Three Essays on Experimental and Microeconomics

This dissertation contains three chapters on experimental economics and microeconomics. In the first chapter, Dynamic Investment and Preferences over the Resolution of Risk, I report the results of a laboratory experiment which attempts to explain the finding that individuals invest less in risky assets when risk is gradually resolved over time, rather than all at once. Though the literature has traditionally attributed this behavior to a cognitive error, Koszegi and Rabin (2009) recently characterized this finding as the result of non-standard preferences over the resolution of risk. My results reject the traditional "cognitive errors" explanation in favor of Koszegi and Rabin's "non-standard preferences" explanation. In the second chapter, Kidney Co-operative: A Mechanism to Improve on Human Kidney Markets, myself and coauthors propose a mechanism called the kidney co-operative which is designed to provide sufficient incentives to alleviate the human kidney shortage, while at the same time addressing the concerns regarding the potential losers to such a reform. We show that it is reasonable to expect that the number of transplants will be larger under the kidney co-operative mechanism than under either the status quo or the conventional market mechanism. In the third chapter, Charity in the Laboratory:Matching, Competition, and Group Identity, myself and a coauthor study the effects of donation matching, competition, and group membership on charitable donations using a laboratory experiment. We find that providing matching donations to all subjects orhaving individuals compete for the privilege to have their donations matched (we match the top half of donations in each session), raises donation levels modestly. However, arbitrarily assigning subjects to teams which competed for matching funds substantially raised donation levels. We appeal to the notions of group identity and team dynamics to explain our results

Modulation of Y356 Photooxidation in E. coli Class Ia Ribonucleotide Reductase by Y731 Across the α2:β2 Interface

Substrate turnover in class Ia ribonucleotide reductase (RNR) requires reversible radical transport across two subunits over 35 A, which occurs by a multi-step proton-coupled electron transfer mechanism. Using a photooxidant-labeled β2 subunit of Escherichia coli class Ia RNR, we demonstrate photoinitiated oxidation of a tyrosine in an α2:β2 complex, which results in substrate turnover. Using site-directed mutations of the redox-active tyrosines at the subunit interface—Y356F(β) and Y731F(α)—this oxidation is identified to be localized on Y356. The rate of Y356 oxidation depends on the presence of Y731 across the interface. This observation supports the proposal that unidirectional PCET across the Y356(β)–Y731(α)–Y730(α) triad is crucial to radical transport in RNR.Chemistry and Chemical Biolog

Reionization: Characteristic Scales, Topology and Observability

Recently the numerical simulations of the process of reionization of the universe at z>6 have made a qualitative leap forward, reaching sufficient sizes and dynamic range to determine the characteristic scales of this process. This allowed making the first realistic predictions for a variety of observational signatures. We discuss recent results from large-scale radiative transfer and structure formation simulations on the observability of high-redshift Ly-alpha sources. We also briefly discuss the dependence of the characteristic scales and topology of the ionized and neutral patches on the reionization parameters.Comment: 4 pages, 5 figures (4 in color), to appear in Astronomy and Space Science special issue "Space Astronomy: The UV window to the Universe", proceedings of 1st NUVA Conference ``Space Astronomy: The UV window to the Universe'' in El Escorial (Spain

Constraining Intra-cluster Gas Models with AMiBA13

Clusters of galaxies have been used extensively to determine cosmological parameters. A major difficulty in making best use of Sunyaev-Zel'dovich (SZ) and X-ray observations of clusters for cosmology is that using X-ray observations it is difficult to measure the temperature distribution and therefore determine the density distribution in individual clusters of galaxies out to the virial radius. Observations with the new generation of SZ instruments are a promising alternative approach. We use clusters of galaxies drawn from high-resolution adaptive mesh refinement (AMR) cosmological simulations to study how well we should be able to constrain the large-scale distribution of the intra-cluster gas (ICG) in individual massive relaxed clusters using AMiBA in its configuration with 13 1.2-m diameter dishes (AMiBA13) along with X-ray observations. We show that non-isothermal beta models provide a good description of the ICG in our simulated relaxed clusters. We use simulated X-ray observations to estimate the quality of constraints on the distribution of gas density, and simulated SZ visibilities (AMiBA13 observations) for constraints on the large-scale temperature distribution of the ICG. We find that AMiBA13 visibilities should constrain the scale radius of the temperature distribution to about 50% accuracy. We conclude that the upgraded AMiBA, AMiBA13, should be a powerful instrument to constrain the large-scale distribution of the ICG.Comment: Accepted for publication in The Astrophysical Journal, 12 pages, 9 figure

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

The pattern of retinal ganglion cell dysfunction in Leber hereditary optic neuropathy

Leber inherited optic neuropathy (LHON) is characterized by subacute bilateral loss of central vision due to dysfunction and loss of retinal ganglion cells (RGCs). Comprehensive visual electrophysiological investigations (including pattern reversal visual evoked potentials, pattern electroretinography and the photopic negative response) performed on 13 patients with acute and chronic LHON indicate early impairment of RGC cell body function and severe axonal dysfunction. Temporal, spatial and chromatic psychophysical tests performed on 7 patients with acute LHON and 4 patients with chronic LHON suggest severe involvement or loss of the midget, parasol and bistratified RGCs associated with all three principal visual pathways

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Quantitative localized proton-promoted dissolution kinetics of calcite using scanning electrochemical microscopy (SECM)

Scanning electrochemical microscopy (SECM) has been used to determine quantitatively the kinetics of proton-promoted dissolution of the calcite (101̅4) cleavage surface (from natural “Iceland Spar”) at the microscopic scale. By working under conditions where the probe size is much less than the characteristic dislocation spacing (as revealed from etching), it has been possible to measure kinetics mainly in regions of the surface which are free from dislocations, for the first time. To clearly reveal the locations of measurements, studies focused on cleaved “mirror” surfaces, where one of the two faces produced by cleavage was etched freely to reveal defects intersecting the surface, while the other (mirror) face was etched locally (and quantitatively) using SECM to generate high proton fluxes with a 25 μm diameter Pt disk ultramicroelectrode (UME) positioned at a defined (known) distance from a crystal surface. The etch pits formed at various etch times were measured using white light interferometry to ascertain pit dimensions. To determine quantitative dissolution kinetics, a moving boundary finite element model was formulated in which experimental time-dependent pit expansion data formed the input for simulations, from which solution and interfacial concentrations of key chemical species, and interfacial fluxes, could then be determined and visualized. This novel analysis allowed the rate constant for proton attack on calcite, and the order of the reaction with respect to the interfacial proton concentration, to be determined unambiguously. The process was found to be first order in terms of interfacial proton concentration with a rate constant k = 6.3 (± 1.3) × 10–4 m s–1. Significantly, this value is similar to previous macroscopic rate measurements of calcite dissolution which averaged over large areas and many dislocation sites, and where such sites provided a continuous source of steps for dissolution. Since the local measurements reported herein are mainly made in regions without dislocations, this study demonstrates that dislocations and steps that arise from such sites are not needed for fast proton-promoted calcite dissolution. Other sites, such as point defects, which are naturally abundant in calcite, are likely to be key reaction sites