cssi/SciSciGPT-SciSciNet huggingface dataset:
Machine) learning to do more with less

Determining the best method for training a machine learning algorithm is critical to maximizing its ability to classify data. In this paper, we compare the standard “fully supervised” approach (which relies on knowledge of event-by-event truth-level labels) with a recent proposal that instead utilizes class ratios as the only discriminating information provided during training. This so-called “weakly supervised” technique has access to less information than the fully supervised method and yet is still able to yield impressive discriminating power. In addition, weak supervision seems particularly well suited to particle physics since quantum mechanics is incompatible with the notion of mapping an individual event onto any single Feynman diagram. We examine the technique in detail — both analytically and numerically — with a focus on the robustness to issues of mischaracterizing the training samples. Weakly supervised networks turn out to be remarkably insensitive to a class of systematic mismodeling. Furthermore, we demonstrate that the event level outputs for weakly versus fully supervised networks are probing different kinematics, even though the numerical quality metrics are essentially identical. This implies that it should be possible to improve the overall classification ability by combining the output from the two types of networks. For concreteness, we apply this technology to a signature of beyond the Standard Model physics to demonstrate that all these impressive features continue to hold in a scenario of relevance to the LHC. Example code is provided on GitHub.
Pressure scrambling effects and the quantification of turbulent scalar flux model uncertainties

The epistemic uncertainty in turbulent scalar flux modeling directly affects the accuracy of scalar transport simulations. Two classical phenomenological theories on the pressure scrambling effect in scalar flux dynamics---return-to-isotropy and isotropization-of-production---are revisited from the perspective of uncertainty quantification (UQ). A prototype scalar flux model UQ method is thus formulated, providing a physical ground for the future data-driven UQ practice.
The differential analytic index in Simons–Sullivan differential K-theory

We define the Simons–Sullivan differential analytic index by translating the Freed–Lott differential analytic index via explicit ring isomorphisms between Freed–Lott differential K-theory and Simons–Sullivan differential K-theory. We prove the differential Grothendieck–Riemann–Roch theorem in Simons–Sullivan differential K-theory using a theorem of Bismut.
Holographic Lifshitz fermions and exponentially suppressed spectral weight

The absence of fixed momentum excitations in a theory with Lifshitz scale invariance gives rise to exponential suppression of spectral weight in the low-frequency limit. In the holographic dual, this suppression arises as a consequence of a tunneling barrier that decouples the horizon from the boundary. We compute the spin-1/2 holographic Green’s function and show that the form of the barrier is identical to that of the scalar case. We furthermore demonstrate that the suppression factor is universal in the $$ \widehat{\omega}\to 0 $$ limit where $$ \widehat{\omega}=\omega /\left|\overrightarrow{k}\right|{}^{\mathrm{z}} $$ . In particular, it depends only on ω and the critical exponent z, and is independent of scaling dimension and spin.
An effective field theory of quantum mechanical black hole horizons

We develop an effective theory which describes black holes with quantum mechanical horizons that is valid at scales long compared to the Schwarzschild radius but short compared to the lifetime of the black hole. Our formalism allows one to calculate the quantum mechanical effects in scattering processes involving black hole asymptotic states. We point out that the EFT Wightman functions which describe Hawking radiation in the Unruh vacuum are not Planck suppressed and are actually enhanced relative to those in the Boulware vacuum, for which such radiation is absent. We elaborate on this point showing how the non-Planck suppressed effects of Hawking radiation cancel in classical observables.
Fast Parallel Randomized QR with Column Pivoting Algorithms for Reliable Low-Rank Matrix Approximations

Factorizing large matrices by QR with column pivoting (QRCP) is substantially more expensive than QR without pivoting, owing to communication costs required for pivoting decisions. In contrast, randomized QRCP (RQRCP) algorithms have proven themselves empirically to be highly competitive with high-performance implementations of QR in processing time, on uniprocessor and shared memory machines, and as reliable as QRCP in pivot quality. We show that RQRCP algorithms can be as reliable as QRCP with failure probabilities exponentially decaying in oversampling size. We also analyze efficiency differences among different RQRCP algorithms. More importantly, we develop distributed memory implementations of RQRCP that are significantly better than QRCP implementations in ScaLAPACK. As a further development, we introduce the concept of and develop algorithms for computing spectrum-revealing QR factorizations for low-rank matrix approximations, and demonstrate their effectiveness against leading low-rank approximation methods in both theoretical and numerical reliability and efficiency.
Logarithmic compactification of the Abel–Jacobi section

Given a smooth curve with weighted marked points, the Abel-Jacboi map produces a line bundle on the curve. This map fails to extend to the full boundary of the moduli space of stable pointed curves. Using logarithmic and tropical geometry, we describe a modular modification of the moduli space of curves over which the Abel-Jacobi map extends. We also describe the attendant deformation theory and virtual fundamental class of this moduli space. This recovers the double ramification cycle, as well as variants associated to differentials.
Multistate Ornstein–Uhlenbeck approach for practical estimation of movement and resource selection around central places

O_LIHome range dynamics and movement are central to a species ecology and strongly mediate both intra- and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture effects of dynamic environmental patterns, such as the impacts of air and water flow on movement. C_LIO_LIHere, we develop a practical, multi-stage approach for statistical inference into the behavioral mechanisms underlying how habitat and dynamic energy landscapes--in this case how airflow increases or decreases the energetic efficiency of flight--shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry. C_LIO_LIThe application to golden eagles revealed effects of habitat variables that align with predicted behavioral ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely. C_LIO_LIThis method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein-Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions. C_LI
Active Sampling for Class Probability Estimation and Ranking

In many cost-sensitive environments class probability estimates are used by decision makers to evaluate the expected utility from a set of alternatives. Supervised learning can be used to build class probability estimates; however, it often is very costly to obtain training data with class labels. Active learning acquires data incrementally, at each phase identifying especially useful additional data for labeling, and can be used to economize on examples needed for learning. We outline the critical features of an active learner and present a sampling-based active learning method for estimating class probabilities and class-based rankings. BOOTSTRAP-LV identifies particularly informative new data for learning based on the variance in probability estimates, and uses weighted sampling to account for a potential example's informative value for the rest of the input space. We show empirically that the method reduces the number of data items that must be obtained and labeled, across a wide variety of domains. We investigate the contribution of the components of the algorithm and show that each provides valuable information to help identify informative examples. We also compare BOOTSTRAP-LV with UNCERTAINTY SAMPLING, an existing active learning method designed to maximize classification accuracy. The results show that BOOTSTRAP-LV uses fewer examples to exhibit a certain estimation accuracy and provide insights to the behavior of the algorithms. Finally, we experiment with another new active sampling algorithm drawing from both UNCERTAINTY SAMPLING and BOOTSTRAP-LV and show that it is significantly more competitive with BOOTSTRAP-LV compared to UNCERTAINTY SAMPLING. The analysis suggests more general implications for improving existing active sampling algorithms for classification.
SF-GRASS: Solver-Free Graph Spectral Sparsification

Recent spectral graph sparsification techniques have shown promising performance in accelerating many numerical and graph algorithms, such as iterative methods for solving large sparse matrices, spectral partitioning of undirected graphs, vectorless verification of power/thermal grids, representation learning of large graphs, etc. However, prior spectral graph sparsification methods rely on fast Laplacian matrix solvers that are usually challenging to implement in practice. This work, for the first time, introduces a solver-free approach (SF-GRASS) for spectral graph sparsification by leveraging emerging spectral graph coarsening and graph signal processing (GSP) techniques. We introduce a local spectral embedding scheme for efficiently identifying spectrally-critical edges that are key to preserving graph spectral properties, such as the first few Laplacian eigenvalues and eigenvectors. Since the key kernel functions in SF-GRASS can be efficiently implemented using sparse-matrix-vector-multiplications (SpMVs), the proposed spectral approach is simple to implement and inherently parallel friendly. Our extensive experimental results show that the proposed method can produce a hierarchy of high-quality spectral sparsifiers in nearly-linear time for a variety of real-world, large-scale graphs and circuit networks when compared with prior state-of-the-art spectral methods.
Correlation functions in massive Landau-Ginzburg orbifolds and tests of dualities

In this paper we discuss correlation function computations in massive topological Landau-Ginzburg orbifolds, extending old results of Vafa [1]. We then apply these computations to provide further tests of the nonabelian mirrors proposal and two-dimensional Hori-Seiberg dualities with (S)O± gauge groups and their mirrors.
Network model and analysis of the spread of Covid-19 with social distancing

The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human–human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.
Towards Dynamic Pricing for Shared Mobility on Demand using Markov Decision Processes and Dynamic Programming

In a Shared Mobility on Demand Service(SMoDS), dynamic pricing plays an important role in the form of an incentive for empowered passengers to decide on the ride offer. Strategies for determining the dynamic tariffs should be suitably designed so that the incurred demand and supply within the SMoDS platform are balanced and therefore economic efficiency is further achieved. In this manuscript, we formulate a discrete time Markov Decision Process (MDP) to determine the probability of acceptance of each empowered passenger that is desired by the SMoDS platform. The proposed MDP formulation is a versatile framework which is shown to explicitly accommodate passenger behavior and realize the desired system objective. Estimated Waiting Time (EWT) is utilized as a suitable metric to measure the balance between demand and supply, with the goal of regulating EWT around a target value. We propose the use of a Dynamic Programming algorithm to derive the optimal policy that achieves the regulation. Computational experiments are conducted to demonstrate effective regulation of EWT, through various scenarios.
Coordinated Operation of Electricity and Natural Gas Systems: A Convex Relaxation Approach

The variability in the generation dispatch of the natural gas generation units will lead to fluctuation in natural gas demand profile that could further jeopardize the security of the natural gas network. The coordinated operation of electricity and natural gas infrastructure systems would help to improve the security and reliability measures in both infrastructure systems and mitigate the risk of demand curtailment. The electricity and natural gas network operation problems are non-convex mixed-integer nonlinear programming problems that are hard to solve in polynomial time. The non-convex feasible regions are formed by the Weymouth constraint and the introduced binary commitment decision variables in the natural gas and electricity network operation problems, respectively. This paper utilized a sparse semidefinite programming (SDP) relaxation to procure the optimal solution for the coordinated operation of electricity and natural gas networks. The presented algorithm leverages the sparseness of the natural gas network to construct several small matrices of lifting variables that are used to form a tight and traceable SDP relaxation. A set of valid constraints that tighten the relaxation ensures the exactness of the solution procured from the relaxed problem. The effectiveness of the presented approach is shown in case studies.
Clifford Analysis with Indefinite Signature

We extend constructions of classical Clifford analysis to the case of indefinite non-degenerate quadratic forms. We define (p, q)-left- and right-monogenic functions by means of Dirac operators that factor a certain wave operator. We prove two different versions of Cauchy’s integral formulas for these functions. The two formulas arise from dealing with singularities in distinct ways, and are inspired by the methods of Frenkel and Libine (Adv Math 228:678–763, 2011) and Libine (Hypercomplex analysis and its applications, Birkhauser, Boston, pp 161–180, 2011). These results indicate the merit of these methods for dealing with singularities.
Ultraintense, ultrashort pulse X-ray scattering in small molecules

We examine X-ray scattering from an isolated organic molecule from the linear to nonlinear absorptive regime. In the nonlinear regime, we explore the importance of both the coherent and incoherent channels and observe the onset of nonlinear behavior as a function of pulse duration and energy. In the linear regime, we test the sensitivity of the scattering signal to molecular bonding and electronic correlation via calculations using the independent atom model (IAM), Hartree–Fock (HF) and density functional theory (DFT). Finally, we describe how coherent X-ray scattering can be used to directly visualize femtosecond charge transfer and dissociation within a single molecule undergoing X-ray multiphoton absorption.
Counting Rational Curves on K3 Surfaces With Finite Group Actions

Gottsche gave a formula for the dimension of the cohomology of Hilbert schemes of points on a smooth projective surface $S$. When $S$ admits an action by a finite group $G$, we describe the action of $G$ on the cohomology spaces. In the case that $S$ is a K3 surface, each element of $G$ gives a trace on $\sum_{n=0}^{\infty}\sum_{i=0}^{\infty}(-1)^{i}H^{i}(S^{[n]},\mathbb{C})q^{n}$. When $G$ acts faithfully and symplectically on $S$, the resulting generating function is of the form $q/f(q)$, where $f(q)$ is a cusp form. We relate the cohomology of Hilbert schemes of points to the cohomology of the compactified Jacobian of the tautological family of curves over an integral linear system on a K3 surface as $G$-representations. Finally, we give a sufficient condition for a $G$-orbit of curves with nodal singularities not to contribute to the representation.
The Arbitration Fairness Act: It Need Not and Should Not be an All or Nothing Proposition

The proposed Arbitration Fairness Act (AFA) would prohibit all pre-dispute agreements to arbitrate in employment, consumer and franchise contracts. Although changes in the ideological composition of Congress mean that the AFA has little chance of enactment in the foreseeable future, mini-AFAs have been enacted banning pre-dispute arbitration agreements as applied to sexual harassment claims by employees of defense contractors and whistleblower claims by employees in the securities and commodities industries. This article charts a middle ground between those who would ban pre-dispute arbitration mandates in employment contracts completely and those who would leave them unregulated. After surveying the empirical evidence concerning arbitration and litigation of statutory employment claims and finding it inconclusive, the article finds that employer motives for imposing arbitration mandates on employees are diverse. Some employers seek a process that is less time-consuming and less costly than litigation while others seek to tilt the playing field to their advantage, suppressing employee claims. The article urges that when policed against abuses, arbitration can provide a fair forum that is more accessible for employees than litigation. It finds, however, that courts have not adequately policed arbitration mandates and recent decisions may undermine efforts of the arbitration community to self-police. The article proposes specific legislative reforms to ensure that employment arbitration mandates are not used to advantage employers at the expense of their employees and to ensure that arbitration provides a less expensive, less time-consuming and more employee-accessible process than litigation.
Recession forecasting using Bayesian classification

Abstract We demonstrate the use of a Naive Bayes model as a recession forecasting tool. The approach is closely connected with Markov-switching models and logistic regression, but also has important differences. In contrast to Markov-switching models, our Naive Bayes model treats National Bureau of Economic Research business cycle turning points as data, rather than as hidden states to be inferred by the model. Although Naive Bayes and logistic regression are asymptotically equivalent under certain distributional assumptions, the assumptions do not hold for business cycle data. As a result, Naive Bayes has a larger asymptotic error rate, but converges to the error rate more quickly than logistic regression, resulting in more accurate recession forecasts with limited data. We show that Naive Bayes outperforms competing models and the Survey of Professional Forecasters consistently for real-time recession forecasting up to 12 months in advance. These results hold under standard error measures, and also under a novel measure that varies the penalty on false signals, depending on when they occur within a cycle; for example, a false signal in the middle of an expansion is penalized more heavily than one that occurs close to a turning point.
Unlikely Democrats: Economic Elite Uncertainty under Dictatorship and Support for Democratization

Influential recent scholarship assumes that authoritarian rulers act as perfect agents of economic elites, foreclosing the possibility that economic elites may at times prefer democracy absent a popular threat from below. Motivated by a puzzling set of democratic transitions, we relax this assumption and examine how elite uncertainty about dictatorship -- a novel and generalizable causal mechanism impacting democratization -- can induce elite support for democracy. We construct a noisy signaling model in which a potential autocrat attempts to convince economic elites that he will be a faithful partner should elites install him in power. The model generates clear predictions about how two major types of elite uncertainty -- uncertainty in a potential autocratic successor's policies produced by variance in the pool of would-be dictator types, and uncertainty in the truthfulness of policy promises made by potential autocratic successors -- impact the likelihood of elite-driven democratization. We demonstrate the model's plausibility in a series of cases of democratic transition.
Prior art: To search or not to search

Abstract To determine patentability, inventions are evaluated in light of existing prior art. Innovators have a duty to disclose any prior art that they are aware of, but have no obligation to search. We study innovators' incentives to search for prior art, their search intensities and the timing of search. We distinguish between early state of the art search—conducted before R&D investment, and novelty search—conducted right before applying for a patent. We identify conditions in which innovators have no incentive to search for prior art. Search intensity increases with R&D cost, the examiners' expected search effort, and with patenting fees. We also find that innovators prefer to correlate their search technology with that of the patent office. In light of our model, we discuss the implications of some proposed policy reforms.
Local labor market shocks and residential mortgage payments: Evidence from shale oil and gas booms

Abstract Frequently, housing is the largest item on a household's balance sheet, and therefore making monthly mortgage payments is often both the largest regular expenditure as well as a primary savings vehicle for households. However, changes to economic conditions impact household spending and savings decisions. To investigate the dynamics of this relationship, we examine mortgage payment choices of homeowners who purchased property in areas that later experienced a positive shock to local economic conditions via the shale oil and gas boom. We find that borrowers with properties located in areas with shale oil and gas booms experienced a 6% reduction in the probability of missing a mortgage payment over the period 2007–2014. Indexing these results to the size of the boom, we find that one hundred additional rigs (billion dollars of oil and gas produced) are associated with a 3.2% (1.6%) decrease in default. Additionally, we find differential effects on housing markets across geography, time, loan leverage, and credit risk categories.
Hyperlinking Unaudited Information to Audited Financial Statements: Effects on Investor Judgments

This study provides evidence that hyperlinking a firm's audited financial statements to unaudited information in a web‐based environment leads investors to blend the unaudited information with the audited statements. I obtain evidence of this blending effect using an experiment where investors assessed a firm's earnings potential by evaluating the firm's audited financial statements and a subsequent optimistic unaudited letter to shareholders from the firm's management. Investors who viewed hyperlinked materials on the Web misclassified more unaudited information as audited and assessed the credibility of the unaudited information as higher than did investors who viewed hardcopy materials. Those investors who assessed the unaudited information as more credible also judged the firm's earnings potential to be higher. Notifying users with an “AUDITED/NOT AUDITED” label attenuated these effects. This evidence suggests that firms can influence financial report users' perceptions by hyperlinking unaudited infor...
Does good corporate governance include employee representation? Evidence from German corporate boards

Abstract Within the German corporate governance system, employee representation on the supervisory board is typically legally mandated. We propose that such representation of labor on corporate boards confers valuable first-hand operational knowledge to corporate board decision-making. Indeed, we find that labor representation provides a powerful means of monitoring and reduces agency costs within the firm. Moreover, we show that the greater the need for coordination within the firm, the greater the potential improvement there is in governance effectiveness through the judicious use of labor representation. These benefits do not appear to hold for union representatives.
Race Discrimination and Human Rights Class Actions: The Virtual Exclusion of Racial Minorities from the Class Action Device

In the era of Jim Crow, racial minorities were segregated and excluded from participating in white society. Minorities were segregated in public schools, excluded from public accommodations, excluded from participation on juries, and excluded from living in certain areas. Harkening back to that earlier time, racial minorities now are often excluded from using the class action device to bring civil rights claims.This paper argues that courts are very tough in how they handle class certification decisions in race discrimination class actions. On the other hand, the courts are quite lenient in how they handle class certification decisions in human rights class actions. The paper tries to explain why this is the case. The paper argues that race discrimination class action cases should be treated in the same lenient fashion as the human rights cases.In Part II of this paper, the author sets out some history regarding class actions. Part Ill sets out the basic requirements for certification of a class action. Part IV examines how the courts have treated human rights class actions in making class certification decisions. Part V compares the human rights cases to the courts' handling of race discrimination class actions and points out that the cases are treated differently. Part VI seeks to explain the differential treatment. Part VII argues that the race cases should be treated in the same lenient fashion as the human rights cases.
CITIZENSHIP AS SHARED FATE: EDUCATION FOR MEMBERSHIP IN A DIVERSE DEMOCRACY

The diversity of contemporary democratic nations challenges scholars and educators to develop forms of education that would both recognize difference and develop a shared foundation for a functioning democracy. In this essay Sigal Ben-Porath develops the concept of shared fate as a theoretical and practical response to this challenge. Shared fate offers a viable alternative to current forms of citizenship education, one that develops a significant shared dimension while respecting deep differences within a political community. It is grounded in the social and moral realities of civic life, and it seeks to weave the historical, political, and social ties among members of the nation into a form of affiliation that would sustain and expand their shared political project. Some particular educational contexts are considered through the lens of shared fate, including the resegregation of some schooling systems, linguistic diversity, and patriotic education.
The WTO and rules-based dispute settlement: Historical evolution, operational success, and future challenges

The World Trade Organization (WTO) has three main functions—first, negotiations on trade matters; second, oversight of existing WTO agreements; and third, dispute settlement. The WTO's negotiation function has broken down and its oversight function, while useful and valuable, is the least visible and least significant of the three functions. Thus, the credibility of the WTO as a functioning international organization essentially depends on ensuring the effectiveness of its dispute settlement function. This paper briefly traces the historical evolution of the dispute settlement system under the General Agreement on Tariffs and Trade (GATT) and then considers the current state of the WTO dispute settlement system—how effectively has it operated to date and what operational and procedural problems have arisen? It concludes by examining the challenges the WTO dispute settlement system will face in the coming years, considering, in particular, whether the system will be able to resolve effectively disputes between the major WTO powers—the United States, the European Union and China.
The politics of admissions in California

This essay discusses the aftermath of Proposition 209, which prohibits (among other things) discrimination and preferential treatment based on race or ethnicity in public education. As its proponents predicted, when campuses of the University of California stopped engaging in race-preferential admissions, the number of African-American and Hispanic students decreased at the most-highly ranked campuses in the system, but they increased on many of the other campuses. The essay discusses in particular results from the University of California at San Diego, where the performance of under-represented minority students improved dramatically following the implementation of Proposition 209. For example, immediately prior to the implementation of Proposition 209, only one black student had a freshman-year GPA of 3.5 or better — a single black honor student in a freshman class of 3,268. In contrast, 20 percent of the white students in the class had such a GPA. The next year, with Proposition 209, a full 20 percent of black students could boast a GPA of 3.5 or better after their first year. Similarly, immediately prior to Proposition 209, 15 percent of black students and 17 percent of American Indian were in academic jeopardy (defined as a GPA of less than 2.0), while only 4% of white students were. Immediately after Proposition 209’s implementation, the under-represented minority failure rate collapsed. The difference between racial groups all but evaporated, with the black and American Indian rate falling to 6 percent.
Establishing an Island of Patent Sanity

There is a growing, inescapable sense that something has gone terribly wrong with the patent system. The patent system is described as a failure, broken, and dysfunctional. Yet, despite the fact that much of today’s headline-grabbing patent activity appears facially unproductive, we really can’t be sure that the system has failed in its mission. Current patent theory is so indeterminate that it is hard to decisively criticize these activities. In fact, the current narrative cannot conclusively show that patent trolls or any other patent-related activities are or are not economically justified. Though depressing and perhaps embarrassing, this patent indeterminacy is not really a surprise; it’s been this way for two hundred years. We continue to use the standard narrative because we don’t think we have anything better. But we need stronger, more determinate backing for the patent system. This article develops an alternative narrative that can justify at least part of the current system. In that narrative, the patent system provides not special inducement as in the current narrative, but rather it provides the underlying legal support for a voluntary market exchange of inventions. The article shows that, even though market exchange of technological ideas or information generally might be problematic, market exchange of inventions is different. Amid all of the current controversy, this new narrative aims to establish an island, perhaps a small one, of economically justified activity that can serve as a normative core for a patent system that we can finally confidently believe in.
Why do loans contain covenants? Evidence from lending relationships

Abstract Despite the importance of banks’ role as delegated monitors, little is known about how non-price terms of loan contracts are structured to optimize information production in a lending relationship. Using a large sample of corporate loans, this paper examines the effect of relationship lending on covenant choice. Consistent with information asymmetry theories, covenant tightness is relaxed over the duration of a relationship, especially for opaque borrowers. In contrast, the effect of lending relationship intensity on the number of covenants included in a loan follows an inverted U shape. I discuss potential explanations for this finding.
Can a Rule-Based Monetary Policy Framework Work in a Developing Country? The Case of Yemen

Monetary policy in Yemen is largely rudimentary and ad hoc in nature. The Central Bank of Yemen's (CBY) approach has been based on discretionary targeting of broad money without any clear target to anchor inflation expectations. This paper argues in favor of a new formal monetary policy framework for Yemen emphasizing a proactive and rule-based approach with a greater direct focus on price stability in the context of a flexible management of the exchange rate. Although, as in many developing countries, institutional capacity is a concern, adopting a more formal framework could impel the kind of changes that are required to strengthen the ability of the CBY in achieving low and stable rates of inflation over the medium term.
Coordination and turnout in large elections

Competitive elections are frequently decided by which side can generate larger turnout on polling day. When decided on whether to turn out voters are assumed to balance the cost of going to the polls with the prospect of making a difference in the election outcome. We present a stochastic model of turnout where voters receive information about current turnout propensities of the voting populus through opinion polls. Voters then decide on whether to vote or not by maximizing their expected utility based on the (potentially noisy) polling information as well as the costs and benefits of participation. We prove the existence of a unique limiting distribution for the process and show that even in large electorates substantial expected turnout is possible if voting factions are sufficiently similar in size. A key requirement for substantial turnout is that polls never provide precise feedback on the current state of the electorate. The effect of noise, however, is non-monotonic: no noise or too much noise results in vanishing turnout, while moderate noise may result in substantial turnout. Our model also can account for known empirical regularities about turnout identified in the political science literature.
Takeover Contests with Asymmetric Bidders

Target firms often face bidders that are not equally well informed, which reduces competition, because bidders with less information fear the winner’s curse more. We analyze how targets should be sold in this situation. We show that a sequential procedure can extract the highest possible transaction price. The target first offers an exclusive deal to a better-informed bidder, without considering a less wellinformed bidder. If rejected, the target offers either an exclusive deal to the less well-informed bidder, or a modified first-price auction. Deal protection devices can be used to enhance a target’s commitment to the procedure. (JEL G34, K22, D44) If a firm is to be sold, the seller’s problem is to identify the buyer who will pay the highest price. Negotiations with potential buyers are one way to discover who this buyer is and at what price a transaction can take place; auctions are an alternative method. Selling firms by inviting competitive bids has become increasingly popular in practice, and the announcement that a firm is ‘‘evaluating strategic alternatives’’ is commonly regarded as an invitation to submit competitive bids. 1 Bidders participating in an auction are not always equally well informed. Management bids are the clearest example: in many cases the target’s management team (or a subset of senior managers) declares an interest in purchasing the target, and their privately known value estimate must be more reliable than any other potential buyer’s. Similarly, a competitor should find it much easier to evaluate a target’s prospects than a bidder with no experience in the target’s line of business. Either way, a less well-informed bidder will be particularly worried about the
Characterizing Non-Myopic Information Cascades in Bayesian Learning

We consider an environment where a finite number of players need to decide whether to buy a certain product (or adopt a trend) or not. The product is either good or bad, but its true value is not known to the players. Instead, each player has her own private information on the quality of the product. Each player can observe the previous actions of other players and estimate the quality of the product. A player can only buy the product once. In contrast to the existing literature on informational cascades, in this work players get more than one opportunity to act. In each turn, a player is chosen uniformly at random from all players and can decide to buy or not to buy. His utility is the total expected discounted reward, and thus myopic strategies may not constitute equilibria. We provide a characterization of structured perfect Bayesian equilibria (sPBE) with forward-looking strategies through a fixed-point equation of dimensionality that grows only quadratically with the number of players. In particular, a sufficient state for players' strategies at each time instance is a pair of two integers, the first corresponding to the estimated quality of the good and the second indicating the number of players that cannot offer additional information about the good to the rest of the players. We show existence of such equilibria and characterize equilibria with threshold strategies w.r.t. the two aforementioned integers. Based on this characterization we study informational cascades and show that they happen with high probability for a large number of players. Furthermore, only a small portion of the total information in the system is revealed before a cascade occurs.
A characterization of virtual Bayesian implementation

We provide a characterization of virtual Bayesian implementation in pure strategies for environments satisfying no-total-indifference. A social choice function in such environments is virtually Bayesian implementable if and only if it satisfie s incentive compatibility and a condition we term virtual monotonicity. The latter is weaker than Bayesian monotonicity—known to be necessary for Bayesian implementation. Virtual monotonicity is weak in the sense that it is generically satisfied in environments with at least three alternatives. Thi s implies that in most environments virtual Bayesian implementation is as successful as it can be (incentive compatibility is the only condition needed).
The power of the pen and executive compensation.

Abstract We examine the press’ role in monitoring and influencing executive compensation practice using more than 11,000 press articles about CEO compensation from 1994 to 2002. Negative press coverage is more strongly related to excess annual pay than to raw annual pay, suggesting a sophisticated approach by the media in selecting CEOs to cover. However, negative coverage is also greater for CEOs with more option exercises, suggesting the press engages in some degree of “sensationalism.” We find little evidence that firms respond to negative press coverage by decreasing excess CEO compensation or increasing CEO turnover.
Neoclassical Economics and the Erosion of Middle-Class Values: An Explanation for Economic Collapse

This article advances its critique as follows: First, it describes and clarifies the sociopathic nature of person that is taught as science in universities. Second, it argues that the middle-class values of honesty, integrity, and concern for community are essential to a healthy society. Third, it examines the content of current and recent economics texts to document the advocacy of rational self-interest as approved behavior. Fourth, it postulates a cause-and-effect connection between the ascendant theory of purely economically driven person and the bad behavior that led to the recent failure of economic institutions. Fifth, it connects economics and legal education with the predations that logically flow from their flawed theory of person. Sixth, it invokes cognitive science to explain some aspects of human moral and political thought. And seventh, it looks at some practical implications of the theory of virtuous person for both economics and law.
Which Felonies Pose a “Serious Potential Risk of Injury” for Federal Sentencing Purposes?

Both the federal Armed Career Criminal Act and Sentencing Guidelines provide greatly enhanced punishment for defendants previously convicted of felonies that present a "serious potential risk of injury." The Supreme Court has by its own admission struggled to develop a formula for ascertaining which felonies meet this description. Most of the Justices agree that empirical data could be probative of the degree to which various offenses present risk of injury, but no existing study compares frequency of injury across a wide range of offenses. This Article tabulates injury data from a single source, the National Incident-Based Reporting System (NIBRS), with respect to 42 crimes, and makes some recommendations.
Value Added to What? How a Ceiling in the Testing Instrument Influences Value-Added Estimation

Value-added measures of teacher quality may be sensitive to the quantitative properties of the student tests upon which they are based. This article focuses on the sensitivity of value added to test score ceiling effects. Test score ceilings are increasingly common in testing instruments across the country as education policy continues to emphasize proficiency-based reform. Encouragingly, we show that over a wide range of test score ceilingseverity,teachers’value-addedestimatesareonly negligibly influenced by ceiling effects. However, as ceiling conditions approach those found in minimumcompetency testing environments, value-added results are significantly altered. We suggest a simple statistical check for ceiling effects.
Integrating dynamic time-to-market, pricing, production and sales channel decisions

Abstract This paper studies a firm’s time-to-market decision and subsequent sales channel, pricing and production decisions under three main sources of uncertainty: possibility of qualifying for lucrative sales channels, competitors’ time-to-market behavior and price-sensitive uncertain demand. In particular, we consider a firm that can potentially sell through two distinct channels. Selling through the primary channel requires the firm to first get its product qualified. The secondary channel does not require qualification. Prior to market entry, the firm performs product and process design activities which improve manufacturing yield and the chances of getting qualified for the primary sales channel. A long delay in market entry allows competitors to enter the market before the firm, reducing the firm’s market share. This delay also affects the firm’s sales channel strategy. While deciding when to enter the market, the firm also needs to decide what price to charge and how much to produce at each period of a finite planning horizon. Demand distributions depend on the product’s price through general stochastic demand functions. Pricing and production decisions can be specified dynamically as a function of the state of the system and they are intertwined with the time-to-market decision. The paper provides a unified model that captures the key relationships and trade-offs among time-to-market, sales channel, pricing and production decisions. Explicitly modeling the linkages among these key decisions enables us to characterize and quantify their joint role in profit generation. This paper provides managers with a tool and a process that can guide them in determining an optimal policy for market-timing, pricing and production decisions that maximize firms’ expected profits.
How Delaware's Corporate Law Monopoly Was Nearly Destroyed

Delaware’s preeminence in corporate law was almost ended by the rise of the minimum contacts test and the expansion of constitutional rights for consumers. This article is the culmination of my work on corporate law and civil procedure. It reveals the intellectual, theoretical, and doctrinal forces behind the attack on Delaware’s corporate law monopoly.Delaware’s success depends upon its ability to assert personal jurisdiction over corporate directors. Delaware used a quasi-in-rem process called sequestration until the Supreme Court declared it to be unconstitutional in Shaffer v. Heitner. Sequestration rested on bedrock constitutional theory until radical developments in two unrelated areas of constitutional law came together. First, a handful of academics reconceived International Shoe, transforming minimum contacts into the basis for nearly all personal jurisdiction. Then, the Supreme Court revolutionized the consumer credit world by giving individual debtors radical new constitutional rights.Neither the modern view of International Shoe nor the debtors’ rights revolution was concerned with corporate law. Nor were these radical changes in constitutional theory related to one another. Yet together, they fomented the intellectual attack that destroyed sequestration and almost caused Delaware to lose its chokehold on corporate law.
Corporations and Autonomy Theories of Contract: A Critique of the New Lex Mercatoria

One of the central problems of contracts jurisprudence is the conflict between autonomy theories of contract and efficiency theories of contract. One approach to solving this conflict is to argue that in the realm of contracts between corporations, autonomy theories have nothing to say because corporations are not real people with whose autonomy we need to be concerned. While apparently powerful, this argument ultimately fails because it implicitly assumes theories of the corporation at odds with economic theories of law. Economics, in turn, offers a vision of the firm that is quite hospitable to autonomy theories of contract. The failure of this argument suggests that a more fruitful avenue for reconciling these competing approaches is to find a principled way of integrating them into a single theory.
Liquidity in the pricing of syndicated loans

Abstract We examine whether banks price expected liquidity in US syndicated term loans. Using extensive data we show that loans with higher expected liquidity have significantly lower spreads at origination, controlling for other determinants of loan spreads such as borrower, loan, syndicate and macroeconomic variables. A matched sample analysis confirms our results. We estimate that the pricing of expected liquidity results in annual savings of over $1.6 billion to the borrowers, in our sample alone. For the first time in the literature, we identify what influences the decision of financial intermediaries to make secondary markets for an asset, and the consequent pricing impact of this decision in the primary market.