Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1985. / Bibliography: leaves [125]-129. / Photocopy. / x, 129 leaves, bound ill. 29 cm

This thesis models the Australian-US Dollar (AUD/USD) exchange rate with particular attention being paid to investor risk aversion. Accounting for investor risk aversion in AUD/USD exchange rate modelling is novel, so too is the method used to measure risk aversion in this thesis. Investor risk aversion is measured using a technique developed in Bliss and Panigirtzoglou (2004), which makes use of Probability Density Functions (PDFs) extracted from option markets. More conventional approaches use forward-market pricing or Uncovered Interest Parity. Several methods of estimating PDFs from option and spot markets are examined, with the estimations from currency spot-markets representing an original application of an arbitrage technique developed in Stutzer (1996) to the AUD/USD exchange rate. The option and spot-market PDFs are compared using their first four moments and if estimated judiciously, the spot-market PDFs are found to have similar shapes to the option-market PDFs. So in the absence of an AUD/USD exchange rate options market, spot-market PDFs can act as a reasonable substitute for option-market PDFs for the purpose of examining market sentiment. The Relative Risk Aversion (RRA) attached to the AUD/USD, the US Dollar-Japanese Yen, the US Dollar-Swiss Franc and the US-Canadian Dollar exchange rates is measured using the Bliss and Panigirtzoglou (2004) technique. Amongst these exchange rates, only the AUD/USD exchange rate demonstrates a significant level of investor RRA and only over a weekly forecast horizon. The Bliss and Panigirtzoglou (2004) technique is also used to approximate a time-varying risk premium for the AUD/USD exchange rate. This risk premium is added to the cointegrating vectors of fixed-price and asset monetary models of the AUD/USD exchange rate. An index of Australia???s export commodity prices is also added. The out-of-sample forecasting ability of these cointegrating vectors is tested relative to a random walk using an error-correction framework. While adding the time-varying risk premium improves this forecasting ability, adding export commodity prices does so by more. Further, including both the time-varying risk premium and export commodity prices in the cointegrating vectors reduces their forecasting ability. So the time-varying risk premium is important for AUD/USD exchange rate modelling, but not as important as export commodity prices.

This dissertation contains a series of essays that provide empirical evidence for Australia on some fundamental predictions of real business cycle models and on the convergence and persistence of real interest rates. Chapter 1 provides a brief introduction to the issues examined in each chapter and provides an overview of the methodologies that are used. Tests of various basic predictions of standard real business cycle models for Australia are presented in Chapters 2, 3 and 4. Chapter 2 considers the question of great ratios for Australia. These are ratios of macroeconomic variables that are predicted by standard models to be stationary in the steady state. Using time series econometric techniques (unit root tests and cointegration tests) Australia great ratios are examined. In Chapter 3 a more restrictive implication of real business cycle models than the existence of great ratios is considered. Following the methodology proposed by Canova, Finn and Pagan (1994) the equilibrium decision rules for some standard real business cycle are tested on Australian data. The final essay on this topic is presented in Chapter 4. In this chapter a large-country, small-country is used to try and understand the reason for the sharp rise in Australia??s share of world output that began around 1990. Chapter 5 discusses real interest rate linkages in the Pacific Basin region. Vector autoregressive models and bootstrap methods are adopted to study financial linkages between East Asian markets, Japan and US. Given the apparent non-stationarity of real interest rates a related issue is examined in Chapter 6, viz. the persistence of international real interest rates and estimation of their half-life. Half-life is selected as a means of measuring persistence of real rates. Bootstrap methods are employed to overcome small sample issues in the estimation and a non-standard statistical inference methodology (Highest Density Regions) is adopted. Chapter 7 reapplies the High Density Regions methodology and bootstrap half-life estimation to the data used in Chapters 2 and 5. This provides a robustness check on the results of standard unit root tests that were applied to the data in those chapters. Main findings of the thesis are as follows. The long run implications of real business cycle models are largely rejected by the Australia data. This finding holds for both the existence of great ratios and when the explicit decision rules are employed. When the small open economy features of the Australian economy are incorporated in a two country RBC model, a country-specific productivity boom seems to provide a possible explanation for the rise in Australia??s share of world output. The essays that examine real interest rates suggest the following results. Following the East Asian financial crisis in 1997-98 there appears to have been a decline in the importance of Japan in influencing developments in the Pacific Basin region. In addition there is evidence that following the crisis Korea??s financial market became less insular and more integrated with the US. Finally results obtained from the half-life estimators suggest that despite the usual findings from unit root tests, real interest rates may in fact exhibit mean-reversion.

Ongoing globalisation has resulted in more liberalisation, integration, and competition among countries. An upshot of this has been higher levels of cross-border investment. Foreign direct investment (FDI), long considered an engine of growth, has led to widespread probe with its recent rapid spread. Nevertheless, while research on the contribution of FDI to host countries has concentrated heavily on the developed and developing economies, there has been a marked neglect of small, developed economies. This study proposes to focus on New Zealand, a country that falls within the latter category. The study seeks to verify econometrically the impact of FDI on the country through causality links with growth, trade, domestic investment and labour productivity. The analysis is based upon time-series data, the econometric techniques of single, autoregressive distributed lag (ARDL), and the multiple equations approach, vector error correction method (VECM). The study found that there have been substantial gains to the New Zealand economy. A positive effect of FDI on the variables mentioned above led to an improvement of the balance of payments through an increase in exports rather than in imports. Economic growth has mainly been achieved through FDI's impact on exports and domestic private investment. The dynamic innovation techniques indicated a bi-directional causality between FDI and the variables. The long-run causality, however, runs mainly from growth and labour productivity to FDI rather than in the opposite direction. Another noticeable feature is that New Zealand's regional agreement with Australia, Closer Economic Relations, has brought the country significant gains in terms of growth and development through FDI. Both the ARDL and VECM approaches suggest that for a small, developed country qualitative impacts are greater than quantitative ones. The policy implication is that maintaining sustainable economic growth with a positive domestic investment environment is vital for attracting foreign investors. New Zealand, while continuing to encourage inward FDI, should aim to channel it into 'innovative' tradable sectors. The challenge lies in providing the right kind of policy mix for this purpose.

Diss. Uppsala : Uppsala universitet, 2006.

Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

While the phenomenon of informality in labor markets is pervasive in many parts of the world, its interaction with the aggregate behavior of economies is not well understood. In this dissertation, I explore the connection between informality and the macroeconomy in two main ways. The first way is to augment a search-and-matching model of labor markets in the tradition of Mortensen and Pissarides (1994) with aggregate shocks and an informal sector. The second is to consider an Aiyagari (1994) setting in which the existence of an informal sector feeds back into the labor income risk and savings decisions of heterogeneous agents. The parameters of both models are chosen so as to match features of micro-data I obtain from Brazil. This dissertation is thus divided into three chapters: the first one presents the data and findings from the empirical exploration. The second chapter describes the model of informality over the business cycle and presents its results. The third chapter introduces the heterogeneous agents model with informality and the conclusions derived therefrom. The first chapter divides the empirical analysis into two components. Firstly, I analyze how informality is distributed over education, income and occupational groups, and how formal-informal income differentials behave over these categories. I find that informality decreases in average income, and that the formal-informal income differential is higher among low income workers. The second component pertains to the evolution of informality over time. I show that, in the time period covered by the data, the rate of informality has a strongly cyclical pattern, which is mostly explained by cyclical variation in formal job creation. In the second chapter, in co-authorship with Livio Maya, we show in a parsimonious model of business cycles and informal labor markets that the differential risk of formal and informal contracts plays a potentially important role in generating the patterns of job creation found in the data. The main finding is that generating substantial countercyclicality in the informality rate in our calibration requires the price of risk to be highly countercyclical. In the third chapter, also in co-authorship with Livio Maya, we show the transition path of a policy designed to fight informality in a heterogeneous agents setting. The main finding is that while eliminating the informal sector makes the economy more productive and reduces unemployment in the long run, the short term impact is influenced by general equilibrium effects. In particular, unemployment increases in the short run due to the impact of the policy on interest rates. Moreover, the effects of such policy are sensitive to the assumptions on the destination of the extra tax revenues derived from increased formalization in the transition path.

This dissertation revolves around robustly measuring and using the information sets of the centralbank and financial markets in order to measure exogenous monetary policy. Modern central banks aggressively use all the available information at their disposal to effectively set monetary policy. This problem of “foresight” renders traditional time series methods ineffective; the information edge of central banks is too large. In the first chapter, I discuss refinements to existing narrative methods, which attempt to the central bank’s own forecasts to capture the information set of the central bank, thus removing their information edge over the econometrician. In the second chapter, I explore how the information sets of financial agents differ central banks and show that there is little direct information transfer between central banks and financial markets around monetary policy actions. Finally, the third chapter details how to use the information sets of financial sector actors to estimate exogenous monetary policy actions that is robust to financial sector revisions about the economy which can be due to the monetary policy actions.

This dissertation studies the role of occupation-specific human capital in explaining the long-run decline in labor market dynamics observed in the United States for the past four decades. Chapter 1 presents empirical facts on labor market outcomes by required occupation-specific training. This is to provide evidence that (i) required length of occupation-specific training is a proxy for the specificity of human capital to perform the occupation and that (ii) increasing occupation specificity has led to the decline in labor market dynamics. First, I find from the Dictionary of Occupational Titles and O*NET that for the past four decades, within occupations, there has been an increase the amount of time needed to become trained in the occupation. I then find from the Survey of Income and Program Participation that the average wage loss experienced by occupation switchers after unemployment increases when their occupation held before unemployment has faced over time an increase in occupation-specific training. I take this as evidence that the observed increase in occupation-specific training over time has made human capital less transferable across occupations. I then proceed to use the Monthly Current Population Survey, combined with the required length of occupation-specific training by occupation from the Dictionary of Occupational Titles and O*NET, to do a shift-share decomposition of the decline in labor market outcomes. The decline in the aggregate job separation rate and the increase in unemployment duration is accounted for mostly by the increase in specific training within occupations. Motivated by my empirical analysis, in Chapter 2, I then build a search-and-matching model to learn how the increase in specificity within occupations explains the decline in the aggregate job separation rate. The main ingredients are endogenous job separations and occupation-specific human capital that workers acquire during employment and lose when they switch occupations. My model has two occupation specificity parameters: (i) the average duration of occupation-specific training and (ii) the output gap by which nontrained workers are less productive because they have not yet acquired the occupation-specific capital. To ask my model how much of a decline it predicts in the aggregate job separation rate when occupations become more specific, the occupation specificity parameters in the model are increased to match the increase in occupation specificity in the data. The increase in the average duration of occupation-specific training matches the required length of occupation-specific training from the Dictionary of Occupational Titles and O*NET. The increase in the output gap is informed by the estimated increase in the wage penalty faced by occupation switchers (relative to non-occupation switchers) when their previously held occupation requires more occupation-specific training, obtained from the Survey of Income and Program Participation. The model predicts 60% of the decline in the aggregate job separation rate. Chapter 3 relaxes the assumption that occupation switching is exogenous in Chapter 2, endogenizing occupation switching in addition to job separations. The model predicts a greater increase in the average unemployment duration in line with the data. In the model, the longer unemployment spells are due to the unemployed trained workers, whose human capital has become more specific to their previous occupation, choosing not to switch occupations. If they switch occupations, they could quickly end their unemployment spell. This would however come at the cost of larger wage cuts because their human capital has become less transferable to a different occupation. Occupation switchers would also have to earn these lower wages for a longer period of time until they become trained in their new occupation. Hence, despite a low probability of getting reemployed in the same occupation as before, previously trained workers increasingly choose not to switch occupations, which increases the average unemployment duration.

This dissertation studies information economics in strategic and decision settings. In Chapter 1, I introduce flexible endogenous monitoring into dynamic moral hazard. A principal can commit to not only an employment plan but also the monitoring technology to incentivize dynamic effort from an agent. Optimal monitoring follows a Poisson process that produces rare informative signals, and the optimal employment plan features decreasing turnover. To incentivize persistent effort, the Poisson monitoring takes the form of "bad news'' that leads to immediate termination. Monitoring is non-stationary: the bad news becomes more precise and less frequent. In Chapter 2, which is joint work with Qingmin Liu, we analyze a model of strategic exploration in which competing players independently explore a set of alternatives. The model features a multiple-player multiple-armed bandit problem and captures a strategic trade-off between preemption---covert exploration of alternatives that the opponent will explore in the future---and prioritization---exploration of the most promising alternatives. Our results explain how the strategic trade-off shapes equilibrium behaviors and outcomes, e.g., in technology races between superpowers and R&D competitions between firms. We show that players compete on the same set of alternatives, leading to duplicated exploration from start to finish, and they explore alternatives that are a priori less promising before more promising ones are exhausted. In Chapter 3, I study how a forward-looking decision maker experiments on unknown alternatives of spatially correlated utilities, modeled by a Brownian motion so that similar alternatives yield similar utilities. For example, a firm experiments on its size that yields unknown, spatially correlated profitability. Experimentation trades off the opportunity cost of exploitation for the indirect inference from the explored alternatives to unknown ones. The optimal strategy is to explore unknown alternatives and then exploit the best known alternative when the explored becomes sufficiently worse than the best. The decision maker explores more quickly as the explored alternative worsens. My model predicts the conditional Gibrat's law and linear relation between firm size and profitability.