The effects of tax deductibility on the mix of property taxes and use charges: an empirical analysis of the spanish case

This paper tests some hypothesis about the determinants of the local tax structure. In particular, we focus on the effects that the property tax deductibility in the national income tax has on the relative use of the property tax and user charges. We deal with the incentive effects that local governments face regarding the different sources of revenue by means of a model in which the local tax structure and the level of public expenditure arise as a result of the maximizing behaviour of local politicians subject to the economic effects of the tax system. We attempt to test the hypothesis developed with data corresponding to a set of Spanish municipalities during the period 1987-9l. We find that tax deductibility provides incentives to raise revenues from the property tax but does not introduce a biass against user charges or in favor of overall spending growth

The effects of tax deductibility on the mix of property taxes and use charges: an empirical analysis of the spanish case

This paper tests some hypothesis about the determinants of the local tax structure. In particular, we focus on the effects that the property tax deductibility in the national income tax has on the relative use of the property tax and user charges. We deal with the incentive effects that local governments face regarding the different sources of revenue by means of a model in which the local tax structure and the level of public expenditure arise as a result of the maximizing behaviour of local politicians subject to the economic effects of the tax system. We attempt to test the hypothesis developed with data corresponding to a set of Spanish municipalities during the period 1987-9l. We find that tax deductibility provides incentives to raise revenues from the property tax but does not introduce a biass against user charges or in favor of overall spending growth

A first-principles analysis of the magnetism of CuII polynuclear coordination complexes: the case of [Cu4(bpy)4(aspartate)2(H2O)3](ClO4)4·2.5H2O

The magnetic structure of the [Cu4(bpy)4(aspartate)2(H2O)3](ClO4)4·2.5 H2Ocrystal - using fractional coordinates determined at room-temperature ¿ has beenanalysed in detail. This analysis has been carried out by extending our first principlesbottom-up theoretical approach, which was initially designed to study through-spacemagnetic interactions, to handle through-bond magnetic interactions. The only input datarequired by this approach are the values of the computed JAB exchange parameters for allthe unique pairs of spin-containing centres. The results allow the magnetic structure ofthe crystal, which presents two types of isolated tetranuclear CuII clusters, to be definedin quantitative terms. Each of these clusters presents ferro and antiferromagneticinteractions, the former being stronger, although outnumbered by the latter. Thecomputed magnetic susceptibility curve shows the same qualitative features as theexperimental data. However, there are small differences that are presumed to beassociated with the use of room-temperature crystal coordinates.

A first-principles analysis of the magnetism of CuII polynuclear coordination complexes: the case of [Cu4(bpy)4(aspartate)2(H2O)3](ClO4)4·2.5H2O

The magnetic structure of the [Cu4(bpy)4(aspartate)2(H2O)3](ClO4)4·2.5 H2Ocrystal - using fractional coordinates determined at room-temperature ¿ has beenanalysed in detail. This analysis has been carried out by extending our first principlesbottom-up theoretical approach, which was initially designed to study through-spacemagnetic interactions, to handle through-bond magnetic interactions. The only input datarequired by this approach are the values of the computed JAB exchange parameters for allthe unique pairs of spin-containing centres. The results allow the magnetic structure ofthe crystal, which presents two types of isolated tetranuclear CuII clusters, to be definedin quantitative terms. Each of these clusters presents ferro and antiferromagneticinteractions, the former being stronger, although outnumbered by the latter. Thecomputed magnetic susceptibility curve shows the same qualitative features as theexperimental data. However, there are small differences that are presumed to beassociated with the use of room-temperature crystal coordinates.

The statistical accuracy of surveys on business and economic perspectives: a case study

In this paper, we develop a new decision making model and apply it in political Surveys of economic climate collect opinions of managers about the short-term future evolution of their business. Interviews are carried out on a regular basis and responses measure optimistic, neutral or pessimistic views about the economic perspectives. We propose a method to evaluate the sampling error of the average opinion derived from a particular type of survey data. Our variance estimate is useful to interpret historical trends and to decide whether changes in the index from one period to another are due to a structural change or whether ups and downs can be attributed to sampling randomness. An illustration using real data from a survey of business managers opinions is discussed.

Factors affecting visual analysis in single-case designs

Visual inspection remains the most frequently applied method for detecting treatment effects in single-case designs. The advantages and limitations of visual inference are here discussed in relation to other procedures for assessing intervention effectiveness. The first part of the paper reviews previous research on visual analysis, paying special attention to the validation of visual analysts" decisions, inter-judge agreement, and false alarm and omission rates. The most relevant factors affecting visual inspection (i.e., effect size, autocorrelation, data variability, and analysts" expertise) are highlighted and incorporated into an empirical simulation study with the aim of providing further evidence about the reliability of visual analysis. Our results concur with previous studies that have reported the relationship between serial dependence and increased Type I rates. Participants with greater experience appeared to be more conservative and used more consistent criteria when assessing graphed data. Nonetheless, the decisions made by both professionals and students did not match sufficiently the simulated data features, and we also found low intra-judge agreement, thus suggesting that visual inspection should be complemented by other methods when assessing treatment effectiveness.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

Assigning and combining probabilities in single-case studies

There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current paper proposes an approach for obtaining further numerical evidence on the importance of the results, complementing the substantive criteria, visual analysis, and primary summary measures. This additional evidence consists of obtaining the statistical significance of the outcome when referred to the corresponding sampling distribution. This sampling distribution is formed by the values of the outcomes (expressed as data nonoverlap, R-squared, etc.) in case the intervention is ineffective. The approach proposed here is intended to offer the outcome"s probability of being as extreme when there is no treatment effect without the need for some assumptions that cannot be checked with guarantees. Following this approach, researchers would compare their outcomes to reference values rather than constructing the sampling distributions themselves. The integration of single-case studies is problematic, when different metrics are used across primary studies and not all raw data are available. Via the approach for assigning p values it is possible to combine the results of similar studies regardless of the primary effect size indicator. The alternatives for combining probabilities are discussed in the context of single-case studies pointing out two potentially useful methods one based on a weighted average and the other on the binomial test.

Particle shape and orientation in laser diffraction and static image analysis size distribution analysis of micrometer sized rectangular particles

Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.

What are the success factors for Spanish textile firms? An exploratory multiple-case study

The objective of this article is to identify differential traits of successful SMEs in comparison to average SME firms in the textile and clothing sector. The method used is the multiple case-study of 12 firms based on qualitative and quantitative data obtained by means of in-depth interviews. Building on recent academic literature, we use four main dimensions that may explain success: i) knowledge generation (R&D) and acquisition; ii) innovation activity; iii) product and market characteristics and iv) strategic characteristics. Our results indicate that a higher R&D intensity and knowledge acquisition do not explain success. The main differential characteristic is that successful firms have a higher level of innovation activity, since innovation is their strategic priority, being a result of perceiving the key success factors of their markets differently. From the analysis it also follows that the prevalent strategy of successful firms is the niche strategy, with a demand pull focus, and a high proximity to the customer

Reconsidering the analysis of the uses of ICTs by political parties : an application to the Catalan case

For years a literature on the uses that political parties make of information andcommunication technologies (ICTs) has been developed. It is a rapidly increasing, rich,and interesting field in the forefront of the investigation in political science. Generally,these works start from the expectation that the ICTs have a regenerative potential forliberal democracies and for the political parties as well. In developed societies, politicalparties have experienced some transformations that have leaded them to an increasingdivorce with the public. This divorce is shown by the decay of party adscription andmembership, and also by the decay of the conventional political participation. In thetheoretical discussion this situation has been described as ¿the crisis of the democracy¿(Norris, 1999). According to the more radically oriented scholars this crisis reflects theincapacities of liberal democracies. In this sense, ICTs suppose a great opportunity tosurpass the representative institutions and to institutionalize new forms of directdemocracy. More moderate scholars have considered that ICTs offer the opportunity for¿renaissance¿ for representative institutions, as they can reinforce the bonds between thepublic and its representatives.

An analysis of the evolution of hydrometeorological extremes in newspapers: the case of Catalonia, 1982-2006

This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation) has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (INUNGAMA) has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use.

Case-Crossover Analysis of Air Pollution Health Effects: A Systematic Review of Methodology and Application

Case-crossover is one of the most used designs for analyzing the health-related effects of air pollution. Nevertheless, no one has reviewed its application and methodology in this context. Objective: We conducted a systematic review of case-crossover (CCO) designs used to study the relationship between air pollution and morbidity and mortality, from the standpoint of methodology and application.Data sources and extraction: A search was made of the MEDLINE and EMBASE databases.Reports were classified as methodologic or applied. From the latter, the following information was extracted: author, study location, year, type of population (general or patients), dependent variable(s), independent variable(s), type of CCO design, and whether effect modification was analyzed for variables at the individual level. Data synthesis: The review covered 105 reports that fulfilled the inclusion criteria. Of these, 24 addressed methodological aspects, and the remainder involved the design’s application. In the methodological reports, the designs that yielded the best results in simulation were symmetric bidirectional CCO and time-stratified CCO. Furthermore, we observed an increase across time in the use of certain CCO designs, mainly symmetric bidirectional and time-stratified CCO. The dependent variables most frequently analyzed were those relating to hospital morbidity; the pollutants most often studied were those linked to particulate matter. Among the CCO-application reports, 13.6% studied effect modification for variables at the individual level.Conclusions: The use of CCO designs has undergone considerable growth; the most widely used designs were those that yielded better results in simulation studies: symmetric bidirectional and time-stratified CCO. However, the advantages of CCO as a method of analysis of variables at the individual level are put to little use