Thesis (Ph. D.)--University of Oregon, 2003. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 139-142). Also available for download via the World Wide Web; free to University of Oregon users.

I study to what extent consumers’ expectations of inflation are formed differently in the short run for countries that belong to a monetary union, which implies a common inflation-targeting central bank, in contrast to countries with national inflationtar geting central banks. I measure if there are differences in consumers’ reaction s to inflation deviation from target, persistency of expected inflation and the ability to predict accurate inflation in the respective considered countries. I also measure average deviation and average absolute deviation of actual and expected inflation from the inflation target. The results suggest that the respective country’s average reaction to inflation deviation from target, degree of persistent expectation and the ability to predict accurate inflation rates are in the same range as well as the results for the average and average absolute deviations. Therefore, I conclude that there are no substantial differences in the formation of consumers’ expectations in countries belonging to a monetary union and countries with national inflation-targeting central banks, in the short run.

Recently, single equation approaches for estimating structural models have become popular in the monetary economics literature. In particular, single-equation Generalized Method Moments estimators have been used for estimating forward-looking models with rational expectations. Two important examples are found in Clarida, Gali, and Gertler (1998) for the estimation of forward- looking Taylor rules and in Gali and Gertler (1999) for the estimation of a forward-looking model for inflation dynamics. In this thesis, we address the issues of identification which have been overlooked due to the incompleteness of the single-equation formulations. We provide extensions to existing results on the properties of GMM estimators and inference under weak identification, pertaining to situations in which only functions of the parameters of interest are identified, and structural residuals exhibit negative autocorrelation. We also characterize the power of the Hansen test to detect mis specification, and address the issues arising from using too many irrelevant instruments as well as from general corrections for residual autocorrelation, beyond what is implied by the maintained model. In general, we show that the non-modelled variables cannot be weakly exogenous for the parameters of interest, and that they are informative about the identification and mis-specification of the model. Modelling the reduced form helps identify pathological situations in which the structural parameters are weakly identified and the GMM estimators are inconsistent and biased in the direction of OLS.We also ¯nd the OLS bias to be increasing in the number of over-identifying instruments, even when the latter are irrelevant, thus demonstrating the dangers of using too many potentially irrelevant instruments. Finally, with regards to the "New Phillips curve", we conclude that, for the US economy, this model is either un-identified or mis-specified, casting doubts on its utility as a model of in°ation dynamics.

Zugl.: Bielefeld, Univ., veränd. Habil.-Schr.

Thesis (M.Com. (Hons.))-University of Western Sydney, Macarthur, Faculty of Business and Technology, 1995. / Bibliography: 159-168.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 112-115).

xi, 87 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / The behavior of the macroeconomy and monetary policy is heavily influenced by expectations. Recent research has explored how minor changes in expectation formation can change the stability properties of a model. One common way to alter expectation formation involves agents' use of econometrics to form forecasting equations. Agents update their forecasts based on new information that arises as the economy progresses through time. In this way agents "learn" about the economy. Previous learning literature mostly focuses on agents using a fixed data size or increasing the amount of data they use. My research explores how agents might endogenously change the amount of data they use to update their forecast equations. My first chapter explores how an established endogenous learning algorithm, proposed by Marcet and Nicolini, may influence monetary policy decisions. Under rational expectations (RE) determinacy serves as the main criterion for favoring a model or monetary policy rule. A determinant model need not result in stability under an alternative expectation formation process called learning. Researchers appeal to stability under learning as a criterion for monetary policy rule selection. This chapter provides a cautionary tale for policy makers and reinforces the importance of the role of expectations. Simulations appear stable for a prolonged interval of time but may suddenly deviate from the RE solution. This exotic behavior exhibits significantly higher volatility relative to RE yet over long simulations remains true to the RE equilibrium. In the second chapter I address the effectiveness of endogenous gain learning algorithms in the presence of occasional structural breaks. Marcet and Nicolini's algorithm relies on agents reacting to forecast errors. I propose an alternative, which relies on agents using statistical information. The third chapter uses standard macroeconomic data to find out whether a model that has non-rational expectations can outperform RE. I answer this question affirmatively and explore what learning means to the economy. In addition, I conduct a Monte Carlo exercise to investigate whether a simple learning model does, empirically, imbed an RE model. While theoretically a very small constant gain implies RE, empirically learning creates bias in coefficient estimates. / Committee in charge: George Evans, Co-Chairperson, Economics; Jeremy Piger, Co-Chairperson, Economics; Shankha Chakraborty, Member, Economics; Sergio Koreisha, Outside Member, Decision Sciences

This study analyses whether historically defensive sectors on the JSE have – with respect to the market – proven to be defensive during the recent global financial crisis. By withstanding the shocks of market volatility, defensive industries (such as pharmaceuticals and consumer staples) are renowned for their consistent performance throughout the business cycle. Using daily data for the period 2000–2009, the study compares the descriptive statistics of sector returns before and during the crisis. The volatility of each sector relative to the market index is calculated using the CAPM beta and a simplified volatility ratio. The same comparison is extended to the conditional volatilities of each of the sectors, which is estimated using the GARCH model and two of its extensions: the EGARCH and GJR GARCH models. While no sector experienced a positive mean return during the financial crisis, Healthcare, Consumer Goods, Consumer Services and Industrials all proved less volatile than the market. Surprisingly, Telecommunications proved more volatile than the market and experienced leverage effects during the financial crisis. Since the timing of a recession is difficult to predict, defensive securities were found to be a useful investment tool for protection against adverse movements in the stock market.

Este trabalho trata das aplicações da Teoria de Controle Ótimo ao problema de otimização da Política Monetária. Esse problema consiste em minimizar uma função que representa o custo da inflação para a sociedade, por meio de manipulações na variável de controle, que é a taxa de juros da economia. Serão considerados dois modelos para a dinâmica macroeconômica: um keynesiano e um novo-keynesiano. O problema de minimização sujeito à dinâmica keynesiana pode ser resolvido por meio dos conceitos tradicionais de controle ótimo, como o LQR e LQG. Por outro lado, o modelo novokeynesiano possui uma dinâmica mais complexa e não-recursiva, impossibilitando a aplicação direta dos métodos de programação estocástica. Assim, o problema de minimização sujeito à essa dinâmica requer métodos mais complexos, como o método do Lagrangiano ou o método do ponto de sela recursivo. É apresentada a solução analítica para o problema de controle ótimo em cada tipo de dinâmica. Em seguida, o problema de estimação de parâmetros é abordado. Métodos como o OLS e o GMM são empregados para estimar os parâmetros do modelo. Também são realizadas simulações para determinar numericamente as políticas de controle ótimo em alguns cenários. Por fim, a política monetária ótima é determinada para o período entre 2008 e 2009 e comparada com a política monetária adotada pelo governo. / This article discusses the applications of the Optimal Control Theory to the Monetary Policy optimization problem. This problem consists in minimizing a function that represents the inflation cost to society, through manipulation on the control variable, which is the interest rate of the economy. It will be considered two models for macroeconomic dynamics: a Keynesian and a new-Keynesian model. The minimization problem subject to Keynesian dynamics can be solved through traditional optimal control tools, such as LQR and LQG. On the other hand, the second model has a more complex and non-recursive dynamic, precluding the direct application of stochastic programming methods. Thus, the minimization problem restricted to this dynamic requires more complex methods, like the Lagrangian or the recursive saddlepoint method. It is presented the analytical solution to the optimal control problem for each type of dynamics. Then, the parameter estimation problem is addressed. Methods such as OLS and GMM are used to estimate the model parameters. Simulations are also carried out to determine numerically the optimal control policies in some scenarios. Finally, the optimal monetary policy is determined for the period between 2008 and 2009 and compared with the monetary policy adopted by the government.

This study investigates the existence of the value premium in South Africa’s equity market, and tests extrapolation as a possible explanation for it. The value premium refers to the widely reported superior performance of share price returns of value companies compared to growth companies. The value premium represents an anomaly in mainstream rational finance theory, because it should not persist, unless it could be explained as the result of some composite form of risk. What is highly vexing is the fact that the value premium not only persists in most financial markets over a long period, but that the risk explanation cannot be upheld convincingly. This contributed to the rise of behavioral finance, an approach which introduces psychological factors to provide new explanations for financial phenomena. The behavioral finance explanation for the value premium observation is extrapolation (the tendency to project recent experience too far into the future). This study applies propositions and methods from behavioral finance to investigate the South African equity market. The existence of a value premium in South Africa was investigated by using twenty-nine years’ worth of accounting and share price data. The study employed one- and two-dimensional tests for portfolio formation, and tracked share price returns for up to five years after portfolio formation. The results indicated that a statistically and economically significant value premium existed in South Africa for the period between 1972 and 2001. Extrapolation as a potential explanation for the value premium observation was investigated by applying internationally used methods. Extrapolation was found to provide a robust explanation for the South African value premium.