The Making of International Tax Law: Empirical Evidence from Tax Treaties Text

We offer the first attempt at empirically testing the level of transnational consensus on the legal language controlling international tax matters. We also investigate the institutional framework of such consensus-building. We build a dataset of 4,052 bilateral income tax treaties, as well as 16 model tax treaties published by the United Nations (U.N.), Organisation for Economic Co-operation and Development (OECD), and the United States. We use natural language processing to perform pair-wise comparison of all treaties in effect at any given year. We identify clear trends of convergence of legal language in bilateral tax treaties since the 1960s, particularly on the taxation of cross-border business income. To explore the institutional source of such consensus, we compare all treaties in effect for any given year to the model treaties in effect during that year. We also explore whether recently concluded treaties converge towards legal language in newly introduced models. We find the OECD Model Tax Convention (OECD Model) to have a significant influence. The years following the adoption of a new OECD Model show a clear trend of convergence in newly adopted bilateral tax treaties towards the language of the new OECD Model. We also find that model treaties published by the U.N. (U.N. Model) have little immediate observable effect, though U.N. treaty policies seem to have a delayed, yet lasting effect. These findings portray the OECD as the institutional source of legal drafting on international tax matters. The normative implications of these findings, however, are not obvious. We offer several normative interpretations for our findings

New Policing, New Segregation: From Ferguson to New York

In popular and political culture, many observers credit nearly twenty-five years of declining crime rates to the “New Policing.” Breaking with a past tradition of “reactive policing,” the New Policing emphasizes advanced statistical metrics, new forms of organizational accountability, and aggressive tactical enforcement of minor crimes. The existing research and scholarship on these developments have focused mostly on the nation’s major cities, where concentrated populations and elevated crime rates provide pressurized laboratories for police experimentation, often in the spotlight of political scrutiny. An additional line of scholarship has looked more closely at how the tactics of the New Policing have become institutionalized in police – citizen interactions in the everyday lives of residents of poorer, often minority, and higher-crime areas of the nation’s cities. These efforts have often overlooked how this New Policing has been woven into the social, political, and legal fabrics of smaller, less densely populated areas. These areas are characterized by more intimate and individualized relationships among citizens, courts, and police, as well as closely spaced local boundaries with a considerable flow of persons through administrative entities such as villages and towns. The New Policing models have had extensive reach into the everyday lives of citizens living in these areas, yet little research has been done on their effect. In popular discourse, small-town policing seems like a different world from urban policing; police – citizen interactions are both quantitatively less common and qualitatively distinct. It is an open question whether the processes of policing and the experiences of citizens in these more intimate spaces can be understood through the same framework as urban policing

DocSCAN: Unsupervised Text Classification via Learning from Neighbors

We introduce DocSCAN, a completely unsupervised text classification approach using Semantic Clustering by Adopting Nearest-Neighbors (SCAN). For each document, we obtain semantically informative vectors from a large pre-trained language model. Similar documents have proximate vectors, so neighbors in the representation space tend to share topic labels. Our learnable clustering approach uses pairs of neighboring datapoints as a weak learning signal. The proposed approach learns to assign classes to the whole dataset without provided ground-truth labels. On five topic classification benchmarks, we improve on various unsupervised baselines by a large margin. In datasets with relatively few and balanced outcome classes, DocSCAN approaches the performance of supervised classification. The method fails for other types of classification, such as sentiment analysis, pointing to important conceptual and practical differences between classifying images and texts.Comment: in Proceedings of the 18th Conference on Natural Language Processing (KONVENS 2022). Potsdam, German

The Performance of Elected Officials: Evidence from State Supreme Courts

This paper provides evidence on the effect of electoral institutions on the performance of public officials. Using panel data on state supreme courts between 1947 and 1994, we measure the effects of changes in judicial electoral processes on judge work quality – as measured by citations by later judges. Judges selected by non-partisan elections write higher-quality opinions than judges selected by partisan elections. Judges selected by technocratic merit commissions write higher-quality opinions than either partisan-elected judges or non-partisan-elected judges. Election-year politics reduces judicial performance in both partisan and non-partisan election systems. Giving stronger tenure to non-partisan-selected judges improves performance, while giving stronger tenure to partisan-selected judges has no effect. These results are consistent with the view that technocratic merit commissions have better information about the quality of candidates than voters, and that political bias can reduce the quality of elected officials

Intrinsic Motivation in Public Service: Theory and Evidence from State Supreme Courts

This paper provides a theoretical and empirical analysis of the intrinsic preferences of state appellate court judges. We construct a panel data set using published decisions from state supreme court cases merged with institutional and biographical information on all (1,700) state supreme court judges for the 50 states of the United States from 1947 to 1994. We exploit variation in the employment conditions of judges over this period of time to measure the effect of these changes on a number of measures of judicial performance. The results are consistent with the hypothesis that judges are intrinsically motivated to provide high-quality decisions, and that at the margin they prefer quality over quantity. When judges face less time pressure, they write more well-researched opinions that are cited more often by later judges. When judges are up for election then performance falls, consistent with the hypothesis that election politics is time-consuming. These effects are strongest when judges have more discretion to select their case portfolio, consistent with psychological theories that posit a negative effect of contingency on motivation (e.g. Deci, 1971). Finally, the intrinsic preference for quality appears to be higher among judges selected by non-partisan elections than among those selected by partisan elections

Mapping the Geometry of Law using Document Embeddings

Recent work in natural language processing represents language objects (words and documents) as dense vectors that encode the relations between those objects. This paper explores the application of these methods to legal language, with the goal of understanding judicial reasoning and the relations between judges. In an application to federal appellate courts, we show that these vectors encode information that distinguishes courts, time, and legal topics. The vectors do not reveal spatial distinctions in terms of political party or law school attended, but they do highlight generational differences across judges. We conclude the paper by outlining a range of promising future applications of these methods

If We Build It, Will They Legislate? Empirically Testing the Potential of the Nondelegation Doctrine to Curb Congressional Abdication

A widely held view for why the Supreme Court would be right to revive the nondelegation doctrine is that Congress has perverse incentives to abdicate its legislative role and evade accountability through the use of delegations, either expressly delineated or implied through statutory imprecision, and that enforcement of the nondelegation doctrine would correct for those incentives. We call this the Field of Dreams Theory—if we build the nondelegation doctrine, Congress will legislate. Unlike originalist arguments for the revival of the nondelegation doctrine, this theory has widespread appeal and is instrumental to the Court’s project of gaining popular acceptance of a greater judicial role in policing congressional decisions regarding delegation. But is it true?In this article, we comprehensively test the theory at the state level, using two original datasets: one comprising all laws passed by state legislatures and the other comprising all nondelegation decisions in the state Supreme Courts. Using a variety of measures and methods, and in contrast with the one existing study on the subject, we do observe at least some statistically measurable decrease in delegation, if only by certain measures. However, when put in context, these findings are underwhelming compared to the predictions of the Field of Dreams Theory. For instance, we observe that, even where it exists, this effect is substantively small and on par with a number of other factors that influence delegation—our best estimate is that nondelegation cases explain about 1.5 percent of the variation in delegation. Moreover, we also find some evidence that is directly contrary to the Field of Dreams Theory—that is, we find evidence that enforcement of the nondelegation doctrine actually leads to more implied delegation in the form of vague and precatory statutory language. These findings have direct relevance to contemporary debate and cases entertaining a revitalization of the nondelegation doctrine in the federal courts. First, the findings that enforcement of the doctrine can prospectively decrease legislative delegation suggest that there may be something to the Field of Dreams Theory, although that in turn raises the stakes of debates over whether less delegation would actually be good for public welfare. Second, even though there is an effect, the weakness of that effect, both in an absolute sense and relative to other factors, undermines the overblown claims that the nondelegation doctrine could fundamentally transform how government works. And finally, our finding that judicial decisions enforcing the nondelegation doctrine can sometimes lead to more implied delegation through imprecise statutory language suggests that there may be unintended consequences from giving the nondelegation doctrine a new lease on life