Elections, information aggregation, and strategic voting

A central role of elections is the aggregation of information dispersed within a population. This article surveys recent work on elections as mechanisms for aggregating information and on the incentives for voters to vote strategically in such elections.

Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

One Person, Many Votes: Divided Majority and Information Aggregation

In elections, majority divisions pave the way to focal manipulations and coordination failures, which can lead to the victory of the wrong candidate. This paper shows how this flaw can be addressed if voter preferences over candidates are sensitive to information. We consider two potential sources of divisions: majority voters may have similar preferences but opposite information about the candidates, or opposite preferences. We show that when information is the source of majority divisions, Approval Voting features a unique equilibrium with full information and coordination equivalence. That is, it produces the same outcome as if both information and coordination problems could be resolved. Other electoral systems, such as Plurality and Two-Round elections, do not satisfy this equivalence. The second source of division is opposite preferences. Whenever the fraction of voters with such preferences is not too large, Approval Voting still satisfies full information and coordination equivalence.

Noise and aggregation of information in large markets

We study a novel class of noisy rational expectations equilibria in markets with largenumber of agents. We show that, as long as noise increases with the number of agents inthe economy, the limiting competitive equilibrium is well-defined and leads to non-trivialinformation acquisition, perfect information aggregation, and partially revealing prices,even if per capita noise tends to zero. We find that in such equilibrium risk sharing and price revelation play dierent roles than in the standard limiting economy in which per capita noise is not negligible. We apply our model to study information sales by a monopolist, information acquisition in multi-asset markets, and derivatives trading. Thelimiting equilibria are shown to be perfectly competitive, even when a strategic solutionconcept is used.

Expert Information and Majority Decisions

This paper studies dichotomous majority voting in common interest committees where each member receives not only a private signal but also a public signal observed by all of them. The public signal represents, e.g. expert information presented to an entire committee and its quality is higher than that of each individual private signal. We identify two informative symmetric strategy equilibria, namely i) the mixed strategy equilibrium where each member randomizes between following the private and public signals should they disagree; and ii) the pure strategy equilibrium where they follow the public signal for certain. The former outperforms the latter. The presence of the public signal precludes the equilibrium where every member follows their own signal, which is an equilibrium in the absence of the public signal. The mixed strategy equilibrium in the presence of the public signal outperforms the sincere voting equilibrium without the public signal, but the latter may be more efficient than the pure strategy equilibrium in the presence of the public signal. We suggest that whether expert information improves committee decision making depends on equilibrium selection.

Aggregation and errors in management accounting

Il est important pour les entreprises de compresser les informations détaillées dans des sets d'information plus compréhensibles. Au chapitre 1, je résume et structure la littérature sur le sujet « agrégation d'informations » en contrôle de gestion. Je récapitule l'analyse coûts-bénéfices que les comptables internes doivent considérer quand ils décident des niveaux optimaux d'agrégation d'informations. Au-delà de la perspective fondamentale du contenu d'information, les entreprises doivent aussi prendre en considération des perspectives cogni- tives et comportementales. Je développe ces aspects en faisant la part entre la comptabilité analytique, les budgets et plans, et la mesure de la performance. Au chapitre 2, je focalise sur un biais spécifique qui se crée lorsque les informations incertaines sont agrégées. Pour les budgets et plans, des entreprises doivent estimer les espérances des coûts et des durées des projets, car l'espérance est la seule mesure de tendance centrale qui est linéaire. A la différence de l'espérance, des mesures comme le mode ou la médiane ne peuvent pas être simplement additionnés. En considérant la forme spécifique de distributions des coûts et des durées, l'addition des modes ou des médianes résultera en une sous-estimation. Par le biais de deux expériences, je remarque que les participants tendent à estimer le mode au lieu de l'espérance résultant en une distorsion énorme de l'estimati¬on des coûts et des durées des projets. Je présente également une stratégie afin d'atténuer partiellement ce biais. Au chapitre 3, j'effectue une étude expérimentale pour comparer deux approches d'esti¬mation du temps qui sont utilisées en comptabilité analytique, spécifiquement « coûts basés sur les activités (ABC) traditionnelles » et « time driven ABC » (TD-ABC). Au contraire des affirmations soutenues par les défenseurs de l'approche TD-ABC, je constate que cette dernière n'est pas nécessairement appropriée pour les calculs de capacité. Par contre, je démontre que le TD-ABC est plus approprié pour les allocations de coûts que l'approche ABC traditionnelle. - It is essential for organizations to compress detailed sets of information into more comprehensi¬ve sets, thereby, establishing sharp data compression and good decision-making. In chapter 1, I review and structure the literature on information aggregation in management accounting research. I outline the cost-benefit trade-off that management accountants need to consider when they decide on the optimal levels of information aggregation. Beyond the fundamental information content perspective, organizations also have to account for cognitive and behavi¬oral perspectives. I elaborate on these aspects differentiating between research in cost accounti¬ng, budgeting and planning, and performance measurement. In chapter 2, I focus on a specific bias that arises when probabilistic information is aggregated. In budgeting and planning, for example, organizations need to estimate mean costs and durations of projects, as the mean is the only measure of central tendency that is linear. Different from the mean, measures such as the mode or median cannot simply be added up. Given the specific shape of cost and duration distributions, estimating mode or median values will result in underestimations of total project costs and durations. In two experiments, I find that participants tend to estimate mode values rather than mean values resulting in large distortions of estimates for total project costs and durations. I also provide a strategy that partly mitigates this bias. In the third chapter, I conduct an experimental study to compare two approaches to time estimation for cost accounting, i.e., traditional activity-based costing (ABC) and time-driven ABC (TD-ABC). Contrary to claims made by proponents of TD-ABC, I find that TD-ABC is not necessarily suitable for capacity computations. However, I also provide evidence that TD-ABC seems better suitable for cost allocations than traditional ABC.

Aggregation invariance in general clustering approaches

General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.

Clinical and Breed Characteristics of Idiopathic Head Tremor Syndrome in 291 Dogs: A Retrospective Study.

Objective. To establish signalment and phenomenology of canine idiopathic head tremor syndrome (IHTS), an episodic head movement disorder of undetermined pathogenesis. Design. Retrospective case series. Animals. 291 dogs with IHTS diagnosed between 1999 and 2013. Procedures. Clinical information was obtained from an online community of veterinary information aggregation and exchange (Veterinary Information Network, 777 W Covell Boulevard, Davis, CA 95616) and conducted with their approval. Information on breed, sex, age of onset, tremor description, mentation during the event, effect of distractions and drugs, diagnostics, presence of other problems, and outcome was analyzed. Results. IHTS was found in 24 pure breeds. Bulldogs, Labrador Retrievers, Boxers, and Doberman Pinschers comprised 69%; mixed breeds comprised 17%. Average onset age was 29 months (range: 3 months to 12 years). First episode occurred before 48 months of age in 88%. Vertical (35%), horizontal (50%), and rotational (15%) movements were documented. Possible trigger events were found in 21%. Mentation was normal in 93%. Distractions abated the tremor in 87%. Most dogs did not respond to antiepileptic drugs. Conclusions and Clinical Relevance. This retrospective study documents IHTS in many breeds including Labrador Retrievers, Boxers, and mixed breeds.

Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders

Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.

A qualitive reasoning approach for improving query results for sketch based queries by topological analysis of spatial aggregation

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Linear Aggregation In The Social Accounting Matrix Framework

In economic literature, information deficiencies and computational complexities have traditionally been solved through the aggregation of agents and institutions. In inputoutput modelling, researchers have been interested in the aggregation problem since the beginning of 1950s. Extending the conventional input-output aggregation approach to the social accounting matrix (SAM) models may help to identify the effects caused by the information problems and data deficiencies that usually appear in the SAM framework. This paper develops the theory of aggregation and applies it to the social accounting matrix model of multipliers. First, we define the concept of linear aggregation in a SAM database context. Second, we define the aggregated partitioned matrices of multipliers which are characteristic of the SAM approach. Third, we extend the analysis to other related concepts, such as aggregation bias and consistency in aggregation. Finally, we provide an illustrative example that shows the effects of aggregating a social accounting matrix model.

Aggregation of liposomes induced by calcium: A structural and kinetic study

In this work, the calcium-induced aggregation of phosphatidylserine liposomes is probed by means of the analysis of the kinetics of such process as well as the aggregate morphology. This novel characterization of liposome aggregation involves the use of static and dynamic light-scattering techniques to obtain kinetic exponents and fractal dimensions. For salt concentrations larger than 5 mM, a diffusion-limited aggregation regime is observed and the Brownian kernel properly describes the time evolution of the diffusion coefficient. For slow kinetics, a slightly modified multiple contact kernel is required. In any case, a time evolution model based on the numerical resolution of Smoluchowski's equation is proposed in order to establish a theoretical description for the aggregating system. Such a model provides an alternative procedure to determine the dimerization constant, which might supply valuable information about interaction mechanisms between phospholipid vesicles.