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Thesis advisor: Peter N. Ireland / This dissertation examines three topics in computational macroeconomics and finance. The first two chapters are closely linked; and the third chapter covers a separate topic in finance. Throughout the dissertation, I place a strong emphasis on constructing computational tools and modeling devices; and using them in appropriate applications. The first chapter examines how a central banks choice of interest rate rule impacts the rate of mortgage default and welfare. In this chapter, a quantitative equilibrium (QE) model is constructed that incorporates incomplete markets, aggregate uncertainty, overlapping generations, and realistic mortgage structure. Through a series of counterfactual simulations, five things are demonstrated: 1) nominal interest rate rules that exhibit cyclical behavior increase the average default rate and lower average welfare; 2) welfare can be substantially improved by adopting a modified Taylor rule that stabilizes house prices; 3) a decrease in the length of the interest rate cycle will tend to increase the average default rate; 4) if the business and housing cycles are not aligned, then aggressive inflation targeting will tend to increase the mortgage default rate; and 5) placing a legal cap on loan-to-value ratios will lower the average default rate and lessen the intensity of extreme events. In addition to these findings, this paper also incorporates an important mechanism for default, which had not pre- viously been included in the QE literature: default spikes happen when income falls and home equity is degraded at the same time. The paper concludes with a policy recommendation for central banks: if they wish to crises where many households default simultaneously, they should either adopt a rule that generates interest rates with slow-moving cycles or use a modified Taylor rule that also targets house price growth. The second chapter generalizes the solution method used in the first and compares it to more common techniques used in the computational macroeconomics literature, including the parameterized expectations approach (PEA), projection methods, and value function iteration. In particular, this chapter compares the speed and accuracy of the aforementioned modifications to an alternative method that was introduced separately by Judd (1998), Sutton and Barto (1998), and Van Roy et al. (1997), but was not developed into a general solution method until Powell (2007) introduced it to the Operations Research literature. This approach involves rewriting the Bellman equation in terms of the post-decision state variables, rather than the pre-decision state variables, as is done in standard dynamic programming applications in economics. I show that this approach yields considerable performance benefits over common global solution methods when the state space is large; and has the added benefit of not forcing modelers to assume a data generating process for shocks. In addition to this, I construct two new algorithms that take advantage of this approach to solve heterogenous agent models. Finally, the third chapter imports the SIR model from mathematical epidemiol- ogy; and uses it to construct a model of financial epidemics. In particular, the paper demonstrates how the SIR model can be microfounded in an economic context to make predictions about financial epidemics, such as the spread of asset-backed securities (ABS) and exchange-traded funds (ETFs), the proliferation of zombie financial institutions, and the expansion of financial bubbles and mean-reverting fads. The paper proceeds by developing the 1-host SIR model for economic and financial contexts; and then moves on to demonstrate how to work with the multi-host version of the model. In addition to showing how the SIR framework can be used to model economic interactions, it will also: 1) show how it can be simulated; 2) use it to develop and estimate a sufficient statistic for the spread of a financial epidemic; and 3) show how policymakers can impose the financial analog of herd immunity-that is, prevent the spread of a financial epidemic without completely banning the asset or behavior associated with the epidemic. Importantly, the paper will focus on developing a neutral framework to describe financial epidemics that can be either bad or good. That is, the general framework can be applied to epidemics that constitute a mean-reverting fad or an informational bubble, but ultimately yield little value and shrink in importance; or epidemics that are long-lasting and yield a new financial in- strument that generates permanent efficiency gains or previously unrealized hedging opportunities. / Thesis (PhD) — Boston College, 2013. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

The three constituent chapters of this thesis tackle independent, self-contained research questions, all concerning welfare economics in general and its application to climate change policy in particular. Climate change is a policy problem for which the costs and benefits are distributed unequally across space and time, as well as one involving a high degree of uncertainty. Therefore, cost-benefit analysis of climate policy ought to be based on a welfare function that is sufficiently sophisticated to incorporate the three dimensions of aggregation: time, risk and space. Chapter 1 is an axiomatic treatment of a stylised model in which all three dimensions appear. The main result is a functional representation of the social welfare function for policy assessment in such situations. Chapter 2 is a numerical mitigation policy analysis. I modify William Nordhaus' RICE-2010 model by replacing his social welfare function with one that allows for different degrees of inequality aversion along the regional and inter-temporal dimension. I find that, holding the inter-temporal coefficient of inequality aversion fixed, performing the optimisation with a greater degree of regional inequality reduces the optimal carbon tax relative to treating the world as a single aggregate consumer. In Chapter 3 I analyse climate policy from the point of view of intergenerational transfers. I propose a system of transfers that allows future generations to compensate the current one for its mitigation effort and demonstrate the effects in an OLG model. When the marginal benefit to a - possibly distant - future generation is greater than the cost of compensating the current generation for its abatement effort, a Pareto improvement is possible by a combination of mitigation policy and transfer payments. I show that under very general assumptions the business-as-usual outcome is Pareto dominated by such policies and derive the conditions for the set of climate policies that are not dominated thus.

The aim of this thesis is to propose and illustrate an alternative approach to economic modeling and policy design that is grounded in the innovative field of agent-based computational economics (ACE). The recent crisis pointed out the fundamental role played by macroeconomic policy design in order to preserve social welfare, and the consequent necessity of understanding the effects of coordinated policy measures on the economic system. Classic approaches to macroeconomic modeling, mainly represented by dynamic stochastic general equilibrium models, have been recently criticized for they difficulties in explaining many economic phenomena. The absence of interaction among heterogeneous agents, along with their strong rationality, are two of the main of criticisms that emerged, among others. Actually, decentralized market economies consist of large numbers of economic agents involved in local interactions and the aggregated macroeconomic trends should be considered as the result of these local interactions. The approach of agent-based computational economics consists in designing economic models able to reproduce the complicated dynamics of recurrent chains connecting agent behaviors, interaction networks, and to explain the global outcomes emerging from the bottom-up. The work presented in this thesis tries to understand the feedback between the microstructure of the economic model and the macrostructure of policy design, investigating the effects of different policy measures on agents behaviors and interactions. In particular, the attention is focused on modeling the relation between the financial and the real sides of the economy, linking the financial markets and the credit sector to the markets of goods and labor. The model complexity is increasing with the different chapters. The agent-based models presented in the first part evolve to a more complex object in the second part, becoming a sort of complete ``artificial economy''. The problems tackled in the thesis are various and go from the investigation of the equity premium puzzle, to study of the effects of classic monetary policy rules (as the Taylor rule) or to the study of the macroeconomic implications of bank's capital requirement or quantitative easing.

We present the rich research potential at the union of multi agent reinforcement learning (MARL), game theory, and financial graphs. We demonstrate how multiple game theoretic scenarios arise in three node financial graphs with minor modifications. We highlight six scenarios used in this study. We discuss how to setup an environment for MARL training and evaluation. We first investigate individual games and demonstrate that MARL agents consistently learn Nash Equilibrium strategies. We next investigate mixed games and find again that MARL agents learn Nash Equilibrium strategies given sufficient information and incentive (e.g. prosociality). We find introducing a embedding layer in agents deep network improves learned representations and as such, learned strategies, (2) MARL agents can learn a variety of complex strategies, and (3) selfishness improves strategies’ fairness and efficiency. Next we introduce populations and find that (1) pro social members in a population influences the action profile and that (2) complex strategies present in individual scenarios no longer emerge as populations’ portfolio of strategies converge to a main diagonal. We identify two challenges that arises in populations; namely (1) identifying partner’s prosociality and (2) identifying partner’s identity. We study three information settings which supplement agents observation set and find having knowledge of partners prosociality or identity to have negligible impact on how portfolio of strategies converges. / Vi presenterar den rika forskningspotentialen vid unionen av multi-agent förstärkningslärning (MARL), spelteori och finansiella grafer. Vi demonstrerar hur flera spelteoretiska scenarier uppstår i tre nodgrafikgrafer med mindre ändringar. Vi belyser sex scenarier som används i denna studie. Vi diskuterar hur man skapar en miljö för MARL -utbildning och utvärdering. Vi undersöker först enskilda spel och visar att MARL -agenter konsekvent lär sig Nash Equilibrium -strategier. Vi undersöker sedan blandade spel och finner igen att MARL -agenter lär sig Nash Equilibrium -strategier med tillräcklig information och incitament (t.ex. prosocialitet). Vi finner att införandet av ett inbäddande lager i agenternas djupa nätverk förbättrar inlärda representationer och som sådan inlärda strategier, (2) MARL-agenter kan lära sig en mängd komplexa strategier och (3) själviskhet förbättrar strategiernas rättvisa och effektivitet. Därefter introducerar vi populationer och upptäcker att (1) pro sociala medlemmar i en befolkning påverkar åtgärdsprofilen och att (2) komplexa strategier som finns i enskilda scenarier inte längre framkommer när befolkningens portfölj av strategier konvergerar till en huvuddiagonal. Vi identifierar två utmaningar som uppstår i befolkningen; nämligen (1) identifiera partnerns prosocialitet och (2) identifiera partnerns identitet. Vi studerar tre informationsinställningar som kompletterar agents observationsuppsättning och finner att kunskap om partners prosocialitet eller identitet har en försumbar inverkan på hur portföljen av strategier konvergerar.

The concept of ‘Industry 4.0’ signalises the rise of innovative manufacturing technologies, including industrial robots. Wider applicability of robotic automation and higher efficiency of production processes shift the profitability analysis of strategic relocation decisions. Despite the technological feasibility, diffusion of technology lowers the profitability threshold for robots. Consequently, competitive labour cost advantages, formerly motivating manufacturing firms to offshore production become less relevant. In fact, robots additionally gain importance in the case of shifted global economic realities, such as stricter environmental regulation on global trade and the convergence of the global wage gap. However, the heterogeneous levels of automation among manufacturing firms have not been taken into account when studying the macroeconomic phenomenon of reshoring. This study adds novelty by offering an agent-based perspective which has allowed insights on how the behaviour of firms, guided by simple economic rules on the micro-level, is dynamically influenced by their complex environment in regard to relocation, decision-making hypotheses. Testing various variables sensitive to initial conditions, increased environmental regulations targeting global trade and upward shifting wage levels in formerly offshore production locations have shown to be driving and inhibiting mechanisms of this socio-technical system. Therefore, the dynamic demonstrates a shift from predominantly cited economic reasoning for relocation strategies towards sustainability aspects, pressingly changing these realities on an environmental and social dimension. The popular debate is driven by increased environmental awareness and the proclaimed fear of robots killing jobs. In view of reshoring shaping the political agenda, interest in the phenomenon has recently been fuelled by the rise of populism and protectionism claiming to “bring jobs back home”.

Submitted by Henrique Teixeira (henrique.oliv@gmail.com) on 2016-03-16T02:51:18Z No. of bitstreams: 1 Dissertacao.pdf: 1894861 bytes, checksum: af73e440cc555c69c32dbb74b4ba3f59 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2016-03-16T21:49:10Z (GMT) No. of bitstreams: 1 Dissertacao.pdf: 1894861 bytes, checksum: af73e440cc555c69c32dbb74b4ba3f59 (MD5) / Made available in DSpace on 2016-03-17T11:42:41Z (GMT). No. of bitstreams: 1 Dissertacao.pdf: 1894861 bytes, checksum: af73e440cc555c69c32dbb74b4ba3f59 (MD5) Previous issue date: 2016-02-18 / Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market. / Partindo da ideia de que os sistemas econômicos se enquadram na teoria da complexidade, onde seus inúmeros agentes interagem entre si sem um controle central e que essas interações são capazes de alterar o comportamento futuro dos agentes e de todo o sistema, semelhante a um sistema caótico, incrementamos o modelo de Russo et al. (2014) para a realização de três experimentos com foco na interação entre bancos e empresas em uma economia artificial. O primeiro experimento diz respeito a Relationship Banking onde, segundo a literatura, a interação ao longo do tempo entre bancos e empresas é capaz de produzir benefícios mútuos, principalmente devido a redução da assimetria de informação entre eles. O experimento seguinte está relacionado a assimetria de informação no mercado de crédito, onde quanto maior o banco, maior sua visibilidade no mercado de crédito, elevando na mesma proporção as consultar para novos emprestimos. Por fim, o terceiro experimento é relativo aos efeitos no mercado de crédito da heterogeneidade de preços que as empresas se deparam no mercado de bens

Submitted by Daniella Santos (daniella.santos@fgv.br) on 2010-03-23T12:01:36Z No. of bitstreams: 1 Dissertacao_Jefferson_Donizeti_Bertolai.pdf: 274926 bytes, checksum: a60c8343a27883dd5e7f529f517bc2e8 (MD5) / Approved for entry into archive by Andrea Virginio Machado(andrea.machado@fgv.br) on 2010-03-23T12:31:24Z (GMT) No. of bitstreams: 1 Dissertacao_Jefferson_Donizeti_Bertolai.pdf: 274926 bytes, checksum: a60c8343a27883dd5e7f529f517bc2e8 (MD5) / Made available in DSpace on 2010-03-24T12:48:06Z (GMT). No. of bitstreams: 1 Dissertacao_Jefferson_Donizeti_Bertolai.pdf: 274926 bytes, checksum: a60c8343a27883dd5e7f529f517bc2e8 (MD5) Previous issue date: 2009-12-08 / The dificulty in characterizing non-stationary allocations or equilibria is one of the main explanations for the use of concepts and assumptions that trivialize the dynamics of the economy. This di¢ culty is especially critical in Monetary Theory, in which the dimensionality of the problem is high even for very simple models. In this context, this paper reports the computational strategy for implementing the recursive method proposed by Monteiro and Cavalcanti (2006), which allows you to calculate the optimal sequence (possibly non-stationary) of distributions of money in an extension of the model proposed by Kiyotaki and Wright (1989). Three aspects of this calculation are emphasized: (i) the computational implementation of the plannerís problem involves the choice of continuous and discrete variables that maximize a nonlinear function and satisÖes nonlinear constraints; (ii) the objective function of this problem is not concave and constraints are not convex, and (iii) the set of admissible choices is not known a priori. The goal is to document the di¢ culties involved, the proposed solutions and available methods and resources to implement the numerical characterization of e¢ cient monetary dynamics under the assumption of random matching. / A dificuldade em se caracterizar alocações ou equilíbrios não estacionários é uma das principais explicações para a utilização de conceitos e hipóteses que trivializam a dinâmica da economia. Tal dificuldade é especialmente crítica em Teoria Monetária, em que a dimensionalidade do problema é alta mesmo para modelos muito simples. Neste contexto, o presente trabalho relata a estratégia computacional de implementação do método recursivo proposto por Monteiro e Cavalcanti (2006), o qual permite calcular a sequência ótima (possivelmente não estacionária) de distribuições de moeda em uma extensão do modelo proposto por Kiyotaki e Wright (1989). Três aspectos deste cálculo são enfatizados: (i) a implementação computacional do problema do planejador envolve a escolha de variáveis contínuas e discretas que maximizem uma função não linear e satisfaçam restrições não lineares; (ii) a função objetivo deste problema não é côncava e as restrições não são convexas; e (iii) o conjunto de escolhas admissíveis não é conhecido a priori. O objetivo é documentar as dificuldades envolvidas, as soluções propostas e os métodos e recursos disponíveis para a implementação numérica da caracterização da dinâmica monetária eficiente sob a hipótese de encontros aleatórios.

Le marché aux poissons de Boulogne-sur-Mer se caractérise par l’organisation singulière de son système de vente. En effet, sur celui-ci, les acheteurs et les vendeurs peuvent choisir chaque jour de recourir à un mécanisme d’enchères ou à un marché de gré à gré (voire à ces deux possibilités en même temps), pour commercer entre eux. La coexistence de ces deux systèmes de vente est stable dans le temps, chacun d’entre eux représentant approximativement la moitié des quantités échangées. Cette singularité économique conduit à s’interroger sur les conditions nécessaires à l’émergence et à la stabilité de cette coexistence. Pourquoi les agents ne s’accordent-ils tous pas pour un unique mécanisme de transaction comme dans la majorité des marchés? pourquoi observe-t-on une si grande volatilité dans les choix individuels de marché? Afin de comprendre les conditions nécessaires à cette coexistence de mécanismes de marché, la présente thèse se déclinera comme suit. La première partie sera dédiée à l’étude empirique des transactions journalières ayant lieu sur chacun des deux sous-marchés. Nous commençons par une analyse statistique et économétrique afin d’extraire les faits stylisés représentatifs des propriétés du marché et de ses acteurs, avant de procéder à une analyse des réseaux sociaux existants sur ce marché,visant à déterminer l’influence des interactions dans la prise de décision. Fort de ces résultats, nous construisons des modèles informatiques multi-agents, capables de reproduire les comportements observés au niveau individuel, et, au travers ceux-ci,le comportement du marché lui-même au niveau agrégé. / Should I buy or should I bid ? The influence of market mechanism : the case of Boulogne-Sur-Mer fish market. The Boulogne-sur-Mer fish market is organized in a very specific way. Each day buyers and sellers can choose to use either an auction mechanism, a negotiated market, or evenboth, in order to sell and buy goods.A stunning fact observed is the stable coexistence of those two sub-markets throughout time, with no convergence of agents toward one of them, each one accounting for roughly half of the exchanged quantities.The present thesis aims at discovering the necessary conditions of the emergence andstability of such a coexistence.To do it, we will begin with an empirical study of daily transactions that have occurred on this market for a few years. We begin with a statistical and econometric study to extract the main stylized facts of this market, then we study the social networks influencing the outcomes. Once those facts determined, we build agent-based computational models able to reproduce the individual behaviours of agents, and through these, the emergence of the market’sbehaviour itself.

This thesis is concerned with the analysis of economic network formation. There are three novel sections to this thesis (Chapters 5, 6 and 8). In the first, the non-cooperative communication network formation model of Bala and Goyal (2000) (BG) is re-assessed under conditions of no inertia. It is found that the Strict Nash circle (or wheel) structure is still the equilibrium outcome for n = 3 under no inertia. However, a counter-example for n = 4 shows that with no inertia infinite cycles are possible, and hence the system does not converge. In fact, cycles are found to quickly dominate outcomes for n > 4 and further numerical simulations of conditions approximating no inertia (probability of updating > 0.8 to 1) indicate that cycles account for a dramatic slowing of convergence times. These results, together with the experimental evidence of Falk and Kosfeld (2003) (FK) motivate the second contribution of this thesis. A novel artificial agent model is constructed that allows for a vast strategy space (including the Best Response) and permits agents to learn from each other as was indicated by the FK results. After calibration, this model replicates many of the FK experimental results and finds that an externality exploiting ratio of benefits and costs (rather than the difference) combined with a simple altruism score is a good proxy for the human objective function. Furthermore, the inequity aversion results of FK are found to arise as an emergent property of the system. The third novel section of this thesis turns to the nature of network formation in a trust-based context. A modified Iterated Prisoners' Dilemma (IPD) model is developed which enables agents to play an additional and costly network forming action. Initially, canonical analytical results are obtained despite this modification under uniform (non-local) interactions. However, as agent network decisions are 'turned on' persistent cooperation is observed. Furthermore, in contrast to the vast majority of non-local, or static network models in the literature, it is found that a-periodic, complex dynamics result for the system in the long-run. Subsequent analysis of this regime indicates that the network dynamics have fingerprints of self-organized criticality (SOC). Whilst evidence for SOC is found in many physical systems, such dynamics have been seldom, if ever, reported in the strategic interaction literature.