安徽省居民消费、投资与经济增长关系的实证研究

运用协整理论,从长期和短期两个角度对安徽省居民消费、固定资产投资与经济增长之间的关系进行了实证分析。结果表明:三者之间存在着长期稳定的关系,居民消费、固定资产投资对经济增长均具有促进作用。政府应努力调整投资与消费比例,逐步形成"消费主导型"的经济增长模式,提高经济增长的质量。     

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.     

Spatially Balanced Sampling: A Review and A Reappraisal

Spatially distributed data exhibit particular characteristics that should be considered when designing a survey of spatial units. Unfortunately, traditional sampling designs generally do not allow for spatial features, even though it is usually desirable to use information concerning spatial dependence in a sampling design. This paper reviews and compares some recently developed randomised spatial sampling procedures, using simple random sampling without replacement as a benchmark for comparison. The approach taken is design‐based and serves to corroborate intuitive arguments about the need to explicitly integrate spatial dependence into sampling survey theory. Some guidance for choosing an appropriate spatial sampling design is provided, and some empirical evidence for the gains from using these designs with spatial populations is presented, using two datasets as illustrations.     

Inventory record inaccuracy: Causes and labor effects

Inventory record inaccuracy (IRI) is a pervasive problem in retailing and causes non-trivial profit loss. In response to retailers’ interest in identifying antecedents and consequences of IRI, we present a study that comprises multiple modeling initiatives. We first develop a dynamic simulation model to compare and contrast impacts of different operational errors in a continuous (Q, R) inventory system through a full-factorial experimental design. While backroom and shelf shrinkage are found to be predominant drivers of IRI, the other three errors related to recording and shelving have negligible impacts on IRI. Next, we empirically assess the relationships between labor availability and IRI using longitudinal data from five stores in a global retail chain. After deriving a robust measure of IRI through Bayesian computation and estimating panel data models, we find strong evidence that full-time labor reduces IRI whereas part-time labor fails to alleviate it. Further, we articulate the reinforcing relationships between labor and IRI by formally assessing the gain of the feedback loop based on our empirical findings and analyzing immediate, intermediate, and long-term impacts of IRI on labor availability. The feedback modeling effort not only integrates findings from simulation and econometric analysis but also structurally explores the impacts of current practices. We conclude by discussing implications of our findings for practitioners and researchers.     

Linear and nonlinear dynamic relationships between housing prices and trading volumes

This study applied linear and nonlinear causality tests and estimation models to investigate the efficiency of housing prices and volumes in the United States and its four major regions. The results of this study confirm that housing volumes can function as a price-discovery indicator. According to the nonlinear volatility of housing prices, this study verified numerous hypotheses. Housing returns can also influence housing volume. The results of this study imply that housing price efficiency can vary based on market conditions. Consequently, estimating the behavior of housing prices through a linear model can result in underestimating the information reflected by housing returns.     

Risk Classification by Fuzzy Inference

Traditionally, policyholders in life insurance are classified in simple mortality tables, most often according to only a few risk characteristics. Instead of a risk classification according to the numerical rating system, this article describes how to classify by using a fuzzy inference methodology. By defining risk factors as fuzzy sets, it is shown that an insurer can utilize multiple prognostic factors that are imprecise and vague. The presented fuzzy risk classification provides a more realistic way of modeling mortality risks since it allows for compensations and interactions between multiple risk factors.     

Advances in Inequality Measurement and Usefulness of Statistical Inference

Assessment of inequality measurement is the focus for this survey. All measures of inequality must be evaluated based on a set of desirable properties. More importantly, the usefulness of statistical inference for measures of inequality needs examination.

智能气调保鲜箱模糊控制系统的研究

针对气调保鲜箱温度、湿度和氮气浓度控制问题，提出了一种简单实用的模糊控制方案，利用模糊推理合成规则，得出了模糊控制结果。     

Drawing inferences about others on the basis of corporate associations

This research examined how observers use corporate associations (e.g., environmental responsibility) in drawing inferences about a target consumers’ dispositions (e.g., whether the target person really cares about the environment). Respondents read a scenario describing a target consumer purchasing a certain brand of pens, whose maker had recently teamed up with an environmental organization. It was found that target-related factors (e.g., impression motivation, the consistency of behavior) and company-related factors (e.g., the congruity of the supported cause with the companys’ reputation) systematically influenced the dispositional inferences made by the observers.