JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Stability and Competitive Equilibrium in Trading Networks John William HatfieldUniversity of Texas at Austin Scott Duke KominersHarvard University and University of Chicago Alexandru Nichifor University of St Andrews Michael OstrovskyStanford University Alexander Westkamp Maastricht UniversityWe introduce a model in which agents in a network can trade via bilateral contracts. We find that when continuous transfers are allowed and utilities are quasi-linear, the full substitutability of preferences is sufficient to guarantee the existence of stable outcomes for any underlying network structure. Furthermore, the set of stable outcomes is essentially equivalent to the set of competitive equilibria, and all stable outcomes are in the core and are efficient. By contrast, for any domain of preferences strictly larger than that of full substitutability, the existence of stable outcomes and competitive equilibria cannot be guaranteed.

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements-an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements-an observation that is consistent with "tipping" theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods-an observation that is consistent with the "invasion" theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities.urban economics | gentrification | urban studies | computer vision | neighborhood effects F or more than a century, urban planners, economists, sociologists, and architects have advanced theories connecting the dynamics of a neighborhood's physical appearance to its location, demographics, and built infrastructure.The tipping theory of Schelling (1) and Grodzins (2) suggests that neighborhoods in bad physical condition will get progressively worse, whereas nicer areas will get better. Economic theories of urban change at the city level often emphasize population density and education (3-6), and it is natural to hypothesize that agglomeration of human capital will predict neighborhood-level improvements as well. Theories from urban sociology, such as the invasion theory of Burgess (7), however, emphasize locations and social networks, predicting that improvements in a city's appearance should be spatially clustered, and that improvements should occur both near the central business districts (CBDs) and near other physically attractive neighborhoods.To test theories of physical neighborhood change, we need to quantify neighborhood appearance at different points in time. Historically, however, methods to quantify neighborhood appearance have not been scalable. The empirical literature on urban appearance, which was pioneered by urban planners such as Lynch (8), Rapoport (9), and Nasar (10), as well as by psychologists such as Milgram (11), has relied on interviews, lowthroughput visual perception surveys, and manual evaluation of images. Those methods, however, can only be used to collect data on a few neighborhoods and have limited spatial resolution. In the past decade, new data on urban appearance have emerged in the form of "street view" imagery (12). As of 2016, Google Street View has photographe...

We develop a model of intergenerational resource transmission that emphasizes the link between cross-sectional inequality and intergenerational mobility. By drawing on first principles of human capital theory, we derive several novel results. In particular, we show that, even in a world with perfect capital markets and without differences in innate ability, wealthy parents invest, on average, more in their offspring than poorer ones. As a result, persistence of economic status is higher at the top of the income distribution than in the middle. Successive generations of the same family may even cease to regress towards the mean. Moreover, we demonstrate that government interventions intended to ameliorate inequality may in fact lower intergenerational mobility-even when they do not directly favor the rich. Lastly, we consider how mobility is affected by changes in the marketplace.

We introduce a two‐sided, many‐to‐one matching with contracts model in which agents with unit demand match to branches that may have multiple slots available to accept contracts. Each slot has its own linear priority order over contracts; a branch chooses contracts by filling its slots sequentially, according to an order of precedence. We demonstrate that in these matching markets with slot‐specific priorities, branches' choice functions may not satisfy the substitutability conditions typically crucial for matching with contracts. Despite this complication, we are able to show that stable outcomes exist in the slot‐specific priorities framework and can be found by a cumulative offer mechanism that is strategy‐proof and respects unambiguous improvements in priority.

We introduce the problem of shape replication in the Wang tile self-assembly model. Given an input shape, we consider the problem of designing a self-assembly system which will replicate that shape into either a specific number of copies, or an unbounded number of copies. Motivated by practical DNA implementations of Wang tiles, we consider a model in which tiles consisting of DNA or RNA can be dynamically added in a sequence of stages. We further permit the addition of RNase enzymes capable of disintegrating RNA tiles. Under this model, we show that arbitrary genus-0 shapes can be replicated infinitely many times using only O(1) distinct tile types and O(1) stages. Further, we show how to replicate precisely n copies of a shape using O(log n) stages and O(1) tile types.

Build more capacity, and stretch what we already have

Software that standardizes the assignment of a unique seeded hash identifier merged through an agreed upon third-party honest broker can enable large-scale secure linkage of EHR data for epidemiologic and public health research. The software algorithm can improve future epidemiologic research by providing more comprehensive data given that patients may make use of multiple healthcare systems.

We introduce a model in which firms trade goods via bilateral contracts which specify a buyer, a seller, and the terms of the exchange. This setting subsumes (many-to-many) matching with contracts, as well as supply chain matching. When firms' relationships do not exhibit a supply chain structure, stable allocations need not exist. By contrast, in the presence of supply chain structure, a natural substitutability condition characterizes the maximal domain of firm preferences for which stable allocations always exist. Furthermore, the classical lattice structure, rural hospitals theorem, and one-sided strategy-proofness results all generalize to this setting.The theoretical literature on two-sided matching began with the simple one-to-one (marriage) model of Gale and Shapley (1962), in which agents on opposite sides of a market (men and women) seek to match into pairs. The central solution concept in this literature is stability, the requirement that, if two agents are not matched to each other, at least one of them prefers his or her assigned partner to the other agent. Gale and Shapley (1962) showed that stable one-to-one matches exist in general, and obtained conditions under which this existence result is preserved even if agents on one side of the market are allowed to match to multiple partners, that is, when the matching is many-to-one (as in college admissions and doctor-hospital matching). Following high-profile applications of matching in labor markets and school choice programs, 1 the foundational work on matching has been extensively generalized. 2 Kelso and Crawford (1982) extended many-to-one matching to a setting in which matches are supplemented by wage negotiations; Hatfield and Milgrom (2005) generalized this framework still further, by allowing agents to negotiate contracts which fully specify both a matching and the conditions of the match; the possibility of such a generalization was first noted by remarks of Crawford and Knoer (1981) and Kelso and Crawford (1982).Meanwhile, a host of work has studied the existence of stable matchings in many-to-many matching settings, two-sided markets in which all agents may match to multiple partners (as in the matching of consultants to firms). Many-to-many matching has been studied, for example, in the work of Sotomayor (1999Sotomayor ( , 2004, Echenique and Oviedo (2006), and Konishi andÜnver (2006). Recently, Walzl (2009) andKominers (2010) merged this line of research with that of Hatfield and Milgrom (2005), introducing a theory of many-to-many matching with contracts.