cssi/SciSciGPT-SciSciNet huggingface dataset:
Lateral spin injection in germanium nanowires.

Electrical injection of spin-polarized electrons into a semiconductor, large spin diffusion length, and an integration friendly platform are desirable ingredients for spin-based devices. Here we demonstrate lateral spin injection and detection in germanium nanowires, by using ferromagnetic metal contacts and tunnel barriers for contact resistance engineering. Using data measured from over 80 samples, we map out the contact resistance window for which lateral spin transport is observed, manifestly showing the conductivity matching required for spin injection. Our analysis, based on the spin diffusion theory, indicates that the spin diffusion length is larger than 100 μm in germanium nanowires at 4.2 K.
Global seismology of the Sun

The seismic study of the Sun and other stars offers a unique window into the interior of these stars. Thanks to helioseismology, we know the structure of the Sun to admirable precision. In fact, our knowledge is good enough to use the Sun as a laboratory. We have also been able to study the dynamics of the Sun in great detail. Helioseismic data also allow us to probe the changes that take place in the Sun as solar activity waxes and wanes. The seismic study of stars other than the Sun is a fairly new endeavour, but we are making great strides in this field. In this review I discuss some of the techniques used in helioseismic analyses and the results obtained using those techniques. I focus on results obtained with global helioseismology, i.e., the study of the Sun using its normal modes of oscillation. I also briefly touch upon asteroseismology, the seismic study of stars other than the Sun, and discuss how seismic data of others stars are interpreted.
A Revised Exoplanet Yield from the Transiting Exoplanet Survey Satellite (TESS)

The Transiting Exoplanet Survey Satellite (TESS) has a goal of detecting small planets orbiting stars bright enough for mass determination via ground-based radial velocity observations. Here, we present estimates of how many exoplanets the TESS mission will detect, the physical properties of the detected planets, and the properties of the stars that those planets orbit. This work uses stars drawn from the TESS Input Catalog Candidate Target List and revises yields from prior studies that were based on Galactic models. We modeled the TESS observing strategy to select approximately 200,000 stars at 2-minute cadence, while the remaining stars are observed at 30-minute cadence in full-frame image data. We placed zero or more planets in orbit around each star, with physical properties following measured exoplanet occurrence rates, and used the TESS noise model to predict the derived properties of the detected exoplanets. In the TESS 2-minute cadence mode we estimate that TESS will find 1250 ± 70 exoplanets (90% confidence), including 250 smaller than 2 R(sub ⊕). Furthermore, we predict that an additional 3100 planets will be found in full-frame image data orbiting bright dwarf stars and more than 10,000 around fainter stars. We predict that TESS will find 500 planets orbiting M dwarfs, but the majority of planets will orbit stars larger than the Sun. Our simulated sample of planets contains hundreds of small planets amenable to radial velocity follow-up, potentially more than tripling the number of planets smaller than 4 R(sub ⊕) with mass measurements. This sample of simulated planets is available for use in planning follow-up observations and analyses.
Shifted dual equivalence and Schur $P$-positivity

By considering type B analogs of permutations and tableaux, we extend abstract dual equivalence to type B in two directions. In one direction, we define involutions on signed permutations and shifted tableaux that give a weak dual equivalence, thereby giving another proof of the Schur positivity of Schur Q- and P-functions. In another direction, we define an abstract shifted dual equivalence parallel to dual equivalence and prove that it can be used to establish Schur P-positivity of a function expressed as a sum of shifted fundamental quasisymmetric functions.
A Multiscale Coarse-grained Model of the SARS-CoV-2 Virion.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and ongoing development of a largely "bottom-up" coarse-grained (CG) model of the SARS-CoV-2 virion. Data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data become publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference.

This paper studies the fundamental problem of learning deep generative models that consist of multiple layers of latent variables organized in top-down architectures. Such models have high expressivity and allow for learning hierarchical representations. Learning such a generative model requires inferring the latent variables for each training example based on the posterior distribution of these latent variables. The inference typically requires Markov chain Monte Caro (MCMC) that can be time consuming. In this paper, we propose to use noise initialized non-persistent short run MCMC, such as finite step Langevin dynamics initialized from the prior distribution of the latent variables, as an approximate inference engine, where the step size of the Langevin dynamics is variationally optimized by minimizing the Kullback-Leibler divergence between the distribution produced by the short run MCMC and the posterior distribution. Our experiments show that the proposed method outperforms variational auto-encoder (VAE) in terms of reconstruction error and synthesis quality. The advantage of the proposed method is that it is simple and automatic without the need to design an inference model.
Non-normality and non-monotonic dynamics in complex reaction networks

The authors characterize the nonlinear dynamics of complex chemical reaction networks using a master equation approach and show that both normal and non-normal systems can exhibit non-monotonic dynamics while only non-normality can lead to non-monotonic R\'enyi entropy.
Notes on Matrix Factorizations and Knot Homology

These are the notes of the lectures delivered by the author at CIME in June 2018. The main purpose of the notes is to provide an overview of the techniques used in the construction of the triply graded link homology. The homology is the space of global sections of a particular sheaf on the Hilbert scheme of points on the plane. Our construction relies on existence on the natural push-forward functor for the equivariant matrix factorizations, we explain the subtleties on the construction in these notes. We also outline a proof of the Markov moves for our homology as well as some explicit localization formulas for knot homology of a large class of links.
Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors

Accurate and rapid evaluation of whether substrates can undergo the desired the transformation is crucial and challenging for both human knowledge and computer predictions. Despite the potential of machine learning in predicting chemical reactivity such as selectivity, popular feature engineering and learning methods are either time-consuming or data-hungry. We introduce a new method that combines machine-learned reaction representation with selected quantum mechanical descriptors to predict regio-selectivity in general substitution reactions. We construct a reactivity descriptor database based on ab initio calculations of 130k organic molecules, and train a multi-task constrained model to calculate demanded descriptors on-the-fly. The proposed platform enhances the inter/extra-polated performance for regio-selectivity predictions and enables learning from small datasets with just hundreds of examples. Furthermore, the proposed protocol is demonstrated to be generally applicable to a diverse range of chemical spaces. For three general types of substitution reactions (aromatic C–H functionalization, aromatic C–X substitution, and other substitution reactions) curated from a commercial database, the fusion model achieves 89.7%, 96.7%, and 97.2% top-1 accuracy in predicting the major outcome, respectively, each using 5000 training reactions. Using predicted descriptors, the fusion model is end-to-end, and requires approximately only 70 ms per reaction to predict the selectivity from reaction SMILES strings.
Dielectrophoretic separation of randomly shaped protein particles

Abstract Recently, insoluble protein particles have been increasingly investigated for artificial drug delivery systems due to their favorable properties, including programmability for active drug targeting of diseases as well as their biocompatibility and biodegradability after administration. One of the biggest challenges is selectively collecting desirable self-repairable particles in the spherical morphology with monodispersity to enable consistent levels and rates of drug loading and release. Therefore, technology that allows sorting of protein particles with respect to size and morphology will enhance the design and production of next-generation drug delivery materials. Here, we introduce a dielectrophoretic (DEP) separation technique to selectively isolate spherical protein particles from a mixture of randomly shaped particles. We tested this approach by applying it to a mixture of precipitated squid ring teeth inspired tandem repeat protein particles with diverse sizes and morphologies. The DEP trapping system enabled us to isolate specific-sized, spherical protein particles out of this mixture: after separation, the fraction of 2 µm and 4 µm spherical particles was increased from 28.64% of mixture to 80.53% and 74.02% with polydispersity indexes (PDIs) decreased from 0.93 of mixture to 0.19 and 0.09, respectively. The protein particles show high aqueous swelling capability (up to 74% by mass) that could enable delivery of drug solutions. This work is intended to inspire the future development of biocompatible drug-delivery systems.
One-sided version of Gale–Shapley proposal algorithm and its likely behavior under random preferences

Abstract For a two-sided ( n men/ n women) stable matching problem) Gale and Shapley studied a proposal algorithm (men propose/women select, or the other way around), that determines a matching, not blocked by any unmatched pair. Irving used this algorithm as a first phase of his algorithm for one-sided (stable roommates) matching problem with n agents. We analyze a fully extended version of Irving’s proposal algorithm that runs all the way until either each agent holds a proposal or an agent gets rejected by everybody on the agent’s preference list. It is shown that the terminal, directed, partnerships form a permutation satisfying a certain stability condition, similar to, but different from the one introduced by Jimmy Tan. A likely behavior of the proposal algorithm is studied under assumption that all n rankings are independently uniform. It is proved that with high probability (w.h.p.) every agent has a partner, and that both the number of agents in cycles of length ≥ 3 and the total number of stable matchings are bounded in probability. W.h.p. the total number of proposals is asymptotic to 0 . 5 n 3 ∕ 2 .
COVID-19 Social Distancing Measures and Loneliness Among Older Adults.

OBJECTIVES: In response to the COVID-19 pandemic, older adults are advised to follow social distancing measures to prevent infection. However, such measures may increase the risk of loneliness. The current study aimed to investigate (1) whether social distancing measures, particularly limiting close social interactions, are associated with loneliness among older adults, and (2) whether the association between social distancing measures and loneliness is moderated by sociodemographic characteristics. METHODS: Data were from the fourth wave (April 29 to May 26, 2020) of the nationally representative Understanding America Study COVID-19 Survey. We used data on adults 50 years or older (N = 3,253). Logistic regression models of loneliness were performed. Five indicators of social distancing measures were considered: (a) avoiding public spaces, gatherings, or crowds, (b) canceling or postponing social activities, (c) social visits, (d) no close contact (within 6 feet) with people living together, and (e) with people not living together. RESULTS: Cancelling or postponing social activities and avoiding close contact with people living together were associated with 33% (OR=1.33, CI=1.06-1.68, p < .05) and 47% (OR=1.47, CI=1.09-1.99, p < .05) greater odds of loneliness, respectively. Furthermore, limiting close contact with co-residents increased the probability of loneliness more for males, non-Hispanic Whites, those with higher levels of education and income. DISCUSSION: Efforts should be made to help older adults maintain social connectedness with close others by virtual communication methods. Our findings also call special attention to vulnerable groups at elevated risks of loneliness, emphasizing the need for tailored interventions.
Spatial Heterogeneity, Accessibility, and Zoning: An Empirical Investigation of Leapfrog Development

Using data on subdivision development from 1960 to 2005 in the Baltimore, Maryland region, we develop a new, subdivision-specific measure of leapfrog development. Applying this measure, we find that about 80% of developable land that was more accessible to the urban center than newly built subdivisions remained undeveloped as of 1960. This amount declined by more than 50% over our 45-year study period to 36% in 2005. We compare this pattern with a hypothesized pattern generated by a parameterized intertemporal urban growth model and find that the observed pattern is consistent with urban economic theory, including the implied effects of zoning. Specifically, by fixing the allowable development density, low-density zoning eliminates the incentive to withhold more accessible land and thus reduces leapfrog development, a prediction that we confirm empirically. The results illustrate the efficacy of the urban growth model and the substantial influence of spatially heterogeneous zoning on urban land development patterns.
Managing Underpricing? The Case of Pre‐IPO Discretionary Accruals in China

Previous studies have found that companies use income-increasing positive discretionary accruals (DAC) prior to initial public offerings (IPOs) to inflate earnings as a signal to anticipate future income and future dividends. This study, directly explores the role of DAC in prospectus information of 691 A-shares IPOs in China during the period 1995–2002 and its relationship with market-adjusted returns. The results suggest that in China, pre-IPO non-discretionary accruals (NDAC) as well as DAC have informative value in explaining first-day returns as well as first-year adjusted returns. However, in yearly cross-sectional models, I find that firms use income-decreasing accruals (conservative accounting) in prospectus financial statements. This downward manipulation or income “understatement” creates a regulatory setting that could explain initial underpricing and abnormally high IPO returns for A-shares. In addition, the results show that as state ownership (SO) increases, cash flow also increases, exacerbating agency costs and adverse selection problems. These findings may suggest that managers might be using more conservative accounting in Prospectus financial data to offset the agency costs related to high cash flow, and high SO, by “banking income” and possibly therefore “smoothing” the effects of possible future suboptimal earnings.
An Inside View: Professional Judges’ and Lay Judges’ Support for Mixed Tribunals

This paper studies the level of specific and general support for mixed tribunals, a form of lay participation in the government. The analyses focus on the opinions provided by 229 Croatian lay judges and eighty professional judges – the insiders in mixed tribunals. The results indicate that the judge's lay or professional role in the criminal justice system and the type of court exhibit stronger influence on the general level of support than any of the variables measuring specific support. Nevertheless, the perceived frequency of lay judges’ comments, the most direct measure of members’ crucial activity during trials and deliberations among the specific variables included in the models, is significantly related to the respondents’ general opinions about mixed tribunals.
Effective information channels for reducing costs of environmentally- friendly technologies: evidence from residential PV markets

Realizing the environmental benefits of solar photovoltaics (PV) will require reducing costs associated with perception, informational gaps and technological uncertainties. To identify opportunities to decrease costs associated with residential PV adoption, in this letter we use multivariate regression models to analyze a unique, household-level dataset of PV adopters in Texas (USA) to systematically quantify the effect of different information channels on aspiring PV adopters' decision-making. We find that the length of the decision period depends on the business model, such as whether the system was bought or leased, and on special opportunities to learn, such as the influence of other PV owners in the neighborhood. This influence accrues passively through merely witnessing PV systems in the neighborhood, increasing confidence and motivation, as well as actively through peer-to-peer communications. Using these insights we propose a new framework to provide public information on PV that could drastically reduce barriers to PV adoption, thereby accelerating its market penetration and environmental benefits. This framework could also serve as a model for other distributed generation technologies.
Understanding Lockups: Effects in Bankruptcy and the Market for Corporate Control

The article investigates the effects of lockups, devices used to compensate unsuccessful bidders. Lockups are relevant in contexts in which sales have auction-like characteristics. Bankruptcy and the market for corporate control are two such situations, since the governing legal regimes prevent sales from being swiftly consummated and require sellers to take the most favorable offer that emerges during the waiting period. Existing scholarship has considered lockups in both areas. The analysis of lockups in the market for corporate control is fairly well developed. This article shows that it is importantly incomplete because it fails both to distinguish between ex ante and ex post analysis of lockups and to apply the auction theory developed by economists. The bankruptcy scholarship lags behind the analysis of mergers and acquisitions and is even less satisfactory. After developing the correct picture of lockups in mergers and acquisitions, the article applies it to the bankruptcy context, showing how differences in the appropriate goals require different standards for courts reviewing lockups.
The Political Economy of Data Protection

Information is the lifeblood of a knowledge-based economy. The control of data and the ability to translate them into meaningful information is indispensable to businesspeople, policymakers, scientists, engineers, researchers, students, and consumers. Having useful, and at times exclusive, information improves productivity, advances education and training, and helps create a more informed citizenry. In the past two decades, those who collected or obtained access to a large amount of data began to explore ways to use the collected data as an income stream. Because the then-existing laws did not offer adequate protection for that particular purpose, they actively lobbied for stronger protection of their data assets. As part of the Data Devolution: Corporate Information Security, Consumers and the Future of Regulation Symposium, this essay recounts the development of two new forms of data protection: sui generis database protection and data exclusivity. It also discusses the concerns raised by the undemocratic processes used to develop such protection. It explains why policy laundering and backdoor lawmaking are harmful to both the United States and the larger international community. The essay then offers suggestions on how to recalibrate the balance of the intellectual property system. It concludes with a plea for caution concerning the development of new intellectual property rights to protect data, drawing on the European Commission's recent evaluation of the EC Database Directive.
Resource Allocation within Firms and Financial Market Dislocation: Evidence from Diversified Conglomerates

We argue and demonstrate that resource allocation within firms' internal capital markets provides an important force countervailing financial market dislocation. We estimate a structural model of internal capital markets to separately identify and quantify the forces driving the reallocation decision and illustrate how these forces interact with external capital market stress. The weaker (stronger) division obtains too much (little) capital, as though it is 12% (9%) more (less) productive than it really is. Out-of-sample simulated data are consistent with the actual data showing that internal capital markets offset financial market stress during the recent financial crisis by 16%–30%.
Knowledge, Moral Claims and the Exercise of Power in Global Health

A number of individuals and organizations have considerable influence over the selection of global health priorities and strategies. For some that influence derives from control over financial resources. For others it comes from expertise and claims to moral authority—what can be termed, respectively, epistemic and normative power. In contrast to financial power, we commonly take for granted that epistemic and normative forms of power are legitimate. I argue that we should not; rather we should investigate the origins of these forms of power, and consider under what circumstances they are justly derived.
Real exchange rate misalignment: Prelude to crisis?

Abstract A model of the long-run equilibrium real exchange rate based upon macroeconomic fundamentals is employed to calculate real exchange rate misalignments for Poland and Russia during the 1990s using the Beveridge and Nelson (Beveridge, S., Nelson, C., 1981. A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the business cycle. J. Monetary Econ. 7, 151–74) decomposition of macrofundamentals into transitory and permanent components. Short-run movements of the real exchange rate are estimated with ARIMA and GARCH error correction specifications. The different nominal exchange rate regimes of the two countries generate different levels of misalignment and different responses to exogenous shocks. The average misalignment in Russia is substantially greater than that in Poland, indicating incipient pressures to devalue the ruble immediately preceding the August 1998 crisis. The half-life of an exogenous shock is found to be much shorter for Poland than for Russia in the pre-crisis period. Dynamic forecasts indicate that the movements of the real exchange rate in the post-crisis period are significantly different from those in the pre-crisis period. Thus, the currency crisis in Russia could not be anticipated with the movements of the real exchange rate estimated with the macroeconomic fundamentals.
Learning and Wage Dynamics

We develop a dynamic model of learning about worker ability in a competitive labor market. The model produces three testable implications regarding wage dynamics: (1) although the role of schooling in the labor market's inference process declines as performance observations accumulate, the estimated effect of schooling on the level of wages is independent of labor-market experience; (2) timeinvariant variables correlated with ability but unobserved by employers ( such as certain test scores) are increasingly correlated with wages as experience increases; and (3) wage residuals are a martingale. We present evidence from the NLSY that is broadly consistent with the model's predictions.
U.S. exchange upgrades: Reducing uncertainty through a two-stage IPO

Abstract We examine the effects on IPO uncertainty of an alternative going-public mechanism – the two-stage IPO, where a firm first gets quoted on the OTC market, and then upgrades to a national exchange where it first issues public equity. We find that a two-stage IPO firm experiences lower underpricing and return volatility than does a similar traditional IPO firm. Our study is the first to analyze the impact of U.S. pre-IPO disclosure and liquidity on levels of uncertainty and pricing at the IPO stage. We find that greater disclosure and liquidity during the first stage leads to greater reduction in IPO uncertainty. We control for the potentially endogenous nature of the two-stage IPOs by using a difference-in-difference analysis that utilizes two exogenous OTC market events.
Portfolio analysis of asset and liability management in small-, medium- and large-sized banks

Abstract The paper presents an analysis of the commercial banking firm based on Markowitz portfolio analysis. A bank is treated as a portfolio of five banking assets and three banking liabilities. The average rate of return and risk of each asset and liability is estimated empirically for groups of banks categorized by size — small, medium and large. Banks' rates return on equity are defined as the weighted average of the assets' rates of return less the liabilities' rates of return. Quadratic programming is used to delineate the set of banking portfolios which have the maximum rate of return on equity at each level of risk.
On Existence and Uniqueness of Equilibrium in a Class of Noisy Rational Expectations Models

I study a general class of noisy rational expectations models that nests the standard Grossman and Stiglitz (1980) and Hellwig (1980) models, but relaxes the usual assumption of joint normality of asset pay-offs and supply, and allows for more general signal structures. I provide a constructive proof of existence of equilibrium, characterize the price function, and provide sufficient conditions for uniqueness within the class of equilibria with continuous price functions, which are met by both the Grossman and Stiglitz (1980) models and the Hellwig (1980) models with a continuum of investors. My solution approach does not rely on the typical “conjecture and verify” method, and I exhibit a number of non-normal examples in which asset prices can be characterized explicitly and in a closed form. The results presented here open up a broad class of models for applied work. To illustrate the usefulness of generalizing the standard model, I show that in settings with non-normally distributed pay-offs, shocks to fundamentals may be amplified purely due to learning effects, price drifts can arise naturally, and the disagreement–return relation depends in a novel way on return skewness.
E‐commerce strategies your shareholders will love

In the "new economy" many firms are searching for ways to participate in the explosion of e-commerce. In part, firms must consider whether or not to develop their e-commerce business internally or externally. If internally, then firms must consider how to best structure their organizations to not only accommodate the new business operations, but to also address stockholder concerns. Recent developments show that firms choose different methods in pursuing e-commerce and thus choose different forms of structuring their e-commerce ventures. What issues firms should consider when trying to achieve one particularly important organization goal, that of maximizing shareholder wealth, are discussed and suggestions are offered for decision makers to consider when addressing how to best structure the firm in light of this particular strategic goal.
Measuring Value Relevance in a (Possibly) Inefficient Market

An interesting question in assessing value relevance of accounting variables is whether measures of value relevance are materially affected by market inefficiencies. We explore this question in two steps: First, we analytically examine the impact of market inefficiencies on the estimation of coefficients in value relevance regressions and derive a procedure that corrects potential biases caused by such inefficiencies. The procedure adjusts contemporaneous stock prices for future risk adjusted price changes, and yields value relevance coefficient estimates that capture both contemporaneous and delayed market reactions. Second, we apply this procedure to three types of studies that have attracted much attention in the accounting literature: 1) the value relevance of earnings and book values; 2) the value relevance of residual income value estimates; and 3) the value relevance of accruals and cash flows. We compare coefficient estimates obtained from conventional value relevance regressions with those from regressions employing our adjustment procedure, and find statistically significant differences in both level and return regression coefficient estimates. The magnitude of differences in coefficient estimates for return regressions is large enough to affect economic inferences. We find that coefficients of lagged price deflated residual income value estimates move significantly closer toward a predicted value of one implying a meaningful reduction of bias. Last, we find that cash flows now have significantly larger coefficient estimates than accruals consistent with their greater persistence.
Is it possible to redistribute the gains from trade using income taxation

Abstract How does international trade affect income redistribution? We consider a country where the government uses a non-linear income tax to maximize some redistributive social welfare function, subject to the constraint that it can observe only individual incomes but not individual characteristics. In autarky, the government can partially equalize equilibrium prices and wages by manipulating quantities through the tax system. If borders are open, prices are determined by world markets and the government is deprived of this possibility. It may therefore be unable to redistribute the gains from trade: opening borders may decrease welfare even after the optimal policy adjustment.
The Pooling and Tranching of Securities: A Model of Informed Intermediation

I show that when an issuer has superior information about the value of its assets, it is better off selling assets separately rather than as a pool due to the information destruction effect of pooling. If, however, the issuer can create a derivative security that is collateralized by the assets, pooling and "tranching" may be optimal. If the residual risk of each asset is not highly correlated, tranching allows the issuer to exploit the risk diversification effect of pooling to create a low-risk and highly liquid security. In contrast, for an uninformed seller, pure pooling reduces underpricing and is preferred to separate asset sales. These results lead to a dynamic model of financial intermediation: originators sell pools of assets, some of which are purchased by informed intermediaries who then further pool and tranche them. Pooling and tranching allow intermediaries to leverage their capital more efficiently, enhancing the returns to their private information. Copyright 2005, Oxford University Press.
The Commerciality Doctrine as Applied to the Charitable Tax Exemption for Homes for the Aged: State and Local Perspectives

Justice Thomas Dickerson said that a Rye retirement community known as The Osborn did not deserve the property tax exemption it once had because it now caters mainly to “healthy and wealthy” senior citizens. At one time, The Osborn had cared for indigent women and was tax-exempt because it was a charity. But changes in its mission compromised that status, and the judge ruled it no longer qualified because it had gone from a nursing home to a continuing care retirement community catering to the needs of healthy and wealthy seniors.1
EFFECTS OF SELF-ESTEEM ON LENIENCY BIAS IN SELF-REPORTS OF PERFORMANCE: A STRUCTURAL EQUATION MODEL ANALYSIS

This study used structural equation model analysis to examine the relationship between self-esteem and leniency bias in self-reports of performance. The results showed that consistent with the prediction of consistency theory (e.g., Korman, 1970), leniency bias was positively correlated with self-esteem. The results also suggest that the relationship between self-esteem and leniency bias was more positive when self-ratings were made on ambiguous performance dimensions rather than on less ambiguous dimensions. Implications for future research and practice are discussed.
The Model State Emergency Health Powers Act: public health and civil liberties in a time of terrorism.

The balance between individual interests and common goods needs to be recalibrated in an age of terrorism. Public health agencies should have a robust infrastructure to conduct essential public health services at a level of performance that matches evolving threats to the health. This includes a well-trained workforce, electronic information, surveillance, and laboratory capacity. Public health preparedness also requires a sound legal infrastructure. This article presents and defends the provisions of the Model Emergency Health Powers Act (MSEHPA). The Center for Law and the Public's Health at the request of the U.S. Centers for Disease Control and Prevention (CDC) and in collaboration with governors, legislators, attorneys general, and public health officials wrote the MSEHPA. First, this article explains the provisions of MSEHPA. The MSEHPA has been adopted in whole or part in 20 states and the District of Columbia. Second, this article shows why extant public health laws provide a weak foundation for public health practice. They are obsolete, inconsistent, and inadequate from a public health and civil liberties perspective. State legislation does not facilitate, and may even impede, all of the critical variables for public health preparedness. Finally, the article offers a systematic defense of MSEHPA. The Model Act has galvanized the public debate around the appropriate balance between public goods and individual rights. This defense shows how the Model Act creates strong public health powers, while safeguarding individual freedoms (adopting clearer standards and more rigorous procedures than existing statutes). In a country too tied to rights rhetoric, any law reform initiative that has the appearance of strengthening governmental authority is bound to travel in tumultuous political waters.
Proxies and Databases in Financial Misconduct Research

ABSTRACT: An extensive literature examines the causes and effects of financial misconduct based on samples drawn from four popular databases that identify restatements, securities class action lawsuits, and Accounting and Auditing Enforcement Releases (AAERs). We show that the results from empirical tests can depend on which database is accessed. To examine the causes of such discrepancies, we compare the information in each database to a detailed sample of 1,243 case histories in which regulators brought enforcement actions for financial misrepresentation. These comparisons allow us to identify, measure, and estimate the economic importance of four features of each database that affect inferences from empirical tests. We show the extent to which each database is subject to these concerns and offer suggestions for researchers using these databases. JEL Classifications: G38; K22; K42; M41.
Regulating Wall Street: The Dodd–Frank Act and the New Architecture of Global Finance, a review

Abstract This article is a review of a 531 page book that in turn is a review and evaluation of the 2319 page Dodd–Frank Wall Street Reform and Consumer Protection Act passed by Congress on July 16, 2010. The overriding theme of the book is to pose two approaches to attaining financial stability in the future. One approach is to establish a council of wise men and women supported by an army of highly skilled professional financial economists to formulate and implement regulations designed to prevent future financial crises that wreak havoc on the real economy and require financial support from taxpayers. This is the approach of the Dodd–Frank Act. The second approach proposed by the authors of this book is to design a taxing system that taxes systemically important financial institutions on the basis of their contribution to systemic risk. Borrowing ideas from the literature on the taxation of negative externalities their view is that financial institutions that create crises should pay for the clean-up. They also argue that requiring the financial polluters to pay for the creation of systemic risk will reduce the supply of systemic risk. The reader is invited to decide which approach is best.
Recent Developments in Corporate Governance: An Overview

Abstract I develop a corporate governance framework, provide a broad overview of recent corporate governance research, and place each of the Special Issue papers within the context of this framework. The papers in the issue contribute to our understanding of a wide range of governance topics including: the role of antitakeover measures, board structure, capital market governance, compensation and incentives, debt and agency costs, director and officer labor markets, fraud, lawsuits, ownership structure, and regulation. In short, the papers span almost every aspect of governance systems.
Internal vs. external habit formation: The relative importance for asset pricing☆

Abstract I present a generalized model that structurally nests both “catching up with the Joneses” (external habit) and “time nonseparable” (internal habit) preference specifications. The model’s asset pricing implications are confronted with the observed aggregate US consumption and asset returns data to determine the relative importance of “catching up with the Joneses” and internal habit formation. I show that long-horizon aggregate returns are more consistent with long-run habit as opposed to “catching up with the Joneses” preferences. This result supports the findings of Parker and Julliard (2005) that the ultimate consumption risk explains more of the cross-sectional variation in stock returns.
Judging Under a Bill of Rights

We are pleased to publish here, as an oratio , the Ebsworth Memorial Lecture delivered by Mr Justice Louis Harms in February 2007. In his lecture he addressed a range of contentious issues regarding the challenges of judging under a (new) Bill of Rights and he inter alia raises, "without answering, the question of whether a bill of rights should reflect existing societal values or whether it should create them." He also spoke candidly of judicial activism, verbosity emanating from the bench, the judiciary and the separation of powers and (in-)consistency in constitutional adjudication. Among his conclusions he states that a Bill of Rights "is supposed to remov e arbitrariness, not only of legislation but also of adjudication."
Creditor Rights, Technology Adoption, and Productivity: Plant-Level Evidence

I analyze the effect of stronger creditor rights on productivity, using U.S. Census microdata. Following the adoption of anti-recharacterization laws that give lenders greater access to the collateral of firms in financial distress, total factor productivity of treated plants increases by 2.6 percent. This effect is concentrated among plants belonging to financially constrained firms. I explore the underlying mechanism and find that treated plants change the composition of their investments and their workforce toward newer capital and skilled labor. My results suggest that stronger creditor rights relax borrowing constraints and help firms adopt production technologies that are more efficient.
Factors Influencing Firms' Disclosures about Environmental Liabilities

This paper examines factors related to environmental liability disclosure decisions for firms in industries with substantial Superfund site involvement. We hypothesize that the extent of disclosure about environmental liabilities is associated with five factors: (1) regulation, including enforcement activity, (2) managements' information, including site uncertainty and allocation uncertainty, (3) litigation and negotiation concerns, (4) capital market concerns, and (5) other regulatory influence. Our empirical tests examine the association between measures of environmental liability disclosure, based on disclosures in firms' annual reports and Forms 10-K, and proxies for the five factors, based on information from other public sources, including the EPA. We find that all of our hypothesized factors except site uncertainty significantly influence firms' environmental disclosure decisions.
Outsourcing Enforcement: Principles to Guide Self-Policing Regimes

In his book Outsourcing Sovereignty, Paul Verkuil warns us to be wary of the possible threats to “democratic principles of accountability and process in what has been a largely unexamined shift from private to public governance.”2 Verkuil notes that the public and private sectors have different boundaries, and suggests that since outsourcing tests those boundaries, governments should “justify delegations of public power to private hands.”3 This goal of this Article is to examine one particular form of outsourcing—the outsourcing of regulatory enforcement to the regulated entities themselves, a practice known as self-policing—to determine whether this type of delegation of public power can be justified as being in the public interest. Part II offers an overview of the particular concerns Verkuil and others have expressed regarding outsourcing in general. Part III provides a definition of self-policing and discusses both the theoretical justifications for the practice as well as the potential pitfalls. Heeding the words quoted above, Part IV presents a case study of the Environmental Protection Agency’s selfpolicing program, assessing the extent to which it is a defensible form of outsourcing. Part V reviews a number of other federal self-policing programs with a brief assessment of their strengths and weaknesses. Finally, Part VI suggests some general guidelines for self-policing
User Preference Learning-Aided Collaborative Edge Caching for Small Cell Networks

While next-generation wireless networks intend leveraging edge caching for enhanced spectral efficiency, quality of service, end-to-end latency, content sharing cost, etc., several aspects of it are yet to be addressed to make it a reality. One of the fundamental mysteries in a cache-enabled network is predicting what content to cache and where to cache so that high caching content availability is accomplished. For simplicity, most of the legacy systems utilize a static estimation - based on Zipf distribution, which, in reality, may not be adequate to capture the dynamic behaviors of the contents popularities. Forecasting user’s preferences can proactively allocate caching resources and cache the needed contents, which is especially important in a dynamic environment with real-time service needs. Motivated by this, we propose a long short-term memory (LSTM) based sequential model that is capable of capturing the temporal dynamics of the users’ preferences for the available contents in the content library. Besides, for a more efficient edge caching solution, different nodes in proximity can collaborate to help each other. Based on the forecast, a non-convex optimization problem is formulated to minimize content sharing costs among these nodes. Moreover, a greedy algorithm is used to achieve a sub-optimal solution. Using extensive simulation and analysis, we validate that the proposed algorithm performs better than other existing schemes.
The effects of fraud risk assessments and a risk analysis decision aid on auditors’ evaluation of evidence and judgment

Using a sample of 258 auditors, two experiments were conducted to study the effects of fraud risk assessments and an automated decision aid on auditors’ evaluation of evidence and judgment. Results indicate that the assessed level of fraud risk systematically affects the evaluation of evidence by auditors. More specifically, auditors facing high levels of assessed fraud risk evaluate audit evidence more thoroughly than auditors facing low levels of assessed fraud risk. In addition, auditors facing high risk assessments exhibit an unexpected bias in their decision processes. These auditors focus on the last evidence received during decision making, and their decisions change when evidence order is altered. The introduction of a computer-based decision aid promotes consistency in auditor decisions and eliminates the undesirable effects of evidence order, while preserving the benefits of more thorough evidence evaluation.
Tribal, State, and Federal Cooperation to Achieve Good Governance

Jurisdictional uncertainty affects tribal sovereignty and public safety. Management of natural resources remains one of the few realms of authority over which tribes have retained control. Ancient wild rice harvesting by the Chippewa provides a context in which to consider a tribes ability to set water standards, as does Pueblo ceremonial use of the Rio Grande River. Cooperative tribal, state, federal, and international responses to the Methamphetamine crisis can address both environmental and human health. This study examines the prospect for integrated protection of health and habitat based upon comity and cooperation. It examines the parameters of homeland security and the requisite degree of public oversight of private activities. This article concludes that tribal, state, and federal cooperation can achieve good governance.
Courts Without Borders: Domestic Sources of U.S. Extraterritoriality in the Regulatory Sphere

Regulating private transactions across international boundaries has long posed a challenge to states. Extraterritoriality—the direct regulation of persons and conduct outside a state's borders—is an increasingly common mechanism by which strong states attempt to manage problems associated with transnational activities. This article seeks to account for variation across issues in the willingness of U.S. courts to regulate extraterritorially by focusing on the potential for external conduct to undermine domestic legal rules. It suggests further how attention to domestic-level regulatory processes, with particular focus on the role of private actors, can shed new light on transnational rulemaking and enforcement.
The Impact of Contract Type on Broker Performance: Submarket Effects

Rutherford, Springer and Yavas (2001) develop and empirically test a model that analyzes the effect the type of listing contract, either exclusive agency (EA) or exclusive right to sell (ERTS), has...
Do CEO beliefs affect corporate cash holdings

Abstract We develop a model of corporate cash holdings that incorporates CEO beliefs. An optimistic CEO views external financing as excessively costly but expects this cost to moderate over time. The optimistic CEO thus delays external financing while funding current investments with existing cash and maintaining a lower cash balance than rational CEOs. We find that, relative to rational CEOs, optimistic CEOs hold 24% less cash, hold lower cash to fund the firms' growth opportunities, and save less cash out of incremental cash flow.