cssi/SciSciGPT-SciSciNet huggingface dataset:
Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

Using a large-scale, experimentally captured 3D microstructure data set, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple-phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN-generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. The ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.
Extending and Analyzing Self-supervised Learning Across Domains

Self-supervised representation learning has achieved impressive results in recent years, with experiments primarily coming on ImageNet or other similarly large internet imagery datasets. There has been little to no work with these methods on other smaller domains, such as satellite, textural, or biological imagery. We experiment with several popular methods on an unprecedented variety of domains. We discover, among other findings, that Rotation is by far the most semantically meaningful task, with much of the performance of Jigsaw and Instance Discrimination being attributable to the nature of their induced distribution rather than semantic understanding. Additionally, there are several areas, such as fine-grain classification, where all tasks underperform. We quantitatively and qualitatively diagnose the reasons for these failures and successes via novel experiments studying pretext generalization, random labelings, and implicit dimensionality. Code and models are available at this https URL.
Improved List-Decodability of Random Linear Binary Codes

There has been a great deal of work establishing that random linear codes are as list-decodable as uniformly random codes, in the sense that a random linear binary code of rate $1 - {H}(\text {p}) - \epsilon $ is $( {p},\text {O}(1/\epsilon))$ -list-decodable with high probability. In this work, we show that such codes are $( {p}, {H}( {p})/\epsilon + 2)$ -list-decodable with high probability, for any $ {p} \in (0, 1/2)$ and $\epsilon > 0$ . In addition to improving the constant in known list-size bounds, our argument—which is quite simple—works simultaneously for all values of p, while previous works obtaining $ {L} = \text {O}(1/\epsilon)$ patched together different arguments to cover different parameter regimes. Our approach is to strengthen an existential argument of (Guruswami, Hastad, Sudan and Zuckerman, IEEE Trans. IT, 2002) to hold with high probability. To complement our upper bound for random linear codes, we also improve an argument of (Guruswami, Narayanan, IEEE Trans. IT, 2014) to obtain an essentially tight lower bound of $1/\epsilon $ on the list size of uniformly random codes; this implies that random linear codes are in fact more list-decodable than uniformly random codes, in the sense that the list sizes are strictly smaller. To demonstrate the applicability of these techniques, we use them to (a) obtain more information about the distribution of list sizes of random linear codes and (b) to prove a similar result for random linear rank-metric codes.
Bridging Knowledge Graphs to Generate Scene Graphs

Scene graphs are powerful representations that parse images into their abstract semantic elements, i.e., objects and their interactions, which facilitates visual comprehension and explainable reasoning. On the other hand, commonsense knowledge graphs are rich repositories that encode how the world is structured, and how general concepts interact. In this paper, we present a unified formulation of these two constructs, where a scene graph is seen as an image-conditioned instantiation of a commonsense knowledge graph. Based on this new perspective, we re-formulate scene graph generation as the inference of a bridge between the scene and commonsense graphs, where each entity or predicate instance in the scene graph has to be linked to its corresponding entity or predicate class in the commonsense graph. To this end, we propose a novel graph-based neural network that iteratively propagates information between the two graphs, as well as within each of them, while gradually refining their bridge in each iteration. Our Graph Bridging Network, GB-Net, successively infers edges and nodes, allowing to simultaneously exploit and refine the rich, heterogeneous structure of the interconnected scene and commonsense graphs. Through extensive experimentation, we showcase the superior accuracy of GB-Net compared to the most recent methods, resulting in a new state of the art. We publicly release the source code of our method (https://github.com/alirezazareian/gbnet).
Fisher Information Under Local Differential Privacy

We develop data processing inequalities that describe how Fisher information from statistical samples can scale with the privacy parameter $\varepsilon $ under local differential privacy constraints. These bounds are valid under general conditions on the distribution of the score of the statistical model, and they elucidate under which conditions the dependence on $\varepsilon $ is linear, quadratic, or exponential. We show how these inequalities imply order-optimal lower bounds for private estimation for both the Gaussian location model and discrete distribution estimation for all levels of privacy $\varepsilon >0$ . We further apply these inequalities to sparse Bernoulli models and demonstrate privacy mechanisms and estimators with order-matching squared $\ell ^{2}$ error.
Smart Cloud: Scalable Cloud Robotic Architecture for Web-powered Multi-Robot Applications

Robots have inherently limited onboard processing, storage, and power capabilities. Cloud computing resources have the potential to provide significant advantages for robots in many applications. However, to make use of these resources, frameworks must be developed that facilitate robot interactions with cloud services. In this paper, we propose a cloud-based architecture called Smart Cloud that intends to overcome the physical limitations of single- or multi-robot systems through massively parallel computation, provided on demand by cloud services. Smart Cloud is implemented on Amazon Web Services (AWS) and available for robots running on the Robot Operating System (ROS) and on the non-ROS systems. Smart Cloud features a first-of-its-kind architecture that incorporates JavaScript-based libraries to run various robotic applications related to machine learning and other methods. This paper presents the architecture and its performance in terms of CPU usage and latency, and finally validates it for navigation and machine learning applications.
Robustness Analysis of Neural Networks via Efficient Partitioning With Applications in Control Systems

Neural networks (NNs) are now routinely implemented on systems that must operate in uncertain environments, but the tools for formally analyzing how this uncertainty propagates to NN outputs are not yet commonplace. Computing tight bounds on NN output sets (given an input set) provides a measure of confidence associated with the NN decisions and is essential to deploy NNs on safety-critical systems. Recent works approximate the propagation of sets through nonlinear activations or partition the uncertainty set to provide a guaranteed outer bound on the set of possible NN outputs. However, the bound looseness causes excessive conservatism and/or the computation is too slow for online analysis. This letter unifies propagation and partition approaches to provide a family of robustness analysis algorithms that give tighter bounds than existing works for the same amount of computation time (or reduced computational effort for a desired accuracy level). Moreover, we provide new partitioning techniques that are aware of their current bound estimates and desired boundary shape (e.g., lower bounds, weighted $\ell _{\infty }$ -ball, convex hull), leading to further improvements in the computation-tightness tradeoff. The letter demonstrates the tighter bounds and reduced conservatism of the proposed robustness analysis framework with examples from model-free RL and forward kinematics learning.
Snapshot Models of Undocumented Immigration

Accurately estimating the size of the undocumented immigrant population is a critical component of assessing the health and security risks of undocumented immigration to the United States. To provide one such estimate, we use data from the Mexican Migration Project (MMP), a study that includes samples of undocumented Mexican immigrants to the United States after their return to Mexico. Of particular interest are the departure and return dates of a sampled migrant's most recent sojourn in the United States, and the total number of such journeys undertaken by that migrant household, for these data enable the construction of data-driven undocumented immigration models. However, such data are subject to an extreme physical bias, for to be included in such a sample, a migrant must have returned to Mexico by the time of the survey, excluding those undocumented immigrants still in the United States. In our analysis, we account for this bias by jointly modeling trip timing and duration to produce the likelihood of observing the data in such a "snapshot" sample. Our analysis characterizes undocumented migration flows including single-visit migrants, repeat visitors, and "retirement" from circular migration. Starting with 1987, we apply our models to 30 annual random snapshot surveys of returned undocumented Mexican migrants accounting for undocumented Mexican migration from 1980 to 2016. Scaling to population quantities and supplementing our analysis of southern border crossings with estimates of visa overstays, we produce lower bounds on the total number of undocumented immigrants that are much larger than conventional estimates based on U.S.-based census-linked surveys, and broadly consistent with the more recent estimates reported by Fazel-Zarandi, Feinstein, and Kaplan.
Red panda: a novel method for detecting variants in single-cell RNA sequencing.

Single-cell sequencing enables us to better understand genetic diseases, such as cancer or autoimmune disorders, which are often affected by changes in rare cells. Currently, no existing software is aimed at identifying single nucleotide variations or micro (1-50 bp) insertions and deletions in single-cell RNA sequencing (scRNA-seq) data. Generating high-quality variant data is vital to the study of the aforementioned diseases, among others. In this study, we report the design and implementation of Red Panda, a novel method to accurately identify variants in scRNA-seq data. Variants were called on scRNA-seq data from human articular chondrocytes, mouse embryonic fibroblasts (MEFs), and simulated data stemming from the MEF alignments. Red Panda had the highest Positive Predictive Value at 45.0%, while other tools—FreeBayes, GATK HaplotypeCaller, GATK UnifiedGenotyper, Monovar, and Platypus—ranged from 5.8–41.53%. From the simulated data, Red Panda had the highest sensitivity at 72.44%. We show that our method provides a novel and improved mechanism to identify variants in scRNA-seq as compared to currently existing software. However, methods for identification of genomic variants using scRNA-seq data can be still improved.
A Fixed Point Framework for Recovering Signals from Nonlinear Transformations

We consider the problem of recovering a signal from nonlinear transformations, under convex constraints modeling a priori information. Standard feasibility and optimization methods are ill-suited to tackle this problem due to the nonlinearities. We show that, in many common applications, the transformation model can be associated with fixed point equations involving firmly nonexpansive operators. In turn, the recovery problem is reduced to a tractable common fixed point formulation, which is solved efficiently by a provably convergent, block-iterative algorithm. Applications to signal and image recovery are demonstrated. Inconsistent problems are also addressed.
Poissonian correlation of higher order differences

Abstract A sequence ( x n ) n = 1 ∞ on the torus T exhibits Poissonian pair correlation if for all s > 0 , lim N → ∞ ⁡ 1 N # { 1 ≤ m ≠ n ≤ N : | x m − x n | ≤ s N } = 2 s . It is known that this condition implies equidistribution of ( x n ) . We generalize this result to four-fold differences: if for all s > 0 we have lim N → ∞ ⁡ 1 N 2 # { 1 ≤ m , n , k , l ≤ N { m , n } ≠ { k , l } : | x m + x n − x k − x l | ≤ s N 2 } = 2 s then ( x n ) n = 1 ∞ is equidistributed. This notion generalizes to higher orders, and for any k we show that a sequence exhibiting 2k-fold Poissonian correlation is equidistributed. In the course of this investigation we obtain a discrepancy bound for a sequence in terms of its closeness to 2k-fold Poissonian correlation. This result refines earlier bounds of Grepstad & Larcher and Steinerberger in the case of pair correlation, and resolves an open question of Steinerberger.
Training Neural Network Controllers Using Control Barrier Functions in the Presence of Disturbances

Control Barrier Functions (CBF) have been recently utilized in the design of provably safe feedback control laws for nonlinear systems. These feedback control methods typically compute the next control input by solving an online Quadratic Program (QP). Solving QPs in real-time can be a computationally expensive process for resource-constrained systems. In the presence of disturbances, finding CBF-based safe control inputs can get even more time consuming as finding the worst-case of the disturbance requires solving a nonlinear program in general. In this work, we propose to use imitation learning to learn Neural Network based feedback controllers which will satisfy the CBF constraints. In the process, we also develop a new class of High Order CBF for systems under external disturbances. We demonstrate the framework on a unicycle model subject to external disturbances, e.g., wind or currents.
Agent-level optimal LQG control of dynamically decoupled systems with processing delays

We consider the problem of controlling a set of dynamically decoupled plants where the plants’ subcontrollers communicate with each other according to a fixed and known network topology. We assume the communication to be instantaneous but there is a fixed processing delay associated with incoming transmissions. We provide explicit closed-form expressions for the optimal decentralized controller under these communication constraints and using standard LQG assumptions for the plants and cost function. Although this problem is convex, it is challenging due to the irrationality of continuous-time delays and the decentralized information-sharing pattern. We show that the optimal subcontrollers each have an observer–regulator architecture containing LTI and FIR blocks and we characterize the signals that subcontrollers should transmit to each other across the network.
Average Idiosyncratic Volatility in G7 Countries

We argue that changes in average idiosyncratic volatility provide a proxy for changes in the investment opportunity set and that this proxy is closely related to the book-to-market factor. We test this idea in two ways using G7 countries’ data. First, we show that idiosyncratic volatility has statistically significant predictive power for aggregate stock market returns over time. Second, we show that idiosyncratic volatility performs just as well as the book-to-market factor in explaining the cross section of stock returns. Our results suggest that the hedge against changes in investment opportunities is an important determinant of asset prices.
BETTER IN PAIRS?: INTERACTIONS BETWEEN ALLIANCES AND CORPORATE VENTURE CAPITAL ON NEW-VENTURE INTERNATIONALIZATION

Drawing on insights from the resource-based view and institutional theory, we examine how alliances with large industry partners, functional-type alliances, CVC and interactions between these different types of partnerships influence foreign market entry. Results show that legitimacy attained through allying with large industry partners is more related to foreign market entry than are the specialized knowledge resources provided by functional alliances. Moreover, CVC does not appear to be related to internationalization. We thus extend research on the identification of resources relating to and the effect of different types of partnerships on new-venture internationalization, and we provide insights for entrepreneurs considering foreign market entry.
The Extraterritorial Reach of Sovereign Debt Enforcement

A significant barrier to enforcing sovereign debt obligations in U.S. court has been finding and attaching non-immune assets of the foreign sovereign debtor. In June 2014, the U.S. Supreme Court issued decisions in litigation between Argentina and hedge fund NML Capital that will significantly benefit creditors in the enforcement process. In one decision, the Court affirmed an order to compel banks to provide information as to how Argentina moves its monetary assets around the world, finding that the U.S. Foreign Sovereign Immunities Act (FSIA) does not limit a court’s power to order post-judgment discovery. In the other decision, the Court denied certiorari to review an injunction prohibiting Argentina from making payments to holders of its restructured debt unless and until it pays NML Capital, and threatening to hold liable third parties that aid and abet Argentina in processing such payments. The NML decisions follow protracted, previously unsuccessful efforts by hedge funds holding defaulted Argentine debt to enforce New York judgments against Argentina. This paper argues that the discovery and injunction orders at issue in NML contravene the FSIA due to their extraterritorial reach. The FSIA should be read to prohibit these orders for several reasons. The Court has interpreted the FSIA to be the exclusive basis for jurisdiction against a foreign state in U.S. court. Additionally, the historical context in which the statute was adopted supports a narrow reading of exceptions to execution immunity under the FSIA. Finally, the presumption against extraterritoriality calls for a restrained interpretive approach. The Supreme Court’s interpretation of the FSIA in NML Capital adopts an acontextual reading of the FSIA’s language to reach an unreasonable result.
Fannie Mae/Freddie Mac Home Mortgage Documents Interpreted as Nonrecourse Debt (with poetic comments lifted from Carl Sandburg)

* Law Alumni Professor of Law, University of Houston Law Center. The author thanks Lauren E. Schroeder, Reference/Research Librarian at the Law Center; student research assistant Karen Gross; Houston real estate attorneys Kim Yelton, Charles Jacobus, and Marvin Nathan; Law Center Professors Aaron Bruhl, Richard Dole, Barbara Evans, Julie Hill, and Ron Turner; and a number of real estate and lending professionals who provided information that was used, at their request, without attribution. The author acknowledges the research method described in George Lefcoe, Land Development Law 713 (1974), ′′informed gossip, the chief empirical tool of lawyers, legislators and law professors.′′
Is the Party Over? Examining the Constitutionality of Proposition 14 as It Relates to Ballot Access for Minor Parties

The U.S. Supreme Court must reexamine its deeply flawed ballot access jurisprudence. California voters passed Proposition 14 on June 8, 2010. This law reduces ballot access for minor parties. This Article argues that the Court has historically overestimated the government interests at stake in restricting ballot access, while derogating the important role that minor parties can play in elections. This must stop. This Article further argues that the Court should apply strict scrutiny to ballot access restrictions and use a holistic approach when examining such restrictions.
The Political Economy of Hatred

This paper develops a model of the interaction between the supply of hate-creating stories from politicians and the willingness of voters to listen to hatred. Hatred is fostered with stories of an out-group's crimes, but the impact of these stories comes from repetition not truth. Hate-creating stories are supplied by politicians when such actions help to discredit opponents whose policies benefit an out-group. Egalitarians foment hatred against rich minorities; opponents of redistribution build hatred against poor minorities. Hatred relies on people accepting, rather than investigating, hate-creating stories. Hatred declines when there is private incentive to learn the truth. Increased economic interactions with a minority group may provide that incentive. This framework is used to illuminate the evolution of anti-black hatred in the United States South, episodes of anti-Semitism in Europe, and the recent surge of anti-Americanism in the Arab world.
Quibbling Siblings: Conflicts between Trademarks and Geographical Indications

The relationship between trademarks and geographical indications (GIs) has historically been tempestuous. Each of these quibbling siblings, members of the broader family of Unfair Competition law, entitles registrants to the exclusive use of a sign. So what happens when a GI collective and a trademark proprietor lay claim to the same sign within a single jurisdiction? As part of the renewed interest in TRIPs flexibilities and attempts at accommodating or reconciling differences between national laws, this paper explores a newly emerging space that may just be big enough for the both of them. The analysis draws on a recent World Trade Organization (WTO) Panel Report, which identifies the legal foundations for cohabitation. The Report coincides with doctrinal developments at the national and regional level which initially identified this zone of compromise: the geographical 'descriptive use' defence in trademark law. Coexistence is significant as it alters the dynamic of a venerable conflict between trademark and GI regimes, which has been locked in the language of trumps for several decades. Accordingly, this paper introduces the players and describes the game of one-upmanship prior to this development in Part I; outlines the WTO decision in Part II and then draws parallels with doctrinal developments in the EU and US which presaged the possibility of coexistence in Part III. It concludes with an endorsement of coexistence as an equitable solution.
Children's Associational Rights? Why Less Is More

This article argues against recognizing children's associational rights, despite compelling calls for such rights in the face of controversial court decisions. The argument is grounded on pragmatic, rather than conceptual, opposition to these rights. While children's interest in maintaining important relationships is at least as great as the parallel interest of adults, children cannot assert those interests on their own. As a result, children are necessarily dependent on some adult surrogate, or group of surrogates, to exercise these rights. The article considers each of these surrogates in turn (interested third parties, lawyers, guardians ad litem, evaluating psychologists, and judges), and concludes that none is in a position to identify a child's associational interests better than the child's parents (the default surrogates in a no-rights world). The article also suggests that invoking children's rights rhetoric, when children have so little control over the associational choices made in their name, risks exploiting children to serve the ends of adults. This piece was written for the symposium on children's associational rights convened by William and Mary's Institute of Bill of Rights Law.
Parties, Coups, and Authoritarian Rule: Patterns of Political Change in Tropical Africa

This study analyzes the emergence of different types of authoritarian regimes across 26 countries in tropical Africa in the first decade of independence. Military, one-party plebiscitary one-party, and competitive one-party regimes are explained in terms of the experience with the introduction of competitive politics during decolonization, specifically the way in which decolonization effected party dominance and electoral participation.
Of Sheepdogs and Ventriloquists: Government Lawyers in Two New Deal Agencies

From the neo-Weberian literature on state-building and the political sociology of the legal profession, one might expect government lawyers to be sheepdogs, nipping at the heels of straying administrators, supplying their agencies with the bureaucratic autonomy so often missing in American government. In this working paper, prepared for "Opportunities for Law's Intellectual History," a conference sponsored by Baldy Center for Law and Social Policy at the State University of New York at Buffalo, October 10-11, 2014, I report my preliminary findings for two agencies created during the Hundred Days of Franklin D. Roosevelt's presidency, the Agricultural Adjustment Administration and the National Recovery Administration. I suggest that the neo-Weberian model tends to minimize the lawyers' agency as political actors. In particular, the New Deal lawyers' projection of their own preferences upon general statutory delegations of legislative power, which they then interpreted authoritatively, could make them less the faithful agents of their master’s voice than ventriloquists in pursuit of their own political agenda.
Does China Still Have a Labor Cost Advantage

In recent years wages in China have been rising and the yuan has appreciated, potentially eroding China’s cost advantage in manufactures. This paper explores the evolution of China’s relative unit ...
On the Minimax Complexity of Pricing in a Changing Environment

We consider a pricing problem in an environment where the customers' willingness-to-pay (WtP) distribution may change at some point over the selling horizon. Customers arrive sequentially and make purchase decisions based on a quoted price and their private reservation price. The seller knows the WtP distribution pre-and postchange but does not know the time at which this change occurs. The performance of a pricing policy is measured in terms of regret: the loss in revenues relative to an oracle that knows the time of change prior to the start of the selling season. We derive lower bounds on the worst-case regret and develop pricing strategies that achieve the order of these bounds, thus establishing the complexity of the pricing problem. Our results shed light on the role of price experimentation and its necessity for optimal detection of changes in market response/WtP. Our formulation allows for essentially arbitrary consumer WtP distributions and purchase request patterns.
Two Cheers for the New Paradigm

This brief essay comments on Attorney General Eric Holder's much-publicized announcement in 2013 of new federal prosecution priorities. While Holder's announcement represents a welcome shift away from the rigid legalism that has dominated federal prosecutorial policies for a generation, some concerns are also highlighted in the essay.
Spillovers, Complementarities, and Sorting in Labor Markets with an Application to Professional Sports

Spillovers to productivity across workers may exist when workers produce in teams. Under certain conditions, these spillovers may cause a worker's marginal product to differ across different firms. Empirical examination of professional basketball finds significant spillovers to offensive productivity but finds relatively little evidence for market sorting based on spillovers. Thus, while teammate composition is important to a player's success, there is no evidence for complementarity.
First Report (final) to the Committee on International Trade Law of the International Law Association on the subject of parallel importation

The First Report on Parallel Imports approaches the exhaustion/parallel imports question in broad economic terms, asking whether there may be an economic and social welfare benefit to permitting IPRs holders to block parallel imports that outweighs the potential harm to liberal trade. The Report addresses each major form of IPR (patent, trademark and copyright) separately. It concludes with respect to each form that the evidence of benefits that might flow from allowing parallel imports to be blocked is insufficient to justify the potential inhibition of trade. The Report observes that most objectives which IPRs holders seek to achieve by the allocation of geographic markets can be attained through less trade restrictive means, namely through the vertical allocation of distribution territories by contract. The interests of the developing countries are a focus of the Report. Some economists have suggested that allowing rules on parallel information to enforce price discrimination in favor of developing countries may increase global economic welfare. The Report concludes that developing and developed countries are better served by open markets and the operation of comparative advantage. The Report recommends that the WTO adopt a rule precluding governments from blocking parallel imports save in certain exceptional cases, and it also suggests that further study of this issue would be desirable.
Is food consumption a good proxy for nondurable consumption

Abstract This paper examines whether there is a discrepancy in estimating the elasticity of intertemporal substitution using food consumption instead of nondurable consumption data. We show that a discrepancy exists and that the discrepancy increases as nondurable consumption increases.
Cheap talk with multiple audiences: An experimental analysis

Abstract We examine strategic information transmission in a controlled laboratory experiment of a cheap talk game with one sender and multiple receivers. We study the change in equilibrium behavior from the addition of another audience as well as from varying the degree of conflict between the senderʼs and receiversʼ preferences. We find that, as in cheap talk games with just one receiver, information transmission is higher in games with a separating equilibrium, than in games with only a babbling equilibrium. More interestingly, we find clear evidence that the addition of another audience alters the communication between the sender and the receiver in a way consistent with the theoretical predictions. There is evidence of the presence of agents that are systematically truthful as senders and trusting as receivers: deviations from the theoretical predictions, however, tend to disappear with experience, and learning is faster precisely in the games where deviations are more pronounced.
The Consent of the Governed: Against Simple Rules for a Complex World

This paper argues that recent proponents of enhanced presidential power overstate the ability of the President to legitimize the regulatory state. It accuses pro- presidentialists of premising their claims on a conception of the "will of the people" that is neither an accurate description of how citizens actually participate in modern government nor an authentic constitutional understanding of how citizens would consent to public policy decisions. The paper concludes by insisting that no single mode of democratic legitimization can "save" the regulatory enterprise; rather, administrative law must look to plurality of institutions and practices that contribute to an ongoing process of legitimizing the administrative state.
The European Onion? How Differentiated Integration is Reshaping the EU

Abstract This paper provides an up‐to‐date overview of the gradual development of differentiated integration and the ensuing changes in the nature of European integration. It considers the dynamics of deepening and widening of the EU and proposes the metaphor of a ‘European Onion’ that is designed to capture the bigger picture. Further, this paper expands upon the centripetal effects of differentiated integration and shows its potential to generate more cooperative public opinion in future enlargement rounds. Finally a state of play in European integration theory is offered that incorporates differentiated integration.
Bank Concentration, Competition, and Financial Inclusion

Expanding access to financial services holds the promise to help reduce poverty and foster economic development. However, little is still known about the determinants of the outreach of financial systems across countries. Our study is the first attempt to employ a large panel of countries, several indicators of financial inclusion and a comprehensive set of bank competition measures to study the role of banking system structure as a determinant of cross-country variability in financial outreach for households. We use panel data from 83 countries over a 10-year period to estimate models with both country and time fixed effects. We find that greater banking industry concentration is associated with more access to deposit accounts and loans, provided that the market power of banks is limited. We find evidence that countries in which regulations allow banks to engage in a broader scope of activities are also characterized by greater financial inclusion. Our results are robust to changes in sample, data, and estimation strategy and suggest that the degree of competition is an important aspect of inclusive financial sectors.
Fiscal Policy in Transition Economies: A Postscript

(2000). Fiscal Policy in Transition Economies: A Postscript. Post-Soviet Geography and Economics: Vol. 41, No. 8, pp. 599-604.
What Do We Know About Worker Displacement in the U.S.

Each year during the eighties, plant closings in the U.S. displaced roughly one-half million workers with three-plus years on the job. The recent data and empirical research reviewed here show that wage cuts lower only slightly the probability that a plant will close. Average earnings losses due to long spells of unemployment and to subsequent reduced wages are substantial. Minorities suffer an above-average rate of displacement, but their earnings losses are not unusually high. Women and older workers are no more likely than others to become displaced or to suffer greater earnings losses, but high-tenure workers lose more.
Risky lending: Does bank corporate governance matter?

Abstract We study the effect of bank governance on risk-taking in commercial lending. Banks with more effective boards are less likely to lend to riskier borrowers. This effect is restricted to periods of distress in the banking industry and is stronger at banks with board-level credit committees. Banks with more effective boards are less likely to lend to riskier borrowers right after the Russian default, which exogenously imposed distress conditions on U.S. banks. Thus, value-maximizing banks appear to ration credit to riskier borrowers precisely when such firms might be credit-constrained, suggesting that bank governance regulations may have potential unintended consequences.
Dynamic Contract Breach

This article studies the design of optimal liquidated damages when breach of contract is possible at multiple points in time. It offers an intuitive explanation for why cancellation fees for some services (e.g., hotel reservations) increase as the time for performance approaches and discusses the incentives to mitigate damages. It is shown that absent externalities, privately stipulated damages induce socially efficient breach and investment decisions, regardless of whether renegotiation is possible. The Author 2009. Published by Oxford University Press on behalf of Yale University. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.
The Effect of Limited Liability on the Market Response to Disclosure

. We formalize the effects of an earnings disclosure on security prices under an assumption of limited liability. We derive various nonlinear relations between equity prices and earnings under a variety of capital structure assumptions and. if possible, we tie the relations attained to results from the existing empirical literature. We also characterize how debt prices respond to earnings when holders of debt have limited liability. Finally, we analyze how changes in the degree of leverage and conversion features of debt affect the relation between price and earnings.
Foreign capital raising by Indian firms: An examination of domestic stock price response

Abstract We examine the domestic stock price response to foreign capital issuance by Indian firms. Firms have extensively used foreign equity and convertible foreign debt sources since 1994. The role of foreign investment bankers, size of the issue, firm's growth opportunities, and other factors are examined in the cross-sectional analysis of domestic stock price response. We find that firms experience positive stock price response to both equity and debt issues abroad, with greater response to issuance of American Depositary Receipts (ADRs), and financing high corporate growth.
Plenary Power is Dead! Long Live Plenary Power

For decades, scholars of immigration law have anticipated the demise of the plenary power doctrine. The Supreme Court could have accomplished this in its recent decision in Kerry v. Din, or it could have reaffirmed plenary power. Instead, the Court produced a splintered decision that did neither. This Essay examines the long process of attrition that has significantly gutted the traditional plenary power doctrine with regard to procedural due process, while leaving it largely intact with regard to substantive constitutional rights.
Growing Out of Trouble? Corporate Responses to Liability Risk

This paper analyzes corporate responses to the risk of large, adverse shocks. In particular, we study how a typical firm responds to an exogenous increase in liability risk arising from its workers’ exposure to newly identified carcinogens. We find that firms, particularly those with weak balance sheets, tend to respond to such risks by undertaking aggressive growth through the acquisition of large, unrelated businesses with relatively high operating cash flows. By diversifying the firms’ operations, the growth likely reduces expected costs of financial distress for shareholders, but also may be motivated by managers’ personal exposure to their firms’ risk. Consistent with an agency conflict driving some of this growth, the acquisitions are associated with negative abnormal returns and the extent of growth is related to firms’ external governance, managerial stockholdings, and institutional ownership. The results suggest that the risk of large, adverse shocks can have a substantial impact on firms’ financing and investment decisions, and that corporate governance can be particularly important when firms encounter a negative shock.
Do charter schools crowd out private school enrollment? Evidence from Michigan ☆

Abstract Charter schools have been one of the most important dimensions of recent school reform measures in the United States. Though there have been numerous studies on the effects of charter schools, these have mostly been confined to analyzing their effects on student achievement, student demographic composition, parental satisfaction, and the competitive effects on traditional public schools. This study departs from the existing literature by investigating the effect of charter schools on enrollment in private schools. To investigate this issue empirically, we focus on the state of Michigan where there was a significant spread of charter schools in the nineties. Using data on private school enrollment from biennial NCES private school surveys, and using a fixed effects as well as an instrumental variables strategy that exploits exogenous variation from Michigan charter law, we investigate the effect of charter school penetration on private school enrollment. We do not find any causal evidence that charter schools led to a decline in enrollment in the private schools. Further, we do not find evidence that enrollments in Catholic or other religious schools were affected differently from those in non-religious private schools. Our results are robust to a variety of sensitivity checks.
Multivariate Lagrange Multiplier Tests for Fractional Integration

We introduce a multivariate Lagrange multiplier (LM) test for fractional integration. We derive and analyze the LM statistic and show that it is asymptotically noncentral chi-squared distributed under local alternatives, and that, under Gaussianity, the LM test is asymptotically efficient against local alternatives. It is shown that the regression variant in Breitung and Hassler (2002, Journal of Econometrics 110, 167--185) is not equivalent to the LM test in the multivariate case, although it is in the univariate case. A generalization of the LM test that explicitly allows for different integration orders for each variable is also introduced. The finite sample properties of the LM test are evaluated by Monte Carlo experiments which demonstrate that it is superior to the Breitung and Hassler (2002) test. An application to multivariate time series of real interest rates for six countries is offered, demonstrating that more clear-cut evidence can be drawn from multivariate tests compared to conducting several univariate tests. Copyright 2005, Oxford University Press.
Regleprudence – at OIRA and Beyond

There are significant domains of legality within the administrative state that are mostly immune from judicial review and have mostly escaped the attention of legal theorists. While administrative law generally focuses on the products of agency action as they are reviewed by the judiciary, there are important aspects of regulatory activity that are legal or law-like but rarely interrogated by systematic analysis with reference to accounts about the role and nature of law. In this Article, we introduce a category of analysis we call "regleprudence," a sibling of jurisprudence and legisprudence. Once we explore some regleprudential norms, we delve into one case study – the Office of Information and Regulatory Affairs and the legal work it undertakes through regulatory review – and gesture at how more general attention to regleprudence can improve our understanding of important corners of the Executive Branch.
The Lawyer as Truth-Teller: Lessons from Enron

This article is included in the symposium "Can the Ordinary Practice of Law Be a Religious Calling?". The teaching and practice of law assume and are shaped by the standard vision of lawyer conduct and ethical responsibility. Under the standard vision, which is reflected in the various codes of professional responsibility governing lawyers, the lawyer is a "neutral partisan" for his or her client: "neutral" in that he does not let his moral values affect his actions on behalf of his client; "partisan" in that she does whatever she can within the limits of the law to advance her client's stated interests. Because the standard vision is readily understood by most lawyers as imposing a code of conduct upon them in their practice of law, the standard vision is referred to as the "Code." Bost evaluates some of the merits or limitations of the Code by examining the decline and fall of Enron Corporation, which has occasioned a comprehensive reappraisal of American business and professional ethics and behavior. He pays particular attention to the role and conduct of Enron's attorneys, especially their primary outside law firm, Vinson & Elkins. Bost proposes that lawyers endeavor to move beyond being mere "implementers" to becoming wise "counselors" to their clients. He concludes the article by examining the Enron situation from the perspective of a Christian lawyer and argues that the teachings of Christ mandate that lawyers must be willing and able to tell their clients the truth, the whole truth and nothing but the truth.
Does Uber Redefine the Firm? The Postindustrial Corporation and Advanced Information Technology

The popular on-demand ride service Uber has become the exemplar of the platform economy and inspired a new narrative about advanced information and communication technologies (ICTs) and the firm. The narrative tells us that Uber facilitates a market between independent businesses and buyers by administering technology that lowers the costs of exchange. Despite borrowing the language of Coasian firm theory, however, the Uber narrative is largely nonsensical within it: Uber appears much more like a seller of transportation services than a market intermediary within a Coasian analysis. By examining disputes over whether drivers for Uber and its competitor Lyft are employees or independent contractors, the Article shows that the Uber narrative reveals not technology’s dissolution of the firm, but rather a disjuncture between the firm and its corporate form. While often belied in practice, major theories of the firm, like that developed by Ronald Coase, assumed the corporation would be a servant to productive enterprise. The emergence of the postindustrial corporation that pursues profit by other means, including speculative activity and regulatory arbitrage, poses another challenge to this ideal. The Uber narrative both obscures and legitimates a weakening nexus between the firm and corporation. The Article hypothesizes several reasons for the Uber narrative’s appeal, despite its illegibility within Coasian theories of the firm, to which judges often appear committed in disputes not involving platform companies. First, the narrative has political valence—it suggests technology renders the firm obsolete, liberating individual producers. Second, the narrative conceals the incongruence between Uber’s corporate identity and organization of productive activity by appealing to the cultural exceptionalism of ICTs and discourses that associate algorithmic programming with the inscrutability of the market. Third, the narrative’s appeal reflects the challenge of theorizing service work under an enduring industrial paradigm. Finally, ICTs disrupt assumptions in Coasian theory about the association of firm and market production with the legal relations of property and contract. ICTs lowered the costs of centralized coordination, or firm production, in part by enabling Uber to control production inputs without acquiring property rights over them.
From consumer to construer: Travels in human subjectivity:

A key component of how human beings organize their lives is how they perceive and make sense of what it means to be human, that is, their subjectivity. Human subjectivity has taken on different dom...
Macroeconomic consequences of accounting : the effect of accounting conservatism on macroeconomic indicators and the money supply

ABSTRACT: This study investigates the macroeconomic consequences of firm-level accounting conservatism. Consistent with conditional conservatism extending to the aggregate level, I demonstrate that annual estimates of aggregate corporate profits and gross domestic product compiled by the U.S. Bureau of Economic Analysis are more sensitive to negative aggregate news than to positive aggregate news. Next, I estimate the dollar value impact of conservatism on measurements of macroeconomic fundamentals. Finally, I show that incorporating the dollar value impact of conservatism increases the explanatory power of a monetary policy reaction function that describes U.S. Federal Reserve interest rate decision behavior. These results suggest that accounting can impact social welfare by altering the measurement attributes of key macroeconomic indicators and by shaping monetary policy decisions that regulate the money supply. JEL Classifications: M41; E43; E52.