cssi/SciSciGPT-SciSciNet huggingface dataset:
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

Pre-trained transformer models have shown enormous success in improving performance on several downstream tasks. However, fine-tuning on a new task still requires large amounts of task-specific labeled data to achieve good performance. We consider this problem of learning to generalize to new tasks, with a few examples, as a meta-learning problem. While meta-learning has shown tremendous progress in recent years, its application is still limited to simulated problems or problems with limited diversity across tasks. We develop a novel method, LEOPARD, which enables optimization-based meta-learning across tasks with a different number of classes, and evaluate different methods on generalization to diverse NLP classification tasks. LEOPARD is trained with the state-of-the-art transformer architecture and shows better generalization to tasks not seen at all during training, with as few as 4 examples per label. Across 17 NLP tasks, including diverse domains of entity typing, natural language inference, sentiment analysis, and several other text classification tasks, we show that LEOPARD learns better initial parameters for few-shot learning than self-supervised pre-training or multi-task training, outperforming many strong baselines, for example, yielding 14.6% average relative gain in accuracy on unseen tasks with only 4 examples per label.
Predictive and Causal Implications of using Shapley Value for Model Interpretation.

Shapley value is a concept from game theory. Recently, it has been used for explaining complex models produced by machine learning techniques. Although the mathematical definition of Shapley value is straight-forward, the implication of using it as a model interpretation tool is yet to be described. In the current paper, we analyzed Shapley value in the Bayesian network framework. We established the relationship between Shapley value and conditional independence, a key concept in both predictive and causal modeling. Our results indicate that, eliminating a variable with high Shapley value from a model do not necessarily impair predictive performance, whereas eliminating a variable with low Shapley value from a model could impair performance. Therefore, using Shapley value for feature selection do not result in the most parsimonious and predictively optimal model in the general case. More importantly, Shapley value of a variable do not reflect their causal relationship with the target of interest.
Logarithmic Regret for Adversarial Online Control

We introduce a new algorithm for online linear-quadratic control in a known system subject to adversarial disturbances. Existing regret bounds for this setting scale as $\sqrt{T}$ unless strong stochastic assumptions are imposed on the disturbance process. We give the first algorithm with logarithmic regret for arbitrary adversarial disturbance sequences, provided the state and control costs are given by known quadratic functions. Our algorithm and analysis use a characterization for the optimal offline control law to reduce the online control problem to (delayed) online learning with approximate advantage functions. Compared to previous techniques, our approach does not need to control movement costs for the iterates, leading to logarithmic regret.
A LASSO-Inspired Approach for Localizing Power System Infeasibility

A method is proposed to identify and localize the cause of network collapse with augmented power flow analysis for a grid model with insufficient resources. Owing to heavy network loading, insufficient generation, component failures and unavoidable disturbances, power grid models can sometimes fail to converge to a feasible solution for a steady-state power flow study. For applications such as system expansion planning, it is desirable to locate the system buses that are contributing to network infeasibilities to facilitate corrective actions. This paper proposes a novel LASSO-inspired regularization of the power flow matrix that enforces sparsity to localize and quantify infeasibilities in the network. One of the examples demonstrates how the proposed method is capable of localizing a source of blackout to a single dominant bus on an 80k+ bus eastern interconnection model.
New Verification Schemes for Frequency-Based Functions on Data Streams

We study the general problem of computing frequency-based functions, i.e., the sum of any given function of data stream frequencies. Special cases include fundamental data stream problems such as computing the number of distinct elements (F₀), frequency moments (F_k), and heavy-hitters. It can also be applied to calculate the maximum frequency of an element (F_{∞}). Given that exact computation of most of these special cases provably do not admit any sublinear space algorithm, a natural approach is to consider them in an enhanced data streaming model, where we have a computationally unbounded but untrusted prover that can send proofs or help messages to ease the computation. Think of a memory-restricted client delegating the computation to a powerful cloud service. The client does not blindly trust the cloud, and with its limited memory, it wants to verify the proof that the cloud sends. Chakrabarti et al. (ICALP '09) introduced this model as the annotated data streaming model and showed that multiple problems including exact computation of frequency-based functions - that have no sublinear algorithms in basic streaming - do have algorithms, also called schemes, in the annotated streaming model with both space and proof-length sublinear in the input size. We give a general scheme for computing any frequency-based function with both space usage and proof-size of O(n^{2/3}log n) bits, where n is the size of the universe. This improves upon the best known bound of O(n^{2/3}log^{4/3} n) given by the seminal paper of Chakrabarti et al. and as a result, also improves upon the best known bounds for the important special cases of computing F₀ and F_{∞}. We emphasize that while being quantitatively better, our scheme is also qualitatively better in the sense that it is simpler than the previously best scheme that uses intricate data structures and elaborate subroutines. Our scheme uses a simple technique tailored for this model: the verifier solves the problem partially by running an algorithm known to be helpful for it in the basic (sans prover) streaming model and then takes the prover’s help to solve the remaining part.
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification

We consider the problem of learning efficient and inductive graph convolutional networks for text classification with a large number of examples and features. Existing state-of-the-art graph embedding based methods such as predictive text embedding (PTE) and TextGCN have shortcomings in terms of predictive performance, scalability and inductive capability. To address these limitations, we propose a heterogeneous graph convolutional network (HeteGCN) modeling approach that unites the best aspects of PTE and TextGCN together. The main idea is to learn feature embeddings and derive document embeddings using a HeteGCN architecture with different graphs used across layers. We simplify TextGCN by dissecting into several HeteGCN models which (a) helps to study the usefulness of individual models and (b) offers flexibility in fusing learned embeddings from different models. In effect, the number of model parameters is reduced significantly, enabling faster training and improving performance in small labeled training set scenario. Our detailed experimental studies demonstrate the efficacy of the proposed approach.
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems

Despite deep neural network (DNN)'s impressive prediction performance in various domains, it is well known now that a set of DNN models trained with the same model specification and the exact same training data could produce very different prediction results. People have relied on the state-of-the-art ensemble method to estimate prediction uncertainty. However, ensembles are expensive to train and serve for web-scale traffic systems. In this paper, we seek to advance the understanding of prediction variation estimated by the ensemble method. Through empirical experiments on two widely used benchmark datasets Movielens and Criteo in recommender systems, we observe that prediction variations come from various randomness sources, including training data shuffling, and random initialization. When we add more randomness sources to ensemble members, we see higher prediction variations among these ensemble members, and more accurate mean prediction. Moreover, we propose to infer prediction variation from neuron activation strength and demonstrate its strong prediction power. Our approach provides a simple way for prediction variation estimation, and opens up new opportunities for future work in many interesting areas (e.g., model-based reinforcement learning) without relying on serving expensive ensemble models.
Debt, inflation and central bank independence

Abstract Increasing the independence of a central bank from political influence, although ex-ante socially beneficial and initially successful in reducing inflation, would ultimately fail to lower inflation permanently. The smaller anticipated policy distortions implemented by a more independent central bank would induce the fiscal authority to decrease current distortions by increasing the deficit. Over time, inflation would increase to accommodate a higher public debt. By contrast, imposing a strict inflation target would lower inflation permanently and insulate the primary deficit from political distortions.
Are Earnings Inequality and Mobility Overstated? the Impact of Non-Classical Measurement Error

Abstract Measures of inequality and mobility based on self-reported earnings reflect attributes of both the joint distribution of earnings across time and the joint distribution of measurement error and earnings. While classical measurement error would increase measures of inequality and mobility, there is substantial evidence that measurement error in earnings is not classical. In this paper, we present the analytical links between nonclassical measurement error and some summary measures of inequality and mobility. The empirical importance of nonclassical measurement error is explored using the Survey of Income and Program Participation (SIPP) matched to tax records. We find that the effects of nonclassical measurement error are large. However, these nonclassical effects are largely offsetting when estimating mobility, as measured by the intertemporal correlation in earnings. As a result, SIPP estimates of the correlation are similar to estimates based on tax records, though SIPP estimates of inequality ...
The challenges of WTO law: strategies for developing country adaptation

Although developing countries vary significantly in terms of trading profiles, they generally face three primary challenges if they are to participate effectively in the WTO dispute settlement system. These challenges are: (i) a relative lack of legal expertise in WTO law; (ii) constrained financial resources, including for the hiring of outside counsel; and (iii) fear of political and economic pressure. We can roughly categorize these challenges as constraints of law, money, and politics. This article explores various strategies for responding to these challenges, none of which involves a modification of the rules of the WTO's Dispute Settlement Understanding.
The Idea of "Too Much Law"

If brevity is the soul of wit, what is verbosity the soul of? Of overweening, inefficient, even tyrannical government—at least according to the critics who, for years, have bewailed the fact that federal laws and regulations are growing by the minute, by the mile, and by the metric ton. These critics argue that America suffers from “hyperlexis,” or the existence of too much law, and their calls for remedies to that malady are now finding a receptive ear in the highest echelons of the federal government. The idea that there is too much federal law has been embraced by all three branches of government and by members of both major political parties. In order to analyze these claims, this Article taxonomizes and evaluates the most common claims of hyperlexis in federal law, including the claims that federal laws and regulations are too numerous, too complex, too costly, and too invasive of state and local prerogatives. Once these arguments are untangled, their individual flaws become evident. Almost each account of federal hyperlexis faces serious conceptual obstacles in either its technique for measuring hyperlexis or in its method for remedying it. This Article then notes one argument that has not been convincingly made: the argument that the proliferation of federal law results from a democratic failure. No public choice account plausibly explains the persistent and widespread overgrowth of law. But the absence of such an account cannot, of course, put a stake through the heart of the hyperlexis critique, which implicates deeply embedded philosophical beliefs concerning the nature of individual liberty and the proper role of government. The critique represents a challenge to the legitimacy of law that current theories of law’s legitimacy are not oriented to deflect. We are left, then, in the worst of both worlds. The hyperlexis critique does not map out a means to achieve the goal of reducing the amount of federal law, but the currency of the critique has corrosive effects upon the sociological legitimacy of federal law and institutions.
Corporate Assets and Enhancing Firm Value: Evidence from the Market for Bank Branches in the US

This study examines the purchase and sale of US bank branches. Large and unproductive banks with less capital sell branches to smaller and more efficient banks with more capital. I use an event study, and find a significant increase in value for both parties. These valuation effects are driven by slightly better operating performance, faster growth in loans, and a smooth transfer of purchased deposits for buyers and by improved operating performance and no substantial decrease in the growth of loans and deposits for sellers. Overall, the evidence shows that branch dealmakers operate efficiently by reallocating branches to better uses.
The regulatory choice of noncompliance in emissions trading programs

This paper addresses the following question: To achieve a fixed aggregate emissions target cost-effectively, should emissions trading programs be designed and implemented to achieve full compliance, or does allowing a certain amount of noncompliance reduce the costs of reaching the emissions target? The total costs of achieving the target consist of aggregate abatement costs, monitoring costs, and the expected costs of collecting penalties from noncompliant firms. Under common assumptions, I show that allowing noncompliance is cost-effective only if violations are enforced with an increasing marginal penalty. However, one can design a policy that induces full compliance with a constant marginal penalty that meets the aggregate emissions target with lower expected costs. This last result does not depend on setting an arbitrarily high constant marginal penalty. In fact, the marginal penalty need not be higher than the equilibrium marginal penalty under the policy with the increasing marginal penalty, and can actually be lower. Finally, tying the marginal penalty directly to the permit price allows the policy objective to be achieved without any knowledge of firms’ abatement costs.
When Voluntary, Incentive-Based Controls Fail: Structuring a Regulatory Response to Agricultural Nonpoint Source Water Pollution

This article is part of the Symposium, Sustainable Agriculture: Food for the Future. Recognizing that, to date, farms had largely escaped regulation under the Clean Water Act, and that agricultural nonpoint source pollution is a leading contributor to impaired water quality, this article advocates for a regulatory response to such pollution. It considers existing programs to control nonpoint source pollution and demonstrates that they are inadequate. The article makes three recommendations: (1) an increased federal regulatory presence is needed; (2) the costs of implementing nonpoint source controls should be distributed in a pragmatic way that recognizes the extraordinary organizational presence and political clout of the agriculture industry; and (3) measures that promise water quality improvements beyond baseline regulatory requirements should be encouraged through such innovative programs as pollution trading.
The Economic Value of Water Quality

Stated preference values for water quality ratings based on the US Environmental Protection Agency National Water Quality Inventory ratings provide an operational basis for benefit assessment. Iterative choice survey results for a very large, nationally representative, Web-based panel imply an average valuation of $32 for each percent increase in lakes and rivers in the region for which water quality is rated “Good.” Valuations are skewed, with the mean value more than double the median. Sources of heterogeneity in benefit values include differences in responses to average water quality information and the base level of water quality. Conjoint estimates are somewhat lower than the iterative choice values. The annual economic value of the decline in inland US water quality from 1994 to 2000 is over $20 billion.
Constrained Efficient Borrowing with Sovereign Default Risk

Using a quantitative sovereign default model, we characterize constrained efficient borrowing by a Ramsey government that commits to income-history-contingent borrowing paths taking as given ex-post optimal future default decisions. The Ramsey government improves upon the Markov government because it internalizes the effects of borrowing decisions in period t on borrowing opportunities prior to t. We show the effect of borrowing decisions in t on utility flows prior to t can be encapsulated by two single dimensional variables. Relative to a Markov government, the Ramsey government distorts borrowing decisions more when bond prices are more sensitive to borrowing, and changes in bond prices have a larger effect on past utility. In a quantitative exercise, more than 80% of the default risk is eliminated by a Ramsey government, without decreasing borrowing. The Ramsey government also has a higher probability of completing a successful deleveraging (without defaulting), while smoothing out the fiscal consolidation.
Transnational Labor Regulation and the Limits of Governance

Governance theories of regulation can be useful in describing and conceptualizing new forms of transnational labor regulation (TLR) that have emerged in a context of weak state regulatory capacity. This Article argues, however, that the prominent governance models that have been applied to TLR, namely systems theory, responsive regulation, and new governance are not suited to the exigencies of labor regulation in developing states. Accordingly, this Article proposes an alternative "integrative approach" to transnational labor regulation that draws upon the insights of governance theory, but that is committed to developing state capacity where the state has a comparative advantage over non-state regulation in realizing the goals of TLR.
Factors affecting secondary share offerings in the IPO process

Abstract We investigate whether the sale of secondary shares in the IPO process is affected by an issuing firm's market-timing and window-dressing activities. We find that secondary share offerings in IPOs exhibit positive autocorrelation, and the positive autocorrelation is mainly affected by the overall stock market return. Similar to the IPO wave, this finding suggests that favorable market conditions attract existing pre-IPO shareholders to sell their shares in IPOs and cause the clustering of secondary share offering in IPOs. In addition, we find that window dressing has a significant effect on both the probability of secondary share offering and the proportion of secondary shares offered in an IPO. The result is robust after controlling for firm age, industry affiliation, and other factors. Our result also indicates that the number of firms offering secondary shares in IPOs, the probability of secondary share offerings, and the proportion of secondary shares offered in IPOs are significantly lower in the Internet bubble period.
Platform Preannouncement Strategies: The Strategic Role of Information in Two-Sided Markets Competition

The release of a new platform version is often preceded by prelaunch activities including a preannouncement of new features, improvements, and other innovations. The information contained within th...
Crime, Freedom and Civic Bonds: Arthur Ripstein’s Force and Freedom: Kant’s Legal and Political Philosophy

There is no question Arthur Ripstein’s Force and Freedom is an engaging and powerful book which will inform legal philosophy, particularly Kantian theories, for years to come. The text explores with care Kant’s legal and political philosophy, distinguishing it from his better known moral theory. Nor is Ripstein’s book simply a recounting of Kant’s legal and political theory. Ripstein develops Kant’s views in his own unique vision illustrating fresh ways of viewing the entire Kantian project. But the same strength and coherence which ties the book to Kant’s important values of independence blinds the work to our shared moral ties grounded in other political values. Ripstein’s thoughts on punishment are novel in that he embeds criminal law, both in its retributivist and consequentialist facets, into Kant’s overarching political philosophy to show how criminal law can be seen as one aspect of the supremacy of public law. But a criminal law solely focused on the preservation of freedom takes little notice of the ways criminal law need expand its view to account for how a polity can restore the victim of a crime back to civic equality, reincorporate offenders after they have been punished and cannot leave past offenders isolated and likely to reoffend, resulting in the rotating door prison system and communities of innocents who remain preyed upon by career criminals. Lastly, a political theory that does not prize our civic bonds will ignore the startling balkanization of our criminal punishment practices, where policing, arresting and imprisonment become tools of racial and social oppression. In illustrating the benefits in viewing criminal law as a coherent part of Kant’s political theory of freedom, Ripstein also highlights what is absent. It then becomes clear that though Kant presents one important facet of punishment, only a republican political theory can meet the most pressing moral demands of punishment by reminding us that criminal law must be used to preserve and strengthen civic society.
Recycling Texts or Stealing Time?: Plagiarism, Authorship, and Credit in Science

Scientific plagiarism is as sui generis as the author function in science. A study of the specificity of scientific plagiarism and the ways in which it diverges from appropriation in other disciplines allows us to question traditional definitions that focus on the copying of published copyrighted materials. The form of plagiarism that is most damaging to scientists does not involve publications, is largely outside the scope of copyright law, and is unlikely to be detected by textual-similarity algorithms. The same features that make this kind of plagiarism difficult to identify and control also provide a powerful window on the unique construction of authorial credit in science, the problems of peer review, and the limitations of plagiarism surveillance technologies.
Analysts' Forecasts and Brokerage‐Firm Trading

Using unique data on brokerage‐firm trading, I examine whether analysts' earnings forecasts and stock recommendations affect their brokerage firms' share of trading in the forecast stocks. I find that individual analyst's forecasts that differ from the consensus forecast generate significant brokerage‐firm trading in the forecast stocks in the two weeks after the forecast release date, affirming that analysts' forecasts affect their brokers' commission revenue. However, I find no evidence that analysts' forecast errors—the difference between forecast earnings and actual earnings—increase brokerage‐firm trading. This result suggests that analysts cannot generate trade for their employers simply by adding error to their forecasts. I find that buy recommendations generate relatively more trading, both buying and selling, through the analyst's brokerage firm. Collectively, these results suggest that analysts can generate higher trading commissions through their positive stock recommendations than by biasing t...
Culture and Judgment and Decision Making: The Constructivist Turn

Cultural influences on individual judgment and decision making are increasingly understood in terms of dynamic constructive processing and the structures in social environments that shape distinct processing styles, directing initial attentional foci, activating particular judgment schemas and decision strategies, and ultimately reinforcing some judgment and decision making (JDM) patterns over others. These structures include the society's observable patterns of normative actions and responses, its prevalent forms of interpersonal interaction, the typical size and density of social networks, the ideational frames represented publically in texts and institutions, and so forth. We review this emerging perspective on culture and JDM in both economic and social domains, noting the distinctive insights it yields. We suggest new ways that cultural research is becoming relevant to mainstream JDM researchers, while also recognizing issues in need of further research.
Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing

Graph classification has practical applications in diverse fields. Recent studies show that graph-based machine learning models are especially vulnerable to adversarial perturbations due to the non i.i. d nature of graph data. By adding or deleting a small number of edges in the graph, adversaries could greatly change the graph label predicted by a graph classification model. In this work, we propose to build a smoothed graph classification model with certified robustness guarantee. We have proven that the resulting graph classification model would output the same prediction for a graph under l 0 bounded adversarial perturbation. We also evaluate the effectiveness of our approach under graph convolutional network (GCN) based multi-class graph classification model.
The effect of relationship quality on individual perceptions of social responsibility in the US.

Social responsibility (SR) has been of continuing interest in the United States and around the world. Organizations make a wide variety of SR decisions that represent differing viewpoints. While a number of definitions of SR exist, many of these definitions indicate that SR decisions may be viewed as existing of various facets, such as legal/regulatory, financial/economic, ethical, environmental, and voluntary. While drivers of SR have been proposed, there has been limited research at a micro-level on how individuals perceive SR activities by the organizations where they work. Based on a prior qualitative study (Thornton and Byrd, 2013) that found SR decisions are related to several traits and influenced by relationships, a model was proposed and tested in this research. The traits found relevant in the qualitative research were conscientiousness, especially in the sense of being responsible, and self-efficacy. Relationship quality was assessed based on positive and negative emotional attractors (PNEA) as proposed in Intentional Change Theory (ICT). Perceptions of individuals in management and non-management showed that relationship quality mediated the effect of conscientiousness and general self-efficacy on the SR. Because there are multiple facets, the author made use of Carroll’s (1991) pyramid of social responsibility to identify activities that business owners and managers consider relevant. The findings indicate that conscientiousness is related to specific SR activities in the areas of legal/regulatory, ethical and discretionary dimensions while general self-efficacy is related to financial/economic and legal/regulatory dimensions. The presence of relationship quality enhanced the effects of both conscientiousness and general self-efficacy on the various SR dimensions. This suggests that individuals perceived SR activities along different traits and that enhancing these traits might improve perceptions of SR decisions.
The Labor Movement Needs a Twenty-First Century Committee for Industrial Organization

The American labor movement is in a moribund state. The percentage of private sector workers in unions has steadily declined from a high of 34.7 in 1954 to 7.9 today. AFL-CIO leaders are exploring ways to reverse this ominous trend and reestablish the economic and political power of unions. In an effort to enhance organizing capacity, the AFLCIO will eliminate 167 traditional jobs and create sixty-one new positions that will pertain to organizing and member mobilization. AFL-CIO President John Sweeney plans to dedicate more efforts to grass roots organizing. Union leaders from the Service Employees International Union (SEIU), the United Food and Commercial Workers (UFCW), the clothing, restaurant, and hotel workers (UNITE-HERE), the Laborers International Union (Laborers), and the International Brotherhood of Teamsters (Teamsters) formed the Change to Win Coalition to generate inter-union cooperative organizing initiatives, and this
Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns

Motivated by existing evidence of a preference among investors for assets with lotterylike payoffs and that many investors are poorly diversified, we investigate the significance of extreme positive returns in the cross-sectional pricing of stocks. Portfolio-level analyses and firm-level cross-sectional regressions indicate a negative and significant relation between the maximum daily return over the past one month (MAX) and expected stock returns. Average raw and risk-adjusted return differences between stocks in the lowest and highest MAX deciles exceed 1% per month. These results are robust to controls for size, book-to-market, momentum, short-term reversals, liquidity, and skewness. Of particular interest, including MAX reverses the puzzling negative relation between returns and idiosyncratic volatility recently shown in Ang, Hodrick, Xing, and Zhang (2006, 2009).
The Supply‐Side Determinants of Loan Contract Strictness

Using a measure of contract strictness based on the probability of a covenant violation, I investigate how lender-specific shocks impact the strictness of the loan contract that a borrower receives. Banks write tighter contracts than their peers after suffering payment defaults to their own loan portfolios, even when defaulting borrowers are in different industries and geographic regions from the current borrower. The effects persist after controlling for bank capitalization, although bank equity compression is also associated with tighter contracts. The evidence suggests that recent defaults inform the lender's perception of its own screening ability, thereby impacting its contracting behavior.
Market definition, market power

Abstract Market definition and market power are central features of competition law and practice but pose serious challenges. On one hand, market definition suffers decisive logical infirmities that render it infeasible, unnecessary, and counterproductive, and the practice of stating market power requirements as market share threshold tests is incoherent as a matter of empirics and policy. On the other hand, market power is often probative of the desirability of liability, yet the typically assumed functional relationship is unexplored and often implausible. These latter deficiencies are addressed through a ground-up analysis of the channels by which market power can be relevant. It is important to explicitly and simultaneously consider both anticompetitive and procompetitive explanations for challenged practices and to attend to the magnitudes of the social consequences of correct and mistaken imposition of liability in order to identify the various ways and senses in which market power bears on optimal decision-making.
OPTIMAL FISCAL AND MONETARY POLICY UNDER STICKY PRICES

This paper studies optimal fiscal and monetary policy under sticky product prices. The theoretical framework is a stochastic production economy without capital. The government finances an exogenous stream of purchases by levying distortionary income taxes, printing money, and issuing one-period nominally risk free bonds. The main findings of the paper are: First, for a miniscule degree of price stickiness (i.e., many times below available empirical estimates), the optimal volatility of inflation is near zero. This result stands in stark contrast with the high volatility of inflation implied by the Ramsey allocation when prices are flexible. The finding is in line with a recent body of work on optimal monetary policy under nominal rigidities that ignores the role of optimal fiscal policy. Second, even small deviations from full price flexibility induce near random walk behavior in government debt and tax rates. Third, sluggish price adjustment raises the average nominal interest rate above the one called for by the Friedman rule. Finally, an interest-rate feedback rule whereby the nominal interest rate depends on inflation and output fits well the data emanating from the Ramsey economy. However, the fitted rule is not of the Taylor type, for the implied inflation coefficient is less than one and close to zero and the output coefficient is negative. JEL Classification: E52, E61, E63.
IDENTIFICATION AND ESTIMATION OF TRIANGULAR SIMULTANEOUS EQUATIONS MODELS WITHOUT ADDITIVITY

This paper uses control variables to identify and estimate models with nonseparable, multidimensional disturbances. Triangular simultaneous equations models are considered, with instruments and disturbances that are independent and a reduced form that is strictly monotonic in a scalar disturbance. Here it is shown that the conditional cumulative distribution function of the endogenous variable given the instruments is a control variable. Also, for any control variable, identification results are given for quantile, average, and policy effects. Bounds are given when a common support assumption is not satisfied. Estimators of identified objects and bounds are provided, and a demand analysis empirical example is given.
Fleurbaey–Michel conjecture on equitable weak Paretian social welfare order

Abstract The paper examines the problem of explicit description of a social welfare order over infinite utility streams, which respects anonymity and weak Pareto axioms. It provides a complete characterization of the domains of one period utilities, for which it is possible to explicitly describe a weak Paretian social welfare order satisfying the anonymity axiom. For domains containing any set of order type similar to the set of positive and negative integers, every equitable social welfare order satisfying the weak Pareto axiom is non-constructive. The paper resolves a conjecture by Fleurbaey and Michel (2003) that there exists no explicit (that is, avoiding the axiom of choice or similar contrivances) description of an ordering which satisfies weak Pareto and indifference to finite permutations. It also provides an interesting connection between the existence of social welfare function and the constructive nature of social welfare order by showing that the domain restrictions for the two are identical.
Asymmetric Pass-Through in U.S. Gasoline Prices

This paper presents new evidence of asymmetric pass-through, the notion that upward cost shocks are passed through faster than downward cost shocks, in U.S. gasoline prices. Much of the extant literature comes to seemingly contradictory conclusions about the existence and causes of asymmetry, though the differences may be due to different aggregation (both over time and geographic markets) and the use of different price series including crude oil, wholesale, and retail gasoline prices. I utilize a large and detailed dataset to determine where evidence of a pass-through asymmetry exists, and how it depends on the aggregation and price series chosen by the researcher. Using the error correction model, I find evidence of pass-through asymmetry based on spot, rack and retail prices, though the largest effect is found in the rack to retail relationship. I find more asymmetry in branded prices compared with unbranded prices, consistent with a consumer search explanation for asymmetry. However, I also find evidence consistent with explanations based on market power as the magnitude of asymmetry is positively associated with retail concentration. On average, retail prices rise three to four times as fast as they fall.
Causal relevance in the law of search and seizure

INTRODUCTION 113 I. CAUSAL RELEVANCE IN SUBSTANTIVE CRIMINAL LAW AND TORT.... 117 A. The Risk Rule 117 B. The Wrongful-Aspect Variant 124 II. CAUSAL RELEVANCE IN HUDSON AND HARRIS 132 A. The Risk Rule in Hudson and Harris 132 B. The Wrongful-Aspect Variant in the Law of Search and Seizure 138 C. Wrongful Aspect and Inevitable Discovery 143 III. THE BROADER IMPLICATIONS OF HARRIS AND HUDSON 146 A. The Risk Rule and the Warrant Requirement 146 B. The Risk Rule and Fruitless Searches 151 IV. WHERE THE COURT WENT WRONG IN ADOPTING THE RISK RULE AS A LIMITATION ON THE EXCLUSIONARY RULE 156 A. Why Causation’s Role Matters 156 B. The Role of Causation in Search and Seizure 157 C. Causal Relevance in the Reckoning of Profits 161 D. Causal Relevance in the Law of Search and Seizure 166 E. Causal Relevance in Harris and Hudson 171 CONCLUSION 173
International Sourcing and Capital Structure

Motivated by the rising importance of international sourcing by US firms in recent decades, we study the influence of international sourcing on capital structure. We find that international sourcing has a significant negative influence on financial leverage. The negative influence is stronger in industries that have high R&D intensities and are financially constrained. However, the negative relation is mitigated when suppliers are from countries with strong legal environments and when the supplier markets are more competitive. Overall, our findings suggest that relationship-specific investments, supplier market characteristics, and financial market conditions are key determinants of the sourcing–leverage relation.
A Dynamical Trichotomy for Structured Populations Experiencing Positive Density-Dependence in Stochastic Environments

Positive density-dependence occurs when individuals experience increased survivorship, growth, or reproduction with increased population densities. Mechanisms leading to these positive relationships include mate limitation, saturating predation risk, and cooperative breeding and foraging. Individuals within these populations may differ in age, size, or geographic location and thereby structure these populations. Here, I study structured population models accounting for positive density-dependence and environmental stochasticity i.e. random fluctuations in the demographic rates of the population. Under an accessibility assumption (roughly, stochastic fluctuations can lead to populations getting small and large), these models are shown to exhibit a dynamical trichotomy: (i) for all initial conditions, the population goes asymptotically extinct with probability one, (ii) for all positive initial conditions, the population persists and asymptotically exhibits unbounded growth, and (iii) for all positive initial conditions, there is a positive probability of asymptotic extinction and a complementary positive probability of unbounded growth. The main results are illustrated with applications to spatially structured populations with an Allee effect and age-structured populations experiencing mate limitation.
Agriculture's Supply and Demand for Energy and Energy Products

Rising energy prices and changing energy and environmental policies have transformed the relationship between the energy and agriculture sectors. Traditionally, the relationship has been one-way, with agriculture using energy products as an input in production; during the past decade, however, the energy sector’s use of agricultural products as renewable-fuel feedstocks has increased substantially. This report examines both sector and farm-level responses to changing market and policy drivers such as the increased production of biofuel crops and other sources of renewable energy, together with changes in production practices to economize on energy-based inputs like fertilizer. We provide insight into how farmers have adapted to the changes and update and provide new data on the evolving linkages between the energy and agricultural sectors.
Disentangling the market value of customer satisfaction: Evidence from market reaction to the unanticipated component of ACSI announcements

Abstract There is a rich literature that examines the impact of customer satisfaction on market value. Surprisingly, the short-run market impact of customer satisfaction has been found to be either insignificant or limited in scope. To address this shortcoming, we introduce the notion that investors form expectations about customer satisfaction and respond only to deviations from these expectations (i.e., “surprises”). We consider two “expectations” models: a naive model that utilizes last year's scores and a model that includes firm characteristics and marketing investments to proxy for the prior allocation of resources devoted to improving customer satisfaction. In our empirical work, we find that the market does indeed respond in the short-run to surprises in customer satisfaction, with more pronounced effects for our second expectations model. Overall, our research offers two distinct contributions. First, it refines the current conceptualization of customer satisfaction by explicitly introducing the notion of investor expectations. Second, we employ this refined conceptualization to unequivocally demonstrate the short-run impact of investments in customer satisfaction.
A note on credible spatial preemption in an entry–exit game

I investigate how an incumbent firm deters entry by crowding the market, even when the incumbent can withdraw its stores in response to entry. In a two-location model, Judd (1985) shows such spatial entry deterrence is not credible. In contrast, I demonstrate spatial preemption can be credibly employed in a circular-city model if the incumbent can build its stores on sufficiently many locations and transportation costs are linear.
Trust in Value Co‐Creation Strategies: Moving Toward a Conceptualization We Can Trust

Within the relational view, trust is a vital governance mechanism. Trust enables companies to: (1) mitigate safeguarding, (2) establish efficient resource-sharing routines, and (3) integrate and leverage complementary competencies for collaborative advantage. As a central psychological construct, extensive research across diverse domains has posited multitudinous trust definitions. Yet substantive inconsistencies exist in conceptualizations of interorganizational trust. Focusing on the supply chain management (SCM) domain, Whipple et al. (2013) find that despite agreement that trust is a nuanced, multifaceted phenomenon, 39 of 42 articles operationalized trust as a single construct. Whipple et al. argue that extant trust scales are underdeveloped, suggesting we cannot trust them. We continue this dialogue commenting on the consequences of trust conceptualizations and propose a new lens to help us better measure and manage trust as an enabler of value co-creation.
Mental Disorder and the Civil/Criminal Distinction

Follow this and additional works at: http://digital.sandiego.edu/lwps_public Part of the Civil Law Commons, Civil Rights and Discrimination Commons, Constitutional Law Commons, Criminal Law Commons, Criminal Procedure Commons, Health Law and Policy Commons, Human Rights Law Commons, Jurisprudence Commons, Law and Psychology Commons, Law and Society Commons, Legal Ethics and Professional Responsibility Commons, Medical Jurisprudence Commons, Public Law and Legal Theory Commons, and the Social Welfare Law Commons
Strengthening the Economic Union: the Charter and the Agreement on Internal Trade

The standard story in public policy and constitutional circles on the relationship between the Constitution and the Canadian Economic Union is a story of constitutional failure: that the Constitution has proven to be ineffective at furthering the integration of the Canadian economy. 1 As a consequence, securing this goal requires either constitutional amendment or, in the face of the impossibility of large-scale constitutional change, the use of non-constitutional policy instruments such as the Agreement on Internal Trade , an intergovernmental agreement designed to remove barriers to interprovincial economic mobility. 2 In this paper, I challenge this view. My argument is that constitutional litigation under the Charter ’s 3 mobility rights provisions can serve as an effective alternative to the various mechanisms (adjudication and negotiation) established under the AIT to further the integration of the Canadian economy. Moreover, I suggest how constitutional litigation can actually strengthen the AIT , rather than simply serve as an alternative to it.
The Style of a Skeptic: The Opinions of Chief Justice Roberts

At the time of his confirmation hearing as Chief Justice of the United States, John Roberts's limited judicial record - forty-eight opinions for the Court of the Appeals for the District of Columbia Circuit - provided few clues to the substance of his likely Supreme Court jurisprudence. Those opinions, together with his first thirteen Supreme Court opinions, do, however, reveal a great deal about Roberts's judicial personality, the voice that a judge crafts from a range of rhetorical choices, including diction, metaphor, syntax, allusion, and tone. A careful reading of the canon of his stylistically artful opinions discloses a judge who writes for a lay as well as a legal audience; who prefers to ground his legal conclusions in the realities of human experience and specific fact rather than in abstract legal theories; and who positions himself as the successor to a line of distinguished judges (Oliver Wendell Holmes, Learned Hand, and Henry Friendly) who represent traditions of skepticism, judicial restraint, and legal craftsmanship. Roberts has spoken of himself as "a modest judge," and the judicial personality expressed in his early opinions suggests that he may pursue a less ambitiously ideological agenda for the Court than some observers may anticipate.
Campaign Disclosure and Tax-Exempt Entities: A Quick Repair to the Regulatory Plumbing

Abstract This article argues that there are some quick regulatory fixes the Treasury can implement to ensure that tax-exempt organizations are operating within the rules and that aggressive tax planning is not being used as a way to obfuscate rules for political organizations requiring disclosure. The article recommends that Treasury promulgate new regulations to require disclosure by tax-exempt entities of expenditures and contributions in excess of $25,000. The article also proposes that Treasury institute procedures to require tax-exempt organizations to file for exempt status, and to provide procedures for ensuring that these organizations meet the requirements in the statute and are not being used as a mechanism to avoid disclosure provisions in the Internal Revenue Code.