CyberSec Research

Ensuring efficiency and envy-freeness in allocating indivisible goods without money often requires randomization. However, existing combinatorial assignment mechanisms (for applications such as course allocation, food banks, and refugee resettlement) guarantee these properties either ex ante or ex post, but not both. We propose a new class of mechanisms based on Competitive Equilibrium from Random Incomes (CERI): Agents receive random token budgets and select optimal lotteries at competitive prices that clear markets in expectation. Our main insight is to let the CERI price vector guide all ex-post allocations. We show that all ordinally efficient allocations are CERI allocations, which can be implemented as lotteries over near-feasible Pareto-efficient outcomes. With identical budget distributions, CERI allocations are ordinally envy-free; with budget distributions on small supports, ex-post allocations are envy-free up to one good. Moreover, we design an asymptotically efficient implementation of CERI that satisfies a strong new non-manipulability property in large markets.

The consumption function maps current wealth and the exogenous state to current consumption. We prove the existence and uniqueness of a consumption function when the agent has a preference for wealth. When the period utility functions are restricted to power functions, we prove that the consumption function is asymptotically linear as wealth tends to infinity and provide a complete characterization of the asymptotic slopes. When the risk aversion with respect to wealth is less than that for consumption, the asymptotic slope is zero regardless of other model parameters, implying wealthy households save a large fraction of their income, consistent with empirical evidence.

Restricting individuals' access to some opportunities may steer their desire toward their substitutes, a phenomenon known as the forbidden fruit effect. We axiomatize a choice model named restriction-sensitive choice (RSC), which rationalizes the forbidden fruit effect and is compatible with the prominent psychological explanations: reactance theory and commodity theory. The model is identifiable from choice data, specifically from the observation of choice reversals caused by the removal of options. We conduct a normative analysis both in terms of the agent's freedom and welfare. We apply our model to shed light on two phenomena: the backfire effect of beliefs and the backlash of integration policies targeted towards minorities.

Completeness and transitivity are standard rationality conditions in economics. However, under ambiguity, decision makers sometimes violate these requirements because of the difficulty of forming accurate predictions about ambiguous events. Motivated by this, we study various ambiguity preferences that partially satisfy completeness and transitivity. Our characterization results show that completeness and a novel yet natural weakening of transitivity correspond to two opposite ways of using multiple probability distributions in mind; that is, these two axioms have dual implications at the level of cognitive processes for ambiguity.

Building on the classical Okishio theorem, we construct a two-sector, multi-period dynamic model that relaxes the rigid assumption of a fixed real wage and introduces an endogenous wage-growth mechanism together with a process of technology diffusion. Through analytical derivations and numerical simulations we find that the long-run trajectory of the profit rate is not unique: it hinges on the relative strength of the speed of wage adjustment and the potency of technical progress. (1) When wage adjustment is relatively sluggish, the technical effect dominates and the profit rate trends upward. (2) When wage adjustment proceeds at a moderate pace, the profit rate first rises and then falls. (3) When wage adjustment is extremely rapid, the wage effect dominates and the profit rate declines continuously. The results offer a new theoretical lens on the intricate interplay among technical change, wage dynamics and profitability.

This paper studies a matching problem in which a group of agents cooperate with agents on two sides. In environments with either nontransferable or transferable utilities, we demonstrate that a stable outcome exists when cooperations exhibit same-side complementarity and cross-side substitutability. Our results apply to pick-side matching problems and membership competition in online duopoly markets.

We propose a new decision model under ambiguity, called the Choquet rank-dependent utility model. The model extends the Choquet expected utility model by allowing for the reduction to the rank-dependent utility model in the absence of ambiguity, rather than to the expected utility model. The model has three major components: a utility function $u$ and a probability distortion $g$, which together capture the risk component of the preferences, and generalized probabilistic beliefs $\nu$, which captures the ambiguity component of the preferences. The representation takes the form $X\succsim Y\iff \int_{\Omega} u(X)d(g\circ\nu)\iff \int_{\Omega} u(Y)d(g\circ\nu).$ To obtain the axiomatization, we work in the uncertainty setting of Savage with a non-ambiguous source. Afterwards, we discuss ambiguity attitudes and their representation with respect to the generalized probabilistic beliefs, along with conditions for a robust representation.

How does targeted advertising influence electoral outcomes? This paper presents a one-dimensional spatial model of voting in which a privately informed challenger persuades voters to support him over the status quo. I show that targeted advertising enables the challenger to persuade voters with opposing preferences and swing elections decided by such voters; under simple majority, the challenger can defeat the status quo even when it is located at the median voter's bliss point. Ex-ante commitment power is unnecessary -- the challenger succeeds by strategically revealing different pieces of verifiable information to different voters. Publicizing all political ads would mitigate the negative effects of targeted advertising and help voters collectively make the right choice.

In this short paper, we define the investment ability of data investors in the data economy and its heterogeneity. We further construct an analytical heterogeneous agent model to demonstrate that differences in data investment ability lead to divergent economic results for data investors. The analytical results prove that: Investors with higher data investment ability can obtain greater utility through data investment, and thus have stronger incentives to invest in a larger scale of data to achieve higher productivity, technological progress, and experience lower financial frictions. We aim to propose a prerequisite theory that extends the analytical framework of the data economy from the currently prevalent representative agent model to a heterogeneous agent model.

We study cheap talk with simple language, where the sender communicates using a score that aggregates a multidimensional state. Both the sender and the receiver share the same payoffs, given by a quadratic loss function. We show that the restriction to scores introduces strategic considerations. First, equilibrium payoffs can be strictly lower than those achievable under commitment to a scoring rule. Second, we prove that any equilibrium score must be either linear or discrete. Finally, assuming normally distributed states, we fully characterize the set of equilibrium linear scores, which includes both the ex-ante best and the worst linear scores.

We formalize what it means to have conceptual knowledge about a statistical decision-making environment. Such knowledge tells agents about the structural relationships among unknown, payoff-relevant states. It allows agents to represent states as combinations of features. Conceptual knowledge is more valuable when states are more "reducible": when their prior variances are explained by fewer features. Its value is non-monotone in the quantity and quality of available data, and vanishes with infinite data. Agents with deeper knowledge can attain the same welfare with less data. This is especially true when states are highly reducible.

We study a Bayesian persuasion setting in which a sender wants to persuade a critical mass of receivers by revealing partial information about the state to them. The homogeneous binary-action receivers are located on a communication network, and each observes the private messages sent to them and their immediate neighbors. We examine how the sender's expected utility varies with increased communication among receivers. We show that for general families of networks, extending the network can strictly benefit the sender. Thus, the sender's gain from persuasion is not monotonic in network density. Moreover, many network extensions can achieve the upper bound on the sender's expected utility among all networks, which corresponds to the payoff in an empty network. This is the case in networks reflecting a clear informational hierarchy (e.g., in global corporations), as well as in decentralized networks in which information originates from multiple sources (e.g., influencers in social media). Finally, we show that a slight modification to the structure of some of these networks precludes the possibility of such beneficial extensions. Overall, our results caution against presuming that more communication necessarily leads to better collective outcomes.

In this paper, we consider finite-strategy approximations of infinite-strategy evolutionary games. We prove that such approximations converge to the true dynamics over finite-time intervals, under mild regularity conditions which are satisfied by classical examples, e.g., the replicator dynamics. We identify and formalize novel characteristics in evolutionary games: choice mobility, and its complement choice paralysis. Choice mobility is shown to be a key sufficient condition for the long-time limiting behavior of finite-strategy approximations to coincide with that of the true infinite-strategy game. An illustrative example is constructed to showcase how choice paralysis may lead to the infinite-strategy game getting "stuck," even though every finite approximation converges to equilibrium.

Generative AI is a technology which depends in part on participation by humans in training and improving the automation potential. We focus on the development of an "AI twin" that could complement its creator's efforts, enabling them to produce higher-quality output in their individual style. However, AI twins could also, over time, replace individual humans. We analyze this trade-off using a principal-agent model in which agents have the opportunity to make investments into training an AI twin that lead to a lower cost of effort, a higher probability of success, or both. We propose a new framework to situate the model in which the tasks performed vary in the ease to which AI output can be improved by the human (the "editability") and also vary in the extent to which a non-expert can assess the quality of output (its "verifiability.") Our synthesis of recent empirical studies indicates that productivity gains from the use of generative AI are higher overall when task editability is higher, while non-experts enjoy greater relative productivity gains for tasks with higher verifiability. We show that during investment a strategic agent will trade off improvements in quality and ease of effort to preserve their wage bargaining power. Tasks with high verifiability and low editability are most aligned with a worker's incentives to train their twin, but for tasks where the stakes are low, this alignment is constrained by the risk of displacement. Our results suggest that sustained improvements in company-sponsored generative AI will require nuanced design of human incentives, and that public policy which encourages balancing worker returns with generative AI improvements could yield more sustained long-run productivity gains.

This paper provides the first econometric evidence for diagnostic expectations (DE) in DSGE models. Using the identification framework of Qu and Tkachenko (2017), I show that DE generate dynamics unattainable under rational expectations (RE), with no RE parameterization capable of matching the volatility and persistence patterns implied by DE. Consequently, DE are not observationally equivalent to RE and constitute an endogenous source of macroeconomic fluctuations, distinct from both structural frictions and exogenous shocks. From an econometric perspective, DE preserve overall model identification but weaken the identification of shock variances. To ensure robust conclusions across estimation methods and equilibrium conditions, I extend Bayesian estimation with Sequential Monte Carlo sampling to the indeterminacy domain. These findings advance the econometric study of expectations and highlight the macroeconomic relevance of diagnostic beliefs.

How can voters induce politicians to put forth more proximate (in terms of preference) as well as credible platforms (in terms of promise fulfillment) under repeated elections? Building on the work of Aragones et al. (2007), I study how reputation and re-election concerns affect candidate behavior and its resultant effect on voters' beliefs and their consequent electoral decisions. I present a formal model where, instead of assuming voters to be naive, I tackle the question by completely characterizing a set of subgame-perfect equilibria by introducing non-naive (or strategic) voting behavior into the mix. I find that non-naive voting behavior, by using the candidate's reputation as an instrument of policy discipline after the election, aids in successfully inducing candidates to put forth their maximal incentive-compatible promise (among a range of such credible promises) in equilibrium. Through the credible threat of punishment in the form of loss of reputation for all future elections, non-naive voters gain a unanimous increase in expected utility relative to when they behave naively. In fact, comparative statics show that candidates who are more likely to win are more likely to keep their promises. In this framework, voters are not only able to bargain for more credible promises but also end up raising their expected future payoffs in equilibrium. Including such forms of strategic behavior thus reduces cheap talk by creating a credible electoral system where candidates do as they say once elected. Later, I present an analysis that includes limited punishment as a political accountability mechanism.

We study a noncooperative $n$-player game of slack allocation in which each player $j$ has entitlement $L_j>0$ and chooses a claim $C_j\ge0$. Let $v_j=(C_j-L_j)_+$ (overage) and $s_j=(L_j-C_j)_+$ (slack); set $X=\sum_j v_j$ and $I=\sum_j s_j$. At the end of the period an overage-proportional clearing rule allocates cooperative surplus $I$ to defectors in proportion to $v_j$; cooperators receive $C_j$. We show: (i) the selfish outcome reproduces the cooperative payoff vector $(L_1,\dots,L_n)$; (ii) with bounded actions, defection is a weakly dominant strategy; (iii) within the $\alpha$-power family, the linear rule ($\alpha=1$) is the unique boundary-continuous member; and (iv) the dominant-strategy outcome is Strong Nash under transferable utility and hence coalition-proof (Bernheim et al., 1987). We give a policy interpretation for carbon rationing with a penalty collar.

This paper studies a two-player game in which the players face uncertainty regarding the nature of their partner. In this variation of the standard Prisoner's Dilemma, players may encounter an 'honest' type who always cooperates. Mistreating such a player imposes a moral cost on the defector. This situation creates a trade-off, resolved in favor of cooperation if the player's trust level, or belief in their partner's honesty, is sufficiently high. We investigate whether an environment where players have explicit beliefs about each other's honesty is more or less conducive to cooperation, compared to a scenario where players are entirely uncertain about their partner's beliefs. We establish that belief diversity hampers cooperation in environments where the level of trust is relatively low and boosts cooperation in environments with a high level of trust.