The Statistical Education of Harold Jeffreys

The paper considers the statistical work of the physicist Harold Jeffreys. In 1933–4 Jeffreys had a controversy with R.A. Fisher, the leading statistician of the time. Prior to the encounter, Jeffreys had worked on probability as the basis for scientific inference and had used methods from the theory of errors in astronomy and seismology. He had also started to rework the theory of errors on the basis of his theory of probability. After the encounter Jeffreys produced a full-scale Bayesian treatment of statistics in the form of his Theory of Probability.     

深基坑支护变形的模糊神经网络预测

由于土体固有性质的复杂性和不确定性，深基坑支护变形与其影响因素之间的关系是极为复杂的非线性关系。本文将神经网络和模糊系统相结合，采用模糊神经网络对深基坑支护变形进行预测，计算实例表明，该方法具有较高的预测精度。     

A quantile approach to US GNP

In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model to the growth rate of real US GNP. We also presented a forecasting method for QSETAR models. This forecasting method makes it possible to obtain the predictive quantiles and predictive distribution function of x_t+m given x_t for m > 0, and hence any quantities of interest can be derived. Therefore, this new approach allows us to study the US GNP from a distribution point view, rather than from a mean point of view. The results obtained in this paper show that the method works very well in practice.     

MIS‐SPECIFICATION TESTING IN RETROSPECT

The primary objective of this paper is threefold. First, to undertake a retrospective view of Mis‐Specification (M‐S) testing, going back to the early 20th century, with a view to (i) place it in the broader context of modeling and inference and (ii) bring out some of its special features. Second, to call into question several widely used arguments undermining the importance of M‐S testing in favor of relying on weak probabilistic assumptions in conjunction with generic robustness claims and asymptotic inference. Third, to bring out the crucial role of M‐S testing in securing trustworthy inference results. This is achieved by extending/modifying Fisher's statistical framework with a view to draw a clear line between the modeling and the inference facets of statistical induction. The proposed framework untangles the statistical from the substantive (structural) model and focuses on how to secure the adequacy of the statistical model before probing for substantive adequacy. A case is made for using joint M‐S tests based on custom‐built auxiliary regressions with a view to enhance the effectiveness and reliability of probing for potential statistical misspecifications.     

Business model schema: business model innovation tool based on direct causal mechanisms of profit

ABSTRACT

Defining business model as the logic/mode/way/framework to seek profit/money and glancing at the evolution of concept business, this paper develops a business model schema (BMS) as a holistic two-dimensions multi-level tool/method for business model innovation (BMI) based on the direct causal mechanisms of profit (DCMP). First, this paper takes DCMP as the logical/theoretical framework by which business model innovation process is identified and specified. And according to that process, it develops a BMS, illustrates an example of BMS to show up its practical usefulness, compares the similarities and differences between BMS and the existing powerful one business model canvas (BMC), and finally asserts that BMS must be a good and useful method in theory and practice because it stands on DCMP that ensures the genuine causality of profit and also it turns out practically useful, recalling the Kurt Lewin’s maxim (1945), “There is nothing so practical as a good theory.     

A simulation estimator for testing the time homogeneity of credit rating transitions

The measurement of credit quality is at the heart of the models designed to assess the reserves and capital needed to support the risks of both individual credits and portfolios of credit instruments. A popular specification for credit-rating transitions is the simple, time-homogeneous Markov model. While the Markov specification cannot really describe processes in the long run, it may be useful for adequately describing short-run changes in portfolio risk. In this specification, the entire stochastic process can be characterized in terms of estimated transition probabilities. However, the simple homogeneous Markovian transition framework is restrictive. We propose a test of the null hypotheses of time-homogeneity that can be performed on the sorts of data often reported. We apply the tests to 4 data sets, on commercial paper, sovereign debt, municipal bonds and S&P-rated Corporates. The results indicate that commercial paper looks Markovian on a 30-day time scale for up to 6 months; sovereign debt also looks Markovian (perhaps due to a small sample size); municipals are well-modeled by the Markov specification for up to 5 years, but could probably benefit from frequent updating of the estimated transition matrix or from more sophisticated modeling, and S&P Corporate ratings are approximately Markov over 3 transitions but not 4.     

Design of a curriculum for destination studies

Since vocational tourism courses started at Sydney Technical College in 1973, there have been problems in teaching about tourist destinations. Historical analysis of the subject's development indicates that problems stem largely from an absence of tourism theory. Throughout this subject's development, there have been four major influences: the vocational needs of tourism students; the definition of tourism systems; the adoption of a primary orientation towards the study of the causes of tourism; and developmental work on the nature of tourist attractions. The current curriculum is described and it is suggested that due to these influences it overcomes many former problems with its integrated inter-disciplinary approach employing tourism theory as the core discipline.     

Perceptions of Deception: Making Sense of Responses to Employee Deceit

In this research, we examine the effects that customer perceptions of employee deception have on the customers’ attitudes toward an organization. Based on interview, archival, and observational data within the international airline industry, we develop a model to explain the complex effects of perceived dishonesty on observer’s attitudes and intentions toward the airline. The data revealed three types of perceived deceit (about beliefs, intentions, and emotions) and three additional factors that influence customer intentions and attitudes: the players involved, the beneficiaries of the deceit, and the harm done by the perceived lie. We develop a model with specific propositions to guide organizations with respect to apparently deceitful behavior of their employees. Implications and directions for future research are provided, focusing on the question of whether organizations should consistently encourage honesty or train their employees to be effective liars.     

中国土地用途监管失灵的法律分析

采取土地用途监管的方法缓解快速城市化给耕地保护、环境保护、弱势群体保护和城乡治理等方面带来的沉重压力,虽取得一定效果,但也出现了"监管失灵"的问题。采用社会性规制的方法,对我国土地用途监管失灵的原因进行了全面分析,研究结果表明土地用途监管失灵既有中国土地法律制度本身存在缺陷的原因,也有土地法律制度没有得以贯彻实施的因素,还有大制度环境对土地用途监管制度的影响。因此,我国当前土地用途监管是改善而不是加强监管。     

Statistical tests of distributional scaling properties for financial return series

Existing empirical evidence of distributional scaling in financial returns has helped motivate the use of multifractal processes for modelling return processes. However, this evidence has relied on informal tests that may be unable to reliably distinguish multifractal processes from other related classes. The current paper develops a formal statistical testing procedure for determining which class of fractal process is most consistent with the distributional scaling properties in a given sample of data. Our testing methodology consists of a set of test statistics, together with a model-based bootstrap resampling scheme to obtain sample p-values. We demonstrate in Monte Carlo exercises that the proposed testing methodology performs well in a wide range of testing environments relevant for financial applications. Finally, the methodology is applied to study the scaling properties of a data-set of intraday equity index and exchange rate returns. The empirical results suggest that the scaling properties of these return series may be inconsistent with purely multifractal processes.