Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 62-66).

This study focuses on the effects of nominal shocks on the real exchange rate. The model used to determine the effects of a monetary expansion on the real exchange rate assumes instantaneously clearing asset markets and sticky goods prices. A monetary expansion causes the nominal exchange rate to initially overshoot its long run equilibrium value followed by a series of appreciations. The real exchange rate depreciates sharply and then appreciates until its initial value is restored. / A simple monetary model, a sticky price monetary model and a random walk model are empirically tested with Canadian/U.S. data over the 1972-1989 time period. Both monetary models were rejected and the random walk model represented the best fit to the data. This evidence supports the hypothesis that the Canadian/U.S. nominal exchange rate follows a random walk process. / An empirical examination of the Canadian real exchange rate over the 1970-1989 period confirms the hypothesis that since the advent of the floating exchange rate period, the Canadian real exchange rate movements have been much larger than most economists predicted.

I propose and test a new model determining the choice of the exchange rate regime in Latin America and the Caribbean. The key insight is that systemic level instability plays an important role in choosing the exchange rate regime. Using new data from Reinhart and Rogoff (2004), a second insight is that countries do not always follow the type of exchange rate regime they claim. Testing the determinants of regime choice against both the traditional, official de jure and new, market de facto data, I find that policymakers are strategically using the observed gap between the measures. The evidence reveals that systemic level variables, namely instability in the US interest rate and the bilateral USD:DEM/Euro exchange rate, significantly impact the choice of the exchange rate regime.

Thesis (Ph. D.)--University of California, San Diego, 2008. / Title from first page of PDF file (viewed June 12, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 150-160).

Thesis (Ph. D.)--University of Hong Kong, 1997. / Includes bibliographical references (leaf 284-317).

Thesis (Ph. D.)--University of California, San Diego, 1997. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--UCLA, 2008. / Vita. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Pennsylvania, 1990. / Includes bibliographical references (leaves 324-330).

Thesis (Ph. D.)--University of Chicago, 1987. / Includes bibliographical references (leaves 109-112).

M.Com. (Financial Economics) / Exchange rate forecasting has been an important and complex field of study originating mainly from the introduction of floating exchange rates in the 1970s. Since then, various models have been developed to explain exchange rate behaviour, all contributing in their own way to the understanding of what economic and financial information reveal about the future price of exchange rates. To measure the performance of a variety of exchange rate models, researchers in exchange rate forecasting almost always use the random walk model as benchmark to evaluate the forecasting performance of exchange rate models. An exchange rate model is regarded as superior if it can outperform a random process. The random walk model, a special case of the unit root process, helps us to identify the kinds of disturbances that drive the exchange rate to follow an independent successive process. If the exchange rate follows a random walk process, it has no mean reversion tendency and a directional shock in the exchange rate will cause it to deviate from its long-run equilibrium. Conversely, if the exchange rate does not follow a random walk, it has mean reverting tendencies, and will follow a stationary process which allows us to accurately forecast the exchange rate based on historic observations (Lam, Wong and Wong, 2005:1). However, it seems unrealistic that exchange rates will follow either a random walk process or a stationary process. If we assume that the exchange rate follows a random walk, we also assume that the order flow information from exchange rate trades follows a random walk, and by implication that macroeconomic exchange rate information follows a random walk [see Lyons (2001) for the link between order flow and macroeconomic fundamentals]. It seems unrealistic that exchange rates will follow an identifiable mean reverting (stationary) process, as daily exchange rates are exposed to risk, news and speculation which functions independent from long-run exchange rate fundamentals. Ironically, Meese and Rogoff (who laid the foundation for the use of random walk models as benchmark in exchange rate forecasting) emphasize that exchange rates do not follow an exact random walk (Meese and Rogoff, 1983:14). However, if it is known that exchange rates do not follow a random process explicitly, alternative exchange rate benchmark models should be considered. Yet, judging by the universal...