series / Department of Economics, No. 345, 2023. (Working Paper)
Over the course of the past two decades, it has become a common experience for consumers authorizing an international transaction via credit card to be invited to choose the currency in which they wish the transaction to be executed. While this choice, made feasible by a technology known as dynamic currency conversion (DCC), seems to foster competition, we argue that the opposite is the case. In fact, the unique pure-strategy equilibrium in a natural fee-setting game, with uninformed and possibly inattentive consumers, turns out to be highly asymmetric, entailing fees for the service provider that persistently exceed the monopoly level. Although losses in welfare may be substantial, a regulatory solution is unlikely to come about due to a global free-rider problem. |
|
Andreas Hefti, Shuo Liu, Armin Schmutzler, Preferences, confusion and competition, In: Working paper series / Department of Economics, No. 344, 2020. (Working Paper)
Do firms seek to make the market transparent,or do they confuse the consumers in their product perceptions? We show that the answer to this question depends decisively on preference heterogeneity. Contrary to the well-studied case of homogeneous goods, confusion is not necessarily an equilibrium in markets with differentiated goods. In particular, if the taste distribution is polarized, so that indifferent consumers are relatively rare, firms strive to fully educate consumers. By contrast, if the taste distribution features a concentration of indecisive consumers, confusion becomes part of the equilibrium strategies. The adverse welfare consequences of confusion can be more severe than with homogeneous goods, as consumers may not only pay higher prices, but also choose a dominated option, or inefficiently refrain from buying. Qualitatively similar insights obtain for political contests, in which candidates compete for voters with heterogeneous preferences. |
|
Nir Jaimovich, Disappearing middle class: job polarization and policy approaches, In: UBS Center Public Paper Series, No. 8, 2020. (Working Paper)
The creeping hollowing out of the middle class and the simultaneous rise of automation have become hotly debated topics in the popular media and among policymakers, and there is certainly no shortage of dire predictions about the ascent of robots and subsequent obsolescence of workers. But – doomsday prophecies aside – what are the facts? What is happening to workers, specifically middle-class ones? And, from a policy perspective, what can (or should) be done to address this fundamental shift in who – or what – does which jobs?
This Public Paper tackles these questions head-on. We first identify the types of individuals who are likely to work in middle-class occupations and track how they act on the labor market outcomes. Then we evaluate policies proposed in recent years that have been aimed at combating the labor market malaise middle-class workers have experienced. |
|
Pol Campos-Mercade, Armando N Meier, Florian H Schneider, Erik Wengström, Prosociality predicts health behaviors during the COVID-19 pandemic, In: Working paper series / Department of Economics, No. 346, 2020. (Working Paper)
Socially responsible behavior is crucial for slowing the spread of infectious diseases. However, economic and epidemiological models of disease transmission abstract from prosocial motivations as a driver of behaviors that impact the health of others. In an incentivized study, we show that a large majority of people are very reluctant to put others at risk for their personal benefit. Moreover, this experimental measure of prosociality predicts health behaviors during the COVID-19 pandemic, measured in a separate and ostensibly unrelated study with the same people. Prosocial individuals are more likely to follow physical distancing guidelines, stay home when sick, and buy face masks. We also find that prosociality measured two years before the pandemic predicts health behaviors during the pandemic. Our findings indicate that prosociality is a stable, long-term predictor of policy-relevant behaviors, suggesting that the impact of policies on a population may depend on the degree of prosociality. |
|