Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 79-81). Also available on the Internet.

Thesis (Ph. D.)--University of Hawaii, 2000. / "May 2000." Includes bibliographical references (leaves 276-294).

abstract: I study the importance of financial factors and real exchange rate shocks in explaining business cycle fluctuations, which have been considered important in the literature as non-technological factors in explaining business cycle fluctuations. In the first chapter, I study the implications of fluctuations in corporate credit spreads for business cycle fluctuations. Motivated by the fact that corporate credit spreads are countercyclical, I build a simple model in which difference in default probabilities on corporate debts leads to the spread in interest rates paid by firms. In the model, firms differ in the variance of the firm-level productivity, which is in turn linked to the difference in the default probability. The key mechanism is that an increase in the variance of productivity for risky firms relative to safe firms leads to reallocation of capital away from risky firms toward safe firms and decrease in aggregate output and productivity. I embed the above mechanism into an otherwise standard growth model, calibrate it and numerically solve for the equilibrium. In my benchmark case, I find that shocks to variance of productivity for risky and safe firms account for about 66% of fluctuations in output and TFP in the U.S. economy. In the second chapter, I study the importance of shocks to the price of imports relative to the price of final goods, led by the real exchange rate shocks, in accounting for fluctuations in output and TFP in the Korean economy during the Asian crisis of 1997-98. Using the Korean data, I calibrate a standard small open economy model with taxes and tariffs on imported goods, and simulate it. I find that shocks to the price of imports are an important source of fluctuations in Korea's output and TFP in the Korean crisis episode. In particular, in my benchmark case, shocks to the price of imports account for about 55% of the output deviation (from trend), one third of the TFP deviation and three quarters of the labor deviation in 1998. / Dissertation/Thesis / Ph.D. Economics 2011

A presente tese de doutorado estuda a economia regional brasileira através de três ensaios. No primeiro, de longo prazo, são investigadas as hipóteses de convergência de renda e formação de clubes de crescimento, por meio de modelos multivariados de componentes não observados, caracterizados como estocásticos. Os resultados mostram que, em nível regional, apenas o Centro Oeste teve trajetória convergente no período analisado. Em nível estadual, há poucas evidências de convergência dentro de cada região. Em relação á formação de clubes, encontra-se o mesmo padrão verificado na literatura empírica brasileira, ou seja, a existência de dois grupos distintos, um mais rico que a média, formado por alguns estados do Sul, Sudeste e Centro Oeste (mais Amazonas), e um mais pobre que a média, formado por estados do Norte e Nordeste. No segundo ensaio, de curto prazo, investiga-se a existência de ciclos conjuntos regionais no Brasil, através de modelos MS-VAR, caracterizados como não lineares. Os resultados mostram similaridades entre os ciclos dentro de cada região, embora entre as diferentes regiões existam dinâmicas distintas. Não obstante, a região Sudeste é a mais semelhante à economia nacional. Adicionalmente destaca-se, em um extremo, as dinâmicas semelhantes do Sul e Centro Oeste, embora a última com desempenho de curto prazo mais satisfatório. Do outro, a fraca conexão regional do Norte e Nordeste, tanto em relação ao país quanto internamente. Finalmente, no terceiro ensaio, executa-se um survey da literatura empírica regional brasileira, condicionado aos problemas de pesquisa abordados nos ensaios anteriores. Tanto em relação ao crescimento de longo prazo quanto no que diz respeito aos ciclos econômicos, a revisão mostra que os principais resultados obtidos na tese de doutorado são amplamente compatíveis com os observados pelas principais publicações brasileiras recentes. Adicionalmente, no terceiro ensaio, salienta-se a necessidade da literatura empírica considerar dois aspectos metodológicos que podem condicionar os resultados: o problema da unidade de área modificável (MAUP), caracterizado como um aspecto metodológico geral; e o problema de escolha ótima do parâmetro de suavização na estimação de uma função de núcleo Kernel, caracterizado como um aspecto metodológico específico. Em relação ao segundo ponto, ilustra-se empiricamente a questão com os mesmos dados utilizados nos dois ensaios anteriores, séries de PIB per capita estaduais, de 1985 a 2008. Os resultados confirmam a sensibilidade das conclusões aos valores dos parâmetros de suavização, bem como corroboram a formação de dois clubes de crescimento no Brasil. / In this doctoral thesis are developed three related essays addressing regional economy. In the first, the income convergence and the growth club formation is analysed thorough a long run perspective using multivariate models of unobserved components, which are characterized as stochastic. The results show that, at the regional level, only the Midwest region presents a converging trajectory. At the state level, there are little evidences of convergence within each region. Regarding the club formation, the found results are similar to the existing results in the Brazilian empirical literature. Two distinct groups were found. One is richer than the average including some states from the South region, Southeast region and Midwest region (plus Amazonas from the North region). And the other is poorer than the average, including the states from the North and Northeast regions. In the second essay, using short run data, the formation of common or combined cycles in the Brazilian regions was investigated using MS-VAR models, characterized as non-linear. The cycles within the regions show similarities, although between regions the dynamics are distinct. Nevertheless, the Southeast region is most similar to the national economy. Additionally it is worth to highlight, in one hand the similar dynamics of South and Midwest, despite the more satisfying performance of Midwest. On the other hand, the North and Northeast show a weak connection internally and with the national economy. In the third essay, a survey of the Brazilian empirical literature about regional studies was developed. For both, long run growth and economic cycles, the results that were found in this doctoral thesis are broadly consistent with those found in the main recent Brazilian publications. Additionally, in the third essay, two methodological aspects which might influence the results are stressed: the problem of the modifiable area unit (MAUP), characterized as a general methodological aspect; and the problem of optimal choice of the smoothing parameter in the estimation of a kernel function, characterized as a specific methodological aspect. The second point is illustrated empirically using the same data from the two previous essays (state GNP from 1985 to 2008). The results confirm the sensitivity of the conclusions to the values of the smoothing parameters, as well as supporter the formation to two growth clubs in Brazil.

This dissertation studies the impact embedding boundedly rational agents in real business cycle-type news-shock models may have on a variety of model predictions, from simulated moments to structural parameter estimates. In particular, I analyze the qualitative and quantitative effects of assuming agents are boundedly rational in a class of DSGE models which attempt to explain the observed volatility and comovements in key aggregate measures of U.S. economic performance as the result of endogenous responses to information in the form of ``news shocks''. The first chapter explores the theoretical feasibility of relaxing the rational expectations hypothesis in a three-sector real business cycle (RBC) model which generates boom-bust cycles as a result of periods of optimism and pessimism on the part of households. The second chapter determines whether agents forming linear forecasts of shadow prices in a nonlinear framework can lead to behavior approximately consistent with fully informed individuals in a one-sector real business cycle model. The third chapter analyzes whether empirical estimates of the relative importance of anticipated shocks may be biased by assuming rational expectations. By merging the two hitherto separate but complementary strands of literature related to bounded rationality and news shocks I am able to conduct in-depth analysis of the importance of both the information agents have and what they choose to do with it. At its core, the study of news in macroeconomics is a study of the specific role alternative information sets play in generating macroeconomic volatility. Adaptive learning on the other hand is concerned with the behavior of agents given an information set. Taken together, these fields jointly describe the input and the ``black box'' which produce model predictions from DSGE models. While previous research has been conducted on the effects of bounded rationality or news shocks in isolation, this dissertation marks the first set of research explicitly focused on the interaction of these two model features.

Doctor of Philosophy / Department of Economics / William F. Blankenau / This dissertation investigates two essential features of the US economy. First, it explores how news about future productivity changes business cycle fluctuations. Using the a representative agent model, it shows that implementation labor in workplace organization could be an important channel through which news about the fundamentals can realistically generate US business cycle fluctuations. Further this idea is extended using the perspective of sunspot fluctuations. In particular, the model can lead to multiple equilibria under specific parameterizations. Second, a general equilibrium model has been developed with heterogeneous agents to explain the wage polarization feature of the US labor market, particularly how the price of an important technology is connected to lifetime earnings of agents and affects their college decisions. The following summarizes the three chapters of my dissertation. The first chapter which I co-authored with Dr. Blankenau, argues that purchasing investment goods does not directly increase the productive capacity of a business. Changes in the business through the installation of capital, worker training, and workplace reorganization are often required. These changes themselves are not easily automated. Change requires workers. We build a model where investment requires a complementary labor input. This mechanism is embedded in a representative agent model with capacity utilization, adjustment costs, and separable preferences. We show that this environment can yield positive co-movement between consumption, investment, and labor hours when the economy experiences a news shock about future productivity, thus providing an additional channel through which news shocks can generate key business cycle features. The second chapter is an extension of the first chapter. I investigate the indeterminacy in a representative agent model with implementation labor and increasing returns in production. First, my analysis shows that a representative agent with implementation labor can exhibit increasing returns to scale. Then I show that self-fulfilling beliefs of agents lead to business cycle fluctuations in which multiple equilibria can arise under specific parameterizations. Specifically, implementation labor in the production of capital is the highly important, necessary condition for the self-fulling equilibrium outcome. The third chapter, which is also a joint work with Dr. Blankenau, discusses the wage polarization feature of the US labor market. We build a general equilibrium model with heterogeneous agents, showing how wage polarization can emerge when the price of computer capital falls. Consequently, we find the share of the population with a college degree decreases. Our findings are consistent with recent empirical data that show a U-shaped wage growth pattern in the US as well as a slower growth rate of college-educated workers despite the high returns of investing in education. In the model, we assume that each agent is born with a portfolio of skills. Specifically, each agent can provide manual labor, routine labor, and abstract labor and must decide how much of each to provide. An agent can increase efficiency in all types of labor by attending college. All three types of labor are valued in the labor market at an endogenously determined wage rate. Computer capital is a substitute for routine labor. As its price falls and its quantity increases, agents with a relative aptitude for routine labor no longer find it advantageous to attend college. Since routinization of tasks harms middle-income agents, the model has government policy implications for observed wage polarization.

This paper develops a multivariate regime switching monetary policy model for the US economy. To exploit a large dataset we use a factor-augmented VAR with discrete regime shifts, capturing distinct business cycle phases. The transition probabilities are modelled as time-varying, depending on a broad set of indicators that influence business cycle movements. The model is used to investigate the relationship between business cycle phases and monetary policy. Our results indicate that the effects of monetary policy are stronger in recessions, whereas the responses are more muted in expansionary phases. Moreover, lagged prices serve as good predictors for business cycle transitions. / Series: Department of Economics Working Paper Series

This thesis presents an examination of the importance of Small and Medium Enterprises (SMEs) for economic growth and examines how sensitive employment in SMEs is to business cycle fluctuations in Brazil. The thesis uses different empirical techniques to investigate the role of SMEs in the Brazilian regional economic growth, using a panel dataset from 1980 to 2004 for 508 Brazilian micro-regions. It first uses standard panel data estimators (OLS, LSDV, system and first differenced GMM) to analyse the (augmented) Solow growth model encompassing the importance of the relative size of the SME sector measured by the share of the SME employment in total formal employment and the level of human capital in SMEs measured by the average years of schooling of SME employees. The results show that the size of the SME sector is not significantly important for regional economic growth, but that human capital embodied in SMEs is more important in this process.

O objetivo deste estudo é investigar, através do estimador de diferenças em diferenças, se a adoção da união monetária européia ampliou tanto o comércio quanto a correlação bilateral dos ciclos econômicos entre seus membros, em comparação com outras economias da OCDE. A evidência apresentada sugere ser esse o caso, nos indicando que a união monetária, como processo último das teorias de integração, pode não ser um fim, mas sim um meio para o alcance da integração entre as economias. / The goal of this paper is to investigate, by means of a simple difs-in-difs technique, whether the adoption of the monetary union among the members of the European Monetary Union (EMU) has increased both bilateral trade and bilateral correlation of business cycles between them rather than amidst other OECD economies. We present evidence suggesting this to be the case, witch tells us that monetary union, as the last stage of the theories of economic integration, may not be an end by itself, but means of achieving the economic integration.

This dissertation consists of two essays. The first essay focuses on developing a quantitative theory for a small open economy dynamic stochastic general equilibrium (DSGE) model with a housing sector allowing for both contemporaneous and news shocks. The second essay is an empirical study on the macroeconomic forecasting using both structural and non-structural models. In the first essay, we develop a DSGE model with a housing sector, which incorporates both contemporaneous and news shocks to domestic and external fundamentals, to explore the kind of and the extent to which different shocks to economic fundamentals matter for driving housing market dynamics in a small open economy. The model is estimated by the Bayesian method, using data from Hong Kong. The quantitative results show that external shocks and news shocks play a significant role in this market. Contemporaneous shock to foreign housing preference, contemporaneous shock to terms of trade, and news shocks to technology in the consumption goods sector explain one-third each of the variance of housing price. Terms of trade contemporaneous shock and consumption technology news shocks also contribute 36% and 59%, respectively, to the variance in housing investment. The simulation results enable policy makers to identify the key driving forces behind the housing market dynamics and the interaction between housing market and the macroeconomy in Hong Kong. In the second essay, we compare the forecasting performance between structural and non-structural models for a small open economy. The structural model refers to the small open economy DSGE model with the housing sector in the first essay. In addition, we examine various non-structural models including both Bayesian and classical time-series methods in our forecasting exercises. We also include the information from a large-scale quarterly data series in some models using two approaches to capture the influence of fundamentals: extracting common factors by principal component analysis in a dynamic factor model (DFM), factor-augmented vector autoregression (FAVAR), and Bayesian FAVAR (BFAVAR) or Bayesian shrinkage in a large-scale vector autoregression (BVAR). In this study, we forecast five key macroeconomic variables, namely, output, consumption, employment, housing price inflation, and CPI-based inflation using quarterly data. The results, based on mean absolute error (MAE) and root mean squared error (RMSE) of one to eight quarters ahead out-of-sample forecasts, indicate that the non-structural models outperform the structural model for all variables of interest across all horizons. Among the non-structural models, small-scale BVAR performs better with short forecasting horizons, although DFM shows a similar predictive ability. As the forecasting horizon grows, DFM tends to improve over other models and is better suited in forecasting key macroeconomic variables at longer horizons.