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In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, nation-wide industry information transmission among stock returns of ten sectors in the U.S. economy is examined through the Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke decomposition for dynamics. The evidence shows that the information technology sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG fro m ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations. In the second essay, the contemporaneous/dynamic behaviors of real estate and stock returns are investigated. Selected macroeconomic variables are included in the model to explain recent movements of both returns. During 1971-2004, there was a single structural break in October 1980. A distinct difference in contemporaneous causal structure before and after the break is found. DAG results show that REITs take the role of a causal parent after the break. Innovation accounting shows significantly positive responses of real estate returns due to an initial shock in default risk but insignificant responses of stock returns. Also, a shock in short run interest rates affects real estate returns negatively with significance but does not affect stock returns. In the third essay, a structural change in the volatility of five Asian and U.S. stock markets is examined during the post-liberalization period (1990-2005) in the Asian financial markets, using the Sup LM test. Four Asian financial markets (Hong Kong, Japan, Korea, and Singapore) experienced structural changes. However, test results do not support the existence of structural change in volatility for Thailand and U.S. Also, results show that the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) persistent coefficient increases, but the Autoregressive Conditional heteroskedasticity (ARCH) impact coefficient, implying short run adjustment, decreases in Asian markets. In conclusion, when the econometric model is set up, it is necessary to consider contemporaneous causality and possible structural breaks (changes). The dissertation emphasizes causal inference and structural consistency in econometric modeling. It highlights their importance in discovering contemporaneous/dynamic causal relationships among variables. These characteristics will likely be helpful in generating accurate forecasts.

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nÃo hà / Este estudo investiga o impacto dos instrumentos de polÃtica monetÃria e fiscal sobreas os recursos arrecadados pelo Governo Federal e disponÃveis aos demais entes federados do Brasil. As variÃveis dependentes estudadas foram o Imposto de Renda (IR), o Imposto sobre Produtos Industrializados (IPI) e algumas componentes daquele, tais como o Imposto de Renda Retido na Fonte e o Imposto de Renda Pessoa JurÃdica de empresas nÃo financeiras, enquanto os controles foram a taxa SELIC, os meios de pagamento restritos (M1) e a taxa de cÃmbio (real/dÃlar). Modelos economÃtricos tradicionais de sÃries temporais foram estimados com dados mensais entre janeiro de 2008 a dezembro de 2012 e os resultados obtidos permitiram inferir com elevada robustez que: i) variaÃÃes positivas no dÃlar proporcionam diminuiÃÃes nas arrecadaÃÃes de ambos os impostos; ii) elevaÃÃes na taxa SELIC e nos meios de pagamento restritos (M1), diferentemente do observado no cÃmbio, tendem a proporcionar aumentos na arrecadaÃÃo de ambos os impostos. Em conjunto, tais resultados justificam a preocupaÃÃo e a necessidade de intervenÃÃo da autoridade monetÃria no intuito de regular o comportamento desses controles. / This work investigates the impact of the instruments of monetary and fiscal policy on the funds raised by the Federal Government and available to other federal entities (cities and states) in Brazil. The dependent variables were the Income Tax (IT), the Tax on Industrialized Products, while controls were the official interest rate (SELIC), the restricted means of payment (M1) and exchange rate (real / U.S. dollar). Traditional econometric time series models were estimated using monthly data from January 2008 to December 2012 and the results allowed to infer that: i) increases in the dollar provide decreases in both taxes; ii) increases in the interest rate and restricted means of payment (M1) tend to provide increases in both taxes. Together, these results justify the concern and the need for intervention by the monetary authority in order to regulate the behavior of these controls.

This thesis is comprised of three independent essays. One essay is in the field of macroeconomics and the other two are in time-series econometrics. The first essay, "Productivity and Business Investment over the Business Cycle", is co-authored with my co-supervisor Hashmat Khan. This essay documents a new stylized fact: the correlation between labour productivity and real business investment in the U.S. data switching from 0.54 to -0.1 in 1990. With the assistance of a bivariate VAR, we find that the response of investment to identified technology shocks has changed signs from positive to negative across two sub-periods: ranging from the time of the post-WWII era to the end of 1980s and from 1990 onwards, whereas the response to non-technology shocks has remained relatively unchanged. Also, the volatility of technology shocks declined less relative to the non-technology shocks. This raises the question of whether relatively more volatile technology shocks and the negative response of investment can together account for the decreased correlation. To answer this question, we consider a canonical DSGE model and simulate data under a variety of assumptions about the parameters representing structural features and volatility of shocks. The second and third essays are in time series econometrics and solely authored by myself. The second essay, however, focuses on the impact of ignoring structural breaks in the conditional volatility parameters on time-varying volatility parameters. The focal point of the third essay is on empirical relevance of structural breaks in time-varying volatility models and the forecasting gains of accommodating structural breaks in the unconditional variance. There are several ways in modeling time-varying volatility. One way is to use the autoregressive conditional heteroskedasticity (ARCH)/generalized ARCH (GARCH) class first introduced by Engle (1982) and Bollerslev (1986). One prominent model is Bollerslev (1986) GARCH model in which the conditional volatility is updated by its own residuals and its lags. This class of models is popular amongst practitioners in finance because they are able to capture stylized facts about asset returns such as fat tails and volatility clustering (Engle and Patton, 2001; Zivot, 2009) and require maximum likelihood methods for estimation. They also perform well in forecasting volatility. For example, Hansen and Lunde (2005) find that it is difficult to beat a simple GARCH(1,1) model in forecasting exchange rate volatility. Another way of modeling time-varying volatility is to use the class of stochastic volatility (SV) models including Taylor's (1986) autoregressive stochastic volatility (ARSV) model. With SV models, the conditional volatility is updated only by its own lags and increasingly used in macroeconomic modeling (i.e.Justiniano and Primiceri (2010)). Fernandez-Villaverde and Rubio-Ramirez (2010) claim that the stochastic volatility model fits better than the GARCH model and is easier to incorporate into DSGE models. However, Creal et al. (2013) recently introduced a new class of models called the generalized autoregressive score (GAS) models. With the GAS volatility framework, the conditional variance is updated by the scaled score of the model's density function instead of the squared residuals. According to Creal et al. (2013), GAS models are advantageous to use because updating the conditional variance using the score of the log-density instead of the second moments can improve a model's fit to data. They are also found to be less sensitive to other forms of misspecification such as outliers. As mentioned by Maddala and Kim (1998), structural breaks are considered to be one form of outliers. This raises the question about whether GAS volatility models are less sensitive to parameter non-constancy. This issue of ignoring structural breaks in the volatility parameters is important because neglecting breaks can cause the conditional variance to exhibit unit root behaviour in which the unconditional variance is undefined, implying that any shock to the variance will not gradually decline (Lamoureux and Lastrapes, 1990). The impact of ignoring parameter non-constancy is found in GARCH literature (see Lamoureux and Lastrapes, 1990; Hillebrand, 2005) and in SV literature (Psaradakis and Tzavalis, 1999; Kramer and Messow, 2012) in which the estimated persistence parameter overestimates its true value and approaches one. However, it has never been addressed in GAS literature until now. The second essay uses a simple Monte-Carlo simulation study to examine the impact of neglecting parameter non-constancy on the estimated persistence parameter of several GAS and non-GAS models of volatility. Five different volatility models are examined. Of these models, three --the GARCH(1,1), t-GAS(1,1), and Beta-t-EGARCH(1,1) models -- are GAS models, while the other two -- the t-GARCH(1,1) and EGARCH(1,1) models -- are not. Following Hillebrand (2005) who studied only the GARCH model, this essay examines the extent of how biased the estimated persistence parameter are by assessing impact of ignoring breaks on the mean value of the estimated persistence parameter. The impact of neglecting parameter non-constancy on the empirical sampling distributions and coverage probabilities for the estimated persistence parameters are also studied in this essay. For the latter, studying the effect on the coverage probabilities is important because a decrease in coverage probabilities is associated with an increase in Type I error. This study has implications for forecasting. If the size of an ignored break in parameters is small, then there may not be any gains in using forecast methods that accommodate breaks. Empirical evidence suggests that structural breaks are present in data on macro-financial variables such as oil prices and exchange rates. The potentially serious consequences of ignoring a break in GARCH parameters motivated Rapach and Strauss (2008) and Arouri et al. (2012) to study the empirical relevance of structural breaks in the context of GARCH models. However, the literature does not address the empirical relevance of structural breaks in the context of GAS models. The third and final essay contributes to this literature by extending Rapach and Strauss (2008) to include the t-GAS model and by comparing its performance to that of two non-GAS models, the t-GARCH and SV models. The empirical relevance of structural breaks in the models of volatility is assessed using a formal test by Dufour and Torres (1998) to determine how much the estimated parameters change over sub-periods. The in-sample performance of all the models is analyzed using both the weekly USD trade-weighted index between January 1973 and October 2016 and spot oil prices based on West Texas Intermediate between January 1986 and October 2016. The full sample is split into smaller subsamples by break dates chosen based on historical events and policy changes rather than formal tests. This is because commonly-used tests such as CUSUM suffer from low power (Smith, 2008; Xu, 2013). For each sub-period, all models are estimated using either oil or USD returns. The confidence intervals are constructed for the constant of the conditional parameter and the score parameter (or ARCH parameter in GARCH and t-GARCH models). Then Dufour and Torres's union-intersection test is applied to these confidence intervals to determine how much the estimated parameter change over sub-periods. If there is a set of values that intersects the confidence intervals of all sub-periods, then one can conclude that the parameters do not change that much. The out-of-sample performance of all time-varying volatility models are also assessed in the ability to forecast the mean and variance of oil and USD returns. Through this analysis, this essay also addresses whether using models that accommodate structural breaks in the unconditional variance of both GAS and non-GAS models will improve forecasts.

In the first essay, I study the power of predictive regressions in a world of forecastable returns and find it to be quite poor. Using a simple model, I investigate the properties of short- and long-horizon regressions. The mechanisms biasing coefficients in short-horizon regressions differ from those affecting longer horizons. Further, I demonstrate that R\(^2s\) are biased and give an estimable bias correction. A calibration exercise shows sample lengths will be insufficient to determine what predicts asset returns until beyond the year 2100. The problem is not isolated to highly persistent predictors; even modestly persistent predictors have difficulties. Further, long-horizon regressions have inferior power relative to their single-period counterparts. These results present a predicament. If return predictability exists, then our ability to identify its source using predictive regressions alone is exceedingly poor. The second essay, written with James Stock and Mark Watson, considers the estimation of approximate dynamic factor models when there is temporal instability in the factors, factor loadings, and errors. We demonstrate that estimators for the factors and for the number of those factors are consistent for their population values even when affected by these instabilities. Further, we characterize the inferential theory in our framework for the estimated factors and for diffusion index forecasts and factor-augmented vector autoregressions that make use of the estimated factors. These results illustrate the broad robustness factor models have against temporal instability. In the third essay, co-author Peter Tufano and I consider the complex accounting rules, explicit fund sponsor supports, and government actions, that grant US money market mutual fund investors an implicit put option allowing them to redeem their shares at a fixed price of $1.00, regardless of the portfolio's market value. We describe the institutional features that generate these options, identify their writers, and estimate their premia. Using a hypothetical MMMF, we find that currently, non-redeeming shareholders, fund sponsors, and the government collectively bear annual premia of 22 to 44 basis points to give MMMF shareholders the right to redeem their shares at $1.00 rather than at the market value of the fund portfolio. These premia rose dramatically during the financial crisis, with the put value potentially being over 50 basis points.

The statistical analysis of cointegration is crucial for inferring shared stochastic trends between variables and is an important area of Econometrics for analyzing long-term equilibriums in the economy. Bayesian inference of cointegration involves the identification of cointegrating vectors that are determined up to arbitrary linear combinations, for which the Gibbs sampler is often used to simulate draws from the posterior distribution. However, economic theory may not suggest linear relations and regime-switching models can be used to account for non-linearity. Modeling cointegration and regime-switching as well as the combination of them are associated with highly parameterized models that can prove to be difficult for Markov Chain Monte Carlo techniques such as the Gibbs sampler. Hamiltonian Monte Carlo, which aims at efficiently exploring the posterior distribution, may thus facilitate these difficulties. Furthermore, posterior distributions with highly varying curvature in their geometries can be adequately monitored by Hamiltonian Monte Carlo. The aim of the thesis is to analyze how Hamiltonian Monte Carlo performs in simulating draws from the posterior distributions of models accounting for cointegration and regime-switching. The results suggest that while it is not necessarily the case that regime-switching will be identified, Hamiltonian Monte Carlo performs well in exploring the posterior distribution. However, high rates of divergences from the true Hamiltonian trajectory reduce the algorithm to a Random Walk to some extent, limiting the efficiency of the sampling.

Submitted by Cristiane Shirayama (cristiane.shirayama@fgv.br) on 2011-05-31T15:00:03Z No. of bitstreams: 1 63090100006.pdf: 1094712 bytes, checksum: 977dab8c82f44b506e1fc9eb0c160c62 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia(suzinei.garcia@fgv.br) on 2011-05-31T15:47:01Z (GMT) No. of bitstreams: 1 63090100006.pdf: 1094712 bytes, checksum: 977dab8c82f44b506e1fc9eb0c160c62 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia(suzinei.garcia@fgv.br) on 2011-05-31T15:48:07Z (GMT) No. of bitstreams: 1 63090100006.pdf: 1094712 bytes, checksum: 977dab8c82f44b506e1fc9eb0c160c62 (MD5) / Made available in DSpace on 2011-06-01T16:42:33Z (GMT). No. of bitstreams: 1 63090100006.pdf: 1094712 bytes, checksum: 977dab8c82f44b506e1fc9eb0c160c62 (MD5) Previous issue date: 2011-04-08 / Neste trabalho abordamos alguns "puzzles" da Paridade do Poder de Compra (PPC) ainda não resolvidos; durante esse processo propomos um novo modelo não-linear e estudamos o papel da agregação temporal e de bases de dados abrangendo apenas um pequeno período histórico. A hipótese de que não existe uma força de convergência agindo sobre o câmbio real ajustado (ARER) foi fortemente rejeitada estatisticamente, e a não-linearidade se mostrou um questão importante. As meia-vidas encontradas para o Brasil usando os modelos padrão parecem ser uma das menores já encontradas para um país, e chegamos à conclusão de que a velocidade de convergência em direção a PPC ainda não pode ser considerada um consenso. Pretendemos, em adição, dar contribuições através do levantamento e esclarecimento de alguns resultados e problemas potenciais concernentes ao estudo da PPC. / In this work we address some unresolved purchasing-power parity (PPP) puzzles; during the process we propose a new nonlinear model and check the role of temporal aggregation and of datasets covering only a small period of time. The hypothesis that there is no convergence force acting on ARER has been strongly statistically rejected and the nonlinearity showed itself as an important issue. The half-lives found for Brazil using standard models seem to be one of the smallest ever found for a country. However, we concluded that the speed of converge towards PPP is not a consensus yet. Besides, we expect to give contributions to PPP literature by pointing out important results and potential pitfalls on PPP research.

[pt] Adequação e validação de métodos econométricos para quantificar o impacto da padronização (normalização) de produtos no consumo e no bem estar dos consumidores. Três são os objetivos centrais da presente pesquisa: (i) caracterização do impacto da implementação da padronização na produção de açúcar, (ii) desenvolvimento de metodologia para a quantificação do impacto da implementação da padronização (normalização de pré-medidos) sobre o nível de produção e, portanto, sobre o bem-estar dos consumidores e (iii) análise do acervo de normas e regulamentação técnica aplicável ao setor açucareiro. Como motivação o trabalho mostra que funções da tecnologia industrial básica constituem de fato instrumentos de redução da assimetria da informação. O trabalho se desenvolveu no recente contexto de implementação de políticas públicas sociais que visam à melhoria do bem-estar de consumidores de baixa renda. O trabalho se desenvolveu em conformidade aos seguintes preceitos metodológicos: (i) revisão da literatura relacionada à assimetria da informação com o propósito de comprovar a hipótese de que a padronização de produtos pode de fato reduzir a assimetria informação; (ii) análise econométrica das sérias históricas da produção brasileira de açúcar. Os resultados do trabalho mostraram que a padronização do açúcar (normalização de pré-medidos), se devidamente implementada, pode implicar na melhoria no bem estar dos consumidores. Uma análise contra-factual clássica dos resultados consolidados mostrou que a padronização brasileira do açúcar reduziu a assimetria da informação presenciada nesse mercado, impactando num aumento de cerca de 8 porcento na produção de açúcar em 2006 devido `a padronização do produto implementada em 1992. Como conclusão a análise econométrica permitiu mostrar que a padronização de produtos constitui-se numa ferramenta estratégica a serviço do Estado promover a competitividade e como instrumento de redução de assimetria da informação em benefício do consumidor e de redução de distorções de mercados. / [en] There are two objetives in this Master dissertation in Metrology: (i) characterization of the impact of the implementation of the standardization in the production of sugar and (ii) development of methodology for quantifying the impact of the implementation of the standardization on the production level and, therefore, on the welfare of consumers. The work was motivated by the use of functions of basic industrial technology to reduce the asymmetric information as market failure is able to generate deficiencies. The investigation was developed in the recent context characterized by the implementation of social public policies aimed to improve the low income consumer s welfare. The work was developed in accordance to the following methodological precepts: (i) review of the literature on asymmetric information in order to verify the hypothesis that the products standardization can reduce the asymmetric information, generating an improvement in the consumer s welfare; (ii) econometric analysis of the Brazilian sugar production time series. As a result, the research shows that the sugar standardization, if correctly implemented, induces consumer s welfare. A contra-factual analysis of the consolidated results has shown that the Brazilian sugar standardization reduced the asymmetric information in this market. The impact of this policy was an increase in roughly 8 percent in the sugar production in 2006 due to the product standardization implemented in 1992. As a conclusion, the econometric analysis developed show that the standardization of products can be considered a powerful strategic tool. Not only to promote specific sector competitiveness, but also as an instrument to reduce the asymmetric information to the benefit of consumers.

Diese Dissertation beantwortet verschiedene politikrelevante ökonomische Fragen in den Bereichen Handelspolitik, Geldpolitik, sowie Rohstoffmärkte und Energieökonomik mit Hilfe von strukturellen Vektorautoregressionsmodellen (SVAR). SVARs stellen eine effektive Möglichkeit dar, die Beziehungen zwischen verschiedenen makroökonomischen und/oder Finanzmarkt-Variablen zu modellieren und werden verwendet, um die dynamischen kausalen Effekte von ökonomischen Schocks zu schätzen. Für jede ökonomische Fragestellung wird eine Identifikationsstrategie angewandt, die auf die betrachteten Daten und ihre statistischen Eigenschaften sowie die zugrundeliegenden Annahmen über ökonomische Mechanismen zwischen den betrachteten Zeitreihen zugeschnitten ist. Im Einzelnen besteht diese Dissertation aus vier Kapiteln. In den ersten beiden Kapiteln werden die Auswirkungen von Handelspolitik auf Finanzmärkte und auf die Makroökonomie geschätzt. Das dritte Kapitel liefert einen methodischen Beitrag zur SVAR-Literatur, der in einer Anwendung zu den Effekten von Geldpolitik dargestellt wird. Das letzte Kapitel verlässt die Felder der Handels- und Geldpolitik und wendet sich Rohstoffmärkten und der Energiewirtschaft zu, stützt sich dabei aber ebenfalls auf Zeitreihenmethoden. Es analysiert die Rolle von Metallen in der Energiewende. / This dissertation answers various policy relevant economic questions in the fields of trade policy, monetary policy, and commodity markets and energy economics using structural vector autoregression (SVAR) models. SVARs constitute a parsimonious way to model the relations between different macroeconomic and/or financial variables and they are used to estimate the dynamic causal effects of economic shocks. For each economic question, this dissertation applies an identification strategy that is tailored to the relevant data and its statistical properties as well as the underlying assumptions about economic mechanisms among the regarded time series. Specifically, this dissertation consists of four chapters. The first two chapters estimate the effects of trade policy on financial markets and on the macroeconomy. The third chapter makes a methodological contribution to the SVAR literature in an application to monetary policy shocks. The final chapter moves away from trade and monetary policy to commodity markets and energy economics but also relies on time series methods. It analyzes the role of metals for the clean energy transition.