2,802 research outputs found

    An instrumental variable model of multiple discrete choice

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    This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. We show that the model delivers set, not point, identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions. The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.

    An instrumental variable model of multiple discrete choice

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    This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. We show that the model delivers set identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions. The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.

    Towards a Framework for DHT Distributed Computing

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    Distributed Hash Tables (DHTs) are protocols and frameworks used by peer-to-peer (P2P) systems. They are used as the organizational backbone for many P2P file-sharing systems due to their scalability, fault-tolerance, and load-balancing properties. These same properties are highly desirable in a distributed computing environment, especially one that wants to use heterogeneous components. We show that DHTs can be used not only as the framework to build a P2P file-sharing service, but as a P2P distributed computing platform. We propose creating a P2P distributed computing framework using distributed hash tables, based on our prototype system ChordReduce. This framework would make it simple and efficient for developers to create their own distributed computing applications. Unlike Hadoop and similar MapReduce frameworks, our framework can be used both in both the context of a datacenter or as part of a P2P computing platform. This opens up new possibilities for building platforms to distributed computing problems. One advantage our system will have is an autonomous load-balancing mechanism. Nodes will be able to independently acquire work from other nodes in the network, rather than sitting idle. More powerful nodes in the network will be able use the mechanism to acquire more work, exploiting the heterogeneity of the network. By utilizing the load-balancing algorithm, a datacenter could easily leverage additional P2P resources at runtime on an as needed basis. Our framework will allow MapReduce-like or distributed machine learning platforms to be easily deployed in a greater variety of contexts

    A Sectarian School Asserts Its Religious Beliefs; Have the Courts Narrowed the Constitutional Right to Free Exercise of Religion?

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    The United States Supreme Court, in denying certiorari, has allowed to stand a Fifth Circuit opinion which held that the segregationist policies of a sectarian school were not religious and, therefore, not protected by the free exercise clause of the first amendment. This holding arose out of a section 1981 action by a black family whose children were turned away when they attempted to enroll. The author argues that the decision was based on erroneous analysis and has resulted in a dangerous narrowing of the scope of constitutional protection of religious freedom

    Revenue implications of New York City's tax system

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    A study of New York City's tax system finds that over the past three decades, the system has become less reliant on property and general sales taxes and more dependent on corporate and personal income taxes. This shift has made the city's tax revenues less stable than the revenues of the 1970s and more sensitive to cyclical swings.Taxation - New York (N.Y.) ; Revenue ; Federal Reserve District, 2nd ; Local government

    What explains variation in the costs of treating patients in English obstetrics specialties?

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    We assess patients admitted to English obstetrics departments to identify what proportion of variation in their costs is explained by patient characteristics and what proportion is due to departmental characteristics. Hospital Episode Statistics records for every patient admitted to obstetrics departments are matched to Reference Cost data by HRG reported by all English hospitals for the year 2005/6. Our sample consists of 951,277 patients in 136 departments. We estimate fixed effects models analysing patient-level costs, explore departmental characteristics that drive variation in costs at department-level and explore the sensitivity of results to the use of the full sample and sub-samples of obstetrics patients. Patient costs depend on various diagnostic characteristics over and above the HRG classification, particularly whether the patient suffered infection. After controlling for patient characteristics a substantial amount of unexplained variation in costs remains at departmental level. Higher costs are evident in departments that are not supported by a neonatology specialty and where factor prices are higher. There is evidence of lower costs in departments with high volumes of activity. We identify departments where further scrutiny of their high costs is required.

    Concord University School of Law\u27s On-Line Law Degree Program

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    Identification of the distribution of valuations in an incomplete model of English auctions

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    An incomplete model of English auctions with symmetric independent private values, similar to the one studied in Haile and Tamer (2003), is shown to fall in the class of Generalized Instrumental Variable Models introduced in Chesher and Rosen (2014). A characterization of the sharp identi.ed set for the distribution of valuations is thereby obtained and shown to re.ne the bounds available until now

    Contributions of temporal encodings of voicing, voicelessness, fundamental frequency, and amplitude variation to audiovisual and auditory speech perception

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    Auditory and audio-visual speech perception was investigated using auditory signals of invariant spectral envelope that temporally encoded the presence of voiced and voiceless excitation, variations in amplitude envelope and F-0. In experiment 1, the contribution of the timing of voicing was compared in consonant identification to the additional effects of variations in F-0 and the amplitude of voiced speech. In audio-visual conditions only, amplitude variation slightly increased accuracy globally and for manner features. F-0 variation slightly increased overall accuracy and manner perception in auditory and audio-visual conditions. Experiment 2 examined consonant information derived from the presence and amplitude variation of voiceless speech in addition to that from voicing, F-0, and voiced speech amplitude. Binary indication of voiceless excitation improved accuracy overall and for voicing and manner. The amplitude variation of voiceless speech produced only a small increment in place of articulation scores. A final experiment examined audio-visual sentence perception using encodings of voiceless excitation and amplitude variation added to a signal representing voicing and F-0. There was a contribution of amplitude variation to sentence perception, but not of voiceless excitation. The timing of voiced and voiceless excitation appears to be the major temporal cues to consonant identity. (C) 1999 Acoustical Society of America. [S0001-4966(99)01410-1]
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