Are rules-based government programs shielded from special-interest politics? Evidence from revenue-sharing transfers in Brazil

Manipulation of government finances for the benefit of narrowly defined groups is usuallythought to be limited to the part of the budget over which politicians exercise discretion inthe short run, such as earmarks. Analyzing a revenue-sharing program between the centraland local governments in Brazil that uses an allocation formula based on local population estimates,I document two main results: first, that the population estimates entering the formulawere manipulated and second, that this manipulation was political in nature. Consistent withswing-voter targeting by the right-wing central government, I find that municipalities withroughly equal right-wing and non-right-wing vote shares benefited relative to opposition orconservative core support municipalities. These findings suggest that the exclusive focus ondiscretionary transfers in the extant empirical literature on special-interest politics may understatethe true scope of tactical redistribution that is going on under programmatic disguise.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Locating emergency services with priority rules: The priority queuing covering location problem

One of the assumptions of the Capacitated Facility Location Problem (CFLP) is thatdemand is known and fixed. Most often, this is not the case when managers take somestrategic decisions such as locating facilities and assigning demand points to thosefacilities. In this paper we consider demand as stochastic and we model each of thefacilities as an independent queue. Stochastic models of manufacturing systems anddeterministic location models are put together in order to obtain a formula for thebacklogging probability at a potential facility location.Several solution techniques have been proposed to solve the CFLP. One of the mostrecently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, isimplemented in order to solve the model formulated. We present some computationalexperiments in order to evaluate the heuristics performance and to illustrate the use ofthis new formulation for the CFLP. The paper finishes with a simple simulationexercise.

Monetary policy rules and macroeconomic stability: Evidence and some theory

We estimate a forward-looking monetary policy reaction function for thepostwar United States economy, before and after Volcker's appointmentas Fed Chairman in 1979. Our results point to substantial differencesin the estimated rule across periods. In particular, interest ratepolicy in the Volcker-Greenspan period appears to have been much moresensitive to changes in expected inflation than in the pre-Volckerperiod. We then compare some of the implications of the estimated rulesfor the equilibrium properties of inflation and output, using a simplemacroeconomic model, and show that the Volcker-Greenspan rule is stabilizing.

Efficient interval scoring rules

Scoring rules that elicit an entire belief distribution through the elicitation of point beliefsare time-consuming and demand considerable cognitive e¤ort. Moreover, the results are validonly when agents are risk-neutral or when one uses probabilistic rules. We investigate a classof rules in which the agent has to choose an interval and is rewarded (deterministically) onthe basis of the chosen interval and the realization of the random variable. We formulatean e¢ ciency criterion for such rules and present a speci.c interval scoring rule. For single-peaked beliefs, our rule gives information about both the location and the dispersion of thebelief distribution. These results hold for all concave utility functions.

Development and Validation of Decision Rules to Guide Frequency of Monitoring CD4 Cell Count in HIV-1 Infection before Starting Antiretroviral Therapy.

Background: Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study.Methodology/Principal Findings: We built up two prediction rules ("Snap-shot rule" for a single sample and "Track-shot rule" for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior >= 5% or < 5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200x10(6)/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold.Conclusions/Significance: Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count > 650 for a threshold of 200, > 900 for 350, or > 1150 for 500x10(6)/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

Rules or consequences? The role of ethical mindsets in moral dynamics

Recent research on the dynamics of moral behavior has documented two contrastingphenomena - moral consistency and moral balancing. Moral balancing refers to thephenomenon whereby behaving (un)ethically decreases the likelihood of doing so againat a later time. Moral consistency describes the opposite pattern - engaging in(un)ethical behavior increases the likelihood of doing so later on. Three studies supportthe hypothesis that individuals' ethical mindset (i.e., outcome-based versus rule-based)moderates the impact of an initial (un)ethical act on the likelihood of behaving ethicallyin a subsequent occasion. More specifically, an outcome-based mindset facilitates moralbalancing and a rule-based mindset facilitates moral consistency.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Assessment of a new MRI classification of spinal stenosis based on cross-sectional morphology of the dural sac : FM2

Introduction: Quantitative measures of degree of lumbar spinal stenosis (LSS) such as antero-posterior diameter of the canal or dural sac cross sectional area vary widely and do not correlate with clinical symptoms or results of surgical decompression. In an effort to improve quantification of stenosis we have developed a grading system based on the morphology of the dural sac and its contents as seen on T2 axial images. The grading comprises seven categories ranging form normal to the most severe stenosis and takes into account the ratio of rootlet/CSF content. Material and methods: Fifty T2 axial MRI images taken at disc level from twenty seven symptomatic lumbar spinal stenosis patients who underwent decompressive surgery were classified into seven categories by five observers and reclassified 2 weeks later by the same investigators. Intra- and inter-observer reliability of the classification were assessed using Cohen's and Fleiss' kappa statistics, respectively. Results: Generally, the morphology grading system itself was well adopted by the observers. Its success in application is strongly influenced by the identification of the dural sac. The average intraobserver Cohen's kappa was 0.53 ± 0.2. The inter-observer Fleiss' kappa was 0.38 ± 0.02 in the first rating and 0.3 ± 0.03 in the second rating repeated after two weeks. Discussion: In this attempt, the teaching of the observers was limited to an introduction to the general idea of the morphology grading system and one example MRI image per category. The identification of the dimension of the dural sac may be a difficult issue in absence of complete T1 T2 MRI image series as it was the case here. The similarity of the CSF to possibly present fat on T2 images was the main reason of mismatch in the assignment of the cases to a category. The Fleiss correlation factors of the five observers are fair and the proposed morphology grading system is promising.

Setting the rules of the game: The choice of electoral systems in advanced democracies

The origins of electoral systems have received scant attention in the literature. Looking at the history of electoral rules in the advanced world in the last century, this paper shows that the existing wide variation in electoral rules across nations can be traced to the strategic decisions that the current ruling parties, anticipating the coordinating consequences of different electoral regimes, make to maximize their representation according to the following conditions. On the one hand, as long as the electoral arena does not change substantially and the current electoral regime serves the ruling parties well, the latter have no incentives to modify the electoral regime. On the other hand, as soon as the electoral arena changes (due to the entry of new voters or a change in their preferences), the ruling parties will entertain changing the electoral system, depending on two main conditions: the emergence of new parties and the coordinating capacities of the old ruling parties. Accordingly, if the new parties are strong, the old parties shift from plurality/majority rules to proportional representation (PR) only if the latter are locked into a 'non-Duvergerian' equilibrium; i.e. if no old party enjoys a dominant position (the case of most small European states)--conversely, they do not if a Duvergerian equilibrium exists (the case of Great Britain). Similarly, whenever the new entrants are weak, a non-PR system is maintained, regardless of the structure of the old party system (the case of the USA). The paper discusses as well the role of trade and ethnic and religious heterogeneity in the adoption of PR rules.

On the efficiency and sensitivity of a pyramidal classification algorithm

In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.

Price regulation of plastic money: A critical assessment of Spanish rules

Recent decisions by the Spanish national competition authority (TDC) mandate paymentsystems to include only two costs when setting their domestic multilateral interchange fees(MIF): a fixed processing cost and a variable cost for the risk of fraud. This artificiallowering of MIFs will not lower consumer prices, because of uncompetitive retailing; but itwill however lead to higher cardholders fees and, likely, new prices for point of saleterminals, delaying the development of the immature Spanish card market. Also, to the extent that increased cardholders fees do not offset the fall in MIFs revenue, the task of issuing new cards will be underpaid relatively to the task of acquiring new merchants, causing an imbalance between the two sides of the networks. Moreover, the pricing scheme arising from the decisions will cause unbundling and underprovision of those services whose costs are excluded. Indeed, the payment guarantee and the free funding period will tend to be removed from the package of services currently provided, to be either provided by third parties, by issuers for a separate fee, or not provided at all, especially to smaller and medium-sized merchants. Transaction services will also suffer the consequences that the TDC precludes pricing them in variable terms.