Asset pricing in created markets

We investigate the applicability of the present-value asset pricing model to fishing quota markets by applying instrumental variable panel data estimation techniques to 15 years of market transactions from New Zealand's individual transferable quota (ITQ) market. In addition to the influence of current fishing rents, we explore the effect of market interest rates, risk, and expected changes in future rents on quota asset prices. The results indicate that quota asset prices are positively related to declines in interest rates, lower levels of risk, expected increases in future fish prices, and expected cost reductions from rationalization under the quota system. © 2007 American Agricultural Economics Association.

Bidding For Parking: The Impact of University Affiliation on Predicting Bid Values in Dutch Auctions of On-Campus Parking Permits

Parking is often underpriced and expanding its capacity is expensive; universities need a better way of reducing congestion outside of building costly parking garages. Demand based pricing mechanisms, such as auctions, offer a possible solution to the problem by promising to reduce parking at peak times. However, faculty, students, and staff at universities have systematically different parking needs, leading to different parking valuations. In this study, I determine the impact university affiliation has on predicting bid values cast in three Dutch Auctions of on-campus parking permits sold at Chapman University in Fall 2010. Using clustering techniques crosschecked with university demographic information to detect affiliation groups, I ran a log-linear regression, finding that university affiliation had a larger effect on bid amount than on lot location and fraction of auction duration. Generally, faculty were predicted to have higher bids whereas students were predicted to have lower bids.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Long-term equity anticipation securities and stock market volatility dynamics

Recent empirical findings suggest that the long-run dependence in U.S. stock market volatility is best described by a slowly mean-reverting fractionally integrated process. The present study complements this existing time-series-based evidence by comparing the risk-neutralized option pricing distributions from various ARCH-type formulations. Utilizing a panel data set consisting of newly created exchange traded long-term equity anticipation securities, or leaps, on the Standard and Poor's 500 stock market index with maturity times ranging up to three years, we find that the degree of mean reversion in the volatility process implicit in these prices is best described by a Fractionally Integrated EGARCH (FIEGARCH) model. © 1999 Elsevier Science S.A. All rights reserved.

A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets

Assuming that daily spot exchange rates follow a martingale process, we derive the implied time series process for the vector of 30-day forward rate forecast errors from using weekly data. The conditional second moment matrix of this vector is modelled as a multivariate generalized ARCH process. The estimated model is used to test the hypothesis that the risk premium is a linear function of the conditional variances and covariances as suggested by the standard asset pricing theory literature. Little supportt is found for this theory; instead lagged changes in the forward rate appear to be correlated with the 'risk premium.'. © 1990.

Agglomeration effects in foreign direct investment and the pollution haven hypothesis

Does environmental regulation impair international competitiveness of pollution-intensive industries to the extent that they relocate to countries with less stringent regulation, turning those countries into "pollution havens"? We test this hypothesis using panel data on outward foreign direct investment (FDI) flows of various industries in the German manufacturing sector and account for several econometric issues that have been ignored in previous studies. Most importantly, we demonstrate that externalities associated with FDI agglomeration can bias estimates away from finding a pollution haven effect if omitted from the analysis. We include the stock of inward FDI as a proxy for agglomeration and employ a GMM estimator to control for endogenous time-varying determinants of FDI flows. Furthermore, we propose a difference estimator based on the least polluting industry to break the possible correlation between environmental regulatory stringency and unobservable attributes of FDI recipients in the cross-section. When accounting for these issues we find robust evidence of a pollution haven effect for the chemical industry. © 2008 Springer Science+Business Media B.V.

Latent Stick-Breaking Processes.

We develop a model for stochastic processes with random marginal distributions. Our model relies on a stick-breaking construction for the marginal distribution of the process, and introduces dependence across locations by using a latent Gaussian copula model as the mechanism for selecting the atoms. The resulting latent stick-breaking process (LaSBP) induces a random partition of the index space, with points closer in space having a higher probability of being in the same cluster. We develop an efficient and straightforward Markov chain Monte Carlo (MCMC) algorithm for computation and discuss applications in financial econometrics and ecology. This article has supplementary material online.

Quantifiable biomarkers of normal aging in the Japanese medaka fish (Oryzias latipes).

BACKGROUND: Small laboratory fish share many anatomical and histological characteristics with other vertebrates, yet can be maintained in large numbers at low cost for lifetime studies. Here we characterize biomarkers associated with normal aging in the Japanese medaka (Oryzias latipes), a species that has been widely used in toxicology studies and has potential utility as a model organism for experimental aging research. PRINCIPAL FINDINGS: The median lifespan of medaka was approximately 22 months under laboratory conditions. We performed quantitative histological analysis of tissues from age-grouped individuals representing young adults (6 months old), mature adults (16 months old), and adults that had survived beyond the median lifespan (24 months). Livers of 24-month old individuals showed extensive morphologic changes, including spongiosis hepatis, steatosis, ballooning degeneration, inflammation, and nuclear pyknosis. There were also phagolysosomes, vacuoles, and residual bodies in parenchymal cells and congestion of sinusoidal vessels. Livers of aged individuals were characterized by increases in lipofuscin deposits and in the number of TUNEL-positive apoptotic cells. Some of these degenerative characteristics were seen, to a lesser extent, in the livers of 16-month old individuals, but not in 6-month old individuals. The basal layer of the dermis showed an age-dependent decline in the number of dividing cells and an increase in senescence-associated β-galactosidase. The hearts of aged individuals were characterized by fibrosis and lipofuscin deposition. There was also a loss of pigmented cells from the retinal epithelium. By contrast, age-associated changes were not apparent in skeletal muscle, the ocular lens, or the brain. SIGNIFICANCE: The results provide a set of markers that can be used to trace the process of normal tissue aging in medaka and to evaluate the effect of environmental stressors.

Designing Climate Mitigation Policy

This paper provides an exhaustive review of critical issues in the design of climate mitigation policy by pulling together key findings and controversies from diverse literatures on mitigation costs, damage valuation, policy instrument choice, technological innovation, and international climate policy. We begin with the broadest issue of how high assessments suggest the near and medium term price on greenhouse gases would need to be, both under cost-effective stabilization of global climate and under net benefit maximization or Pigouvian emissions pricing. The remainder of the paper focuses on the appropriate scope of regulation, issues in policy instrument choice, complementary technology policy, and international policy architectures.

The dynamic efficiency costs of common-pool resource exploitation

We conduct the first empirical investigation of common-pool resource users' dynamic and strategic behavior at the micro level using real-world data. Fishermen's strategies in a fully dynamic game account for latent resource dynamics and other players' actions, revealing the profit structure of the fishery. We compare the fishermen's actual and socially optimal exploitation paths under a time-specific vessel allocation policy and find a sizable dynamic externality. Individual fishermen respond to other users by exerting effort above the optimal level early in the season. Congestion is costly instantaneously but is beneficial in the long run because it partially offsets dynamic inefficiencies.