This dissertation consists of four chapters. In the first chapter, a review is made of the research on international reserve demand in the last decade. The next three chapters offer alternative models of reserve demand. One motive for why foreign currencies are held by national central banks (NCBs) is to intervene in the foreign exchange market. A primary goal of the last three chapters is to incorporate such an intervention motive in modeling demand for foreign exchange reserves by the public sector. Another goal--more fully studied in the last chapter--is to assess the effects of exchange controls on demand for reserves. Disequilibrium regime-switching econometrics is the modeling framework employed. This methodology allows for the possibility that a different demand regime may be in effect in periods when the NCB is a net buyer of foreign currencies as compared to periods when it is a net seller. To deal with the effects of constant changes in the exchange control environment--which could alter demand behavior--a robust method is used which weighs down observations from periods where the standard model performs poorly. Some evidence is found that market intervention changes the response of demand for foreign reserves with respect to trade and the opportunity cost. This effect is not uniform across countries however. National demands for foreign reserves are also found to vary. Furthermore, the period where the model performs poorly are not characterized chiefly by heavy exchange controls but by political/economic shocks and uncertainty. Shocks and uncertainty alter demand for foreign currency reserves while exchange controls appear to be ineffective.

The simple market efficiency hypothesis implies that prediction errors, such as forward less spot exchange rates, will be orthogonal to elements of the information set. One can therefore test for market efficiency via ordinary least squares by regressing the prediction errors on pieces of information available at the time the predictions are made and checking if the intercept term and slope coefficients are jointly equal to zero. Two econometric complications have to be dealt with when testing for market efficiency in the above manner. The first complication arises from the fact that multi-period-ahead predictions lead to an inter-temporal band structure for the covariance matrix. This complication can be handled by employing Hansen's Generalized Method of Moments (GMM) estimate which takes explicit account of the band structure of the covariance matrix. The second complication arises from the fact that the disturbances in the regression may also be heteroskedastic. Insofar as heteroskedasticity might adversely affect inference, we propose a White-type test that indicates whether or not a covariance matrix correction for heteroskedasticity is necessary. The test essentially checks if the difference between the homoskedastic and heteroskedastic consistent forms of Hansen's GMM estimate tend towards zero. Monte Carlo experiments examining the performance of the proposed test show that at least in large samples, the White-type test works well under a variety of heteroskedastic specifications. By actually applying the above procedures to test the simple foreign exchange market efficiency hypothesis, we find that for particular regression specifications and data sets, it does not make a practical difference whether we base inferences on the homoskedastic or the heteroskedastic consistent forms of Hansen's GMM covariance estimate. For other data sets and regression specifications, however, we are able to reject market efficiency only if we use the appropriate form of Hansen's GMM estimate as determined by the White-type test.

This dissertation focuses on the heterogeneous production technologies in banking and finance within the context of efficiency-analyses. The first essay studies the cost efficiency of Turkish banking industry. Studies of bank efficiency tend to draw conclusions from pooled estimates, assuming that all banks in a sample use the same technology, or estimates based on a priori classifications of the banks. It is well known that efficiency rankings may be corrupted if banks that use different technologies are pooled together in estimating the technological frontier with respect to which inefficiency is estimated. We model unobserved heterogeneity in banking technologies as a mixture model, and investigate the efficiencies of 53 Turkish banks using likelihood-based stochastic frontier analysis for the period 1990--2000. Our likelihood-based analysis finds no evidence of heterogeneity along the state vs. private and Islamic vs. conventional dimensions. The estimated classifications and mixture components have intuitive ex post institutional explanations. The second essay investigates the labor efficiency of Turkish banks for 1990--2000 by using a flexible translog functional form where the demand for labor is a function of loans, deposits, number of branches, total fixed assets and a time variable. The model allows for the possibility that at any point banks' observed employment may not be optimal. We expand the labor-use model by utilizing the EC (Estimation-Classification) estimator to obtain data-driven identification of bank-technology-classes in our sample. The third essay uses a set of semiparametric efficient (SPE) estimators for a panel data of 32 developing countries to investigate the effect of sources of external financing on production efficiency. The idea of production frontiers for firms in a given industry is applied in a macroeconomic context in which countries are producers of output (GDP) given inputs (capital and labor) and some external factors (i.e. debt, equity and foreign direct investment (FDI) stocks). Using two recent datasets, we are able to investigate the individual impact of foreign liabilities, namely debt, equity and FDI, on production efficiency. The estimates indicate that FDI plays a more prominent role of promoting production efficiency than debt or equity financing for developing countries.

This thesis deals with market rules that define the price and the generation schedule in electricity markets. The research has focused on three approaches: Pool Cost Minimization (PCM) with marginal pricing, Consumer Payment Minimization (CPM), and mixed Pool Cost/Consumer Payment Minimization (PCM/CPM). Each method is examined from the perspective of the solution characteristics and the relevant economic principle, together with numerical examples. Especially in the CPM method, several fundamental theoretical results are obtained regarding the nature of the minimum consumer payment and the corresponding generation schedule. In addition, some generator bidding strategies are studied with respect to PCM and CPM so as to identify how Gencos can obtain a competitive advantage.

<p> Construction materials cost estimation is considered one of the most important tasks in the development of project budget. Using material hedging to mitigate the risk of material price volatility is a new concept for construction companies.</p><p> This thesis matched material hedging with the fuel hedging application utilized by airlines. The weather hedging process was used as a precedent for material hedging application in the construction industry. This thesis developed a model to provide a step by step guidance to apply material hedging in the construction industry. Further, this thesis matched its model with the model presented by Macdonald (2013) and provided a lower level of detail to support actual implementation of material hedging.</p><p> Future work in this area could be the investigation of material hedging cost to decide if the hedging application is feasible. Also, validity and reliability of the model presented by this thesis should be investigated. </p>

In Part I, two pool-based electricity market models are compared in terms of their economic impact on the market participants, the Lossless Economic Dispatch (LED) and the Optimal Power Flow (OPF). The OPF is shown to be economically more efficient, more accurate and more equitable to the participants. / In Part II, a stochastic electricity market simulator (SEMS) is designed using elements of Monte Carlo methods and game theory. Each generator is assumed to operate in a stochastic manner, according to a bid strategy composed of a set of pre-established bid instances and a corresponding set of bid probabilities. The Pool dispatches power and defines prices according to either the LED or OPF models from Part I. Generators can update their bidding strategies according to a profit performance index reflecting their degree of risk tolerance, Chicken (risk averse), Average, and Cowboy (risk taker). SEMS can predict issues such as unintended collusion, as well as to evaluate bidding strategies.

Thesis (Ph.D.)--Indiana University, Kelley School of Business, 2007. / Source: Dissertation Abstracts International, Volume: 68-09, Section: A, page: 3966. Adviser: Eric B. Rasmusen. Title from dissertation home page (viewed May 5, 2008).

Thesis (Ph.D.)--Indiana University, Kelley School of Business, 2007. / Source: Dissertation Abstracts International, Volume: 68-07, Section: A, page: 3030. Adviser: Alan M. Rugman. Title from dissertation home page (viewed Apr. 9, 2008).

Zugl.: Krems, Univ., Masterarbeit, 2007

Thesis (Ph.D.)--Indiana University, Dept. of Economics, 2008. / Title from PDF t.p. (viewed on May 11, 2009). Source: Dissertation Abstracts International, Volume: 69-08, Section: A, page: 3253. Advisers: Michael Baye; Michael Rauh.