cssi/SciSciGPT-SciSciNet huggingface dataset:
Error Correction Methods with Political Time Series

While traditionally considered for non-stationary and cointegrated data, DeBoef and Keele suggest applying a General Error Correction Model (GECM) to stationary data with or without cointegration. The GECM has since become extremely popular in political science but practitioners have confused essential points. For one, the model is treated as perfectly flexible when, in fact, the opposite is true. Time series of various orders of integration–stationary, non-stationary, explosive, near- and fractionally integrated–should not be analyzed together but researchers consistently make this mistake. That is, without equation balance the model is misspecified and hypothesis tests and long-run-multipliers are unreliable. Another problem is that the error correction term's sampling distribution moves dramatically depending upon the order of integration, sample size, number of covariates, and the boundedness of Yt. This means that practitioners are likely to overstate evidence of error correction, especially when using a traditional t-test. We evaluate common GECM practices with six types of data, 746 simulations, and five paper replications.
Gravity-Assisted Solution of the Mass Gap Problem for Pure YANG-MILLS Fields

In 1979, Louis Witten demonstrated that stationary axially symmetric Einstein field equations and those for static axially symmetric self-dual SU(2) gauge fields can both be reduced to the same (Ernst) equation. In this paper, we use this result as point of departure to prove the existence of the mass gap for quantum source-free Yang–Mills (Y–M) fields. The proof is facilitated by results of our recently published paper, J. Geom. Phys.59 (2009) 600–619. Since both pure gravity, the Einstein–Maxwell and pure Y–M fields are described for axially symmetric configurations by the Ernst equation classically, their quantum descriptions are likely to be interrelated. Correctness of this conjecture is successfully checked by reproducing (by different methods) results of Korotkin and Nicolai, Nucl. Phys. B475 (1996) 397–439, on dimensionally reduced quantum gravity. Consequently, numerous new results supporting the Faddeev–Skyrme (F–S)-type models are obtained. We found that the F–S-like model is best suited for description of electroweak interactions while strong interactions require extension of Witten's results to the SU(3) gauge group. Such an extension is nontrivial. It is linked with the symmetry group SU(3) × SU(2) × U(1) of the standard model. This result is quite rigid and should be taken into account in development of all grand unified theories. Also, the alternative (to the F–S-like) model emerges as by-product of such an extension. Both models are related to each other via known symmetry transformation. Both models possess gap in their excitation spectrum and are capable of producing knotted/linked configurations of gauge/gravity fields. In addition, the paper discusses relevance of the obtained results to heterotic strings and to scattering processes involving topology change. It ends with discussion about usefulness of this information for searches of Higgs boson.
Returns and option activity over the option-expiration week for S&P 100 stocks☆

Abstract For S&P 100 stocks, we find that the weekly returns over option-expiration (OE) weeks (a month’s third-Friday week) tend to be high, relative to: (1) the third-Friday weekly returns of other stocks with less option activity, (2) the own stock’s other weekly returns, (3) the risk, based on asset-pricing alphas. For these same stocks, a month’s fourth-Friday weekly returns underperform modestly. We suggest the following two avenues are likely partial contributors towards understanding these return patterns: (1) delta-hedge rebalancing by option market makers, with a reduction in short-stock hedge positions over the OE week, and (2) declining risk perceptions over the OE week, as measured by option-derived implied volatilities. Our findings suggest option activity can induce reliable patterns in the weekly returns of option-active large-cap stocks.
R&D Intensity and the Value of Analysts’ Recommendations*

This study examines the relationship between the value of financial analysts’ recommendations and the intensity of firms’ research and development (R&D) expenditures. We conduct univariate, portfolio and regression analyses using a sample of 8,620 public firms for the period 1993-2004. The empirical results reveal that the value of analysts’ recommendations is significantly greater for firms that are more heavily invested in R&D. In addition, we investigate factors that contribute to the value of analysts’ recommendations. We find that analysts with advanced degrees (e.g., Ph.D., M.D.), more firm-specific experience and greater industry expertise issue more valuable recommendations particularly for R&D-intensive firms. Our findings shed light on the important issue of how informed market participants’ activities expedite the price discovery process of R&D firms. Prior research (Lev and Sougiannis 1996) shows that, despite the absence of mandatory financial reporting on R&D, investors incorporate information on the value and productivity of R&D investments into share prices. Our study suggests that analyst recommendations serve as an important channel through which information on the value and productivity of R&D projects becomes impounded into security prices.
Happiness and Punishment

This Article continues our project of applying new findings in the behavioral psychology of human happiness to some of the most deeply analyzed questions in law. When a state decides how to punish criminal offenders, at least one important consideration is the amount of harm any given punishment is likely to inflict. It would be undesirable, for example, to impose greater harm on those who commit less serious crimes or to impose harm that rises to the level of cruelty. Our penal system fits punishments to crimes primarily by adjusting the size of monetary fines and the length of prison terms, but new findings about human adaptability unsettle the assumptions upon which the system rests. Specifically, people adapt well to negative changes in wealth and even to many features of prison life, whereas they adapt poorly to typical conditions of postprison life such as unemployment, disease, and loss of social ties. As a result, adjusting the size of a fine or the length of a prison term will not change in a linear fashion the amount of harm imposed. A large difference in the size of two punishments will not necessarily result in a large (or, in the case of some fines, any) difference in the harm felt by the respective offenders. This result is relevant to both retributive and utilitarian punishment theories, as well as to the practice of criminal justice. New approaches to punishment are necessary to achieve proportionality in light of the challenges posed by adaptation.
The Strategic Substitution of United States Foreign Aid

I present a foreign policy decision-making theory that accounts for why US food aid is used strategically when other more powerful economic aid tools are at the disposal of policymakers. I focus my analysis on US food aid because this aid program provides an excellent case with which to test for the existence of foreign policy substitution. Substitution is an important assumption of many foreign policy theories yet proves to be an allusive empirical phenomenon to observe. Central to this analysis is the identification of legal mechanisms such as the ‘‘needy people’’ provision in the US foreign aid legislation that legally restrict certain types of aid; this mechanism, however, does allow for the allocation of certain types of foreign aid, such as food aid, to human rights abusing regimes. Thus, I test if food aid is used as a substitute for human rights abusing states while methodologically accounting for other aid options. The empirical results, estimated with a multinomial logit and Heckman model, demonstrate that countries with high levels of human rights abuse are (i) more likely to receive food aid and (ii) receive greater amounts of food aid even when controlling for other economic aid, the conditioning effect of strategic interests and humanitarian need over the period 1990‐2004.
On Strategic Control

The purpose of this note is to clarify and complement several comments on my work [Chichilnisky, 1980, 1982a], which appeared in this Journal: Baigent [1987], Nitzan [1989], and Baigent [1989]. I shall offer two new results. The first result constructs a continuous, anonymous social selection rule that respects unanimity and the proximity of preferences, for a large family of preferences (Theorem 1). This complements the result of Nitzan [1989] and Baigent's [1989] extension of it and is achieved by accepting, as they do, that social outcomes be optimal choices, rather than rankings of all possible choices or social preferences This result is of interest because it appears to contradict the original impossibility theorem of Chichilnisky, which establishes that, for the same family of preferences, social aggregation rules with these properties do not exist (Theorem 2).
Does Legal Doctrine Matter? Unpacking Law and Policy Preferences on the U.S. Supreme Court

Judicial scholars often struggle to disentangle the effects of law and policy preferences on U.S. Supreme Court decision making. We employ a new approach to measuring the effect—if any—of the law on justices’ decisions. We use positions taken on Supreme Court cases by members of Congress and presidents to identify policy components of voting. Doing so enables us to isolate the effects of three legal doctrines: adherence to precedent, judicial restraint, and a strict interpretation of the First Amendment’s protection of speech clause. We find considerable evidence that legal factors play an important role in Supreme Court decision making. We also find that the effect of legal factors varies across justices.
The Adoption of Proportional Representation

The debate between economic and political explanations of the adoption of proportional representation (PR) has yielded mixed results. We reexamine this debate and argue that one has to take the different levels on which the causal mechanisms are located into account. This leads to a novel reformulation of Rokkan’s hypotheses: we claim that PR is introduced when legislators face strong district-level competition and when their parties expect to gain seats from a change of the electoral law. In the empirical part, we model legislators’ support for the PR adoption and evaluate the relative importance of district-level competition and vulnerability resulting from electoral inroads made by Social Democratic candidates; partisan calculations arising from disproportionalities in the allocation of votes to seats; and economic conditions at the district-level, specifically variation in skill profiles. Support for the adoption of PR is explained by a combination of district vulnerabilities and seat-vote disproportionality.
Quiver Gauge Theory and Conformality at the TeV Scale

Abstract This review describes the conformality approach to extending the standard model of particle phenomenology using an assumption of no conformal anomaly at high energy. Topics include quiver gauge theory, the conformality approach to phenomenology, strong–electroweak unification at 4 TeV, cancellation of quadratic divergences, cancellation of U ( 1 ) anomalies and a dark matter candidate.
The Microeconomics of Depression Unemployment

Microeconomic evidence reveals that the incidence and duration of unemployment in the 1930s varied significantly within the labor force. Long-term unemployment, which was especially high by historical standards, may have been exacerbated by federal relief policies.
Eclectic Distributional Ethics

Utilitarians, maximinners, prioritarians, and sufficientarians each provide examples of situations demonstrating, often apparently compellingly, that a sensible ethical observer must adopt their vi...
Evaluating the effectiveness of generic advertising versus nonadvertising marketing activities on New York State milk markets

This study distinguishes nonadvertising marketing activities from generic advertising and investigates their separate impacts on the retail demand for fluid milk in New York State. Advertising, having an estimated elasticity (of demand) of 0.038 using panel data, is found to be about five times as effective as nonadvertising; therefore, it remains the more powerful marketing tool. Such results have policy implications in benefit-cost analysis and optimal allocation of fluid-milk check-off funds. Our results suggest that NYS dairy producers have much to gain from investing more of their check-off budgets in advertising. [EconLit citations: Q11, M37]. © 2009 Wiley Periodicals, Inc.
Beyond Paternalism: The Role of Counsel for Children in Abuse and Neglect Proceedings

When children are abused or neglected, the State often intervenes and assumes care and control of the child. As a result, legal proceedings begin in a juvenile court. The decisions made during such proceedings directly impact the substantive and procedural due process rights of children. Juvenile courts routinely appoint lawyers to represent children in abuse and neglect cases. However, the appointed lawyers receive conflicting directives about their roles. Lawyers for children are often instructed to take on a guardian ad litem role through which they make a recommendation to the court about the “best interests” of the child, rather than to act in the traditional attorney role and advocate for the child client’s legal interests. This guardian ad litem model of lawyering is ineffective in the context of a rights-based juvenile court system. The better model is that of the traditional attorney who gives voice to the client’s wishes and advocates for the protection of the child’s legal rights. The traditional attorney model necessarily encompasses the best interests of the client while also giving voice to the child’s wishes. The model of representation for children in abuse and neglect proceedings must transcend the paternalistic notion that lawyers know what is best for children. Only true legal advocacy will effectively protect the legal rights of child clients. In juvenile proceedings, a child’s right to counsel should mean a right to counsel who functions as an advocate not as a guardian ad litem.
The effect of the Sarbanes-Oxley act on non-US companies cross-listed in the US

Abstract This paper uses a natural experiment to measure market response to the adoption of the Sarbanes–Oxley Act (ʽʽSOX"). Because SOX applies to all US public companies, US-based studies have difficulty separating the effects of contemporaneous events. However, controlled analysis is available: SOX applies to some cross-listed firms (those listed on level 2 or 3), but not to others (listed on level 1 or 4). By comparing reactions of SOX-exposed foreign firms to reactions of otherwise similar SOX-unexposed foreign firms, we can test investor beliefs about the costs and benefits of SOX in a way that is not cleanly available for US-based studies. We find that stock prices of foreign firms subject to SOX declined (increased) significantly, compared to cross-listed firms not subject to SOX and to non-cross-listed firms, during key announcements indicating that SOX would (would not) fully apply to cross-listed issuers. In cross-sectional tests, high-disclosing firms and firms from high-disclosing countries experienced the strongest declines, while faster-growing companies experienced weaker declines. This evidence is consistent with the view that investors expected the Sarbanes–Oxley Act to have a net negative effect on cross-listed foreign companies, with high-disclosing and low-growth companies suffering larger net costs, and faster-growing companies suffering smaller costs, particularly when they are located in poorly governed countries.
A Primer on Structured Finance

The traditional view of financial stability concentrates analytical efforts on the identification of increasing vulnerabilties prior to stress from individual failure in institutions, markets and infrastructure, assuming that the financial system is in equilibrium and adjusts when it experiences a shock. As opposed to this conventional approach, the presence of systemic vulnerabilties warrant the monitoring of ongoing developments in evolving areas of financial markets where the impact of unsustainable imbalances on financial stability is deemed most severe and widespread but difficult to measure, leave alone forecast. Given the increasing sophistication of financial products, the diversity and global reach of financial institutions, as well as the growing interdependence of financial markets and services, such areas exposed to extreme scenarios are likely to be found in financial innovation, where market forces and participants are left to their own devices and when complex incentive structures encourage greater risk taking in a benign economic environment but entail more adverse economic consequences when stress occurs.
A Modest Proposal: Recognizing (at Last) That the Federal Rules Do Not Declare That Discovery Is Presumptively Public

The theme of this event implies that there is considerable reason for alarm about “Secrecy in Litigation.” Against that backdrop, one who argues against public openness cannot avoid feeling like the Grinch. Consider the sort of hypothetical that would be launched against a pro-confidentiality position: Defendant produces, through discovery, a document from a member of its professional staff that acknowledges that one of defendant's products poses a significant danger to users of the product. Defendant has assiduously avoided release of this information and claimed that its product is safe. It then asks that the court keep its secret. Does one who says discovery is not inherently public insist that the court accede to this request? The easy answer is no; the court has more than enough discretion to refuse defendant's request and, presented with a situation as stark as that suggested by this example, it is likely that all, or nearly all, courts would refuse. But that scenario is not, I submit, the real problem. Rather, the real problem is that the overbroad notion that all information turned over in discovery (no matter what it contains, or what the court or even the parties, know about the material involved) is presumptively open to the public, even if no party wants to permit public access to the information. Yet, in court, representatives of the media still urge just such a broad proposition. Moreover, this position is said to be commanded by the Federal Rules of Civil Procedure and is occasionally accepted by courts as a decisive factor in determining whether use of discovery fruits may be restricted to litigation purposes.
Four Reasons To Teach Psychology To Legal Writing Students

Over the past quarter century we have learned a great deal about psychological biases that are by-products of the strategies we use in everyday reasoning. This essay invites educators to introduce some basic facts about these biases to students in legal writing courses. By teaching students to understand the psychological phenomena that underlie some of the core strategies of good legal writing, legal writing instructors may help students to internalize more of what they learn in legal writing classes. This will make it more likely that they will be able to transfer the skills to tasks performed in their legal careers. While a number of psychological biases are relevant to good legal writing, the essay describes four: the preference for simple writing; the confirmation bias (causing us to ignore evidence that contradicts positions we have taken); the correspondence bias (overemphasizing character and undervaluing context in explaining an individual’s conduct); and the bias blind spot (thinking we ourselves are less susceptible to these biases than are people in general). The essay suggests ways to introduce each of these psychological phenomena into the legal writing course in ways that should enhance the student’s sensitivity to these important issues, and not take up too much class time.
A replication about cause–effect linkage benefits and managers’ strategic judgments

Managers must constantly scan a sea of new information and judge (1) if this information is relevant to evaluating the firm’s strategy (i.e. information relevance judgments), and (2) if this information suggests the firm’s strategy is appropriate or inappropriate (i.e. strategy appropriateness judgments). I examine these judgments in a behavioral experiment with Amazon Mechanical Turk workers. Replicating prior research, I test how these judgments are affected by formatting the firm’s strategy to include cause–effect linkages, a defining feature of strategic performance measurement systems. I also add a manipulation of causal relatedness, i.e. the subjective probability of a given cause–effect linkage, especially as it relates to the inferred bridging mediators that can logically connect a cause–effect linkage. Like prior research, I find that adding cause–effect linkages improves managers’ information relevance judgments, specifically improving managers’ ability to filter out irrelevant information. Extending prior research, I also find that cause–effect linkages only improve strategy appropriateness judgments when those linkages have high causal relatedness. Experience also moderates this latter improvement such that it is limited to those with relatively low experience.
A Remark on the Concentration Compactness Principle in Critical Dimension

We prove some refinements of concentration compactness principle for Sobolev space $W^{1,n}$ on a smooth compact Riemannian manifold of dimension $n$. As an application, we extend Aubin's theorem for functions on $\mathbb{S}^{n}$ with zero first order moments of the area element to higher order moments case. Our arguments are very flexible and can be easily modified for functions satisfying various boundary conditions or belonging to higher order Sobolev spaces.
Dynamics of Research and Strategic Trading

We study how dynamic research affects information acquisition in financial markets. In our strategic trading model, the trader performs costly research to generate private information but does not always succeed. Optimal research activity responds to market conditions and generates novel empirical and policy implications. First, more frequent public disclosures can “crowd in” private information acquisition, and increase price informativeness and harm liquidity, instead of “leveling the playing field.” Second, measures of research activity may be negatively associated with informed trading. Finally, policies that improve research effectiveness or increase market participation by uninformed investors can simultaneously improve price informativeness and liquidity.
Predicting Emotions Perceived from Sounds

Sonification is the science of communication of data and events to users through sounds. Auditory icons, earcons, and speech are the common auditory display schemes utilized in sonification, or more specifically in the use of audio to convey information. Once the captured data are perceived, their meanings, and more importantly, intentions can be interpreted more easily and thus can be employed as a complement to visualization techniques. Through auditory perception it is possible to convey information related to temporal, spatial, or some other context-oriented information. An important research question is whether the emotions perceived from these auditory icons or earcons are predictable in order to build an automated sonification platform. This paper conducts an experiment through which several mainstream and conventional machine learning algorithms are developed to study the prediction of emotions perceived from sounds. To do so, the key features of sounds are captured and then are modeled using machine learning algorithms using feature reduction techniques. We observe that it is possible to predict perceived emotions with high accuracy. In particular, the regression based on Random Forest demonstrated its superiority compared to other machine learning algorithms.
Capital Meets Democracy: The Impact of Franchise Extension on Sovereign Bond Markets

By giving political rights to poor voters, did democratic political institutions pose a risk to financial capital? This paper draws lessons from the reaction of sovereign bond markets to franchise extensions between 1800 and 1920. If franchise extension transferred political power from economic and financial elites to workers, as redistributive theories of democratization suggest, then this should have resulted in a fall in the market price (increase in the yield) of a country’s bonds. Exploiting the asynchronous timing of franchise reforms across countries, we provide evidence that franchise extension contributed to large increases in the premium demanded by investors to hold sovereign debt, reflecting an increased risk of default. However, bond markets became less sensitive to franchise extensions over time, a pattern potentially due to the structure of inequality and the strategic adoption of institutions which protected financial interests.
Beamline Spectroscopy of Integrated Circuits With Hard X-Ray Transition Edge Sensors at the Advanced Photon Source

At Argonne National Laboratory, we are developing hard X-ray (2 to 20 keV) Transition Edge Sensor (TES) arrays for beamline science. The significantly improved energy resolution provided by superconducting detectors compared to semiconductor-based energy-dispersive detectors, but with better collection efficiency than wavelength-dispersive instruments, will enable greatly improved X-ray emission and absorption spectroscopic measurements. A prototype instrument with 24 microwave-frequency multiplexed pixels is now in testing at the Advanced Photon Source (APS) 1-BM beamline. Initial measurements show an energy resolution ten times better (150 eV compared to $ 15 eV) than the silicon-drift detectors currently available to APS beamline users, and in particular demonstrate the ability to resolve closely-spaced emission lines in samples containing multiple transition metal elements, such as integrated circuits. Comparing fluorescence spectra of integrated circuits measured with our TESs at the beamline to those measured with silicon detectors, we find emission lines and elements largely hidden (e.g. Hf alongside Cu) from a semiconductor-based detector but well resolved by a TES. This directly shows the strengths of TES-based instruments in fluorescence mapping.
Strong approximation of time-changed stochastic differential equations involving drifts with random and non-random integrators

The rates of strong convergence for various approximation schemes are investigated for a class of stochastic differential equations (SDEs) which involve a random time change given by an inverse subordinator. SDEs to be considered are unique in two different aspects: (i) they contain two drift terms, one driven by the random time change and the other driven by a regular, non-random time variable; (ii) the standard Lipschitz assumption is replaced by that with a time-varying Lipschitz bound. The difficulty imposed by the first aspect is overcome via an approach that is significantly different from a well-known method based on the so-called duality principle. On the other hand, the second aspect requires the establishment of a criterion for the existence of exponential moments of functions of the random time change.
Cortical surface alignment using geometry driven multispectral optical flow

Spatial normalization is frequently used to map data to a standard coordinate system by removing inter-subject morphological differences, thereby allowing for group analysis to be carried out. In this paper, we analyze the geometry of the cortical surface using two shape measures that are the key to distinguish sulcal and gyral regions from each other. Then a multispectral optical flow (OF) warping procedure that aims to align the shape measure maps of an atlas and a subject brain’s normalized maps is described. The variational problem to estimate the OF field is solved using a Euclidean framework. After warping one brain given the OF result, we obtain a better structural and functional alignment across multiple brains.
On-line restricted caching

We study the on-line caching problem in a restricted cache where each memory item can be placed in only a restricted subset of cache locations. Examples of restricted caches in practice include victim caches, assist caches, and skew caches. To the best of our knowledge, all previous on-line caching studies have considered on-line caching in identical or fully-associative caches where every memory item can be placed in any cache location.In this paper, we focus on companion caches, a simple restricted cache that includes victim caches and assist caches as special cases. Our results show that restricted caches are significantly more complex than identical caches. For example, we show that the commonly studied Least Recently Used algorithm is not competitive unless cache reorganization is allowed while the performance of the First In First Out algorithm is competitive but not optimal. We also present two near optimal algorithms for this problem as well as lower bound arguments.
On-Line Algorithms for the Dynamic Traveling Repair Problem

We consider the dynamic traveling repair problem in which requests with deadlines arrive through time on points in a metric space. Servers move from point to point at constant speed. The goal is to plan the motion of servers so that the maximum number of requests are met by their deadline. We consider a restricted version of the problem in which there is a single server and the length of time between the arrival of a request and its deadline is constant. We give upper bounds for the competitive ratio of two very natural algorithms as well as several lower bounds for any deterministic algorithm. Most of the results in this paper are expressed as a function of β, the diameter of the metric space. In particular, we prove that the upper bound given for one of the two algorithms is within a constant factor of the best possible competitive ratio.
Planning With Learned Dynamics: Probabilistic Guarantees on Safety and Reachability via Lipschitz Constants

We present a method for feedback motion planning of systems with unknown dynamics which provides probabilistic guarantees on safety, reachability, and goal stability. To find a domain in which a learned control-affine approximation of the true dynamics can be trusted, we estimate the Lipschitz constant of the difference between the true and learned dynamics, and ensure the estimate is valid with a given probability. Provided the system has at least as many controls as states, we also derive existence conditions for a one-step feedback law which can keep the real system within a small bound of a nominal trajectory planned with the learned dynamics. Our method imposes the feedback law existence as a constraint in a sampling-based planner, which returns a feedback policy around a nominal plan ensuring that, if the Lipschitz constant estimate is valid, the true system is safe during plan execution, reaches the goal, and is ultimately invariant in a small set about the goal. We demonstrate our approach by planning using learned models of a 6D quadrotor and a 7DOF Kuka arm. We show that a baseline which plans using the same learned dynamics without considering the error bound or the existence of the feedback law can fail to stabilize around the plan and become unsafe.
Exploiting signal flow and logic dependency in standard cell placement

Most existing placement algorithms consider only connectivity information during the placement process, and ignore other information available from the higher levels of design process. In this paper, we exploit the use of signal flow and logic dependency in standard cell placement by using the maximum fanout-free cone (MFFC) decomposition technique. We developed a containment tree based algorithm for splitting large MFFCs into smaller ones to get clusters with restricted sizes. We also developed a placement algorithm, named MFFC-TW, which first clusters the circuit based on MFFC decomposition and then feeds the clustered circuit to the Timberwolf 6.0 placement package. Very promising experimental results were obtained.
The Firm Next Door: Using Satellite Images to Study Local Information Advantage

We use novel satellite data that track the number of cars in the parking lots of 92,668 stores for 71 publicly listed U.S. retailers to study the local information advantage of institutional investors. We establish car counts as a timely measure of store‐level performance and find that institutional investors adjust their holdings in response to the performance of local stores, and that these trades are profitable on average. These results suggest that local investors have an advantage when processing information about nearby operations. However, some institutional investors do not adjust for the quality of their local information and continue to rely on local signals even when they are poor predictors of firm performance and returns. This overreliance on poor local information is reduced for institutional investors with greater industry expertise and those with greater incentives to maximize short‐term trading profits.
Anonymous Equity Research

Crowdsourced financial information platforms often allow content contributors to publish equity research anonymously. This study examines whether investors value or discount information in anonymous equity research. In the short window around research releases, we find that investors’ stock price reaction to anonymous research is muted in comparison to nonanonymous research. Consistent with credibility concerns influencing investor response, we document that this discount to anonymous research dissipates as the monitoring of content contributors intensifies and as authors develop a reputation for high‐quality reporting. In addition, we perform a content analysis on the research reports and find that the muted market reaction to anonymous equity research is robust to controlling for textual attributes of information content, further supporting our inference that investors’ are concerned about the credibility of anonymous equity research.
Bootstrap inference for quantile-based modal regression

In this article, we develop uniform inference methods for the conditional mode based on quantile regression. Specifically, we propose to estimate the conditional mode by minimizing the derivative o...
The effect of in-person primary and secondary school instruction on county-level SARS-CoV-2 spread in Indiana.

OBJECTIVE: To determine the county-level effect of in-person primary and secondary school reopening on daily cases of SARS-CoV-2 in Indiana. METHODS: This is a county-level population-based study using a panel data regression analysis of the proportion of in-person learning to evaluate an association with community-wide daily new SARS-CoV-2 cases. The study period was July 12-October 6, 2020. We included 73 out of 92 (79.3%) Indiana counties in the analysis, accounting for 85.7% of school corporations and 90.6% of student enrollment statewide. The primary exposure was the proportion of students returning to in-person instruction. The primary outcome was the daily new SARS-CoV-2 cases per 100,000 residents at the county level. RESULTS: There is a statistically significant relationship between the proportion of students attending K-12 schools in-person and the county level daily cases of SARS-CoV-2 28 days later. For all ages, the coefficient of interest (s) is estimated at 3.36 (95% CI: 1.91-4.81; p < 0.001). This coefficient represents the effect of a change the proportion of students attending in-person on new daily cases 28 days later. For example, a 10 percentage point increase in K-12 students attending school in-person is associated with a daily increase in SARS-CoV-2 cases in the county equal to 0.336 cases/100,000 residents of all ages. CONCLUSION: In-person primary and secondary school is associated with a statistically significant but proportionally small increase in the spread of SARS-CoV-2 cases.
Localization and eigenvalue statistics for the lattice Anderson model with discrete disorder

We prove localization and probabilistic bounds on the minimum level spacing for the Anderson tight-binding model on the lattice in any dimension, with single-site potential having a discrete distri...
Heterogeneous, Defect-Rich Battery Particles and Electrodes: Why Do They Matter, and How Can One Leverage Them?

Correlating local materials properties with global battery electrochemistry is nontrivial, because battery particles and electrodes are heterogeneous and defect-rich. Pinpointing the root cause of ...
Accrual Accounting and Resource Allocation: A General Equilibrium Analysis

This paper evaluates the role of accrual accounting in improving firms' production decisions and resource allocation across firms. I introduce two imperfect firm-performance measures, cash flows and accounting earnings, into a general equilibrium model with heterogeneous firms under imperfect information. The model demonstrates that improvements in measurement systems lead to more informed decisions on the part of firms and ultimately to allocation of greater resources to high-productivity firms via the product and input markets. Estimated parameter values are consistent with accrual accounting improving managers' information about current productivity by providing a better measure of historical firm performance. Quantitative analysis suggests that introducing accrual-accounting information on top of cash-accounting information leads to a 0.5% increase in aggregate U.S. productivity and a 0.7% increase in aggregate U.S. output via improved resource allocation. The corresponding estimates for China and India, as benchmarks for developing countries, are larger: a 1.5% to 2.3% increase in aggregate productivity and a 2.3% to 3.4% increase in aggregate output. I conclude that accrual accounting plays a significant role in determining aggregate productivity via improved resource allocation.
The impact of arbitrage on market liquidity

Abstract I study how arbitrage affects liquidity by analyzing several billion trades in the American Depositary Receipt (ADR) market from 2001 to 2016. Price deviations persist, on average, for 12 min, and mainly arise because of price pressure. Impulse response functions estimated at 1 min intervals indicate that a positive shock to arbitrage—simultaneous trades of the ADR and the home-market share in the opposite direction—decreases deviations and bid-ask spreads. I confirm these findings by exploiting institutional details that create exogenous variation in the impediments to arbitrage across days. Overall, these results suggest that arbitrage decreases price pressure and provides liquidity.
Critical decisions for crisis management: An introduction

In the presence of crisis, such as global COVID-19 pandemic crisis, governments have more and more take critical decisions to cope with consequential environmental threats in the presence of highly restricted time. This chapter provides a simple description of techniques of decision making in different environments/conditionsof crisis management and how that process is influenced by manifold social, economic and/or technical factors; ultimately it is presented how the approach of improvisation can support the process of decision-makingto cope with unforeseen and new events, rapid changes, turbulent environment and/or specific situations of emergency. Keywords. Critical decision, Decision making, Decision support, Uncertainty, COVID-19, Crisis management, Problem solving, Bounded rationality, Improvisation. JEL. F21, F68, O53, K23 .
Color-octet scalars in Dirac gaugino models with broken $R$ symmetry

In this work we study the collider phenomenology of color-octet scalars (sgluons) in supersymmetric models with Dirac gaugino masses that feature an explicitly broken R symmetry (R-broken models). We construct such models by augmenting minimal R-symmetric models with a fairly general set of supersymmetric and softly supersymmetry-breaking operators that explicitly break R symmetry. We then compute the rates of all significant two-body decays and highlight new features that appear as a result of R symmetry breaking, including enhancements to extant decay rates, novel tree- and loop-level decays, and improved cross sections of single sgluon production. We demonstrate in some detail how the familiar results from minimal R-symmetric models can be obtained by restoring R symmetry. In parallel to this discussion, we explore constraints on these models from the Large Hadron Collider. We find that, in general, R symmetry breaking quantitatively affects existing limits on color-octet scalars, perhaps closing loopholes for light CP-odd (pseudoscalar) sgluons while opening one for a light CP-even (scalar) particle. Qualitatively, however, we find that — much as for minimal R-symmetric models, despite stark differences in phenomenology — scenarios with broken R symmetry and two sgluons below the TeV scale can be accommodated by existing searches.
From algebraic geometry to machine learning

David Mumford made groundbreaking contributions in many fields, including the pure mathematics of algebraic geometry and the applied mathematics of machine learning and artificial intelligence. His work in both fields influenced my career at several key moments.
Complex Ratio Masking For Singing Voice Separation

Music source separation is important for applications such as karaoke and remixing. Much of previous research focuses on estimating short-time Fourier transform (STFT) magnitude and discarding phase information. We observe that, for singing voice separation, phase can make considerable improvement in separation quality. This paper proposes a complex ratio masking method for voice and accompaniment separation. The proposed method employs DenseUNet with self attention to estimate the real and imaginary components of STFT for each sound source. A simple ensemble technique is introduced to further improve separation performance. Evaluation results demonstrate that the proposed method outperforms recent state-of-the-art models for both separated voice and accompaniment.
Environmental and energy efficiency evaluation of residential gas and heat pump heating

Energy efficiency and source air pollutant emission factors of gas heaters, gas engine heat pumps, and electric heat pumps for domestic heating has been evaluated and compared
Multimodal Face Synthesis From Visual Attributes

Synthesis of face images from visual attributes is an important problem in computer vision and biometrics due to its applications in law enforcement and entertainment. Recent advances in deep generative networks have made it possible to synthesize high-quality face images from visual attributes. However, existing methods are specifically designed for generating unimodal images (i.e., visible faces) from attributes. In this paper, we propose a novel generative adversarial network which simultaneously synthesizes identity preserving multimodal face images (i.e., visible, sketch, thermal, etc.) from visual attributes without requiring paired data in different domains for training the network. We introduce a novel generator with multimodal stretch-out modules to simultaneously synthesize multimodal face images. Additionally, multimodal stretch-in modules are introduced in the discriminator which discriminate between real and fake images. Extensive experiments and comparison with several state-of-the-art methods are performed to verify the effectiveness of the proposed attribute-based multimodal synthesis method.
Choosing between incompatible ideals

Abstract Suppose I and J are proper ideals on some set X . We say that I and J are incompatible if I ∪ J does not generate a proper ideal. Equivalently, I and J are incompatible if there is some A ⊆ X such that A ∈ I and X ∖ A ∈ J . If some B ⊆ X is either in I ∖ J or in J ∖ I , then we say that B chooses between I and J . We consider the following Ramsey-theoretic problem: Given several pairs ( I 1 , J 1 ) , ( I 2 , J 2 ) , … , ( I k , J k ) of incompatible ideals on a set X , find some A ⊆ X that chooses between as many of these pairs of ideals as possible. The main theorem is that for every n ∈ N , there is some I ( n ) ∈ N such that given at least I ( n ) pairs of incompatible ideals on any set X , there is some A ⊆ X choosing between at least n of them. This theorem is proved in two main steps. The first step is to identify a (purely finitary) problem in extremal combinatorics, and to show that our problem concerning ideals is equivalent to this combinatorial problem. The second step is to analyze the combinatorial problem in order to show that the number I ( n ) described above exists, and to put bounds on it. We show 1 2 n log 2 n − O ( n ) I ( n ) n ln n + O ( n ) . The upper bound is proved by considering a different but closely related combinatorial problem involving hypergraphs, which may be of independent interest. We also investigate some applications of this theorem to a problem concerning conditionally convergent series.
Rapid Cortical Adaptation and the Role of Thalamic Synchrony during Wakefulness

Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in-vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex. SIGNIFICANCE STATEMENT Rapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical sub-populations of neurons.