The evolution of tax morale in modern Spain

This paper studies the evolution of tax morale in Spain in the post-France era. In contrast to the previous tax compliance literature, the current paper investigates tax morale as the dependent variable and attempts to answer what actually shapes tax morale. Te analysis uses suevey data from two sources; the World Values Survey and the European Values Survey, allowing us to observe tax morale in Spain for the years 1981,1990, 1995 and 1999/2000. The sutudy of evolution of tax morale in Spain over nearly a 20-year span is particularly interesting because the political and fiscal system evolved very rapidly during this period.

A Knight without a Sword? The Effects of Audit Courts on Tax Morale

The intention of this paper is to analyse how audit courts affect tax morale, controlling in a multivariate analysis for a broad variety of potential factors. Switzerland, with its variety of audit-court competence among the cantons, has been analysed. With data from the ISSP [1998] (Swiss data 1999), evidence has been found that higher audit-court competence has a significantly positive effect on tax morale. Thus, the results in Switzerland suggest that in the cantons where audit courts are not just knights without swords; they help improve taxpayers' tax morale and thus citizens' intrinsic motivation to pay taxes.

Gender and public attitude toward corruption and tax evasion

The topics of corruption and tax evasion have attracted significant attention in the literature in recent years. We build on that literature by investigating empirically: (1) whether attitudes toward corruption and tax evasion vary systematically with gender and (2) whether gender differences decline as men and women face similar opportunities for illicit behavior. We use data on eight Western European countries from the World Values Survey and the European Values Survey. The results reveal significantly greater aversion to corruption and tax evasion among women. This holds across countries and time, and across numerous empirical specifications. (JEL H260, D730, J160, Z130)

The impact of tax morale and institutional quality on the shadow economy

This paper uses a multivariate analysis to examine how countries‘ tax morale and institutional quality affect the shadow economy. The literature strongly emphasizes the quantitative importance of these factors in understanding the level of and changes in the shadow economy. Newly available data sources offer the unique opportunity to further illuminate a topic that has received increased attention. After controlling for a variety of potential factors, we find strong support that a higher tax morale and a higher institutional quality lead to a smaller shadow economy.

Local autonomy, tax morale, and the shadow economy

Policymakers often propose strict enforcement strategies to fight the shadow economy and to increase tax morale. However, there is an alternative bottom-up approach that decentralises political power to those who are close to the problems. This paper analyses the relationship with local autonomy. We use data on tax morale at the individual level and macro data on the size of the shadow economy to analyse the relevance of local autonomy and compliance in Switzerland. The findings suggest that there is a positive (negative) relationship between local autonomy and tax morale (size of the shadow economy).

Serious tax non compliance : motivation and guardianship

This article reviews what international evidence exists on the impact of civil and criminal sanctions upon serious tax noncompliance by individuals. This construct lacks sharp definitional boundaries but includes large tax fraud and large-scale evasion that are not dealt with as fraud. Although substantial research and theory have been developed on general tax evasion and compliance, their conclusions might not apply to large-scale intentional fraudsters. No scientifically defensible studies directly compared civil and criminal sanctions for tax fraud, although one U.S. study reported that significantly enhanced criminal sanctions have more effects than enhanced audit levels. Prosecution is public, whereas administrative penalties are confidential, and this fact encourages those caught to pay heavy penalties to avoid publicity, a criminal record, and imprisonment.

Estimating the cost of health care–associated infections : mind your p’s and q’s

Monetary valuations of the economic cost of health care–associated infections (HAIs) are important for decision making and should be estimated accurately. Erroneously high estimates of costs, designed to jolt decision makers into action, may do more harm than good in the struggle to attract funding for infection control. Expectations among policy makers might be raised, and then they are disappointed when the reduction in the number of HAIs does not yield the anticipated cost saving. For this article, we critically review the field and discuss 3 questions. Why measure the cost of an HAI? What outcome should be used to measure the cost of an HAI? What is the best method for making this measurement? The aim is to encourage researchers to collect and then disseminate information that accurately guides decisions about the economic value of expanding or changing current infection control activities.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Estimating the latent demand for rail transit : a case study in Perth, Western Australia

This paper presents a study on estimating the latent demand for rail transit in Australian context. Based on travel mode-choice modelling, a two-stage analysis approach is proposed, namely market population identification and mode share estimation. A case study is conducted on Midland-Fremantle rail transit corridor in Perth, Western Australia. The required data mainly include journey-to-work trip data from Australian Bureau of Statistics Census 2006 and work-purpose mode-choice model in Perth Strategic Transport Evaluation Model. The market profile is analysed, such as catchment areas, market population, mode shares, mode specific trip distributions and average trip distances. A numerical simulation is performed to test the sensitivity of the transit ridership to the change of fuel price. A corridor-level transit demand function of fuel price is thus obtained and its characteristics of elasticity are discussed. This study explores a viable approach to developing a decision-support tool for the assessment of short-term impacts of policy and operational adjustments on corridor-level demand for rail transit.

Evaluation of TxDOT’s J.A.C.K. model for revenue and expenditure projections

This research report documents work conducted by the Center for Transportation (CTR) at The University of Texas at Austin in analyzing the Joint Analysis using the Combined Knowledge (J.A.C.K.) program. This program was developed by the Texas Department of Transportation (TxDOT) to make projections of revenues and expenditures. This research effort was to span from September 2008 to August 2009, but the bulk of the work was completed and presented by December 2008. J.A.C.K. was subsequently renamed TRENDS, but for consistency with the scope of work, the original name is used throughout this report.