The backfiring effect of auditing on tax compliance

Using country-level data from 2003–2014, we examine the association between auditing level (measured as number of verification actions taken by tax authorities per 100 taxpayers in each country) and tax compliance (measured as business executives’ perception of tax evasion). Our hypothesis is that compliance increases until a certain auditing level is reached, and decreases beyond that level (i.e., an elevated auditing level backfires). In line with our expectation, the results of a series of tests indicate that there is a U-shaped association between auditing and tax evasion. We discuss how a potential backfiring effect may depend on the extent to which compliance is voluntary.     

VALIDATION OF EXPERT SYSTEMS- WITH APPLICATIONS TO AUDITING AND ACCOUNTING EXPERT SYSTEMS*

This paper proposes a set of definitions for the concepts “validation” and “assessment” applied to expert systems (ESs). It develops a framework for this validation and demonstrates the framework on existing accounting and auditing ESs to elicit some of the research issues involved in ES validation. Validation is critical to the design and implementation of decision-making ESs. In a setting where objectivity is sought and variance is avoided, validation ascertains what a system knows, knows incorrectly, or does not know. Validation ascertains the system's level of expertise and investigates the theoretical basis on which the system is based. It evaluates the reliability of decisions made by the system. The validation framework developed in this paper is research methods. It is designed to reflect the unique aspects of ESs (in contrast to other types of computer programs) and can be used by ES developers as a basis from which to perform validation and by researchers as a framework to elicit research issues in validation.     

Auditors' Assessment of Management's Disposition: An Attributional Analysis*

Auditors' assessment of management's dispositions presumably affects their subsequent judgments. However, little is known about the process by which auditors infer characteristics of management. This paper proposes the theory of correspondent inferences [25] as a framework for examining auditors' assessment of management's dispositions; the model is tested in a laboratory experiment using experienced audit managers. The results are consistent with the proposed theoretical framework. Implications for future research are discussed.     

Construction of Confidence Intervals for the IVIean of a Population Containing Many Zero Values

The likelihood ratio method is used to construct a confidence interval for a population mean when sampling from a population with certain characteristics found in many applications, such as auditing. Specifically, a sample taken from this type of population usually consists of a very large number of zero values, plus a small number of nonzero values that follow some continuous distribution. In this situation, the traditional confidence interval constructed for the population mean is known to be unreliable. This article derives confidence intervals based on the likelihood-ratio-test approach by assuming (1) a normal distribution (normal algorithm) and (2) an exponential distribution (exponential algorithm). Because the error population distribution is usually unknown, it is important to study the robustness of the proposed procedures. We perform an extensive simulation study to compare the percentage of confidence intervals containing the true population mean using the two proposed algorithms with the percentage obtained from the traditional method based on the central limit theorem. It is shown that the normal algorithm is the most robust procedure against many different distributional error assumptions.     

Robust models in probability sampling

In the estimation of a population mean or total from a random sample, certain methods based on linear models are known to be automatically design consistent, regardless of how well the underlying model describes the population. A sufficient condition is identified for this type of robustness to model failure; the condition, which we call 'internal bias calibration', relates to the combination of a model and the method used to fit it. Included among the internally bias-calibrated models, in addition to the aforementioned linear models, are certain canonical link generalized linear models and nonparametric regressions constructed from them by a particular style of local likelihood fitting. Other models can often be made robust by using a suboptimal fitting method. Thus the class of model-based, but design consistent, analyses is enlarged to include more realistic models for certain types of survey variable such as binary indicators and counts. Particular applications discussed are the estimation of the size of a population subdomain, as arises in tax auditing for example, and the estimation of a bootstrap tail probability.     

高校应该如何加强基建维修工程审计

当前市场经济体制改革已打破了高校以国家拨款为主要来源的预算资金管理体制 ,逐步形成了多渠道筹措经费的新格局。在新形势下高校内部应采取完善的措施 ,以提高基建维修工程的审计质量     

企业内部控制中存在的问题与对策

内部控制是企业经营活动中强化内部会计监督,进行自我调节和自我约束的内在机制。我国企业在内部控制环境、会计责权控制和内部审计方面存在一些问题,必须建立健全企业内部控制机制。推动企业内部控制目标的实现,实现企业价值最大化。     

周、汉审计史新议——兼评《中国审计史》第一卷

新出版的巨著《中国审计史》体现了我国审计史研究的新高度。其第一卷古代审计史,内容充实,美中不足之处是个别史料有误解,对宝贵的简牍史料发掘不够。本文着重论述了开独立于行政系统的国家审计之先河的周朝内史审计和汉简中的审计活动。     

A Bayesian method of sample size determination with practical applications

Summary.  The problem motivating the paper is the determination of sample size in clinical trials under normal likelihoods and at the substantive testing stage of a financial audit where normality is not an appropriate assumption. A combination of analytical and simulation-based techniques within the Bayesian framework is proposed. The framework accommodates two different prior distributions: one is the general purpose fitting prior distribution that is used in Bayesian analysis and the other is the expert subjective prior distribution, the sampling prior which is believed to generate the parameter values which in turn generate the data. We obtain many theoretical results and one key result is that typical non-informative prior distributions lead to very small sample sizes. In contrast, a very informative prior distribution may either lead to a very small or a very large sample size depending on the location of the centre of the prior distribution and the hypothesized value of the parameter. The methods that are developed are quite general and can be applied to other sample size determination problems. Some numerical illustrations which bring out many other aspects of the optimum sample size are given.     

刑事庭审旁听制度研究

旁听制度作为刑事审判公开制度中的一个必要方面,对于整个刑事审判制度具有重要意义,但是无论在理论上或是司法实践中旁听制度都未能引起足够的重视。通过对我国目前旁听制度存在问题进行分析,找到症结之所在,从认识上进行一定的转变,并且给予旁听以更完善的保障措施,才能在此基础上不断推进旁听制度的完善。