Heterogeneous Agents

Using the strategy method (Selten 1967) we elicit subjects' strategies for playing any 2-person 3x3-game with integer payoffs between 0 and 99. In each of 5 tournaments, every strategy pair plays 500000 games. The frequency of pure strategy equilibrium play increases from 51% in the first to 74% in the last tournament, with the equilibria that maximize joint payoff being preferred when multiple exist. For games without pure equilibria, strategies are typically based on elements of the best-reply cascade: MAP (maximize the expected payoff against uniformly randomizing opponents), BR-MAP (best reply to MAP), and BR-BR-MAP (best reply to BR-MAP).

We propose a model economy consisting of interdependent real, monetary and stock markets. The money market is influenced by the real one through a standard LM equation. Private expenditures depend on stock prices, which in turn are affected by interest rates and real profits, as these contribute to determine the participation level in the stock market. An evolutionary mechanism regulates agents' participation in the stock market on the basis of a fitness measure that depends on the comparison between the stock return and the interest rate. Relying on analytical investigations complemented by numerical simulations, we study the economically relevant static and dynamic properties of the equilibrium, identifying the possible sources of instabilities and the channels through which they spread across markets. We aim at understanding what micro-and macro-factors affect the dynamics and, at the same time, how the dynamics of asset prices, which are ultimately influenced by the money market, behave over the business cycle. Starting from isolated markets, we show the effect of increasing the market interdependence on the national income, the stock price and the share of agents that participate in the stock market at the equilibrium. Moreover, we investigate the stabilizing/destabilizing role of market integration and the possible emergence of out-of-equilibrium dynamics.

We study a financial market populated by heterogeneous fundamentalists, whose decisions are driven by "animal spirits". Each agent may have optimistic or pessimistic beliefs about the fundamental value, which are selected from time to time on the basis of an evolutionary mechanism. The evolutionary selection depends on a weighted evaluation of the general market sentiment perceived by the agents and on a profitability measure of the existent strategies. As the relevance given to the sentiment index increases, a herding phenomenon in agents behavior may take place and the animal spirits can drive the market toward polarized economic regimes, which coexist and are characterized by persistent high or low levels of optimism and pessimism. This conduct is detectable from agents polarized shares and beliefs, which in turn influence the price level. Such polarized economic regimes can consist in stable steady states or can be characterized by endogenous complex dynamics, generating persistent alternating waves of optimism and pessimism, as well as return distributions displaying fat tails and excess volatility.

Students learn through a series of systemic and innovative learning activities instead of only learning resources. However, most e-Learning systems nowadays are resources-oriented instead of processoriented. In addition, existing systems are designed without adequate pedagogical principles and provide little capabilities to cater for different student's individual needs. This paper investigates the possibility of applying process-oriented approach to design, enact, control, and refine the e-Learning processes. Furthermore, agent technology is applied to deal with dynamic situations. A processoriented and agent-based e-Learning environment is developed, with case scenario to demonstrate the usability of the approach.

In this paper, we study the existence of an intertemporal equilibrium in a Ramsey model with heterogenous discounting, elastic labor supply and borrowing constraints. Applying a fixed-point argument by , we prove the existence of an equilibrium in a truncated bounded economy. This equilibrium is also an equilibrium of any unbounded economy with the same fundamentals. Then, we prove the existence of an equilibrium in an infinite-horizon economy as a limit of a sequence of truncated economies. On the one hand, our paper generalizes because of the elastic labor supply and, on the other hand, Bosi and Seegmuller (2010) because of a proof of global existence. Our methodology can be also applied to other Ramsey models with different market imperfections. The issue of bubbles existence and efficiency is raised at the end of the paper.

This paper studies the properties of the continuous double-auction trading mechanism using an artificial market populated by heterogeneous computational agents. In particular, we investigate how changes in the population of traders and in market microstructure characteristics affect price dynamics, information dissemination, and distribution of wealth across agents. In our computer-simulated market only a small fraction of the population observe the risky asset's fundamental value with noise, while the rest of the agents try to forecast the asset's price from past transaction data. In contrast to other artificial markets, we assume that the risky asset pays no dividend, thus agents cannot learn from past transaction prices and subsequent dividend payments. We find that private information can effectively disseminate in the market unless market regulation prevents informed investors from short selling or borrowing the asset, and these investors do not constitute a critical mass. In such case, not only are markets less efficient informationally, but may even experience crashes and bubbles. Finally, increased informational efficiency has a negative impact on informed agents' trading profits and a positive impact on artificial intelligent agents' profits.

Optimal monetary policy is studied, by way of numerical examples, in a model with (i) heterogeneity in the degree to which different people are monitored (have publicly known histories); (ii) idiosyncratic shocks that give rise to heterogeneity in earning and spending realizations; and (iii) central-bank intervention in a "market" in claims or credit in which the participants are those who are heavily monitored. The results serve as counterexamples to two widely held views: optimal policy is unrelated to what makes money important; and, there are simple and well-known principles to guide monetary policy. [For the Bank of England in 1805] knowing the direction of the wind was [important] ... If ... from the east, ships would soon be sailing up the Thames to unload goods in London. The Bank would need to supply lots of money..... If a westerly was blowing, the Bank would mop up any excess money..., thereby avoiding inflation. The 19th century Bank knew the importance of money ..., Mervyn King, the current governor, told the FT in an interview .... But money matters were much simpler in 1805 than today ("Winds of change" by Chris Giles, Financial Times, (FT), May 14, 2007).

Due to the spread of distributed systems, a number of agent systems have been developed. Since most existing multiagent systems implement different agent platforms, it is extremely hard to get heterogeneous agents to work together. In this paper, we introduce a new network protocol called Agent Platform Protocol (APP), which is designed to meet the exact demands of agent interaction

We study the quantitative implications of fiscal policy decisions in an heterogeneous agent model with incomplete markets, and where equity and government debt are not perfect substitutes. This set-up allows us to study the impact on macroeconomic activity, cross-sectional wealth distribution, asset prices and the risk premium, in a unified framework. For a given level of government expenditures, a 10% increase in government debt to GDP decreases the capital stock between 1.0% and 1.5%, depending on how the new debt is financed, while the cost of government debt increases by between 6 to 12 basis points, inducing households to hold the extra bonds. Given the crowding out of investment the return on capital also rises. Despite the modest impact of fiscal policy decisions on asset returns we show that it is very important to measure the impact of those decisions in a model where the capital stock and government bonds are not perfect substitutes. More precisely, our results identify the portfolio re-allocation behavior of households (asset substitution channel), as extremely important for determining the impact of fiscal policy decisions on capital accumulation, and aggregate economic activity in general. On the other hand, the crowding-out effect of taxes through the tightening of liquidity constraints is very small since the households potentially affected by these constraints own a very small fraction of the capital stock.

Illinois and UCLA) is an outstanding scholar in several fields of Economics. He is very special to the JEIC community because he is one of the founder-fathers of the ESHIA and a pioneer of the HIA approach. Taken at the conference building of the First Meeting of ESHIA,

We try to construct an evolutionary theory of economic and social interaction of heterogeneous agents. Modern physics is helpful for such an attempt, as the recent flourishing of econophysics exemplifies. In this article, we are interested in a specific or more fundamental use of physics rather than in the recent researches of econo-physics. In the first part of this article, we mainly focus on the traditional von Neumann-Sraffa model of production as complex adaptive system and examine the measure of complexity on this model in view of thermodynamical ideas. We then suggest the idea of hierarchical inclusion on this model to define complexity of production. In the latter part, we try to construct an elementary theory of social interaction of heterogeneous agents in view of statistical mechanics.

This paper presents a stylized model of technology adoptions for sustainable development under the three potentially most important "stylized facts": increasing returns to adoption, uncertainty, and heterogeneous agents following diverse technology development and adoption strategies. The stylized model deals with three technologies and two heterogeneous agents: a risk-taking one and a risk-averse one. Interactions between the two agents include trade in resources and goods, and technological spillover (free riding and technology trade). With the two heterogeneous agents, we run optimizations to minimize their aggregated costs in order to find out what rational behaviors are under different assumptions if the two agents are somehow cooperative. By considering uncertain carbon taxes, the model also addresses environmental issues as potential driving forces for technology adoptions.

Which strategies do agents use when forming expectations about future prices, and how often does this lead to stable or unstable outcomes? We performed a four-round strategy experiment in a cobweb economy with expectations feedback. Subjects received feedback about their performance, and could revise their strategy. Over the rounds forecasting errors decrease and realized market prices move close to the rational expectations steady state, but the complexity of the price fluctuations also increases. Convergence to the unique RE steady state occurs in less than 10% of all cases. In the final round 60% of the price fluctuations appears to be chaotic. Heterogeneous interaction of simple prediction strategies seems to be the main source of the endogenous price fluctuations, frequently leading to a boundedly rational equilibrium of 'close to the steady state chaos'.

This paper presents an analytical treatment of economic systems with an arbitrary number of agents that keeps track of the systems' interactions and agent's complexity. The formalism does not seek to aggregate agents: it rather replaces the standard optimization approach by a probabilistic description of the agents' behaviors and of the whole system. This is done in two distinct steps. A …rst step considers an interacting system involving an arbitrary number of agents, where each agent's utility function is subject to unpredictable shocks. In such a setting, individual optimization problems need not be resolved. Each agent is described by a time-dependent probability distribution centered around its utility optimum. The whole system of agents is thus de…ned by a composite probability depending on time, agents' interactions, relations of strategic dominations, agents' information sets and expectations. This setting allows for heterogeneous agents with di¤erent utility functions, strategic domination relations, heterogeneity of information, etc. This dynamic system is described by a path integral formalism in an abstract space -the space of the agents' actions -and is very similar to a statistical physics or quantum mechanics system. We show that this description, applied to the space of agents' actions, reduces to the usual optimization results in simple cases. Compared to the standard optimization, such a description markedly eases the treatment of a system with a small number of agents. It becomes however useless for a large number of agents. In a second step therefore, we show that, for a large number of agents, the previous description is equivalent to a more compact description in terms of …eld theory. This yields an analytical, although approximate, treatment of the system. This …eld theory does not model an aggregation of microeconomic systems in the usual sense, but rather describes an environment of a large number of interacting agents. From this description, various phases or equilibria may be retrieved, as well as the individual agents' behaviors, along with their interaction with the environment. This environment does not necessarily have a unique or stable equilibrium and allows to reconstruct aggregate quantities without reducing the system to mere relations between aggregates. For illustrative purposes, this paper studies several economic models with a large number of agents, some presenting various phases. These are models of consumer/producer agents facing binding constraints, business cycle models, and psycho-economic models of interacting and possibly strategic agents.

Individuals in social networks often imperfectly monitor others' network relationships and have incomplete information about the value of forming new relationships. This paper introduces the Generalized Conjectural Equilibrium (GCE) concept for such settings and completely characterizes the set of GCE networks when players observe only local parts of the network. Incomplete information and imperfect monitoring generate different types of inefficiency. These inefficiencies increase in number and scope as network observation becomes more localized. These results suggest that actual social networks will be structured inefficiently in general.

Individuals in many social networks imperfectly monitor other individuals' network relationships. This paper shows that, in a model of a communication network, imperfect monitoring leads to the existence of many ine cient equilibria. Reasonable restrictions on actions or on beliefs about others' actions can, however, eliminate many of these ine cient equilibria even with imperfect monitoring. Star networks, known to be e cient in many settings, are shown to have desirable monitoring characteristics. More generally, this paper provides a formal framework in which to study incorrect perceptions as an equilibrium phenomenon in social networks.

We investigate the role of search frictions in markets with price competition and how it leads to sorting of heterogeneous agents. There are two aspects of value creation: the match value when two agents actually trade and the probability of trading governed by the search technology. We show that positive assortative matching obtains when complementarities in the former outweigh complementarities in the latter. This happens if and only if the match-value function is root-supermodular, that is, its nth root is supermodular, where n reflects the elasticity of substitution of the search technology. This condition is weaker than the condition required for positive assortative matching in markets with random search.

We develop a model of decentralized monetary exchange that can be used to examine the distributional effects of inflation across heterogeneous agents who have private information. The private information can be about the productivity, preferences, or money holdings of the agents. Matching is multilateral and each seller is visited by a stochastic number of buyers. The good is allocated according a second-price auction in money. In equilibrium, homogeneous buyers hold different amounts of money leading to price dispersion. We find the closed-form solution for the distribution of money holdings. Entry of sellers is suboptimal except at the Friedman rule. When agents differ in productivity, inflation acts as a regressive tax, at least for moderate rates of money growth. * We thank Randy Wright for his support and encouragement. We benefitted from the comments of our editor Steve Williamson, an anonymous referee as well as Ed Green, Guillaume Rocheteau, Gustavo Ventura, Neil Wallace and Ruilin Zhou, and conference and seminar participants. Earlier versions of this paper were circulated under the titles "Directed Multilateral Matching in a Monetary Economy" and "Dispersion of Money Holdings and Efficiency.

We investigate under which conditions price competition in a market with matching frictions leads to sorting of buyers and sellers. Positive assortative matching obtains only if there is a high enough degree of complementarity between buyer and seller types. The relevant condition is rootsupermodularity; i.e., the square root of the match value function is supermodular. It is a necessary and sufficient condition for positive assortative matching under any distribution of buyer and seller types, and does not depend on the details of the underlying matching function that describes the search process. The condition is weaker than log-supermodularity, a condition required for positive assortative matching in markets with random search. This highlights the role competition plays in matching heterogeneous agents. Negative assortative matching obtains whenever the match value function is weakly submodular.

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The aim of this paper is to examine the effect of neighborhood structures on the evolution of cooperative behavior in a spatial IPD (Iterated Prisoner's Dilemma) game where every player is located in a cell of a two-dimensional grid-world. In our spatial IPD game, a player in each cell plays against players in its neighboring cells. A game strategy of each player is represented by a binary string, which determines the next action based on a finite history of previous rounds of the IPD game. A new strategy for a player is generated by genetic operations from a pair of parent strategies, which are selected from its neighbors. We use two neighborhood structures: One is for the interaction among players (i.e., IPD game) and the other is for the genetic operations. Simulation results show that the evolution of cooperative behavior is facilitated by small neighborhood structures for the genetic operations as well as for the IPD game. We also examine a variant of our spatial IPD game where an opponent of a player is randomly selected from its neighbors at every round of the IPD game. This means that the IPD game is not iterated against the same opponent.

We propose a stylized model of production and exchange in which long-term investors set their production decision over a horizon τ , the "time to produce", and are liquidity constrained, while financial investors trade over a much shorter horizon δ ( τ ) and are therefore more duly informed on the exogenous shocks affecting the production output. The equilibrium solution proves that: (i) long-term producers modify their production decisions to anticipate the impact of short-term investors allocations on prices; (ii) short-term investments return a positive expected profit commensurate to the informational advantage. While the presence of financial investors improves the efficiency of risk allocation in the short-term and reduces price volatility, the model shows that the aggregate effect of commodity market financialization results in rising the volatility of both farms' default risk and production output.

We add some elements of prospect theory to an analytically tractable version of Lucas's "islands" model and show that the inclusion of reference dependence, declining sensitivity and loss aversion into the agents' utility function leads to three main results. First, the equilibrium labor supply and the natural level of output are negatively affected by the presence of behavioral elements, whereas the cyclical response of output to a monetary shock remains unaltered. Second, the expected utility of a representative agent is generally lower than that obtained when loss aversion is absent. Third, the presence of loss aversion eliminates the paradoxical increase in expected utility that may be generated, in the standard model, by an increase in monetary policy uncertainty.

Abstract. Argumentation theories have recently emerged and gained popularity in the agents community, since argumentation represents a natural and intuitive way to model non-monotonic reasoning. In a multiagent context, argumentation has recently been proposed as a component of dialogue frameworks. However, despite the large interest in argumentation theories in multiagent domains, most proposed frameworks stay at a general though abstract level, and operational counterparts to abstract frameworks are not many. The aim of this ...

Abstract. This paper presents a framework thai integrates three aspects of agency: planning, for proactive behaviour, negotiation, for social behaviour and resource achievement, and control of operation, for reconciling rationality with reactivity. Agents are designed and programmed in a computational logic-based language where these aspects are accommodated in a declarative and modular way. We show how this framework can be applied to agent problems requiring negotiation and resource achievement and present ...

In most proposals for multi-agent systems, an Agent Communication Language (ACL) is the formalism designed to express knowledge exchange among agents. However, a universally accepted standard for ACLs is still missing. Among the different approaches to the definition of ACL semantics, the social approach seems the most appropriate to express semantics of communication in open societies of autonomous and heterogeneous agents. In this paper we propose a formalism (deontic constraints) to express social ACL semantics, which can be grounded on a computational logic framework, thus allowing automatic verification of compliance by means of appropriate proof procedures. We also show how several common communication performatives can be defined by means of deontic constraints.

Abstract. Agent communication is one of the key issues in multi-agent systems. Traditional interprocess communication formalisms are usually considered insufficient for this purpose because of their lack of expressiveness; thus, in most proposals for multi-agent architectures, an Agent Communication Language (ACL) is designed to provide for agent communication. However, a universally accepted standard for ACLs is still missing. Agent communication in open societies of heterogeneous agents poses requirements on ACLs ...

Agents and Artifacts" (A&A) and CARTAGO are becoming increasingly popular as, respectively, a general-purpose pro- gramming model and a related infrastructure for developing shared computational environments in agent-based software systems. However, so far there has been no work on devel- oping multiagent systems (MAS) where agents implemented and deployed in dierent agent-programming platforms can interact as part of the same

We describe a scheme for moving living code between a set of distributed processes coordinated with unification based Linda operations, and its application to building a comprehensive Logic programming based Internet programming framework. Mobile threads are implemented by capturing first order continuations in a compact data structure sent over the network. Code is fetched lazily from its original base turned into a server as the continuation executes at the remote site. Our code migration techniques, in combination with a dynamic recompilation scheme, ensure that heavily used code moves up smoothly on a speed hierarchy while volatile dynamic code is kept in a quickly updatable form. Among the examples, we describe how to build programmable client and server components (Web servers, in particular) and mobile agents.

The paper discusses three key economic problems raised by the emergence and diffusion of Open source software: motivation, coordination, and diffusion under a dominant standard. First, the movement took off through the activity of a software development community that deliberately did not follow profit motivations. Second, a hierarchical coordination emerged without the support of an organization with proprietary rights. Third, Linux and other open source systems diffused in an environment dominated by established proprietary standards, which benefited from significant increasing returns. The paper shows that recent developments in the theory of critical mass in the diffusion of technologies with network externality may help to explain these phenomena.

We study the role of habit formation in shaping the amount of precautionary savings and the wealth distribution in heterogeneous agents model economies with idiosyncratic uncertainty. We adjust preferences to equate the Intertemporal Elasticity of Substitution in all model economies. We find that habit formation brings a hefty increase in precautionary savings and very mild reductions in the coefficient of variation and in the Gini index of wealth. These findings hold for both persistent and non-persistent habits, with the effects of the former being much larger.

This paper studies the effect that illiquid assets and collateral credit frictions have on the level of wealth inequality in a standard model of ex-ante heterogenous agents with idiosyncratic uncertainty. We calibrate our model so that its steady state statistics match selected aggregate statistics of the U.S. economy and data on the earnings distribution. We find that adding illiquid assets and collateral credit frictions decreases wealth inequality decreases slightly relative to an economy with liquid assets and no credit frictions. The effect is small because these frictions mostly affect poor households that account for a small fraction of aggregate wealth. Nevertheless, our richer model allows us to study other dimensions of wealth inequality. In particular, our model replicates the fact that financial assets are more concentrated than total wealth, while residential assets are less concentrated. Furthermore, we document that, in the U.S., the earnings and housing distributions are remarkably similar. Our model can account for this fact so long as the earnings process is fairly persistent

Achieving optimal results in real-life production scheduling is precluded by a number of problems. One such problem is dynamics of environments with unavailable resources (such as machine breakdowns and ill workers) and new demands (e.g. new orders) coming during the schedule execution. Traditional approach to react to unexpected events occurring on the shop floor is generating a new schedule from scratch. Complete rescheduling,however,mayrequireexcessivecomputation time. Moreover, the recovered schedule may deviate a lot from the ongoing schedule. Some work has focused on tackling these shortcomings, but none of the existing approaches tries to substitute jobs that cannot be executed with a set of alternative jobs. This paper reviews techniques related to predictive-reactive scheduling and suggests the future goal, which is to propose algorithms for dealing with unexpected events using the possibility of alternative processes.

In open multi-agent systems trust is necessary to improve cooperation by enabling agents to choose good partners. Most trust models work by taking, in addition to direct experiences, other agents' communicated evaluations into account. However, in an open multi-agent system other agents may use different trust models and as such the evaluations they communicate are based on different principles. This article shows that trust alignment is a crucial tool in this communication. Furthermore we show that trust alignment improves significantly if the description of the evidence, upon which a trust evaluation is based, is taken into account.

Ontology alignment foundations are hard to find in the literature. The abstract nature of the topic and the diverse means of practice make it difficult to capture it in a universal formal foundation. We argue that such a lack of formality hinders further development and convergence of practices, and in particular, prevents us from achieving greater levels of automation. In this article we present a formal foundation for ontology alignment that is based on interaction models between heterogeneous agents on the Semantic Web. We use the mathematical notion of information flow in a distributed system to ground our three hypotheses of enabling semantic interoperability and we use a motivating example throughout the article: how to progressively align two ontologies of research quality assessment through meaning coordination. We conclude the article with the presentation-in an executable specification language-of such an ontology-alignment interaction model.

In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. This issue is substantial, e.g., in modeling multiagent systems, where a group of loosely coupled heterogeneous agents cooperate in achieving a common goal. Information exchange, leading ultimately to knowledge fusion, is a natural and vital ingredient of this process. We use a generalization of rough sets and relations , which depends on allowing arbitrary similarity relations. The starting point of this research is , where a framework for knowledge fusion in multiagent systems is introduced. Agents' individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams. This aggregation, expressing a shift from individual to social level of agents' activity, has been formalized by means of dynamic logic. The approach of Doherty et al. (2007) [6] uses the full propositional dynamic logic, which does not guarantee tractability of reasoning. Our idea is to adapt the techniques of Nguyen to provide an engine for tractable approximate database querying restricted to a Horn fragment of serial dynamic logic. We also show that the obtained formalism is quite powerful in applications.

We introduce heterogeneous expectations in a standard housing market model linking housing rental levels to fundamental buying prices. Using quarterly data we estimate the model parameters for eight different countries. We find that the data support heterogeneity in expectations, with temporary endogenous switching between fundamental meanreverting and trend-following beliefs based on their relative performance. For all countries we identify temporary, long lasting house price bubbles amplified by trend extrapolation and crashes reinforced by mean-reverting expectations. The average market sentiment may be used as an early warning signal of a (temporary) bubble regime. The qualitative predictions of such non-linear models are very different from standard linear benchmarks with important policy implications. The fundamental price becomes unstable when the interest rate is set too low or mortgage tax deductions are too high, giving rise to multiple non-fundamental equilibria and/or global instability.

While there is much work in the literature on agent component technologies, there are comparatively few results on the engineering issues arising from the integration of these technologies into a complete and coherent agent architecture. This paper addresses these issues from both implementation and general architectural design point of view. The KGP (Knowledge, Goals and Plan) agent model developed in the EU SOCS project (IST-2001 32530) is used as an example to illustrate these engineering issues.

Abstract. This paper presents a framework thai integrates three aspects of agency: planning, for proactive behaviour, negotiation, for social behaviour and resource achievement, and control of operation, for reconciling rationality with reactivity. Agents are designed and programmed in a computational logic-based language where these aspects are accommodated in a declarative and modular way. We show how this framework can be applied to agent problems requiring negotiation and resource achievement and present ...

This paper focuses on two approaches to a general functional architecture, currently being tested at the Institute for Systems and Robotics, for the control of robot teams acting in cooperation with applications to planetary exploration and satellite inspection or maintenance. This paper presents an overview of both architectures and highlights the main differences between them. Results of simulations regarding a formation control experiment a r e presented in the paper.

Efficient coordination among large numbers of heterogeneous agents promises to revolutionize the way in which some complex tasks, such as responding to urban disasters can be performed. However, state of the art coordination algorithms are not capable of achieving efficient and effective coordination when a team is very large. Building on recent successful token-based algorithms for task allocation and information sharing, we have developed an integrated and efficient approach to effective coordination of large scale teams. We use tokens to encapsulate anything that needs to be shared by the team, including information, tasks and resources. The tokens are efficiently routed through the team via the use of local decision theoretic models. Each token is used to improve the routing of other tokens leading to a dramatic performance improvement when the algorithms work together. We present results from an implementation of this approach which demonstrates its ability to coordinate large teams.

We study whether a redesign of the social security and income tax-and-transfer systems can deliver significant welfare gains. Our rich quantitative model features both realistic inequality over the life-cycle and the key main channels through which redistributive policies can distort aggregate allocations. We find that there are two distinct ways to achieve significant welfare gains with joint policy reforms. The first prioritizes reducing distortions through a regressive pension system, resulting in higher inequality. The second reduces inequality through progressive pensions, complemented with a less progressive tax system to mitigate the rise in distortions. In both reform types, pension progressivity emerges as the most powerful instrument, either to manage distortions or to redistribute income within generations. Since redistributive instruments turn out to be highly distortionary in our benchmark economy, utilitarian social welfare is maximized through a reduction in distortions.

The present paper uses an analytical approach to derive approximate closed-form solutions for the asset moments of a real-business-cycle model with idiosyncratic risk. To preserve analytical tractability, risk sharing is completely shut down. Further, the firm is assumed to maximize a variant of value maximization, given that its usual objective is no longer well defined under market incompleteness. When idiosyncratic risk is incorporated into the model, the asset moments can be decomposed into their value under identical households plus a new idiosyncratic term. Under full constrained persistence, in which case the same household determines the asset moments every period, the model is able to generate the risk premium in the data with reasonable parameter values, but it cannot generate the risk return trade-off. While the quantitative impact of idiosyncratic risk is smaller when there is only some persistence in who is constrained, the qualitative predictions are unaltered.

A growing body of recent literature allows for heterogenous trading strategies and limited rationality of agents in behavioral models of financial markets. More and more, this literature has been concerned with the explanation of some of the stylized facts of financial markets. It now seems that some previously mysterious time-series characteristics like fat tails of returns and temporal dependence of volatility can be observed in many of these models as macroscopic patterns resulting from the interaction among different groups of speculative traders. However, most of the available evidence stems from simulation studies of relatively complicated models which do not allow for analytical solutions. In this paper, this line of research is supplemented by analytical solutions of a simple variant of the seminal herding model introduced by . Embedding the herding framework into a simple equilibrium asset pricing model, we are able to derive closed-form solutions for the time-variation of higher moments as well as related quantities of interest enabling us to spell out under what circumstances the model gives rise to realistic behavior of the resulting time series.

We consider the dynamics of a stochastic cobweb model with linear demand and a backwardbending supply curve. In our model, forward-looking expectations and backward-looking ones are assumed, in fact we assume that the representative agent chooses the backward predictor with probability q, 0 q 1, and the forward predictor with probability �1 − q�, so that the expected price at time t is a random variable and consequently the dynamics describing the price evolution in time is governed by a stochastic dynamical system. The dynamical system becomes a Markov process when the memory rate vanishes. In particular, we study the Markov chain in the cases of discrete and continuous time. Using a mixture of analytical tools and numerical methods, we show that, when prices take discrete values, the corresponding Markov chain is asymptotically stable. In the case with continuous prices and nonnecessarily zero memory rate, numerical evidence of bounded price oscillations is shown. The role of the ...

We consider a random matching model where heterogeneous agents endogenously choose to invest time and real resources in education. Generically in the space of the economies, there is an open interval of possible lengths of schooling such that, at at least one of the associated steady states equilibria, some agents, but not all of them, choose to invest. Regular steady state equilibria are constrained Pareto inefficient in a strong sense. The Hosios (1990) condition is neither necessary, nor sufficient, for constrained Pareto optimality. We also provide restrictions on the fundamentals, which are sufficient to guarantee that equilibria are characterized by overeducation (undereducation), and present some results on their comparative statics properties.