1000 resultados para Data Secrecy


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New data on the distributibn and conservation status of some angiosperms of the Cape Verde Islands, W Africa Intensive field work aud analysis of the state of biodiversity ou all islands during the years iYY.3 lo IYYY Icd lo lhc publication ol’several contributions lo the flora and vegelalion of the archipclago of Cabo Verde (Brochniann & al. 1997, Gornes & Vera-Cruz 1993. Gonles & al. I9YSa-h. 1998, Games 1997. Kilian & Leyens 1994, Leyens 1998. Leyens & Lobin 1995, Lobin & al. 1995) as well as to the compilation of the First Red Data List for the Cape Verde Islnuds (Lcyrus & Lobin 1996). the elaboration of the National Strategy for Biodiversity Conservation (SIPA 19YY) and ! compilation of all areas in urgent need of protection (Leyens unpubl. diplonla thc.\is IYYJ. Gwnes & al. iu prep.). As part UC the activities of the lnstituto National de Invcstig;u$o c Dcscnvolvitucnto Agriirio (INIDA) and the Dcpurtamcnto de GeociSncias do Institute Supcriot de Educ;u$o t ISE) iutcnsive t’icld studies were conducted PI many diffcrctu localilics OII xcvcr;~I islands. resulting in a thesis tGo~nes IY97) and several terminal study papers (Luz IYYY. Cosi;t 1994. Gonsalvez 1999). The results show that the vegetation and flora of the islands arc still IWI fully known and much more field work is needed. hllhot~gh Sanliiqw is one of lhc islands whcrc lhc firs1 holanicill iIlVcxligilliollx wcrr c:crriul WI (Wcbh 1x49. Schruidt 1x52. Chcvalicr IY35) and where uu~ny intensive field studirs wcrc

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Bakeriella lata sp. nov. (Brazil, Rondônia), Bakeriella aurata sp. nov. (Brazil, Amazonas) and Bakeriella sulcaticeps sp. nov. (Brazil, Amazonas) are described and illustrated. New geographic records and variation data for B. cristata Evans, 1964, B. floridana Evans, 1964, B. flavicornis Kieffer, 1910, B. incompleta Azevedo, 1994, B. mira Evans, 1997, B. montivaga (Kieffer, 1910), B. olmeca Evans, 1964 and B. subcarinata Evans, 1965 are provided. The male of B. incompleta is described for the first time.

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The growth of pharmaceutical expenditure and its prediction is a major concern for policy makers and health care managers. This paper explores different predictive models to estimate future drug expenses, using demographic and morbidity individual information from an integrated healthcare delivery organization in Catalonia for years 2002 and 2003. The morbidity information consists of codified health encounters grouped through the Clinical Risk Groups (CRGs). We estimate pharmaceutical costs using several model specifications, and CRGs as risk adjusters, providing an alternative way of obtaining high predictive power comparable to other estimations of drug expenditures in the literature. These results have clear implications for the use of risk adjustment and CRGs in setting the premiums for pharmaceutical benefits.

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A method to estimate DSGE models using the raw data is proposed. The approachlinks the observables to the model counterparts via a flexible specification which doesnot require the model-based component to be solely located at business cycle frequencies,allows the non model-based component to take various time series patterns, andpermits model misspecification. Applying standard data transformations induce biasesin structural estimates and distortions in the policy conclusions. The proposed approachrecovers important model-based features in selected experimental designs. Twowidely discussed issues are used to illustrate its practical use.

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With the quickening pace of crash reporting, the statistical editing of data on a weekly basis, and the ability to provide working databases to users at CTRE/Iowa Traffic Safety Data Service, the University of Iowa, and the Iowa DOT, databases that would be considered incomplete by past standards of static data files are in “public use” even as the dynamic nature of the central DOT database allows changes to be made to both the aggregate of data and to the individual crashes already reported. Moreover, “definitive” analyses of serious crashes will, by their nature, lag seriously behind the preliminary data files. Even after these analyses, the dynamic nature of the mainframe data file means that crash numbers can continue to change long after the incident year. The Iowa DOT, its Office of Driver Services (the “data owner”), and institutional data users/distributors must establish data use, distribution, and labeling protocols to deal with the new, dynamic nature of data. In order to set these protocols, data must be collected concerning the magnitude of difference between database records and crash narratives and diagrams. This study determines the difference between database records and crash narratives for the Iowa Department of Transportation’s Office of Traffic and Safety crash database and the impacts of this difference.

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Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

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Young women involved in the juvenile justice system present with characteristics and experiences that differentiate them from their male counterparts. As such, the juvenile justice system in Iowa must consider these factors if it is to effectively and efficiently impact recidivism and rehabilitation.

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We evaluate conditional predictive densities for U.S. output growth and inflationusing a number of commonly used forecasting models that rely on a large number ofmacroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used normality assumption fit actual realizationsout-of-sample. Our focus on predictive densities acknowledges the possibility that, although some predictors can improve or deteriorate point forecasts, they might have theopposite effect on higher moments. We find that normality is rejected for most modelsin some dimension according to at least one of the tests we use. Interestingly, however,combinations of predictive densities appear to be correctly approximated by a normaldensity: the simple, equal average when predicting output growth and Bayesian modelaverage when predicting inflation.

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Using historical data for all Swiss cantons from 1890 to 2000, we estimate the causal effect of direct democracy on government spending. The main innovation in this paper is that we use fixed effects to control for unobserved heterogeneity and instrumental variables to address the potential endogeneity of institutions. We find that the budget referendum and lower costs to launch a voter initiative are effective tools in reducing canton level spending. However, we find no evidence that the budget referendum results in more decentralized government or a larger local government. Our instrumental variable estimates suggest that a mandatory budget referendum reduces the size of canton spending between 13 and 19 percent. A 1 percent lower signature requirement for the initiative reduces canton spending by up to 2 percent.

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Foreign trade statistics are the main data source to the study of international trade.However its accuracy has been under suspicion since Morgernstern published hisfamous work in 1963. Federico and Tena (1991) have resumed the question arguing thatthey can be useful in an adequate level of aggregation. But the geographical assignmentproblem remains unsolved. This article focuses on the spatial variable through theanalysis of the reliability of textile international data for 1913. A geographical biasarises between export and import series, but because of its quantitative importance it canbe negligible in an international scale.

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In spite of its relative importance in the economy of many countriesand its growing interrelationships with other sectors, agriculture has traditionally been excluded from accounting standards. Nevertheless, to support its Common Agricultural Policy, for years the European Commission has been making an effort to obtain standardized information on the financial performance and condition of farms. Through the Farm Accountancy Data Network (FADN), every year data are gathered from a rotating sample of 60.000 professional farms across all member states. FADN data collection is not structured as an accounting cycle but as an extensive questionnaire. This questionnaire refers to assets, liabilities, revenues and expenses, and seems to try to obtain a "true and fair view" of the financial performance and condition of the farms it surveys. However, the definitions used in the questionnaire and the way data is aggregated often appear flawed from an accounting perspective. The objective of this paper is to contrast the accounting principles implicit in the FADN questionnaire with generally accepted accounting principles, particularly those found in the IVth Directive of the European Union, on the one hand, and those recently proposed by the International Accounting Standards Committee’s Steering Committeeon Agriculture in its Draft Statement of Principles, on the other hand. There are two reasons why this is useful. First, it allows to make suggestions how the information provided by FADN could be more in accordance with the accepted accounting framework, and become a more valuable tool for policy makers, farmers, and other stakeholders. Second, it helps assessing the suitability of FADN to become the starting point for a European accounting standard on agriculture.

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Many factors inhibiting and facilitating economic growth havebeen suggested. Can agnostics rely on international incomedata to tell them which matter? We find that agnostic priorslead to conclusions that are sensitive to differences acrossavailable income estimates. For example, the PWT 6.2 revisionof the 1960-96 income estimates in the PWT 6.1 leads tosubstantial changes regarding the role of government,international trade, demography, and geography. We concludethat margins of error in international income estimates appeartoo large for agnostic growth empirics.