Thesis (Ph.D.)--Brown University, 2008. / Thesis advisor : Oded Galor. Vita. Includes bibliographical references (leaves 97-106).

Thesis (Ph.D.)--Brown University, 2008. / Vita. Advisor: Mark M. Pitt. Includes bibliographical references (leaves 81-85).

New theoretical developments and recent experimental studies involving the sealed-bid k-double auction mechanism for bilateral bargaining under incomplete information have raised new questions about procedures that induce efficient bargaining behavior and about the applicability of extant adaptive learning models. It is now generally accepted that a theory of bargaining behavior for individuals who typically do not meet the stringent assumptions about common knowledge of rationality cannot be complete without systematic empirical investigations of the properties of the various mechanisms that structure bargaining. The aim of this dissertation is to critically explore the extent to which efficient bargaining outcomes can be achieved while dynamically accounting for individual behavior across repeated play of the game. In the first study, an endogenous bonus is introduced into the baseline single-stage game. Although theoretically doing so induces truth-telling behavior for both players, the experimental data provide very limited support. In the second study, the baseline game is extended by incorporating an additional, costless period of bargaining, thereby giving players an increased opportunity to reveal information about their respective reservation values. The data show that subjects quickly learn not to reveal information about their private valuation despite the increased opportunity to bilaterally improve efficiency. Finally, the third study investigates behavior sensitivity to variation in the trading parameter, k. Instead of following the historical precedent of setting k = ½, extreme values of k are invoked in an asymmetric information environment endowing a player with exclusive price-setting power. Although theoretical analysis suggests that expected profits for a seller (buyer) decreases (increases) in k, experimental results show that under conditions of dramatic information asymmetry, the observed share of the surplus is much smaller for the player with price setting power if countered with an information disadvantage resulting in poor support of the LES. Furthermore, the price setting power effectively counters the information disparity advantage demonstrated in previous studies. Results from a previously proposed reinforcement-based adaptive learning model not only demonstrate robust applicability across studies but also the model's ability to account remarkably well for the dynamics of play across iterations of the stage game.

This dissertation investigates the conditions that shape the governance structure of contractual agreements and how different contract types address the potential problems that can arise in R&D partnerships under technological uncertainty. The motivation for this study arises from the emergence of new forms of R&D organization to cope with challenges as well as opportunities created by rapid technological change. This dissertation demonstrates the significance of technological uncertainty in determining the observed variety of contractual arrangements in the biotechnology industry. It also shows that the returns from collaborative arrangements as measured by the number of successful patents differ among various contract types. The first part of this research focuses on biotechnology alliances with pharmaceutical companies involving drug discovery research. It demonstrates how advances in technology affect the structure of R&D contracts. Using contractual data over time, it is shown that newer technologies associated with higher uncertainty result in the choice of more equity participation by the pharmaceutical partner and more hierarchical contractual arrangements. This result supports the transaction cost arguments that as contractual difficulties arise, allying firms are more likely to choose a more hierarchical governance form over simpler arrangements. The second part of the dissertation investigates the significance of external R&D investments by large pharmaceutical companies to their overall innovation process. The performance of collaborations on the overall R&D productivity are evaluated in terms of their impact on successful patent production. This study measures the innovative returns to R&D collaborations separate from in-house R&D resources and possible knowledge spillovers. Using a panel data set of large pharmaceutical companies, a knowledge production function is estimated. The results indicate that the implied long-run elasticity of successful patent output with respect to all active R&D alliances is lower than the elasticity estimate with respect to in-house R&D investments. In addition, marginal returns to R&D collaborations differ among various contractual types, in terms of their contribution to patent production process. It is also shown that knowledge spillovers by competitors contribute to patent production, but scientific publications hinder it.

The main objective of the project is to quantify, in the Italian context, some relationships among technology, energy and the economy, which can be used in an existing modeling framework to simulate the impact of atmospheric pollution control policies on the economic system. The framework consists of an Input-Output model with variable coefficients (the PFE model), and a Linear Programming model (MARKAL-Italy), linked by a two-way feedback. The specific object of this project is to expand the energy section of the I/O model to include inter-energy substitution elasticities. For this purpose, econometric models of translog input-demand equations are estimated for thirteen final energy consumption sectors and five energy commodity groups. As a necessary step, a data-base on energy consumption and prices for the various sectors covering the period 1966-1992 is created. A trend decomposition analysis, separating energy consumption in a growth component, an activity mix component and a technological change component, is performed on these data to obtain some insight on the evolution of final energy use. A better understanding of these processes is obtained through a review of energy and environmental policies in Italy over the period considered. Both the quantitative and the descriptive analyses stress the role of fiscal policy on energy products, carried out by the Italian governments, in shaping energy consumption patterns. The effect of including the estimated elasticities in the existing modeling framework is then tested in an experiment in which the technological and economic response of the energy system to changes in CO2 emissions standards is simulated via the LP model MARKAL, and the resulting changes in energy prices are used as inputs into the expanded I/O model. The latter, in turn, measures the impacts of each environmental tax policy scenario on total output, value added, final demand, imports, exports and prices. The results of this experiment, which assumes an explicit tax redistribution scheme, help define the feasibility margin for policy action on CO2 emission standards in the Italian context, indicating the structural changes that would take place as control policies tighten.

This dissertation attempts to advance our understanding of price dynamics by investigating how prices adjust following a change in demand. Previous work has the common feature of an equilibrium that supports collusion among firms. A new explanation based upon the private incentives of unilateral market power is offered for sluggish or countercyclical price adjustment. After discussing the theoretical and empirical literature on the cyclical nature of prices and price-cost margins in chapter one, the next three chapters develop and test the market power model. The second chapter examines the short-run version of the model. The market power of firms changes with the business cycle, and this affects the cyclical pricing behavior of firms. Following a decrease in demand in the short-run, capacity-constrained firms all choosing a market clearing price as a best response may have a strong incentive not to lower their prices to the new competitive price. Experimental markets with complete information convincingly support the conjecture that unilateral market power is a source of countercyclical markups. This short-run market power model of cyclical pricing is then extended in chapter three to a long-run framework. In the long-run version of the market power model, duopolists simultaneously choose capacity with an uncertain demand in the first stage. Once capacity is chosen, the demand is revealed to the firms and they compete in prices. The fourth chapter tests the unique implications of the market power model with a time series field study. The market power model predicts that real price changes are drawn from a distribution with a high variance when output concurrently is in a contractionary state, but from a low variance when output is in an expansionary state. The evidence is consistent with the unique prediction of the market power model. Chapter five explores other explanations for sluggish price adjustment which have received considerable theoretical attention in macroeconomics, but which have been subjected to limited direct testing. This chapter uses experimental economies to test how menu costs and their interactions with potentially rigid factor costs affect product price adjustment.

The primary objectives of this research were to (1) estimate survival functions and the natural history of patients infected with human immunodeficiency virus who are using antiretroviral medication with a protease inhibitor and those who are under treatment protocols without protease inhibitors, and (2) estimate average lifetime treatment costs of infected patients for both drug regimens. A secondary objective was to provide a step by step discussion of the applicability of a Markov process in modeling survival and cost profiles of acquired immunodeficiency syndrome, a complex set of diseases, to managed care organizations. Data used in this study were collected using two techniques: expert physician panel interviews and a literature search. The transition rates for patients moving from one disease state to another were obtained from both sources. Cost estimates were calculated predominantly from published literature. The fundamental matrix solution of a Markov chain model was used to estimate survival functions, natural history profiles, and lifetime costs of therapy for HIV-infected patients. The research was conducted from the perspective of a managed health care organization. Results indicated that protease inhibitors significantly improved overall survival of infected patients by deterring the progression of disease and onset of various opportunistic infections. Lifetime costs of treatment, however, were substantially higher for treatment protocols using protease inhibitors as one of the components of recommended combination retroviral therapy. Estimates obtained from this study also indicated that unless significant reductions in high resource intensive events such as hospitalization can be achieved, protease inhibitors might not be cost efficient in treating HIV-infected patients. Lastly, this research showed that Markov modeling techniques can offer valuable benchmarks for both clinical and economic decision making in planning disease intervention to improve health outcomes and evaluate costs.

The purpose of this dissertation is to examine potential solutions to the problem of groundwater contamination between Arizona and Sonora, Mexico. The focus of the study is the binational Santa Cruz River, and other groundwater resources, shared by the two countries. The Santa Cruz River runs through the shared farming and cattle-raising areas to the south and east of Nogales, Sonora and Nogales, Arizona (Ambos Nogales). In addressing the potential problem of contamination in this border area, two approaches are applied to address this potential problem. First, an economic model, the Kathleen Segerson model, which was developed to assess the liability of farmers and agricultural chemical manufacturers in the United States, was expanded to include Mexico and to examine cross-border agricultural contamination. Secondly, a binational groundwater management model, the Bellagio Draft Treaty, was applied to the region of Ambos Nogales to see how it might work in addressing both cross-border agricultural contamination on the Santa Cruz River, as well as industrial and bacterial contamination in the Nogales Wash. Segerson showed that an economically efficient solution could be achieved by holding agricultural chemical manufacturers liable for groundwater contamination. However, the legal difficulties associated with establishing manufacturer liability are numerous and substantial. In addition, holding farmers to best management practices in Mexico is doubtful based on Mexico's ineffective environmental regulatory system. Because of these difficulties, the conditions established by Segerson for the model to work cannot be met. A more effective solution lies in the Bellagio Draft Treaty. The Bellagio Draft Treaty was determined to be a potentially effective way to solve a spectrum of border water issues for the Ambos Nogales area. Some of the problems that could be addressed under the Draft Treaty include: water contamination, equitable division of shared water, health emergencies, and drought planning and response. While this dissertation determines that the Bellagio Draft Treaty could be applicable to the water related problems of Ambos Nogales, the author states that much work will be needed to actually expand the powers of a potential management agency, such as the International Boundary and Water Commission (IBWC).

Advances in information technology (IT) have enabled the design and development of innovations in software and computer-assisted business methods. Firms attempt to leverage these innovations to gain competitive advantages through cost reduction, or quality improvements, and often pass some benefits to consumers. However such competitive advantages are increasingly difficult to sustain because IT-enabled innovations are becoming easier to copy or imitate. Competitors can use reverse engineering or decryption techniques to discover how an innovation operates, modify the original and distribute the amended innovation as a new product. Unfortunately, the ability of competing firms to imitate quickly and cheaply may reduce the incentives for firms to incur the cost to innovate. Much literature discusses ways government may induce firms to innovate and thus increase current and future social welfare. One tool available to government to provide such incentives is patent protection, i.e. providing an exclusive right of the innovations to the innovator. One goal of patent policy is to maximize social welfare by providing incentives to innovate while simultaneously maintaining a competitive market. Policymakers disagree over how to balance these two often-conflicting goals. Much of the disagreement is based on what factors the government may control to provide protection for innovating firms and the socially optimal level of patent protection. Determining optimal protection policy is a non-trivial task. The complexity arises from stakeholders who may have contradictory objectives and a menu or mix of options. Of course it is difficult to reach the first-best solution because the social planner does not have full access to information about firms and consumers. This dissertation reviews economic theories of patent protection, address problems and issues related to the progress of ITs, and investigate how a specific set of patent policy affect the incentives for firm to develop technological innovations and the way developed innovations are adopted and diffused throughout the marketplace. This work builds on, and contributes to, literatures in the areas of information systems, economics, public policy and law and provides valuable insights for regulators responsible for designing and evaluating patent systems and for firms competing strategically under these systems.

<p> In an industry characterized by oligopolistic market structures there are generally firms that have enough market power as to influence the pricing and output decisions of all participants, forcing others to follow the strategies decided by the dominant firm(s) with very little opportunity to do otherwise (Besanko et al 2010, Tirole 1990). When a dominant firm is at the same time part of a larger corporation, and due to the financial support it is likely to have from its parent, it has the capacity to support an above-average, constant long-term investment strategy as a logical reaction to protect (or minimize) the loss of market share, and the rest of the participants in the industry are expected to also make an attempt to increase their investments, permanently affecting their long-term capital structure strategy (Chevalier 1995). This dissertation&rsquo;s contribution to the literature in the field consists on presenting an empirical analysis of the capital structure decisions of the non-dominant firms in the Self-Service Discount Stores Industry (SSDSI) that result from the rapid expansion of Wal-Mart in the Mexican market, as well as an empirical analysis of the investment decisions in radiofrequencies of the incumbents firms in the capital structure of the other firms in the Mobile sector in Mexico.</p><p> Keywords (Industrial organization, Economics of Strategy, market structure, oligopolistic competition, capital structure, conditioned investment, market concentration, supermarket sector, spectrum auctions). </p>