Thesis advisor: Fabio Ghironi / Thesis advisor: Susanto Basu / My dissertation develops a set of tools for thinking about heterogeneity in economic models in an analytically tractable way. Many models use the representative agent framework, which greatly simplifies macroeconomic aggregation but abstracts from the heterogeneity we see in the real world. Models with heterogeneity in general equilibrium have too many moving parts, so that it is hard to disentangle cause and effect. First, my work in international macroeconomics incorporates heterogeneity via idiosyncratic shocks across countries in a simple and analytical way. Second, my work on financial frictions helps to understand the role of asymmetric information between lenders and borrowers in different contractual environments. Crucially, these insights can be incorporated into the models currently used by academics and central banks for policy analysis. / Thesis (PhD) — Boston College, 2014. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

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This thesis proposes a new econometric methodology for the estimation and inference of macro- economic models in the presence of time variation in the parameters. A novel quasi-Bayesian local likelihood (QBLL) approach is established and it is shown that the method gives rise to as- ymptotically valid quasi-posterior distributions. In addition, in the special case of linear Gaussian models, expressions of the quasi-posteriors are derived in closed form, which simpli es inference and makes the use of MCMC unnecessary. Inference based on the QBLL approach, as a consequence of modelling parameter variation nonparametrically, is robust to di¤erent processes for the drifting parameters, as its validity does not depend on parametric restrictions typically imposed by alterna- tive state space models. In addition, the Bayesian treatment of the approach provides a remedy to the curse of dimensionality by accommodating large dimensional systems. We demonstrate that the proposed estimators exhibit good nite sample properties, and, unlike the alternative para- metric state space models, are robust to di¤erent parameter processes. We provide a variety of interesting macroeconomic applications and forecasting exercises to reduced-form VAR models. In addition, we develop the methodology to the estimation of structural DSGE models in the presence of parameter drift. We apply the proposed algorithms to di¤erent medium-sized DSGE models in order to study structural change in the parameters.

The thesis elaborates on the potential impact of the financial crisis on the European value system. At root of this work lies the debate on the prospectively changed perception of human nature, freedom and economic progress, taking into consideration European humanist inheritance and contribution of contemporary economic and political thinkers.

This paper examines the possible contribution of evolutionary economics to macro-economic modelling of flood impacts to provide guidance for future economic risk modelling. Most macro-economic models start from a neoclassical economic perspective and focus on equilibrium outcomes, either in a static or dynamic way, and describe economic processes at a high level of aggregation. As a consequence, they typically fail to account for the complexity of social interactions and other behavioural responses of consumers and producers to disasters, which may affect the macroeconomic impacts of floods. Employing evolutionary principles and methods, such as agent-based modelling, may help to address some of the shortcomings of current macro-economic models. We explore and discuss the implications of applying consumer and producer heterogeneity, bounded rationality, network effects, social and technological learning, co-evolution and adaptive policy-making concepts into existing economic frameworks for the assessment of macro-economic impacts of floods. (authors' abstract)

This dissertation focuses on assessing the sustainability of China’s long-term economic growth. The evaluation is performed, first, by examining economic and social issues from the past thirty years that shape China to where it is now, and second, by taking an empirical approach in understanding what factors are critical to China’s economic growth. The empirical model framework consists of three blocks representing the main areas of development in China: economic growth, health and environmental development, and the model is estimated with two-stage least squares methodology. We identify strong, simultaneous feedback between economic growth and health development. The estimation results show that continued improvements in the health status of Chinese workers are important to support stronger economic growth in China. Environmental stress is detrimental to China’s long-term health status, which indirectly reduces the country’s long-term economic potential. We test the robustness of our model, and confirm that, the proposed model setup produce a set of forecast values that are closer to the actual values than a model without health- and environmental-related variables. / Economics

Statistical quality control (SQC) is one technique companies are using in the development of a Total Quality Management (TQM) culture. Shewhart control charts, a widely used SQC tool, rely on an underlying normal distribution of the data. Often data are skewed. The inverse Gaussian distribution is a probability distribution that is wellsuited to handling skewed data. This analysis develops models and a set of tools usable by practitioners for the constrained economic statistical design of control charts for inverse Gaussian distribution process centrality and process dispersion. The use of this methodology is illustrated by the design of an x-bar chart and a V chart for an inverse Gaussian distributed process.

Álgebra Linear e particularmente a teoria das matrizes e dos sistemas lineares são tópicos da Matemática que têm aplicações, não só dentro da própria Matemática, mas também em várias outras áreas do conhecimento humano. Neste trabalho, além de estudar estas teorias, estudamos algumas de suas aplicações na área da Economia, como em modelos lineares de produção, modelos de Markov para emprego e modelos de benefícios obtidos no pagamento de impostos após realizarmos contribuições filantrópicas. / Linear Algebra and particularly matrices and linear systems theory are topics in Mathematics with many applications in several branches of science. In this work we study this theory and some of its applications in Economy as in linear models of production, Markov models of employment and tax benefits of charitable contributions.