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Previous evidence shows that better insurance coverage increases medical expenditure. However, formal studies on the effect of spending on health outcomes, and especially mental health, are lacking. To fill this gap, we reanalyze data from the Rand Health Insurance Experiment and estimate a joint non-linear model of spending and mental health. We address the endogeneity of spending in a flexible copula regression model with Bernoulli and Tweedie margins and discuss its implementation in the freely available GJRM R package. Results confirm the importance of accounting for endogeneity: in the joint model, a $1000 spending in mental care is estimated to reduce the probability of low mental health by 1.3 percentage points, but this effect is not statistically significant. Ignoring endogeneity leads to a spurious (upwardly biased) estimate.

Humans form impressions toward individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Outgroup-focused theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals, while ingroup-focused theories predict that ingroup experiences play a dominant role. Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. While undergoing fMRI, male participants had identical experiences with different ingroup or outgroup members and rated their social closeness and impressions toward the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning, with larger effects in individuals with stronger ingroup identification. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. Neurally, the individual weight for ingroup prediction errors was related to the coupling between the left inferior parietal lobule and the left anterior insula, which, in turn, predicted learning-related changes in intergroup impressions. Our findings provide computational and neural evidence for ingroup-focused theories, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings. SIGNIFICANCE STATEMENT Living in multicultural societies, humans interact with individuals of their own social groups (ingroup members) and of different social groups (outgroup members). However, little is known about how people learn from the mixture of ingroup and outgroup interactions, the most natural experiences in current societies. Here, participants had identical, intermixed experiences with different ingroup and outgroup individuals and rated their closeness and impressions toward the ingroup and the outgroup. Combining computational models and fMRI, we find that the weight given to ingroup experiences (ingroup prediction errors) is the main source of intergroup impression change, captured by changes in connectivity between the parietal lobe and insula. These findings highlight the importance of ingroup experiences in shaping intergroup impressions in complex social environments.

We study optimal employment contracts for present-biased employees if firms cannot commit to long-term contracts. Assuming that an employee's effort increases his chances to obtain a future benefit, we show that individuals who are naive about their present bias will actually be better off than sophisticated or time-consistent individuals. Moreover, firms might benefit from being ignorant about the extent of an employee's naivet'e. Our results also indicate that naive employees might be harmed by policies such as employment protection or a minimum wage, whereas sophisticated employees are better of

At the time of writing, the Riemann Hypothesis (RH) is one of the major unsolved problems in pure mathematics. In this note, a parameterized family of non-cooperative games is constructed with the property that, if RH holds true, then any game in this family admits a unique Nash equilibrium.

Theoretical accounts disagree on the role of dopamine in intertemporal choice and assume that dopamine either promotes delay of gratification by increasing the preference for larger rewards or that dopamine reduces patience by enhancing the sensitivity to waiting costs. Here, we reconcile these conflicting accounts by providing empirical support for a novel process model according to which dopamine contributes to two dissociable components of the decision process, evidence accumulation and starting bias. We re-analyzed a previously published data set where intertemporal decisions were made either under the D2 antagonist amisulpride or under placebo by fitting a hierarchical drift diffusion model that distinguishes between dopaminergic effects on the speed of evidence accumulation and the starting point of the accumulation process. Blocking dopaminergic neurotransmission not only strengthened the sensitivity to whether a reward is perceived as worth the delay costs during evidence accumulation (drift rate) but also attenuated the impact of waiting costs on the starting point of the evidence accumulation process (bias). In contrast, re-analyzing data from a D1 agonist study provided no evidence for a causal involvement of D1R activation in intertemporal choices. Taken together, our findings support a novel, process-based account of the role of dopamine for cost-benefit decision making, highlight the potential benefits of process-informed analyses, and advance our understanding of dopaminergic contributions to decision making., eLife, 12, ISSN:2050-084X

Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama-French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In this paper, we show that using weighted least squares (WLS) or adaptive least squares (ALS) to estimate model parameters generally leads to smaller HC standard errors compared to ordinary least squares (OLS), which translates into improved inference in the form of shorter confidence intervals and more powerful hypothesis tests. In an extensive empirical analysis based on historical stock returns and commonly used factors, we find that conditional heteroskedasticity is pronounced and that WLS and ALS can dramatically shorten confidence intervals compared to OLS, especially during times of financial turmoil.

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. This version: February 2023

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. Specifically, 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 difference of noise terms rather than on its components.

Modern communication technologies enable efficient exchange of information but often sacrifice direct human interaction inherent in more traditional forms of communication. This raises the question of whether the lack of personal interaction induces individuals to exploit informational asymmetries. We conducted two experiments with a total of 848 subjects to examine how human versus machine interaction influences cheating for financial gain. We find that individuals cheat about three times more when they interact with a machine rather than a person, regardless of whether the machine is equipped with human features. When interacting with a human, individuals are particularly reluctant to report unlikely and therefore, suspicious outcomes, which is consistent with social image concerns. The second experiment shows that dishonest individuals prefer to interact with a machine when facing an opportunity to cheat. Our results suggest that human presence is key to mitigating dishonest behavior and that self-selection into communication channels can be used to screen for dishonest people. This paper was accepted by Axel Ockenfels, decision analysis.

Decisions in management and finance rely on information that often includes win-lose feedback (e.g., gains and losses, success and failure). Simple reinforcement then suggests to blindly repeat choices if they led to success in the past and change them otherwise, which might conflict with Bayesian updating of beliefs. We use finite mixture models and hidden Markov models, adapted from machine learning, to uncover behavioral heterogeneity in the reliance on difference behavioral rules across and within individuals in a belief-updating experiment. Most decision makers rely both on Bayesian updating and reinforcement. Paradoxically, an increase in incentives increases the reliance on reinforcement because the win-lose cues become more salient. This paper was accepted by Gustavo Manso, finance. Funding: C. Alós-Ferrer gratefully acknowledges financial support from the Deutsche Forschungsgemeinschaft under [Grant AL1169/4], part of the research unit “Psychoeconomics” (FOR 1882). Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2022.4584 .

Surveys that measure subjective states like happiness or preferences often generate discrete ordinal data. Ordered response models, which are commonly used to analyze such data, suffer from a fundamental identification problem. Their conclusions depend on unjustified assumptions about the distribution of a latent variable. In this paper, we propose using survey response times to solve that problem. Response times contain information about the distribution of the latent variable even among subjects who give the same survey response, through a chronometric effect. Using an online survey, we test and verify the existence of the chronometric effect. We then provide theoretical conditions under which group differences in happiness or other variables are detectable based on response time data without making distributional assumptions. In our survey, we find evidence supporting the assumptions of traditional ordered response models for some common survey questions but not for others.

We study paternalistic preferences in two large-scale experiments with participants from the general population in the United States. Spectators decide whether to intervene to prevent a stakeholder, who is mistaken about the choice set, from making a choice that is not aligned with the stakeholders' own preferences. We find causal evidence for the nature of the intervention being of great importance for the spectators' willingness to intervene. Only a minority of the spectators implement a hard intervention that removes the stakeholder's freedom to choose, while a large majority implement a soft intervention that provides information without restricting the choice set. This finding holds regardless of the stakeholder's responsibility for being mistaken about the choice set - whether the source of mistake is internal or external - and in different subgroups of the population. We introduce a theoretical framework with two paternalistic types - libertarian paternalists and welfarists - and show that the two types can account for most of the spectator behavior. We estimate that about half of the spectators are welfarists and that about a third are libertarian paternalists. Our results shed light on attitudes toward paternalistic policies and the broad support for soft interventions.

Return event studies generally involve several companies but there are also cases when only one company is involved. This makes the relevant testing problems, abnormal return (AR) and cumulative abnormal return (CAR), more difficult since one cannot exploit the multitude of companies (by using a relevant central limit theorem, say). We propose a permutation test that is valid under weaker conditions than the tests that have previously proposed in the literature in this context. We address the question of the power of the test via a brief simulation study and also illustrate the method with two applications to real data.

Transitivity is perhaps the most fundamental choice axiom and, therefore, almost all economic models assume that preferences are transitive. The empirical literature has regularly documented violations of transitivity, but these violations pose little problem as long as they are simply a result of somewhat-noisy decision making and not a reflection of the deterministic part of individuals' preferences. However, what if transitivity violations reflect individuals' genuinely nontransitive preferences? And how can we separate nontransitive preferences from noise-generated transitivity violations-a problem that so far appears unresolved? Here we tackle these fundamental questions on the basis of a newly developed, non-parametric method which uses response times and choice frequencies to distinguish genuine preferences from noise. We extend the method to allow for nontransitive choices, enabling us to identify the share of weak stochastic transitivity violations that is due to nontransitive preferences. By applying the method to two different datasets, we document that a sizeable proportion of transitivity violations reflect nontransitive preferences. Specifically, in the two datasets, 19% and 14% of all cycles of alternatives for which preferences are revealed involve genuinely nontransitive preferences. These violations cannot be accounted for by any noise or utility specification within the universe of random utility models. Revised version, January 2023

The potential benefits and mechanistic effects of working memory training (WMT) in children are the subject of much research and debate. We show that after five weeks of school-based, adaptive WMT 6-9 year-old primary school children had greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times compared to controls. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability is useful in quantifying the immediate impact of cognitive training interventions, being a better predictor of academic skills and well-being 6-12 months after the end of training than task accuracy. Taken together, our results suggest that attention control is the initial mechanism that leads to the long-run benefits from adaptive WMT. Selective and sustained attention abilities may serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.

This paper studies the impact of a key feature of competitive markets on moral behavior: the possibility that a competitor will step in and conclude the deal if a conscientious market actor forgoes a profitable business opportunity for ethical reasons. We study experimentally whether people employ the argument "if I don't do it, someone else will" to justify taking a narrowly self-interested action. Our data reveal a clear pattern. Subjects do not employ the "replacement excuse" if a social norm exists that classifies the selfish action as immoral. But if no social norm exists, subjects are more inclined to take a selfish action in situations where another subject can otherwise take it. By demonstrating the importance of social norms of moral behavior for limiting the power of the replacement excuse, our paper informs the long-standing debate on the effect of markets on morals.

This paper proposes a procedure for assessing the 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 high-dimensional 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 degree of certainty that decision-makers have about their evaluations of available choice alternatives and their confidence about selecting the subjectively best alternative are important factors that affect current and future value-based choices. Assessments of the alternatives in a given choice set are rarely unidimensional; their values are usually derived from a combination of multiple distinct attributes. For example, the taste, texture, quantity, and nutritional content of a snack food may all be considered when determining whether to consume it. We examined how certainty about the levels of individual attributes of an option relates to certainty about the overall value of that option as a whole and/or to confidence in having chosen the subjectively best available option. We found that certainty and confidence are derived from unequally weighted combinations of attribute certainties rather than simple, equal combinations of all sources of uncertainty. Attributes that matter more in determining choice outcomes also are weighted more in metacognitive evaluations of certainty or confidence. Moreover, we found that the process of deciding between two alternatives leads to refinements in both attribute estimations and the degree of certainty in those estimates. Attributes that are more important in determining choice outcomes are refined more during the decision process in terms of both estimates and certainty. Although certainty and confidence are typically treated as unidimensional, our results indicate that they, like value estimates, are subjective, multidimensional constructs.

It is a common experience for present-day consumers making an international payment via credit or debit card to be invited to choose the currency in which they wish to have the transaction 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. This version: January 2023

Social Cognitive and Affective Neuroscience, ISSN:1749-5016, ISSN:1749-5024

Using a large-scale real effort experiment, we explore whether and how different peer assignment mechanisms affect worker performance and stress. Letting individuals choose whom to compare to increases productivity to the same extent as a targeted exogenous matching policy aimed at maximizing motivational spillovers. These effects are significantly larger than those obtained through random assignment and their magnitude is comparable to the impact of monetary incentives that increase pay by about 10 percent. A downside of targeted peer assignment is that, unlike endogenous peer selection, it leads to a large increase in stress. We uncover the behavioral origins of these desirable effects of peer choice using a combination of choice data, text analysis and simulations. The key advantage of letting workers choose whom to compare to is that it allows those workers who want to be motivated to compare to a motivating peer while also permitting those for whom social comparisons have little benefits or are too stressful to avoid them. Altogether, our results highlight that policies should not only be compared regarding their effects on output, but also with respect to their potential unintended consequences.

We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor mimicking portfolios to build climate risk hedge portfolios. The new mimicking portfolio approach is much more efficient than traditional sorting or maximum correlation approaches by taking into account new methodologies of estimating large-dimensional covariance matrices in short samples. In an extensive empirical out-of-sample performance test, we demonstrate the superior all-around performance delivering markedly higher and statistically significant alphas and betas with the climate risk indices.

Using newly collected data on death rates and aerial victories of more than 5,000 German fighter pilots during World War II, we examine the effects of public recognition on performance and risk-taking. When a particular pilot is honoured publicly, both the victory rate and the death rate of his former peers increase. Fellow pilots react more if they come from the same region of Germany, or if they worked closely with him. Our results suggest that personal rivalry can be a prime motivating force, and that non-financial rewards can lead to a crowd-in of both effort and risk-taking via social connections.

Understanding differences in business cycle phenomena between Emerging Market Economies (EMEs) and industrialized countries has been at the center of recent research on macroeconomic fluctuations. The purpose of this paper is to investigate the importance of certain credit market imperfections in different EMEs. To this end, we develop a small open economy Dynamic Stochastic General Equilibrium (DSGE) framework featuring both permanent and transitory productivity shocks, differentiated home and foreign goods, and endogenous exchange rate movements. Furthermore, our model incorporates liability dollarization as a particular form of financial frictions in EMEs. In this vein, we account for the fact that emerging markets traditionally have had difficulties in borrowing in domestic currency on international capital markets and thus allow for valuation effects in our analysis. We estimate our model using Bayesian techniques for a number of EMEs and thereby control for potential heterogeneity across countries. Contrary to previous studies in this strand of the literature, we include a (vector-)autoregressive measurement error component to capture off-model dynamics. Regarding business cycles in emerging markets, our main findings are that (i) even though we incorporate financial frictions in the framework, trend shocks are the main determinant of macroeconomic fluctuations, (ii) accounting for liability dollarization ameliorates the model fit, and (iii) valuation effects on average stabilize changes in the net foreign asset position.

This paper studies the effect of disclosing conflicts of interest on strategic communication when the sender has lying costs. I present a simple economic mechanism under which such disclosure often leads to more informative and, at the same time, also to more biased messages. This benefits rational receivers but exerts a negative externality from them on naive or delegating receivers. Disclosure is thus not a Pareto-improvement among receivers. I identify general conditions of the information structure under which this effect manifests and show that whenever it does, full disclosure is socially inefficient. These results hold independently of the degree of the receivers' risk-aversion and for an arbitrary precision of the disclosure statement., Games and Economic Behavior, 130, ISSN:0899-8256

BackgroundWhenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules. The results of this procedure have been argued to be ethically problematic.MethodsWe use a formal-analytical approach arising from the mathematical social sciences which allows to investigate whether any allocation methods (known or unknown) fulfill a combination of (ethical) desiderata and, if so, how they are formulated algorithmically.ResultsStrikingly, we find that there exists one and only one method that allows to treat people equally while giving priority to those who are worse off. We identify this method down to the algorithmic level and show that it is easily implementable and it exhibits additional, desirable properties. In contrast, we show that the procedures used during the COVID-19 pandemic violate both principles.ConclusionsOur research delivers an actual algorithm that is readily applicable and improves upon previous ones. Since our axiomatic approach shows that any other algorithm would either fail to treat people equally or fail to prioritize those who are worse off, we conclude that ethical principles dictate the adoption of this algorithm as a standard for the COVID-19 or any other comparable vaccination campaigns.

The rise of opinion programs has transformed television news. Because they present anchors’ subjective commentary and analysis, opinion programs often convey conflicting narratives about reality. We experimentally document that people across the ideological spectrum turn to opinion programs over “straight news”, even when provided large incentives to learn objective facts. We then examine the consequences of diverging narratives between opinion programs in a high-stakes setting: the early stages of the COVID-19 pandemic in the US. We find stark differences in the adoption of preventative behaviours among viewers of the two most popular opinion programs, both on the same network, which adopted opposing narratives about the threat posed by the COVID-19 pandemic. We then show that areas with greater relative viewership of the program downplaying the threat experienced a greater number of COVID-19 cases and deaths. Our evidence suggests that opinion programs may distort important beliefs and behaviours.

Surveys and opinion polls are essential instruments to elicit societal preferences and uncover differences between socioeconomic or demographic groups. However, survey data is noisy, and survey bias is ubiquitous, limiting the reliability and usefulness of standard analyses. We provide a new method that uncovers group preferences and unambiguously ranks the relative strength of preference between groups of agents, leveraging the information contained in response times. The method delivers a nonparametric criterion to determine whether a group (defined, e.g., by gender, age cohort, socioeconomic status, political orientation, etc.) prefers an option over its alternative, and whether it does so more strongly than another group, without any assumptions on the underlying noise. We demonstrate the practical value of this method by studying preferences over important socioeconomic topics in a representative sample of the U.K. population. We find that the new method often provides results when tests based on choice frequencies are inconclusive, and also identifies cases where tests are significant but inferences on preferences are unwarranted.

Do strong states affect the culture and actions of their citizens in a persistent way? And if so, can the capacity to tax, by itself, have a role in driving this effect? I study how the historical capacity of a state to collect taxes affects the decision of citizens to evade the mandatory military draft. I look at Italy during World War I and identify quasi-exogenous variation in tax collection induced by the administrative structure of Piedmont during the 1814-1870 period. Using newly collected and digitised individual data on nearly all the men of the 1899 cohort drafted in the province of Turin, I find that citizens born in towns with lower historical fiscal capacity are more likely to evade the military draft, and that the effect transmits through changes in culture. Results are consistent with fiscal capacity spurring norms of rule-following able to persist in the long run. Placebo estimates from other Italian territories confirm that the effect I estimate can be attributed to fiscal capacity, and it is not confounded by legal capacity.

In this paper I study whether citizens' tax morale (and, more broadly, citizens' attitudes towards the state) can be affected by past institutions, focusing on the role of historical fiscal capacity. Exploiting the features of the tax collection system of a pre-unification state in XIX Century Italy I identify differences in local historical fiscal capacity (as proxied by geographical proximity to a tax collector) and map them into contemporary tax morale, as measured by evasion of the TV Tax in 2014. Exploiting only variation in historical fiscal capacity that arises within matched pairs of neighbouring towns on the border of tax districts, I find imprecisely estimated and arguably small differences in tax morale today between towns where fiscal capacity was different. Investigating the mechanisms of transmission, I provide evidence that phenomena associated with structural transformation are likely to have halted the persistence of the historical fiscal capacity effect.

Serial dictatorships have emerged as the canonical simple mechanisms in the literature on the allocation of indivisible goods without transfers. They are the only neutral and group-strategy-proof mechanisms in environments in which agents have no outside options and hence no individual rationality constraints (Svensson in Soc Choice Welfare 16:557–567, 1999). Accounting for outside options and individual rationality constraints, our main result constructs the class of group-strategy-proof, neutral, and non-wasteful mechanisms. These mechanisms are also Pareto efficient and we call them binary serial dictatorships. The abundance of the outside option—anybody who wants can opt out to get it—is crucial for our result.

Poor psychological health is associated with Takotsubo cardiomyopathy, cardiac syndrome X, coronary microcirculatory dysfunction, peripheral artery disease, or spontaneous coronary artery dissection. Data regarding pessimism, cardiovascular disease (CVD) events and mortality and all-cause mortality remained inconclusive. This systematic review and meta-analysis aim to provide an overview of the association between pessimism, CVD outcomes and mortality. A systematic search of electronic databases was conducted from inception through July 2022 for studies evaluating pessimism and adverse outcomes. A total of 17 studies published between 1966 and July 2022 met our inclusion criteria, for a total of 232,533 individuals. Pooled hazard ratios were calculated in random-effects meta-analyses. Based on pooled analysis of adjusted HRs, pessimism was associated with adjusted HR of 1.13 (95% CI 1.07-1.19) for all-cause mortality with minimal heterogeneity (I

Participation payments are used in many transactions about which people know little, but can learn more: incentives for medical trial participation, signing bonuses for job applicants, or price rebates on consumer durables. Who opts into the transaction when given such incentives? We theoretically and experimentally identify a composition effect whereby incentives disproportionately increase participation among those for whom learning is harder. Moreover, these individuals use less information to decide whether to participate, which makes disappointment more likely. The learning-based composition effect is stronger in settings in which information acquisition is more difficult.

Testosterone has been hypothesized to promote sexual motivation and behavior. However, experimental evidence in healthy humans is sparse and rarely establishes causality. The present study investigated how testosterone affects delay of gratification for sexual rewards. We administered a single dose of testosterone to healthy young males in a double-blind, placebo-controlled, between-participant design (N = 140). Participants underwent a sexual delay discounting task, in which they made a choice between a variable larger-later option (i.e., waiting longer to view a sexual picture for a longer duration) and a smaller-sooner option (i.e., waiting for a fixed shorter period of time to view the same picture for a shorter duration). We found that testosterone administration increased preference for the smaller-sooner option and induced steeper discounting for the delayed option. These findings provide direct experimental evidence that rapid testosterone elevations increase impulsivity for sexual rewards and represent an important step towards a better understanding of the neuroendocrine basis of sexual motivation in humans.