Explaining Fiscal Balances with a Simultaneous Equation Model of Revenue and Expenditure : A Case Study of Swiss Cantons Using Panel Data

Empirical literature on the analysis of the efficiency of measures for reducing persistent government deficits has mainly focused on the direct explanation of deficit. By contrast, this paper aims at modeling government revenue and expenditure within a simultaneous framework and deriving the fiscal balance (surplus or deficit) equation as the difference between the two variables. This setting enables one to not only judge how relevant the explanatory variables are in explaining the fiscal balance but also understand their impact on revenue and/or expenditure. Our empirical results, obtained by using a panel data set on Swiss Cantons for the period 1980-2002, confirm the relevance of the approach followed here, by providing unambiguous evidence of a simultaneous relationship between revenue and expenditure. They also reveal strong dynamic components in revenue, expenditure, and fiscal balance. Among the significant determinants of public fiscal balance we not only find the usual business cycle elements, but also and more importantly institutional factors such as the number of administrative units, and the ease with which people can resort to political (direct democracy) instruments, such as public initiatives and referendum.

The health promotion model and rare disease patients : a mixed methods study examining adherence to treatment in men with congenital hypogonadotropic hypogonadism

Rare diseases are typically chronic medical conditions of genetic etiology characterized by low prevalence and high complexity. Patients living with rare diseases face numerous physical, psychosocial and economic challenges that place them in the realm of health disparities. Congenital hypogonadotropic hypogonadism (CHH) is a rare endocrine disorder characterized by absent puberty and infertility. Little is known about the psychosocial impact of CHH on patients or their adherence to available treatments. This project aimed to examine the relationship between illness perceptions, depressive symptoms and adherence to treatment in men with CHH using the nursing-sensitive Health Promotion Model (HPM). A community based participatory research (CBPR) framework was employed as a model for empowering patients and overcoming health inequities. The study design used a sequential, explanatory mixed-methods approach. To reach dispersed CHH men, we used web-based recruitment and data collection (online survey). Subsequently, three patient focus groups were conducted to provide explanatory insights into the online survey (i.e. barriers to adherence, challenges of CHH, and coping/support) The online survey (n=101) revealed that CHH men struggle with adherence and often have long gaps in care (40% >1 year). They experience negative psychosocial consequences because of CHH and exhibit significantly increased rates of depression (p<0.001). Focus group participants (n=26) identified healthcare system, interpersonal, and personal factors as barriers to adherence. Further, CHH impacts quality of life and impedes psychosexual development in these men. The CHH men are active internet users who rely on the web forcrowdsourcing solutions and peer-to-peer support. Moreover, they are receptive to web-based interventions to address unmet health needs. This thesis contributes to nursing knowledge in several ways. First, it demonstrates the utility of the HPM as a valuable theoretical construct for understanding medication adherence and for assessing rare disease patients. Second, these data identify a range of unmet health needs that are targets for patient-centered interventions. Third, leveraging technology (high-tech) effectively extended the reach of nursing care while the CBPR approach and focus groups (high-touch) served as concurrent nursing interventions facilitating patient empowerment in overcoming health disparities. Last, these findings hold promise for developing e-health interventions to bridge identified shortfalls in care and activating patients for enhanced self- care and wellness -- Les maladies rares sont généralement de maladies chroniques d'étiologie génétique caractérisées par une faible prévalence et une haute complexité de traitement. Les patients atteints de maladies rares sont confrontés à de nombreux défis physiques, psychosociaux et économiques qui les placent dans une posture de disparité et d'inégalités en santé. L'hypogonadisme hypogonadotrope congénital (CHH) est un trouble endocrinien rare caractérisé par l'absence de puberté et l'infertilité. On sait peu de choses sur l'impact psychosocial du CHH sur les patients ou leur adhésion aux traitements disponibles. Ce projet vise à examiner la relation entre la perception de la maladie, les symptômes dépressifs et l'observance du traitement chez les hommes souffrant de CHH. Cette étude est modélisée à l'aide du modèle de la Promotion de la santé de Pender (HPM). Le cadre de l'approche communautaire de recherche participative (CBPR) a aussi été utilisé. La conception de l'étude a reposé sur une approche mixte séquentielle. Pour atteindre les hommes souffrant de CHH, un recrutement et une collecte de données ont été organisées électroniquement. Par la suite, trois groupes de discussion ont été menées avec des patients experts impliqués au sein d'organisations reliés aux maladies rares. Ils ont été invités à discuter certains éléments additionnels dont, les obstacles à l'adhésion au traitement, les défis généraux de vivre avec un CHH, et l'adaptation à la maladie en tenant compte du soutien disponible. Le sondage en ligne (n = 101) a révélé que les hommes souffrant de CHH ont souvent de longues périodes en rupture de soins (40% > 1 an). Ils vivent des conséquences psychosociales négatives en raison du CHH et présentent une augmentation significative des taux de dépression (p <0,001). Les participants aux groupes de discussion (n = 26) identifient dans l'ordre, les systèmes de soins de santé, les relations interpersonnelles, et des facteurs personnels comme des obstacles à l'adhésion. En outre, selon les participants, le CHH impacte négativement sur leur qualité de vie générale et entrave leur développement psychosexuel. Les hommes souffrant de CHH se considèrent être des utilisateurs actifs d'internet et comptent sur le web pour trouver des solutions pour trouver des ressources et y recherchent le soutien de leurs pairs (peer-to-peer support). En outre, ils se disent réceptifs à des interventions qui sont basées sur le web pour répondre aux besoins de santé non satisfaits. Cette thèse contribue à la connaissance des soins infirmiers de plusieurs façons. Tout d'abord, elle démontre l'utilité de la HPM comme une construction théorique utile pour comprendre l'adhésion aux traitements et pour l'évaluation des éléments de promotion de santé qui concernent les patients atteints de maladies rares. Deuxièmement, ces données identifient une gamme de besoins de santé non satisfaits qui sont des cibles pour des interventions infirmières centrées sur le patient. Troisièmement, méthodologiquement parlant, cette étude démontre que les méthodes mixtes sont appropriées aux études en soins infirmiers car elles allient les nouvelles technologies qui peuvent effectivement étendre la portée des soins infirmiers (« high-tech »), et l'approche CBPR par des groupes de discussion (« high-touch ») qui ont facilité la compréhension des difficultés que doivent surmonter les hommes souffrant de CHH pour diminuer les disparités en santé et augmenter leur responsabilisation dans la gestion de la maladie rare. Enfin, ces résultats sont prometteurs pour développer des interventions e-santé susceptibles de combler les lacunes dans les soins et l'autonomisation de patients pour une meilleure emprise sur les auto-soins et le bien-être.

Creating a customer profitability accounting model

Customer profitability accounting is a well-researched topic in the academic field, and it has been proved to posses rather undisputable benefits. However, the calculation of the customer profitabilities can be challenging, therefore the usage of the accounting is not self-explanatory in organizations. The aim of this study was to create a customer profitability accounting model for a wholesales unit in the case company to function as a sales management tool. The literature review of the study presents certain fundamental issues related to customer profitability accounting, in addition a theoretical framework for accounting model design is provided. The creation of the model was commenced by setting the requirements for it and examining the foundation of the model design, which consisted of for instance price setting and cost structure of products. This was followed by selecting approaches to the creation of the model. The result of the study was an accounting model, for which a determination of included revenues and costs was executed, along with the formulation of an allocation criteria of the costs. Lastly, the customer profitabilities were calculated in accordance with the accounting principles and the calculation logic of the model. The attained figures proved the model to provide an appropriate solution for obtaining the customer profitabilities and thus to use the accounting information as a sales management tool in for instance decision making and negotiation situations.

E-tailer business model creation: an information technology perspective

This research analyzes e-tailer business model formulation and the role of information technology in enabling value creation from the point of view of an e-tailer. The thesis explains the value creation dynamics and the components of an e-tailer business model and further illustrates how information technology enables value creation throughout the different components of e-tailer business models. The theoretical part of the thesis describes the sources of value creation in virtual markets through evaluating the explanatory value of traditional strategic management theories. The theoretical part advances to present an integrated model of the value creation mechanisms in the virtual markets and further describes the components of an e-tailer business model. The role of information technology in e-tailer business models are represented by illustrating how it is able to add value throughout the activities and processes of the e-tailer business model. The empirical descriptive qualitative single-case research focuses on demonstrating how a global retailer of consumer goods operates the different components in its business model. The findings indicate that information technology plays a considerable role in all the components of an e-tailer business model and should not be treated solely as a supporting business function, but rather as one of the most valuable assets in enabling successful e-tailing operations.

A Log-linear model of grain size influence on the geochemistry of sediments

Sediment composition is mainly controlled by the nature of the source rock(s), and chemical (weathering) and physical processes (mechanical crushing, abrasion, hydrodynamic sorting) during alteration and transport. Although the factors controlling these processes are conceptually well understood, detailed quantification of compositional changes induced by a single process are rare, as are examples where the effects of several processes can be distinguished. The present study was designed to characterize the role of mechanical crushing and sorting in the absence of chemical weathering. Twenty sediment samples were taken from Alpine glaciers that erode almost pure granitoid lithologies. For each sample, 11 grain-size fractions from granules to clay (ø grades <-1 to >9) were separated, and each fraction was analysed for its chemical composition. The presence of clear steps in the box-plots of all parts (in adequate ilr and clr scales) against ø is assumed to be explained by typical crystal size ranges for the relevant mineral phases. These scatter plots and the biplot suggest a splitting of the full grain size range into three groups: coarser than ø=4 (comparatively rich in SiO2, Na2O, K2O, Al2O3, and dominated by “felsic” minerals like quartz and feldspar), finer than ø=8 (comparatively rich in TiO2, MnO, MgO, Fe2O3, mostly related to “mafic” sheet silicates like biotite and chlorite), and intermediate grains sizes (4≤ø <8; comparatively rich in P2O5 and CaO, related to apatite, some feldspar). To further test the absence of chemical weathering, the observed compositions were regressed against three explanatory variables: a trend on grain size in ø scale, a step function for ø≥4, and another for ø≥8. The original hypothesis was that the trend could be identified with weathering effects, whereas each step function would highlight those minerals with biggest characteristic size at its lower end. Results suggest that this assumption is reasonable for the step function, but that besides weathering some other factors (different mechanical behavior of minerals) have also an important contribution to the trend. Key words: sediment, geochemistry, grain size, regression, step function

What should we expect of a liberal explanatory theory?

One of the most problematic aspects of the ‘Harvard School’ of liberal international theory is its failure to fulfil its own methodological ideals. Although Harvard School liberals subscribe to a nomothetic model of explanation, in practice they employ their theories as heuristic resources. Given this practice, we should expect them neither to develop candidate causal generalizations nor to be value-neutral: their explanatory insights are underpinned by value-laden choices about which questions to address and what concepts to employ. A key question for liberal theorists, therefore, is how a theory may be simultaneously explanatory and value-oriented. The difficulties inherent in resolving this problem are manifested in Ikenberry’s writing: whilst his work on constitutionalism in international politics partially fulfils the requirements of a more satisfactory liberal explanatory theory, his recent attempts to develop prescriptions for US foreign policy reproduce, in a new form, key failings of Harvard School realism.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Cálculo do Value at Risk (VaR) para o Ibovespa, pós crise de 2008, por meio dos modelos de heterocedasticidade condicional (GARCH) e de volatilidade estocástica (Local Scale Model - LSM)

O objetivo deste estudo é propor a implementação de um modelo estatístico para cálculo da volatilidade, não difundido na literatura brasileira, o modelo de escala local (LSM), apresentando suas vantagens e desvantagens em relação aos modelos habitualmente utilizados para mensuração de risco. Para estimação dos parâmetros serão usadas as cotações diárias do Ibovespa, no período de janeiro de 2009 a dezembro de 2014, e para a aferição da acurácia empírica dos modelos serão realizados testes fora da amostra, comparando os VaR obtidos para o período de janeiro a dezembro de 2014. Foram introduzidas variáveis explicativas na tentativa de aprimorar os modelos e optou-se pelo correspondente americano do Ibovespa, o índice Dow Jones, por ter apresentado propriedades como: alta correlação, causalidade no sentido de Granger, e razão de log-verossimilhança significativa. Uma das inovações do modelo de escala local é não utilizar diretamente a variância, mas sim a sua recíproca, chamada de “precisão” da série, que segue uma espécie de passeio aleatório multiplicativo. O LSM captou todos os fatos estilizados das séries financeiras, e os resultados foram favoráveis a sua utilização, logo, o modelo torna-se uma alternativa de especificação eficiente e parcimoniosa para estimar e prever volatilidade, na medida em que possui apenas um parâmetro a ser estimado, o que representa uma mudança de paradigma em relação aos modelos de heterocedasticidade condicional.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Community College Student Participation in Undergraduate Research: An Explanatory Case Study for Faculty and Research Mentors

This study adapted the current model of science undergraduate research experiences (URE's) and applied this novel modification to include community college students. Numerous researchers have examined the efficacy of URE's in improving undergraduate retention and graduation rates, as well as matriculation rates for graduate programs. However, none have detailed the experience for community college students, and few have employed qualitative methodologies to gather relevant descriptive data from URE participants. This study included perspectives elicited from both non-traditional student participants and the established laboratory community. The purpose of this study was to determine the effectiveness of the traditional model for a non-traditional student population. The research effort described here utilized a qualitative design and an explanatory case study methodology. Six non-traditional students from the Maine Community College System participated in this study. Student participants were placed in six academic research laboratories located throughout the state. Student participants were interviewed three times during their ten-week internship and asked to record their personal reflections in electronic format. Participants from the established research community were also interviewed. These included both faculty mentors and other student laboratory personnel. Ongoing comparative analysis of the textual data revealed that laboratory organizational structure and social climate significantly influence acculturation outcomes for non-traditional URE participants. Student participants experienced a range of acculturation outcomes from full integration to marginalization. URE acculturation outcomes influenced development of non-traditional students? professional and academic self-concepts. Positive changes in students? self-concepts resulted in greater commitment to individual professional goals and academic aspirations. The findings from this study suggest that traditional science URE models can be successfully adapted to meet the unique needs of a non-traditional student population – community college students. These interpretations may encourage post-secondary educators, administrators, and policy makers to consider expanded access and support for non-traditional students seeking science URE opportunities.

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

Bayesian model selection methodology for road safety

Road accidents are a very relevant issue in many countries and macroeconomic models are very frequently applied by academia and administrations to reduce their frequency and consequences. The selection of explanatory variables and response transformation parameter within the Bayesian framework for the selection of the set of explanatory variables a TIM and 3IM (two input and three input models) procedures are proposed. The procedure also uses the DIC and pseudo -R2 goodness of fit criteria. The model to which the methodology is applied is a dynamic regression model with Box-Cox transformation (BCT) for the explanatory variables and autorgressive (AR) structure for the response. The initial set of 22 explanatory variables are identified. The effects of these factors on the fatal accident frequency in Spain, during 2000-2012, are estimated. The dependent variable is constructed considering the stochastic trend component.

Information systems outsourcing satisfaction: some explanatory factors

Purpose – The purpose of this paper is to analyse Information Systems outsourcing success, measuring the latter according to the satisfaction level achieved by users and taking into account three success factors: the role played by the client firm’s top management; the relationships between client and provider; and the degree of outsourcing. Design/methodology/approach – A survey was carried out by means of a questionnaire answered by 398 large Spanish firms. Its results were examined using the partial least squares software and through the proposal of a structural equation model. Findings – The conclusions reveal that the perceived benefits play a mediating role in outsourcing satisfaction and also that these benefits can be grouped together into three categories: strategic; economic; and technological ones. Originality/value – The study identifies how some success factors will be more influent than others depending which type of benefits are ultimately sought with outsourcing.

Size and book to market effects and the Fama French three factor asset pricing model: Evidence from the Australian stockmarket

The present study adds to the sparse published Australian literature on the size effect, the book to market (BM) effect and the ability of the Fama French three factor model to account for these effects and to improve on the asset pricing ability of the Capital Asset Pricing Model (CAPM). The present study extends the 1981–1991 period examined by Halliwell, Heaney and Sawicki (1999) a further 10 years to 2000 and addresses several limitations and findings of that research. In contrast to Halliwell, Heaney and Sawicki the current study finds the three factor model provides significantly improved explanatory power over the CAPM, and evidence that the BM factor plays a role in asset pricing.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.