Working papers

Are the players “commonly meta-certain” of an interactive belief model itself? The paper formalizes what it means by: “a player is (meta-)certain of her own belief-generating map” or “the players are (meta-)certain of the profile of belief-generating maps (i.e., the model).” The paper shows: a player is (meta-)certain of her own belief-generating map if and only if her beliefs are introspective. The players are commonly (meta-)certain of the model if and only if, for any event which some player i believes at some state, it is common belief at the state that player i believes the event. This paper then asks whether the “common meta-certainty” assumption is needed for epistemic characterizations of game-theoretic solution concepts. The paper shows: common belief in rationality leads to actions that survive iterated elimination of strictly dominated actions, as long as each player is logical and (meta-)certain only of her own strategy and belief-generating map

Algorithms are becoming the standard tool for bidding in auctions through which digital advertising is sold. To explore how algorithmic bidding might affect functioning of these auctions, this study undertakes a series of simulated experiments where bidders employ Artificial Intelligence algorithms (Q-learning and Neural Network) to bid in online advertising auctions. We consider both the generalized second-price (GSP) auction and the Vickrey-Clarke-Groves (VCG) auction. We find that the more detailed information is available to the algorithms, the better it is for the efficiency of the allocations and the advertisers profit. Conversely, the auctioneer revenues tend to decline as more complete information is available to the advertiser bidding algorithms. We also compare the outcomes of algorithmic bidding to those of equilibrium behavior in a range of different specifications and find that algorithmic bidding has a tendency to sustain low bids both under the GSP and VCG relative to competitive benchmarks. Moreover, the auctioneer revenues under the VCG setting are either close to or lower than those under the GSP setting. In addition, we consider three extensions commonly observed in the data: introduction of a non-stategic player, bidding through a common intermediary, and asymmetry of the information across bidders. Consistent with the theory, the non-strategic player presence leads to increased efficiency, whereas bidding through a common intermediary leads to lower auctioneer revenue compared to the case of individual bidding. Moreover, in experiments with information asymmetry, more informed players earn higher rewards.

We evaluate how traditional parties may respond to populist parties on issues aligning with populist messages. During the 2020 Italian referendum on the reduction of members of Parliament, we conducted a large-scale field experiment, exposing 200 municipalities to nearly a million impressions of programmatic advertisement. Our treatments comprised two video ads against the reform: one debunking populist rhetoric and another attributing blame to populist politicians. This anti-populist campaign proved effective through demobilization, as it reduced both turnout and the votes in favor of the reform. Notably, the effects were more pronounced in municipalities with lower rates of college graduates, higher unemployment, and a history of populist votes. This exogenous influence introduced a unique populist dynamic, observable in the 2022 national election where treated municipalities showed increased support for Brothers of Italy, a rising populist party, and decreased support for both traditional parties and the populists behind the 2020 reform. A follow-up survey further showed increased political interest and diminished trust in political institutions among the residents of municipalities targeted by the campaign.

In a recent paper, Lin & Palfrey (2024) developed a theory of cognitive hierarchies (CH) in sequential games and observed that this solution concept is not reduced-normal-form invariant. In this note I qualify and explain this observation. I show that the CH model is normal-form invariant, and that the differences arising from the application of the CH model to the reduced normal form depend only on how randomization by level-0 types is modeled. Indeed, while the uniform behavior strategy in the extensive form yields the uniform mixed strategy in the normal form, the latter does not correspond to the uniform randomization in the reduced normal form, because different reduced strategies may correspond to sets of equivalent strategies with different cardinalities. I also comment on (i) the invariance of the CH model to some transformations of the sequential game, and (ii) the independence of conditional beliefs about co-players' level-types.

We study whether a better knowledge of the functioning of pay-as-you-go pension systems and recent demographic trends affects natives’ attitudes towards immigration. In two online experiments conducted in Italy and Spain, we randomly treated participants with a video explaining how, in pay-as-you-go systems, the payment of current pensions depends on the contributions paid by current workers. The video also informs participants about population aging trends in their countries. The treatment increases knowledge of pay-as-you-go systems and future demographic trends for all participants. However, it improves attitudes towards migrants only for treated participants who do not support populist and anti-immigrant parties.

We document the spiral of populism in Europe and the direct and indirect role of economic insecurity shocks. Using survey data on individual voting, we make two contributions to the literature, namely: (1) Economic insecurity shocks have a significant impact on the populist vote share, directly as demand for protection, and
indirectly through the induced changes in trust and attitudes; (2) A key consequence of increased economic insecurity is a drop in turnout. The impact of this largely neglected turnout effect is substantial: conditional on voting, when economic insecurity increases almost 40% of the induced change in the vote for a populist party comes from the turnout channel.

This paper empirically shows that the imbalance between an ethnic group’s political and military power is crucial to understanding the likelihood that such a group engages in a conflict. We develop a novel measure of a group’s military power by combiningmachine learning techniques with rich data on ethnic group characteristics and
outcomes of civil conflicts in Africa and theMiddle East. We couple thismeasure with available indicators of an ethnic group’s political power as well as with a novel proxy based on information about the ethnicity of cabinet members. We find that groups characterized by a highermismatch betweenmilitary and political power are between 30% and 50% more likely to engage in a conflict against their government depending on the specification used. We also find that the effects of power mismatch are nonlinear, which is in agreement with the predictions of a simplemodel that accounts for the cost of conflict. Moreover, our results suggest that high-mismatched groups are typically involved in larger and centrist conflicts. The policy implication is that powersharing recommendations and institutional design policies for peace should consider primarily the reduction of power mismatches between relevant groups, rather than focusing exclusively on equalizing political power in isolation.

We analyze the infinite repetition with imperfect feedback of a simultaneous or sequential game, assuming that players are strategically sophisticated---but impatient---expected-utility maximizers. Sophisticated strategic reasoning in the repeated game is combined with belief updating to provide a foundation for a refinement of self-confirming equilibrium. In particular, we model strategic sophistication as rationality and common strong belief in rationality. Then, we combine belief updating and sophisticated reasoning to provide sufficient conditions for a kind of learning---that is, the ability, in the limit, to exactly forecast the sequence of future observations---thus showing that impatient agents end up playing a sequence of self-confirming equilibria in strongly rationalizable conjectures of the one-period game.

How do people form beliefs about novel risks, with which they have little or no experience? Motivated by survey data we collected in 2020, which showed that beliefs about Covid’s lethality depended on a range of personal experiences in unrelated domains, we build a model based on the psychology of selective memory. When a person thinks about an event, different experiences compete for retrieval, and retrieved experiences are used to simulate the event based on how similar they are to it. The model yields predictions on how experiences interfere with each other in recall and how non domain-specific experiences bias beliefs based on their similarity to the assessed event. We test these predictions using data from our Covid survey and from a primed-recall experiment about cyberattack risk. Experiences and their measured similarity to the cued event successfully help explain beliefs, with patterns consistent with our theory. Our approach offers a new, structured way to study and jointly account for systematic biases and substantial belief heterogeneity.

We construct an index of long term expected earnings growth for S&P500 firms and show that it has remarkable power to jointly predict future errors in these expectations and stock returns, in both the aggregate market and the cross section. The evidence supports a mechanism whereby good news cause investors to become too optimistic about long term earnings growth, for the market as a whole but especially for a subset of firms. This leads to inflated stock prices and, as beliefs are systematically disappointed, to subsequent low returns in the aggregate market and for the subset of firms. Overreaction of long term expectations helps resolve or asset pricing puzzles without time series or cross-sectional variation in required returns.

We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis by attending “bottom up” to its salient features while neglecting other, potentially more relevant, ones. Only the statistics associated with salient features are used, others are neglected. The model unifies Gambler’s Fallacy, its variation by sample size, under- and overreaction in inference, and insensitivity to multiple signals, all as a byproduct of selective attention. The model also makes new predictions on how controlled changes in the salience of specific features should jointly shape measured attention and biases. We test and confirm these predictions experimentally, including by measuring attention and documenting novel biases predicted by the model. Bottom-up attention to features emerges as a unifying framework for biases conventionally explained using a variety of stable heuristics or distortions of the Bayes rule. 

This handbook chapter studies how natural resource wealth can in many contexts fuel armed conflict. Starting from a simple theoretical model, we stress the role of geography and power mismatch in the so called "natural resource curse". Drawing on recent empirical evidence, the importance of resource abundance, asymmetry and capital-intensiveness is highlighted, alongside local grievances and international interventions. We propose a series of evidence-driven policy conclusions, ranging from "smart green transition" and democratic institution building over labor-market intervention to a series of specific policies requiring international coordination.

This paper discusses the historical and social origins of the bifurcation in the political institutions of China and Western Europe. An important factor, recognized in the literature, is that China centralized state institutions very early on, while Europe remained politically fragmented for much longer. These initial differences, however, were amplified by the different social organizations (clans in China, corporate structures in Europe) that spread in these two societies at the turn of the first millennium AD. State institutions interacted with these organizations, and were shaped and influenced by this interaction. The paper discusses the many ways in which corporations contributed to the emergence of representative institutions and gave prominence to the rule of law in the early stages of state formation in Europe, and how specific features of lineage organizations contributed to the consolidation of the Imperial regime in China. 

This paper explores the tradeoff between competition and financial inclusion given by the vertical integration between mobile network and money operators. Joining novel data on mobile money fees built through the WayBack machine, with sources on network coverage and financials, we examine the staggering across African operators and countries of platform interoperability – a policy that promotes transactions and competition across mobile money operators. Our findings show that interoperability lowers mobile money fees and reduces network coverage and mobile towers, especially in rural and poor districts. Interoperability also results in a decline in various survey metrics of financial inclusion.

We compute new estimates for Total Factor Productivity (TFP) growth in five European countries and in the United States. Departing from standard methods, we account for positive profits and use firm surveys to proxy for unobserved changes in factor utilization. These novelties have a major impact in Europe, where our estimated TFP growth series are less volatile and less cyclical than the ones obtained with standard methods. Based on our approach, we provide annual industry-level and aggregate TFP series, as well as the first estimates of utilization-adjusted quarterly TFP growth in Europe.

JEL Codes: E01, E30, O30, O40

We study the stabilizing role of benefit extensions. We develop a tractable quantitative model with heterogeneous agents, search frictions, and nominal rigidities. The model allows for a stabilizing aggregate demand channel and a destabilizing labor market channel. We characterize each channel analytically and find that aggregate demand effects quantitatively prevail in the US. When feeding-in estimated shocks, the model tracks unemployment in the two most recent downturns. We find that extensions lowered unemployment by a maximum of 0.35 pp in the Great Recession, while the joint stabilizing effect of extensions and benefit compensation peaked at 1.08 pp in the pandemic. 

We offer a theory of changing dimensions of political polarization based on endogenous social identity. We formalize voter identity and stereotyped beliefs as in Bonomi et al. (2021), but add parties that compete on policy and also spread or conceal group stereotypes to persuade voters. Parties are historically connected to different social groups, whose members are more receptive to the ingroup party messages. An endogenous switch from class to cultural identity accounts for three major observed changes: i) growing conflict over cultural issues between voters and between parties, ii) dampening of political conflict over redistribution, despite rising inequality, and iii) a realignment of lower class voters from the left to the right. The incentive of parties to spread stereotypes is a key driver of identity-based polarization. Using survey data and congressional speeches we show that - consistent with our model - there is evidence of i) and ii) also in the voting realignment induced by the ”China Shock” (Autor et al. 2020).

I show that offering monetary rewards to whistleblowers can backfire as a moral aversion to being paid for harming others can reverse the effect of financial incentives. I run a field experiment with employees of the Afghan Ministry of Education, who are asked to confidentially report on their colleagues’ attendance. I use a two-by-two design, randomizing whether or not reporting absence carries a monetary incentive as well as the perceived consequentiality of the reports. In the consequential treatment arm, where employees are given examples of the penalties that might be imposed on absentees, 15% of participants choose to denounce their peers when reports are not incentivized. In this consequential group, rewards backfire: only 10% of employees report when denunciations are incentivized. In the non-consequential group, where participants are guaranteed that their reports will not be forwarded to the government, only 6% of employees denounce absence without rewards. However, when moral concerns of harming others are limited through the guarantee of non-consequentiality, rewards do not backfire: the incentivized reporting rate is 12% 

Debt moratoria that allow borrowers to postpone loan payments are a frequently used tool intended to soften the impact of economic crises. We conduct a nationwide experiment with a large consumer lender in India to study how debt forbearance offers affect loan repayment and banking relationships. In the experiment, borrowers receive forbearance offers that are presented either as an initiative of their lender or the result of government regulation. We find that delinquent borrowers who are offered a debt moratorium by their lender are 4 percentage points (7 percent) less likely to default on their loan, while forbearance has no effect on repayment if it is granted by the regulator. Borrowers who are offered forbearance by their lender also have higher demand for future interactions with the lender: in a follow-up experiment conducted several months after the main intervention, demand for a non-credit product offered by the lender is 10 percentage points (27 percent) higher among customers who were offered repayment flexibility by the lender than among customers who received a moratorium offer presented as an initiative of the regulator. Overall, our results suggest that, rather than generating moral hazard, debt forbearance can improve loan repayment and support the creation of longer-term banking relationships not only for liquidity but also for relational contracting reasons. This provides a rationale for offering repayment flexibility even in settings where lenders are not required to provide forbearance.

Real-world contests are inherently uncertain since the player who exerts the highest effort can still lose. In this paper, I consider a general asymmetric incomplete information contest model with a nonparametric distribution of uncertainty in the contest success function. It generalizes all-pay auctions, Tullock contests, and rank-order tournaments with two asymmetric players. Uncertainty in the contest success function summarizes other factors that influence the contest win outcome apart from the efforts of the players, such as, for example, players’ reputation or luck. First, I nonparametrically identify and estimate the distribution of uncertainty using the information on contest win outcomes and efforts. Next, I nonparametrically identify and estimate the distributions of the players’ costs of exerting effort. The model provides a method to disentangle two sources of player’s advantage: asymmetry in the costs’ distributions and the effect of the uncertainty distribution on the winning probability. As an empirical example, I apply the model to the U.S. House of Representatives elections.

We study mean-variance approximations for a large class of preferences. Compared to the standard mean-variance approximation that only features a risk variability term, a novel index of variability appears. Its neglect in an empirical estimation may result in puzzling in ated risk terms of standard mean-variance approximations.

We consider a model of a limit order book and determine the optimal tick size set by a social planner who maximizes the welfare of market participants. In a 2-period model where only two agents arrive sequentially, the tick size is a friction that constrains investors to use discrete price grids, and as a consequence the optimal tick size is equal to zero. However, in a model with sequential arrival of more than two investors who can endogenously either take liquidity or supply liquidity by undercutting or queuing behind existing orders, the tick size is positive: it is a strategic tool a social planner uses to optimally affect the choice made by investors between liquidity demand and supply. In addition, the optimal tick size is a function both of the value of the asset and of trading volume. The policy implication of such findings is that the European tick size regime and the “Intelligent Ticks” Nasdaq proposal dominate Reg. NMS Rule 612 that formalizes the tick size regime for the U.S. markets. Using data  from the U.S. and the European markets we test our model’s empirical predictions.

Why, in the face of scandals and misbehaviors, do partisan supporters hardly change their minds about their favored candidates? We study individuals’ online engagement with negative news on candidates in the 2016 US Presidential Election. Compared to independents, partisan users avoid commenting bad news on their favorite candidate, but seek them on its opponent, a political “ostrich effect”. When they do comment on bad news about their candidate, they try to rationalize them, display a more negative sentiment, and are more likely to cite scandals of the opponent. This behavior is consistent with the predictions of a model of online interactions where paying attention to non-consonant news is emotionally or psychologically costly, while paying attention to consonant ones is pleasing. Because users enjoy receiving positive feedback on their views, intrinsic biases that drive ideological segregation are amplified on social media.

We explore how business groups use internal labor markets (ILMs) in response to changing economic conditions. We show that following the exit of a large industry competitor, groupaffiliated firms expand and gain market share by increasing their reliance on the ILM to ensure swift hiring, especially of technical managers and skilled blue collar workers. The ability to take advantage of this shock to growth opportunities is greater in firms with closer access to their affiliates’ human capital, as geographical proximity facilitates employee relocations across units. Overall, our findings point to the ILM as a prominent mechanism making affiliation with a business group valuable at times of change. For the ILM to perform its role in the face of industry shocks, group sectoral diversification must be combined with geographical proximity between affiliates. 

We study the implications of employment targets on firm dynamics during the privatization of the East German economy. Exploiting novel contract-level data, we document three stylized facts. First, the policy distorted firm size choices and generated bunching of firms around their committed employment target. Second, exploiting heterogeneous labor preferences of privatizers, we show that assigning tight commitments to firms causes an increase in employment growth and leads to higher productivity growth. Finally, tighter commitments also result in significant costs by leading to increased firm exit. We interpret these results through the lens of a dynamic model with endogenous productivity growth at the firm level. The model highlights that while tight commitments distort the employment decision statically and lead to a higher exit probability, they also induce a “catch-up” increase in productivity growth. This is because although firm profits are lower under tight commitments, marginal profits with respect to  productivity are higher. We calibrate the model to our data and find that the policy lead to a 3 percentage points higher aggregate TFP growth thanks to the productivity improvements of firms with tight contracts. 

We investigate the impact of prices on ratings using Airbnb data. We theoretically illustrate two opposing channels: higher prices reduce the value for money, worsening ratings, but they increase the taste-based valuation of the average traveler, improving ratings. Results from panel regressions and a regression discontinuity design suggest a dominant value-for-money effect. In line with our model, hosts strategically complement lower prices with higher effort more when ratings are relatively low. Finally, we provide evidence that, upon entry, strategic hosts exploit the dominant value-for-money effect. The median entry discount of seven percent improves medium-run monthly revenues by three percent.

 

 

 

We compute new estimates for Total Factor Productivity (TFP) growth in the United States and in five European countries. Departing from standard methods, we account for positive profits and use firm surveys to proxy for unobserved changes in factor utilization. These novelties have a major impact, especially in Europe, where our estimated TFP growth series are less volatile and less cyclical than the ones obtained with standard methods. Based on our approach, we provide annual industry-level and aggregate TFP series, as well as the first estimates of utilization-adjusted quarterly TFP growth in Europe.

We revisit the role of temporary layoffs in the business cycle, motivated by their unprecedented surge during the pandemic recession.We first measure the contribution of temporary layoffs to unemployment dynamics over the period 1979 to the present. While many have emphasized a stabilizing effect due to recall hiring, we quantify an important destabilizing effect due to "loss-of-recall", whereby workers in temporary-layoff unemployment lose their job permanently and do so at higher rates in recessions. We then develop a quantitative model that allows for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures well pre-pandemic unemployment dynamics and shows how loss-of-recall enhances the recessionary contribution of temporary layoffs. We also show that with some modification the model can capture the pandemic recession. We then use our structural model to show that the Paycheck Protection program generated significant employment gains. It did so in part by significantly reducing loss-of-recall.

We study strategic reasoning in a signaling game where players have common belief in an outcome distribution and in the event that the receiver believes that the sender's first-order beliefs are independent of her payoff-type. We characterize the behavioral implications of these epistemic hypotheses through a rationalizability procedure with second-order belief restrictions. Our solution concept is related to, but weaker than Divine Equilibrium (Banks and Sobel, 1987). First, we do not obtain sequential equilibrium, but just Perfect Bayesian Equilibrium with heterogeneous off-path beliefs (Fudenberg and He, 2018). Second, when we model how the receiver may rationalize a particular deviation, we take into account that some types could have preferred a different deviation, and we show this is natural and relevant via an economic example.

A start-up and an incumbent negotiate over an acquisition price under asymmetric information about the start-up's ability to succeed in the market. The acquisition may result in the shelving of the start-up's project or the development of a project that would otherwise never reach the market because of financial constraints. Despite this possible pro-competitive effect, the optimal merger policy commits to standards of review that prohibit high-price takeovers, even if they may be welfare-beneficial ex post. Ex ante this pushes the incumbent to acquire startups lacking the financial resources to develop independently, and increases expected welfare.

A central aspect of strategic reasoning in sequential games consists in anticipating how co-players would react to information about past play, which in turn depends on how co-players update and revise their beliefs. Several notions of belief system have been used to model how players' beliefs change as they obtain new information, some imposing considerably more discipline than others on how beliefs at different information sets are related. We highlight the differences between these notions of belief system in terms of introspection about one's own conditional beliefs, but we also show that such differences do not affect the essential aspects of rational planning and the behavioral implications of strategic reasoning, as captured by rationalizability.

We propose that the mathematical representation of situations of strategic interactions, i.e., of games, should separate the description of the rules of the game from the description of players’ personal traits. Yet, we note that the standard extensive-form partitional representation of information in sequential games does not comply with this separation principle. We offer an alternative representation that extends to all (finite) sequential games the approach adopted in the theory of repeated games with imperfect monitoring, that is, we describe the flow of information accruing to players rather than the stock of information retained by players, as encoded in information partitions. Mnemonic abilities can be represented independently of games. Assuming that players have perfect memory, our flow representation gives rise to information partitions satisfying perfect recall. Different combinations of rules about information flows and of players mnemonic abilities may give rise to the same information partition . All extensive-form representations with information partitions, including those featuring absentmindedness, can be generated by some such combinations. 

Macroeconomic  outcomes depend on the distribution of markups across firms and over time, making firm-level markup estimates key for macroeconomic analysis. Methods to obtain these estimates require data on the prices that firms charge. Firm-level data with wide coverage, however,  primarily comes from financial statements, which lack information on  prices. We use an analytical framework to show that trends in markups or the dispersion of markups across firms can still be well-measured with such data. Finding the average level of the markup does require pricing data, and we propose a consistent estimator for such settings. We validate the analytical results with simulations of a quantitative macroeconomic model and firm-level administrative production and pricing data. Our analysis supports the use of financial data to measure trends in aggregate markups.

We investigate the effects of the Federal Reserve's quantitative easing and maturity extension programs on the yields of US dollar-denominated corporate bonds using a multiple-regime heteroskedasticity-based VAR identification approach. Impulse response functions suggest that a traditional, rate-based expansionary policy may lead to an increase in yields while quantitative easing is linked to a general and persistent decrease in yields, particularly for long-term bonds. The responses generated by the maturity extension program are significant and of larger magnitude. A decomposition shows that the unconventional programs reduce the cost of private debt primarily through a reduction in risk premia that cannot be entirely accounted for by a reduction in corporate default risk.

We determine optimal market access pricing for an exchange or Social Planner. Exchanges optimally use rebate-based pricing (vs. strictly positive fees) when ex ante gains-from-trade and trading activity are low (high). Exchange rebate-based pricing increases (decreases) welfare when investor valuation dispersion and trading activity are low (high). A Social Planner increases welfare using rebate-based pricing. High-frequency traders strengthen exchange incentives for rebate-based pricing; a new explanation for widespread Maker-Taker and Taker-Maker pricing. With HFTs, rebate-based pricing improves total welfare, but Pareto transfers are needed to improve investor welfare. Sequential bargaining games between competing exchanges setting fees have pure-strategy equilibria.

We show that rational but inattentive agents can become polarized, even in expectation. This is driven by agents' choice of not only how much information to acquire, but also what type of information. We present how optimal information acquisition, and subsequent belief formation, depends crucially on the agent-specific status quo valuation. Beliefs can systematically update away from the realized truth and even agents with the same initial beliefs might become polarized. We design a laboratory experiment to test the model's predictions; the results confirm our predictions about the mechanism (rational information acquisition) and its effect on beliefs (systematic polarization).

During the 2020 Corona virus crisis in Lombardy -a stranger time- the Game Design Workshop at Bocconi University studied the implementation of the algorithms proposed by Maccheroni (2020, SSRN paper 3622663) for digital play using only six-sided dice. Swords & Wizardry by Finch (2011, Frog God Games) is a popular restatement of the Original Dungeons & Dragons Game by Gygax and Arneson (1974, Tactical Studies Rules). A case study, the present paper presents an implementation of the aforementioned algorithms for this game.

The paper develops a foundational model of the decentralized allocation of subsidies through competitive grantmaking. Casting the problem in a simple supply and demand framework, we characterize the equilibrium acceptance standard and applications. The equilibrium success rate (grants over applications) decreases in the budget, consistent with some recent evidence, if and only if the distribution of types has decreasing hazard rate. In all stable equilibria resulting when funds are allocated across fields proportionally to applications-as well as under apportionment rules in a general class characterized in the paper-an increase in noise in the evaluation in a field perversely raises applications in that field and reduces applications in all the other fields. We characterize how the design of allocation rules can be modified to improve welfare.

Lower costs of international trade affect both firms' innovation incentives and theirmarket power. We develop a dynamic general equilibrium model with endogenous innovation and endogenous markups to study the interaction between these effects. Lower trade costs stimulate innovation by large firms that are technologically close to their rivals. However, as innovators increase their productivity advantage over others, they also increase their markups. Our calibrated model suggests that a fall in trade costs which increases the trade-to-GDP ratio of the US manufacturing sector from 12% (its level in the 1970s) to 24% (its current level) increases productivity growth by 0.12 percentage points and the aggregate markup by 1.70 percentage points. Without the feedback effect of innovation on the productivity distribution, markups would actually have fallen.

This paper studies electoral competition over redistributive taxes between a safe incumbent and a risky opponent. As in prospect theory, economically disappointed voters become risk lovers, and hence are intrinsically attracted by the more risky candidate. We show that, after a large adverse economic shock, the equilibrium can display policy divergence: the more risky candidate proposes lower taxes and is supported by a coalition of very rich and very disappointed voters, while the safe candidate proposes higher taxes. This can explain why new populist parties are often supported by economically dissatisfied voters and yet they run on economic policy platforms of low redistribution. We show that survey data on the German SOEP are consistent with our theoretical predictions on voters' behavior.

We present a theory of war onset and war duration in which power is multidimensional and can evolve through conflict. The resources players can secure without fighting are determined by their political power, while the ability of appropriating resources with violence is due to their military power. When deciding whether to wage a war, players evaluate the consequences on the current allocation of resources as well as on the future distribution of military and political power. We deliver three main results: a key driver of war is the mismatch between military and political power; dynamic incentives may amplify static incentives, leading forward-looking players to be more belligerent; and a war is more likely to last for longer if political power is initially more unbalanced than military power and the politically under-represented player is militarily advantaged. Our results are robust to allowing the peaceful allocation of resources to be a function of both political and military power. Finally, we provide empirical correlations on inter-state wars that are consistent with the theory.

We use decision theory to confront uncertainty that is sufficiently broad to incorporate 'models as approximations'.We presume the existence of a featured collection of what we call 'structured models' that have explicit substantive motivations. The decision maker confronts uncertainty through the lens of these models, but also views these models as simplifications, and hence, as misspecified. We extend min-max analysis under model ambiguity to incorporate the uncertainty induced by acknowledging that the models used in decision-making are simplified approximations. Formally, we provide an axiomatic rationale for a decision criterion that incorporates model misspecification concerns.

We use a recently developed right-tail variation of the Augmented Dickey-Fuller unit root test to identify and date-stamp periods of mildly explosive behavior in the weekly time series of eight U.S. fixed income yield spreads between September 2002 and April 2018. We find statistically significant evidence of mildly explosive dynamics in six of these spreads, two of which are short/medium-term mortgagerelated spreads. We show that the time intervals characterized by instability that we estimate from these yield spreads capture known episodes of financial and economic distress in the U.S. economy. Mild explosiveness migrates from short-term funding markets to medium- and long-term markets during the Great Financial Crisis of 2007-09. Furthermore, we statistically validate the conjecture that the initial panic of 2007 migrated from segments of the ABX market to other U.S. fixed income markets in the early phases of the financial crisis.

Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and its global impacts are unprecedented, decisions need to be made in a highly uncertain, complex and rapidly changing environment. In such a context, in which human lives and the economy are at stake, we argue that using ideas and constructs from modern decision theory, even informally, will make policymaking more a responsible and transparent process.

This paper investigates the effect of terrorism financing and recruitment on attacks. A Sharia-compliant institution in Pakistan induces exogenous variation in the funding of terrorist groups through their religious affiliation. I isolate the supply of terrorist attacks by following multiple terrorist groups with different affiliations operating in various cities. Higher terrorism financing, in a given location and period, generates more attacks in the same location and period. This effect increases in recruitment, measured through darkweb data, inputs by two judges and machine-learning. This evidence is consistent with terrorist organizations facing financial frictions to their internal capital market.

Negative advertising is frequent in electoral campaigns, despite its ambiguous effectiveness: negativity may reduce voters' evaluation of the targeted politician but have a backlash effect for the attacker. We study the effect of negative advertising in electoral races with more than two candidates with a large scale field experiment during an electoral campaign for mayor in Italy and a survey experiment in a fictitious mayoral campaign. In our field experiment, we find a strong, positive spillover effect on the third main candidate (neither the target nor the attacker). This effect is confirmed in our survey experiment, which creates a controlled environment with no ideological components nor strategic voting. The negative ad has no impact on the targeted incumbent, has a sizable backlash effect on the attacker, and largely benefits the idle candidate. The attacker is perceived as less cooperative, less likely to lead a successful government, and more ideologically extreme.

We provide two characterizations, one axiomatic and the other neuro-computational, of the dependence of choice probabilities on deadlines, within the widely used softmax representation (see below picture) where pt (a; A) is the probability that alternative a is selected from the set A of feasible alternatives if t is the time available to decide, is a time dependent noise parameter measuring the unit cost of information, u is a time independent utility function, and a is an alternative-specific bias that determines the initial choice probabilities and possibly reflects prior information. Our axiomatic analysis provides a behavioral foundation of softmax (also known as Multinomial Logit Model when a is constant). Our neuro-computational derivation provides a biologically inspired algorithm that may explain the emergence of softmax in choice behavior. Jointly, the two approaches provide a thorough understanding of soft-maximization in terms of internal causes (neurophysiological mechanisms) and external effects (testable implications).

We study agents in a social network who receive initial noisy signals about a fundamental parameter and then, in each period, solve a robust non-parametric estimation problem given their previous information and the most recent estimates of their neighbors. The resulting robust opinion aggregators are characterized by simple functional properties: normalization, monotonicity, and translation invariance. These aggregators admit the linear DeGroot's model as a particular parametric specification. However, robust opinion aggregators allow for additional features such as overweighting/underweighting of extreme opinions, confirmatory bias, as well as discarding information obtained from sources perceived as redundant. We show that under this general model, it is still possible to link the long-run behavior of the opinions to the structure of the underlying network. In particular, we provide sufficient conditions for convergence and consensus and we offer some bounds on the rate of convergence. In some parametric cases, we derive the influence of the agents on the limit opinions and we stress how it depends on their centrality as well as on their initial signals. Finally, we study sufficient conditions under which a large society learns the true parameter while also highlighting why this property may fail.

Recent studies argue that major crises can have long lasting effects on individual behavior. While most studies focused on natural disasters, we explore the consequences of the global pandemic caused by a lethal influenza virus in 1918-19: the so-called "Spanish Flu". This was by far the worst pandemic of modern history, causing up to 100 million deaths worldwide. Using information about attitudes of respondents to the General Social Survey (GSS), we find evidence that experiencing the pandemic likely had permanent consequences in terms of individuals' social trust. Our findings suggest that lower social trust was passed on to the descendants of the survivors of the Spanish Flu who migrated to the US. As trust is a crucial factor for long-term economic development, our research offers a new angle from which to assess current health threats.

This paper describes price discovery and liquidity provision in a dynamic limit order market with asymmetric information and non-Markovian learning. Investors condition on information in both the current limit order book and also, unlike in previous research, on the prior order history when deciding whether to provide or take liquidity. Our analysis shows that the information content of the prior order history can be substantial. Surprisingly, the information content of equilibrium orders can differ from order direction and aggressiveness.

We study the role of perceived threats from cultural diversity induced by terrorist attacks and a salient criminal event on public discourse and voters' support for far-right parties. We first develop a rule which allocates Twitter users in Germany to electoral districts and then use a machine learning method to compute measures of textual similarity between the tweets they produce and tweets by accounts of the main German parties. Using the dates of the aforementioned exogenous events we estimate constituency-level shifts in similarity to party language. We find that following these events Twitter text becomes on average more similar to that of the main far-right party, AfD, while the opposite happens for some of the other parties. Regressing estimated shifts in similarity on changes in vote shares between federal elections we find a significant association. Our results point to the role of perceived threats on the success of nationalist parties.

We study the interplay between information acquisition and signaling. A sender decides whether to learn his type at a cost prior to taking a signaling action. A receiver responds after observing the signaling action. In the benchmark model where the sender's information acquisition decision is observed the sender does not acquire information and, therefore, does not signal. A rationale for signaling is provided by the model in which information acquisition is covert. There, in the unique equilibrium outcome surviving a form of never weak best response refinement the sender does acquire information and signals when the information is cheap.

We relate two representations of the cost of acquiring information: a cost that depends on the experiment performed, as in statistical decision theory, and a cost that depends on the distribution of posterior beliefs, as in the theory of rational inattention. In many cases of interests, the two representations prove to be inconsistent with each other. We provide a systematic analysis of the inconsistency, propose a way around it, and apply our findings to information acquisition in games.

We add here another layer to the literature on nonatomic anonymous games started with the 1973 paper by Schmeidler. More specifically, we define a new notion of equilibrium which we call '-estimated equilibrium and prove its existence for any positive '. This notion encompasses and brings to nonatomic games recent concepts of equilibrium such as self-confirming, peer-confirming, and Berk-Nash. This augmented scope is our main motivation. At the same time, our approach also resolves some conceptual problems present in Schmeidler (1973), pointed out by Shapley. In that paper the existence of pure-strategy Nash equilibria has been proved for any nonatomic game with a continuum of players, endowed with an atomless countably additive probability. But, requiring Borel measurability of strategy profiles may impose some limitation on players' choices and introduce an exogenous dependence among players' actions, which clashes with the nature of noncooperative game theory. Our suggested solution is to consider every suset of players as measurable. This leads to a nontrivial purely finitely additive component which might prevent the existence of equilibria and requires a novel mathematical approach to prove the existence of '-equilibria.

The allocation of bureaucrats across tasks constitutes a pivotal instrument for achieving an organization's objectives. In this paper, I measure the performance of World Bank bureaucrats by combining the universe of task assignment with an evaluation of task outcome and a hand-collected dataset of bureaucrat CVs. I introduce two novel stylized facts. First, bureaucrat performance correlates with task features and individual characteristics. Second, there exists a negative assortative matching between high-performing bureaucrats and low-performing countries. In the aftermath of natural disasters, which may weaken countries' performance even further, I observe that low-performing countries receive an additional allocation of high-performing bureaucrats. I discuss various interpretations of these findings.

We show that the incentive to engage in exclusionary tying (of two complementary products) may arise even when tying cannot be used as a defensive strategy to protect the incumbent's dominant position in the primary market. By engaging in tying, an incumbent firm sacrifices current profits but can exclude a more efficient rival from a complementary market by depriving it of the critical scale it needs to be successful. In turn, exclusion in the complementary market allows the incumbent to be in a favorable position when a more efficient rival will enter the primary market, and to appropriate some of the rival's efficiency rents. The paper also shows that tying is a more profitable exclusionary strategy than pure bundling, and that exclusion is the less likely the higher the proportion of consumers who multi-home.

We report on a laboratory experiment measuring the preferences of a unique pool of risk professionals over various sources of uncertainty that entail different degrees of complexity. We then compare these preferences with those of a control group composed of social science students to obtain a deeper understanding of the mechanisms driving behaviors under risk and ambiguity. We find that (1) ambiguity aversion is robust to subjects' degree of sophistication in probabilistic reasoning and background. (2) An association exists between attitudes toward ambiguity and compound risk for students/less sophisticated subjects, and is mainly explained by their attitudes toward complexity. Such an association does not exist for risk professionals/more sophisticated subjects. (3) The failure to reduce compound risk emerges as a sufficent, but not necessary, condition for ambiguity non-neutrality. These findings suggest that decision making under ambiguity cannot be reduced to decision making under risk.

Two extensive game structures with imperfect information are said to be behaviorally equivalent if they share the same map (up to relabelings) from profiles of structurally reduced strategies to induced terminal paths. We show that this is the case if and only if one can be transformed into the other through a composition of two elementary transformations, commonly known as "Interchanging of Simultaneous Moves" and "Coalescing Moves/Sequential Agent Splitting."

This paper proposes a new approach to factor modeling based on the long-run equilibrium relation between prices and related drivers of risk (integrated factors). We show that such relationship reveals an omitted variable in standard factor models for returns that we label as Equilibrium Correction Term (ECT). Omission of this term implies misspecification of every factor model for which the equilibrium (cointegrating) relation holds. The existence of this term implies short-run mispricing that disappears in the long-run. Such evidence of persistent but stationary idiosyncratic risk in prices is consistent with deviations from rational expectations. Its inclusion in a traditional factor model improves remarkably the performance of the model along several dimensions. Furthermore, the ECT -being predictive- has strong implications for risk measurement and portfolio allocation. A zero-cost investment strategy that consistently exploits temporary idiosyncratic mispricing earns an average annual excess return of 6.21%, mostly unspanned by existing factors.

This paper presents a model of selective exposure to information and an experiment to test its predictions. An agent interested in learning about an uncertain state of the world can acquire information from one of two sources which have opposite biases: when informed on the state, they report it truthfully; when uninformed, they report their favorite state. When sources have the same reliability, a Bayesian agent is better off seeking confirmatory information. On the other hand, it is optimal to seek contradictory information if and only if the source biased against the prior is sufficiently more reliable. We test these predictions with an online experiment. When sources are symmetrically reliable, subjects are more likely to seek confirmatory information but they listen to the other side too frequently. When sources are asymmetrically reliable, subjects are more likely to consult the more reliable source even when prior beliefs are strongly unbalanced and listening to the less reliable source is more informative. Moreover, subjects follow contradictory advice sub-optimally; are too trusting of information in line with a source bias; and too skeptic of information misaligned with a source bias. Our experiment suggests that biases in information processing and simple heuristics - e.g., listen to the more reliable source - are important drivers of the endogenous acquisition of information.

MIn many domains, committees bargain over a sequence of policies and a policy remains in effect until a new agreement is reached. In this paper, I argue that, in order to assess the consequences of veto power, it is important to take into account this dynamic aspect. I analyze an infinitely repeated divide-the-dollar game with an endogenous status quo policy. I show that, irrespective of legislators' patience and the initial division of resources, policy eventually gets arbitrarily close to full appropriation bythe veto player; that increasing legislators' patience or decreasing the veto player's ability to set the agenda makes convergence to this outcome slower; and that the veto player supports reforms that decrease his allocation. These results stand in sharp contrast to the properties of models where committees bargain over a single policy. The main predictions of the theory find support in controlled laboratory experiments.

Here we report the results of a large RCT conducted at the pan-African level that wants to shed light on the impact of peer effects on innovation and entrepreneurship. The experiment involved around 5000 entrepreneurs (some established, other just aspiring) from 49 African countries. All of those entrepreneurs completed an online business course, while only the treated ones had the additional possibility of interacting with peers, within groups of sixty, and in one of three different setups: (a) face-to-face, (b) virtually 'within' (where interaction was conducted through an Internet platform in groups of entrepreneurs of the same country), (c) virtually 'across' (where the virtually connected groups displayed a balanced heterogeneity across countries). After two and a half months, all participants were asked to submit business proposals. The ones submitted were then evaluated in a two-stage procedure. First, they were graded by a panel of African professionals; subsequently, the pool of highest-graded proposals were again assessed and graded by senior investors, who selected some for possible funding. Two outcome variables follow from this evaluation exercise: the (optional) decision of whether to submit a proposal, and the grades (1 to 5) obtained by the proposals that were submitted. Next, we outline our main results concerning the effect of the treatment on the two aforementioned outcomes - submission and quality (measured in the intensive margin) - as well as the combination of both of them that we call, for short, extensive quality. (1) Virtual-within interaction has a positive and significant treatment effect on the three dimensions: submission, intensive quality, and extensive quality. Instead, when interaction is face-to-face (thus also "within') only submission and the extensive quality margin are affected (positively so). (2) Virtual-across interaction yields no significant effect on any of the former three dimensions. (3)When effective on quality (cf. (1)), the treatment operates by shifting up, on average the evaluation grade of business proposals from low levels (grades 1 or 2) to high ones (grades 4 or 5). (4) The baseline quality of entrepreneurs has a positive effect on performance. However, the average such quality of the peers in one's own group has a negative composition effect on intensive quality. In fact, a similarly negative effect is also induced by peers' average experience level. (5) As a robustness test, the core treatment effects described in (1)-(2) are confirmed to remain essentially unchanged under a full range of control (baseline) variables, while the composition effects identified in (4) are found to survive a standard placebo test. As a second step in the analysis, we construct a social network in each group by defining the weigh of a directed link between two entrepreneurs as the amount of information (overall size of messages) written by one of them for which there is evidence that the other has been exposed to, then writing a subsequent message. Then, on the basis of the network structure so defined, we estimate the induced peer effects and arrive at the following conclusions. (6) In large countries (the only ones for which a sufficient number homogeneous groups can be formed), virtual-within interaction leads to positive and significant peer effects on submission and extensive quality, but not intensive quality. Instead, when entrepreneurs of large countries are exposed to virtual-across interaction, no significant peer effects arise in any of the three outcomes. (7) In the set of small countries, where only virtual-across interaction is possible, there are positive and significant peer effects on both extensive and intensive quality but not on submission. (8) Composition effects on network peers are weak, largely captured by (outcome-based) peer effects. (9) Results (6)-(7) are structurally robust to redefining the network links in the following two ways: (a) they are limited to involve less than a maximum communication lag, suitably parametrized; (b) they are two-sided, their weight tailored to the flow information channeled in both directions. A combined consideration of (1)-(9) reveals an interesting contrast between treatment and peer effects. For example, in view of (1)-(3), we may conclude that whereas some group homogeneity - or face-to-face contact - bring about positive treatment effects, the group heterogeneity induced by virtual-across interaction fails to deliver significant such effects on all three dimensions. Instead, (6)-(7) indicate that network-based peer effects deliver an intriguingly different pattern. For, under virtual-within interaction, we find that entrepreneurs' peers exert a significantly positive influence on submission (and the extensive margin) but not so on quality per se (in the intensive margin, while a some what polar behavior arises in small countries who undergo virtual-across interaction. This suggests that whereas homogeneity leads to peer interaction that is rather independent of peer performance, heterogeneity has peer performance play an important role (both in positive or negative terms, depending on the quality of that performance). Overall, this induces an effect of the treatment that is significantly positive under homogeneity (virtual-within interaction for large countries) but not strong enough to be significant under full-fledged heterogeneity (virtual-across interaction for small countries). The aforementioned contrast between the nature and implications of the treatment effects stated in (1)-(4) and the network peer effects in (6)-(8) is interesting and deserves further investigation. A possible explanation for it might hinge upon the positive role that homogeneity/familiarity may play as a source of encouragement (and hence participation), as opposed to the negative impact it could have in reducing the novelty of ideas and/or highlighting the fear of competition (thus dis-incentivizing information sharing and thus a genuine effect induced by peer performance). To gain a good understanding of these issues, however, one needs the help of theory as well as a detailed investigation of how communication actually unfolds in our context. Both lines of work are part of our ongoing research. Here, we provide a preliminary account of the latter, which is included in the final part of the paper. Our approach to semantic analysis relies on the machine-learning tools developed by the modern field of Natural Language Processing (NLP). This methodology is applied to the vast flow of information exchanged by entrepreneurs (over 140,000 messages) in order to identify, first, what have been the modes/categories of peer communication more prevalent in our context, e.g. business focus, sentiment/encouragement, target audience, etc. Then we use this information to understand what are the different patterns of communication most prevalent in our context, as captured by a corresponding set of conditional and unconditional distributions that show and how communication is associated to: (a)endogenous variables such as behavior or performance; (b)exogenous variables, such as treatment type or individual baseline characteristics. The main conclusions obtained so far can be summarized as follows. Messages are quite polarized in either the business or sentiment dimension, showing an inverse dependence in the (strong) FOSD sense between the respective distributions. Applying the same comparison criterion, we also find that highly performing agents use more business-focused messages, which are not only neutral in sentiment but also targeted to specific peers (rather than being general messages). Interestingly, however, the treatment arm (virtual-within or -across) has no significant effect on the type of communication, while baseline quality and a measure of "motivation' do have an effect analogous to that described before for performance. Finally, we also rely on the message categorization induced by the NLP analysis to construct semantically weighted networks on two specific features/categories: business relevance and sentiment. Quite remarkably, the corresponding peer effects are found to be unaffected by either of these "semantic projections' of the social network. This suggests that, even though entrepreneurs' messages focus heavily on business issues, their communication displays a feature that is often observed in ordinary (non-virtual) interaction: there is a balance between business focus and a comparable amount of sentiment-laden talk.

Do candidates use populism to maximize the impact of political campaigns? Is the supply of populism strategic? We apply automated text analysis to all available 2016 US Presidential campaign speeches and 2018 midterm campaign programs using a continuous index of populism. This novel dataset shows that the use of populist rhetoric is responsive to the level of expected demand for populism in the local audience. In particular, we provide evidence that current U.S. President Donald Trump uses more populist rhetoric in swing states and in locations where economic insecurity is prevalent. These findings were confirmed when the analysis was extended to recent legislative campaigns wherein candidates tended towards populism when campaigning in stiffly competitive districts where constituents are experiencing high levels of economic insecurity. We also show that pandering is more common for candidates who can credibly sustain anti-elite positions, such as those with shorter political careers. Finally, our results suggest that a populist strategy is rewarded by voters since higher levels of populism are associated with higher shares of the vote, precisely in competitive districts where voters are experiencing economic insecurity.

The mathematical framework of psychological game theory is useful for describing many forms of motivation where preferences depend directly on own or others beliefs. It allows for incorporating, e.g., emotions, reciprocity, image concerns, and self-esteem in economic analysis. We explain how and why, discussing basic theory, experiments, applied work, and methodology.

A randomized control trial with 945 entrepreneurs in Jamaica shows positive shortterm impacts of soft-skills training on business outcomes. The effects are concentrated among men, and disappear twelve months after the training. We argue that the main channel is increased adoption of recommended business practices, exclusively observed in the short run. We see persistent effects on an incentivized behavioral measure of perseverance after setbacks, a focus of this training. We compare a course focused only on soft-skills to one that combines soft-skills training with traditional business training. The effects of the combined training are never statistically significant.

A growing literature emphasizes that the output effect of fiscal consolidation hinges on its composition, as the choice of increasing revenues vs cutting expenditure is not neutral. Existing studies, however, underscore the role of local governments in a federal setting. Indeed, transfer cuts at the central level might translate into higher local taxes, changing the effective composition of the fiscal adjustment. We evaluate this transmission mechanism in Italy, where municipalities below the threshold of 5,000 inhabitants were exempted from (large) transfer cuts in 2012. This allows us to implement a difference-in-discontinuities design in order to estimate the causal impact of transfer cuts on the composition of fiscal adjustment, also because tight fiscal rules impose a balanced budget on Italian municipalities. We disclose a pass-through mechanism by which local governments react to the contraction of intergovernmentalrants by mainly increasing taxes rather than reducing spending. From a political economy perspective, this revenue based fiscal consolidation is driven by municipalities with low electoral competition and low party fragmentation.

We consider an expanded notion of social norms that render them belief-dependent and partial, formulate a series of related testable predictions, and design an experiment based on a variant of the dictator game that tests for empirical relevance. Main results: Normative beliefs influence generosity, as predicted. Degree of partiality leads to more dispersion in giving behavior, as predicted.

Psychological game theory (PGT), introduced by Geanakoplos, Pearce & Stacchetti (1989) and significantly generalized by Battigalli & Dufwenberg (2009), extends the standard game theoretic framework by letting players'utility at endnodes depend on their interactive beliefs. While it is understood that a host of applications that model and/or test the role of emotional and other psychological forces find their home in PGT, the framework is abstract and comprises complex mathematical objects, such as players' infinite hierarchies of beliefs. Thus, PGT provides little guidance on how to model specific belief-dependent motivations and use them in game theoretic analysis. This paper takes steps to fill this gap. Some aspects are simplified -e.g., which beliefs matter -but others are refined and brought closer to applications by providing more structure. We start with belief-dependent motivations and show how to embed them in game forms to obtain psychological games. We emphasize the role of time and of the perception of players' intentions. We take advantage of progress made on the foundations of game theory to expand and improve on PGT solution concepts.

We consider multi-stage games with incomplete information and observable actions, and we analyze strategic reasoning by means of epistemic events within a total state space made of all the profiles of behaviors (paths of play) and possibly incoherent infinite hierarchies of conditional beliefs. Thus, we do not rely on types structures, or similar epistemic models. Subjective rationality is defined by the conjunction of coherence of belief hierarchies, rational planning, and consistency between plan and on-path behavior. Since consistent hierarchies uniquely induce beliefs about behavior and belief hierarchies of others, we can define rationality and common strong belief in rationality, and analyze their behavioral and low-order beliefs implications, which are characterized by strong rationalizability. Our approach allows to extend known techniques to the epistemic analysis of psychological games where the utilities of outcomes depend on beliefs of order k or lower. This covers almost all applications of psychological game theory.

This paper shows that vertical foreclosure can have a dynamic rationale. By refusing to supply an efficient downstream rival, a vertically integrated incumbent sacrifices current profits but can exclude the rival by depriving it of the critical profits it needs to be successful. In turn, monopolising the downstream market may prevent the incumbent from losing most of its future profits because: (a) it allows the incumbent to extract more rents from an efficient upstream rival if future upstream entry cannot be discouraged; or (b) it also deters future upstream entry by weakening competition for the input and reducing the post-entry profits of the prospective upstream competitor.

We use monthly data on the US riskless yield curve for a 1982-2015 sample to show that mixing simple regime switching dynamics with Nelson-Siegel factor forecasts from time series models extended to encompass variables that summarize the state of monetary policy, leads to superior predictive accuracy. Such spread in forecasting power turns out to be statistically significant even controlling for parameter uncertainty and sample variation. Exploiting regimes, we obtain evidence that the increase in predictive accuracy is stronger during the Great Financial Crisis in 2007-2009, when monetary policy underwent a significant, sudden shift. Although more caution applies when transaction costs are accounted for, we also report that the increase in predictive power owed to the combination of regimes and of monetary variables that capture the stance of unconventional monetary policies is tradeable. We devise and test butterfly strategies that trade on the basis of the forecasts from the models and obtain evidence of riskadjusted profits both per se and in comparisons to simpler models.

Consider a set of agents who play a network game repeatedly. Agents may not know the network. They may even be unaware that they are interacting with other agents in a network. Possibly, they just understand that their optimal action depends on an unknown state that is, actually, an aggregate of the actions of their neighbors. Each time, every agent chooses an action that maximizes her instantaneous subjective expected payoff and then updates her beliefs according to what she observes. In particular, we assume that each agent only observes her realized payoff. A steady state of the resulting dynamic is a selfconfirming equilibrium given the assumed feedback. We characterize the structure of the set of selfconfirming equilibria in the given class of network games, we relate selfconfirming and Nash equilibria, and we analyze simple conjectural best-reply paths whose limit points are selfconfirming equilibria.

We present a theory of identity politics that builds on two ideas. First, voters identify with the social group whose interests are closest to theirs and that features the strongest policy conflict with outgroups. Second, identification causes voters to slant their beliefs toward the group's distinctive opinion. The theory yields two main implications: i) voters' beliefs are polarized and distorted along group boundaries; ii) economic shocks that induce new cleavages to emerge also bring about large changes in beliefs and preferences across many policy issues. In particular, exposure to globalization or cultural changes may induce voters to switch identities, dampening their demand for redistribution and exacerbating conflicts in other social dimensions. We show that survey evidence is consistent with these implications.

I study unawareness by the lack of knowledge on a generalized state space. In order to understand and contrast properties of unawareness in a non-partitional standard state space model and a partitional generalized state space model, I provide a generalized framework that accommodates both models. I ask: when and how a generalized (in particular, standard) state space model has a sensible form of unawareness; and how unawareness relates to ignorance and possibility. First, unawareness can only take two forms: an agent is ignorant of knowing that she does not know an event; and the agent is ignorant of knowing an event. In either case, unawareness is also associated with the ignorance of the possibility of knowing an event. Second, the agent, who is unaware of an event, is ignorant (but not necessarily unaware) of being unaware of it. Third, the agent, facing infinitely many objects of knowledge, may know that there is an event of which she is unaware, while she cannot know that she is unaware of any particular event. Fourth, getting more information can cause the agent to become unaware of some event.

Journal of Economic Literature Classification Numbers: C70, D83

We exploit one of the largest data leaks to date to study whether and how firms use secret offshore vehicles. From the leaked data, we identify 338 listed firms as users of secret offshore vehicles and document that these vehicles are used to finance corruption, avoid taxes, and expropriate shareholders. Overall, the leak erased $174 billion in market capitalization among implicated firms. Following the increased transparency brought about by the leak, implicated firms experience lower sales from perceptively corrupt countries and avoid less tax. We estimate conservatively that one in seven firms have offshore secrets.

This paper formalizes an informal idea that an agent's knowledge is characterized by a collection of sets such as a -algebra within the framework of a state space model of knowledge. The formalization is based on the agent's logical and introspective abilities and on the underlying structure of the state space. The agent is logical and introspective about what she knows if and only if her knowledge is summarized by a collection of events with the property that, for any event, the collection has the maximal event included in the original event. When the underlying space is a measurable space, the collection becomes a -algebra if and only if the agent is additionally introspective about what she does not know. The paper characterizes why the agent's knowledge takes (or does not take) such a set algebra as a -algebra or a topology, depending on the agent's logical and introspective abilities and on the underlying environment.

Journal of Economic Literature Classification Numbers: C70, D83

We consider revealed preference relations over risky (or uncertain) prospects, and allow them to be nontransitive and/or fail the classical Independence Axiom. We identify the rational part of any such preference relation as its largest transitive subrelation that satisfies the Independence Axiom and that exhibits some coherence with the original relation. It is shown that this subrelation, which we call the rational core of the given revealed preference, exists in general, and under fairly mild conditions, it is continuous. We obtain various representation theorems for the rational core, and decompose it into other core concepts for preferences. These theoretical results are applied to compute the rational cores of a number of well-known preference models (such as Fishburn's SSB model, justifiable preferences, and variational and multiplier modes of rationalizable preferences). As for applications, we use the rational core operator to develop a theory of risk aversion for nontransitive nonexpected utility mod als (which may not even be complete). Finally, we show that, under a basic monotonicity hypothesis, the Preference Reversal Phenomenon cannot arise from the rational core of one's preferences.

One of the most well-known models of non-expected utility is Gul (1991)'s bmodel of Disappointment Aversion. This model, however, is defined implicitly, as the solution to a functional equation; its explicit utility representation is unknown, which may limit its applicability. We show that an explicit representation can be easily constructed, using solely the components of the implicit one. We also provide a more general result: an explicit representation for preferences in the Betweenness class that also satisfy Negative Certainty Independence (Dillenberger, 2010).

In this teaching note we discuss the relation between rational inattention and a major branch of information theory called rate distortion theory. Focusing on methods, we translate tools from rate distortion theory into the language of rational inattention. These tools provide an alternative, more primitive, approach to the study of optimal attention allocation.

We adopt the epistemic framework of Battigalli and Siniscalchi (J. Econ. Theory 88:188-230, 1999) to model the distinction between a player's behavior at each node, which is part of the external state, and his plan, which is described by his beliefs about his own behavior. This allows us to distinguish between intentional and unintentional behavior, and to explicitly model how players revise their beliefs about the intentions of others upon observing their actions. Rational players plan optimally and their behavior is consistent with their plans. We illustrate our approach with detailed examples and some results. We prove that optimal planning, belief in continuation consistency and common full belief in both imply the backward induction strategies and beliefs in games with perfect information and no relevant ties. More generally, we present within our framework relevant epistemic assumptions about backward and forward-induction reasoning, and relate them to similar ones studied in the previous literature.

We develop a general framework to study source-dependent preferences in economic contexts. We behaviorally identify two key features. First, we drop the assumption of uniform uncertainty attitudes and allow for source-dependent attitudes. Second, we introduce subjective prices to compare outcomes across different sources. Our model evaluates profiles source-wise, by computing the source-dependent certainty equivalents; the latter are converted into the unit of account of a common source and then aggregated into a unique evaluation. By viewing time and location as instances of sources, we show that subjective discount factors and subjective exchange rates are emblematic examples of subjective prices. Finally, we use the model to explore the implications on optimal portfolio allocations and home bias.

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean-variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968-2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean-variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the constituents of the S&P100 index shows that cross-firm connectivity significantly increased over the period 1999-2003 and during the financial crisis in 2008-2009. Finally, we provide evidence that firm-level centrality does not correlate with market values and it is instead positively linked to realized financial losses.

What are the effects of a housing bubble on the rest of the economy? We show that if firms and banks face collateral constraints, a housing bubble initially raises credit demand by housing firms while leaving credit supply unaffected. It therefore crowds out credit to non-housing firms. If time passes and the bubble lasts, however, housing firms eventually pay back their higher loans. This leads to an increase in banks' net worth and thus to an expansion in their supply of credit to all firms: crowding-out gives way to crowding-in. These predictions are confirmed by empirical evidence from the recent Spanish housing bubble. In the early years of the bubble, non-housing firms reduced their credit from banks that were more exposed to the bubble, and firms that were more exposed to these banks had lower credit and output growth. In its last years, these effects were reversed.

Since the middle of the 1990s, productivity growth in Southern Europe has been substantially lower than in other developed countries. In this paper, we argue that this divergence was partly caused by inefficient management practices, which limited Southern Europe's gains from the IT Revolution. To quantify this effect, we build a multi-country general equilibrium model with heterogeneous firms and workers. In our model, the IT Revolution generates divergence for three reasons. First, inefficient management limits Southern firms' productivity gains from IT adoption. Second, IT increases the aggregate importance of management, making its inefficiencies more salient. Third, IT-driven wage increases in other countries stimulate Southern high-skill emigration. We calibrate our model using firm-level evidence, and show that it can account for 28% of Italy's, 39% of Spain's and 67% of Portugal's productivity divergence with respect to Germany between 1995 to 2008.

We experimentally explore decision-making under uncertainty using a framework that decomposes uncertainty into three distinct layers: (1) physical uncertainty, entailing inherent randomness within a given probability model, (2) model uncertainty, entailing subjective uncertainty about the probability model to be used and (3) model misspecification, entailing uncertainty about the presence of the true probability model among the set of models considered. Using a new experimental design, we measure individual attitudes towards these different layers of uncertainty and study the distinct role of each of them in characterizing ambiguity attitudes. In addition to providing new insights into the underlying processes behind ambiguity aversion -failure to reduce compound probabilities or distinct attitudes towards unknown probabilities- our study provides the first empirical evidence for the intermediate role of model misspecification between model uncertainty and Ellsberg in decision-making under uncertainty.

We study in a theoretical and experimental setting the interaction between belief-dependent preferences and reputation building in a finitely repeated trust game. We focus mainly on the effect of guilt aversion. In a simple two-types model, we analyze the effect of reputation building in presence of guilt-averse players and derive behavioral predictions. In the experiment, we elicit information on trustees' belief-dependent preferences and disclose it to the paired trustor before the repeated game. Our experimental results show that disclosing information on the trustee's belief-dependent preferences and thus letting players play the repeated trust game in presence of almost complete information leads to higher trust and cooperation than in the corresponding incomplete information game setting. In particular, disclosure of information on preferences of guilt-averse trustees also enhances the trustors'cooperation. Disclosure of information on belief-dependent preferences of reciprocity-concerned trustees, instead, does not lead to higher trust and cooperation. We show that this is theoretically consistent with subjects featuring low reciprocity concerns.

In social dilemmas, choices may depend on belief-dependent motivations enhancing the credibility of promises or threats at odds with personal gain maximization. We address this issue theoretically and experimentally in the context of the Ultimatum Minigame, assuming that the choice of accepting or rejecting an unfair proposal is affected by a combination of frustration, due to unfulfilled expectations, and inequity aversion. We increase the responder's payoff from the default allocation (the proposer's outside option) with the purpose of increasing the responder's frustration due to the unfair proposal, and thus his willingness to reject it. In addition, we manipulate the method of play, with the purpose of switching on (direct response method) and off (strategy method) the responder's experience of anger. Our behavioral predictions across and within treatments are derived from the theoretical model complemented by explicit auxiliary assumptions, without relying on equilibrium analysis.

We show that a probability measure on a metric space X has full support if and only if the set of all probability measures that are absolutely continuous with respect to it is dense in P (X). We illustrate the result through a general version of Laplace's method, which in turn leads to a general stochastic convergence result to global maxima.

Firm-level productivity shocks can help understand sector- and macroeconomic-level outcomes. Capturing the market power of these firms is important: it determines how productivity gains translate into prices and markups. In existing models, firms do not internalize the impact of their systemic size. This paper explores the alternative oligopolistic market structure. To this end, I build a tractablemulti-sector heterogeneous-firmgeneral equilibriummodel featuring oligopolistic competition and an input-output (I-O) network. By affecting price and markup, firm-level productivity shocks propagate both to the downstream and upstream sectors. Sector-level competition intensity affects the strength of these new propagation mechanisms. The structural importance of a firm is determined by the interaction of (i) the sector-level competition intensity, (ii) the firm's sector position in the I-O network, and (iii) the firm size. In a calibration exercise, the aggregate volatility arising from independent firm-level shock is 34% of the one observed in the data.

by Nicola Fontana, Tommaso Nannicini, Guido Tabellini

The Italian civil war and the Nazi occupation of Italy occurred at a critical juncture, just before the birth of a new democracy. We study the impact of these traumatic events by exploiting geographic heterogeneity in the duration and intensity of civil war, and the persistence of the battlefront along the "Gothic line" cutting through Northern-Central Italy. We find that the Communist Party gained votes in postwar elections where the Nazi occupation lasted longer, mainly at the expense of centrist parties. This effect persists until the late 1980s and appears to be driven by equally persistent changes in political attitudes.

In this work we propose a definition of comonotonicity for elements of B (H)sa, i.e., bounded self-adjoint operators defined over a complex Hilbert space H. We show that this notion of comonotonicity coincides with a form of commutativity. Intuitively, comonotonicity is to commutativity as monotonicity is to bounded variation. We also define a notion of Choquet expectation for elements of B (H)sa that generalizes quantum expectations. We characterize Choquet expectations as the real-valued functionals over B (H)sa which are comonotonic additive, c- monotone, and normalized.

We review recent models of choices under uncertainty that have been proposed in the economic literature. The framework that we propose is general and may be applied in many different fields of environmental economics. To illustrate, we provide a simple application in the context of an optimal mitigation policy. Our objective is to offer guidance to policy makers who face uncertainty when designing climate policy.

We provide both an axiomatic and a neuropsychological characterization of the dependence of choice probabilities on time in the softmax (or Multinomial Logit Process) form (see below picture) MLP is the most widely used model of preference discovery in all fields of decision making, from Quantal Response Equilibrium to Discrete Choice Analysis, from Psychophysics and Neuroscience to Combinatorial Optimization. Our axiomatic characterization of softmax permits to empirically test its descriptive validity and to better understand its conceptual underpinnings as a theory of agents'rationality. Our neuropsychological foundation provides a computational model that may explain softmax emergence in human behavior and that naturally extends to multialternative choice the classical Diffusion Model paradigm of binary choice. These complementary approaches provide a complete perspective on softmaximization as a model of preference discovery, both in terms of internal (neuropsychological) causes and external (behavioral) effects.

We develop new likelihood-based methods to estimate factor-based Stochastic Discount Factors (SDF) that may accommodate Hidden Markov dynamics in the factor loadings. We use these methods to investigate whether it is possible to find a SDF that jointly prices the cross-section of eight U.S. portfolios of stocks, Treasuries, corporate bonds, and commodities. In particular, we test a range of possible different specification of the SDF, including single-state and Hidden Markov models and compare their statistical and pricing performances. In addition, we assess whether and to which extent a selection of these models replicates the observed moments of the return series, and especially correlations. We report that regime-switching models clearly outperform single-state ones both in term of statistical and pricing accuracy. However, while a four-state model is selected by the information criteria, a two-state three-factor full Vector Autoregression model outperforms the others as far as the pricing accuracy is concerned.

Deposit volatility and costly bank liquidity increase the long-term lending rates offered by banks, which reduce loan maturities, long-term investment and output. We formalise this mechanism in a banking model and analyse exogenous variation in deposit volatility induced by a Sharia levy in Pakistan. Data from the credit registry and a firm-level survey show that deposit volatility and liquidity cost: 1) reduce loan maturities and lending rates; 2) leave loan amounts and total investment unchanged; 3) redirect investment from fixed assets towards working capital. A targeted liquidity program is quantified to generate yearly output gains between 0.042% and 0.205%.

The regulation of bank liquidity can create a commitment device on repaying depositors in bad states, if deposit insurance is absent. A theoretical model shows that liquidity regulation can: 1) stimulate a deposit inflow, moderating the limited liability inefficiency; 2) promote lending and branching, if deposit growth exceeds the intermediation margin decline. Our empirical test exploits an unexpected policy change, which fostered the liquid assets of Ethiopian banks by 25% in 2011. Exploiting the cross-sectional heterogeneity in bank size and bank-level databases, we find an increase in deposits, loans and branches, with no decline in profits.