浅谈事故路段道路的排队长度问题

通过观察参考文献视频一中各个时间段内交通事故路段输入车辆与输出车辆的数目,运用SPSS软件,建立了统计回归模型。运用回归系数,得出了统计回归模型的参数。对模型进行了评估．进而得出了交通事故所影响的路段车辆排队长度与事故横断面实际通行能力和事故持续时间之间的关系。     

试论构建地方政府债务绩效考核指标体系

公共产品理论认为,地方政府债务是一把“双刃剑”,如何发挥其积极作用具有重要的理论和现实意义。文章通过构建地方政府债务绩效考核指标体系和分析模型,对当地政府债务投入绩效进行考核。地方政府根据绩效考核结果和当地财政收支情况及经济发展战略,从债务投入的源头入手,引导其投入领域和项目及投入规模,提高债务资金的使用效益,充分发挥债务资金这把“双刃剑”的积极作用,防范债务风险的发生。     

高科技风投企业家项目考察阶段的非理性决策实证研究——基于人口统计特征分析

基于人口统计特征,采用列联表和多元线性回归的方法分析人口统计特征中有关的年龄、学历、留学经历与家庭结构等要素与高科技风投企业家非理性行为在项目考察阶段决策的相关性结果显示:国外留学经验、创业成功经验与企业家项目考察阶段的非理性决策存在着相关性。     

Predicting Corporate Bankruptcy: An Evaluation of Alternative Statistical Frameworks

Corporate bankruptcy prediction has attracted significant research attention from business academics, regulators and financial economists over the past five decades. However, much of this literature has relied on quite simplistic classifiers such as logistic regression and linear discriminant analysis (LDA). Based on a large sample of US corporate bankruptcies, we examine the predictive performance of 16 classifiers, ranging from the most restrictive classifiers (such as logit, probit and linear discriminant analysis) to more advanced techniques such as neural networks, support vector machines (SVMs) and “new age” statistical learning models including generalised boosting, AdaBoost and random forests. Consistent with the findings of Jones et al. ( 2015 ), we show that quite simple classifiers such as logit and LDA perform reasonably well in bankruptcy prediction. However, we recommend the use of “new age” classifiers in corporate bankruptcy modelling because: (1) they predict significantly better than all other classifiers on both the cross‐sectional and longitudinal test samples; (2) the models may have considerable practical appeal because they are relatively easy to estimate and implement (for instance, they require minimal researcher intervention for data preparation, variable selection and model architecture specification); and (3) while the underlying model structures can be very complex, we demonstrate that “new age” classifiers have a reasonably good level of interpretability through such metrics as relative variable importances (RVIs).     

Asymptotics for Autocovariances and Integrated Periodograms for Linear Processes Observed at Lower Frequencies

One of the most frequently used class of processes in time series analysis is the one of linear processes. For many statistical quantities, among them sample autocovariances and sample autocorrelations, central limit theorems are available in the literature. We investigate classical linear processes under a nonstandard observation pattern; namely, we assume that we are only able to observe the linear process at a lower frequency. It is shown that such observation pattern destroys the linear structure of the observations and leads to substantially different asymptotic results for standard statistical quantities. Central limit theorems are given for sample autocovariances and sample autocorrelations as well as more general integrated periodograms and ratio statistics. Moreover, for specific autoregressive processes, the possibilities to estimate the parameters of the underlying autoregression from lower frequency observations are addressed. Finally, we suggest for autoregressions of order 2 a valid bootstrap procedure. A small simulation study demonstrates the performance of the bootstrap proposal for finite sample size.     

Understanding China’s official statistics

In response to the three influential doubts about government statistics, this article expounds the differences between relevant common economic statistical indicators and the national account indicators that reflect demand structure and national income distribution structure. The comparisons include the following aspects: the differences between household consumption expenditure from household survey and from expenditure-based GDP; the differences between total retail sales of consumer goods and final consumption expenditure from expenditure-based GDP; the differences between government expenditure from government fiscal statistics and government consumption expenditure from expenditure-based GDP; the differences between total investment in fixed assets from investment statistics and gross fixed capital formation from expenditure-based GDP; the differences between inventories and change in inventories from expenditure-based GDP; the differences between foreign trade balance from customs statistics and net exports of goods and services from expenditure-based GDP; and the differences between household disposable income from the household survey and from the Flow of Funds Table, etc. In addition, this article answers the questions proposed by the three doubts correspondingly.     

Assessing the role of components of life satisfaction

Factors affecting subjective well-being and their gross effect measurement have been widely studied. However, how people derive utility from these factors has not been fully explored. This article provides a way to decompose the gross effect of major determinants on life satisfaction into direct and indirect effects and make inference for the latter. Because the indirect effect is nonlinear in parameters associated with different models in an equation system, it creates a problem in estimating the standard error. Besides, the categorical nature in survey data further introduces bias to the covariance estimation even asymptotically. To address these issues without knowing the form of heteroskedasticity under the null hypothesis, we propose to extend the wild bootstrap procedure in this particular context. Its robustness against various data properties is validated via several simulation experiments. Using three recent waves of World Values Survey, we find that the relative importance of life control has significantly increased recently, and endowing citizens with the right to enjoy their freedoms and liberties is a more effective policy in raising life satisfaction than promoting national income.     

Economic importance and statistical significance: Guidelines for communicating empirical research

Abstract

A critical objective for many empirical studies is a thorough evaluation of both substantive importance and statistical significance. Feminist economists have critiqued neoclassical economics studies for an excessive focus on statistical machinery at the expense of substantive issues. Drawing from the ongoing debate about the rhetoric of economic inquiry and significance tests, this paper examines approaches for presenting empirical results effectively to ensure that the analysis is accurate, meaningful, and relevant for the conceptual and empirical context. To that end, it demonstrates several measurement issues that affect the interpretation of economic significance and are commonly overlooked in empirical studies. This paper provides guidelines for clearly communicating two distinct aspects of “significance” in empirical research, using prose, tables, and charts based on OLS, logit, and probit regression results. These guidelines are illustrated with samples of ineffective writing annotated to show weaknesses, followed by concrete examples and explanations of improved presentation.     

Estimation employing a priori information within mass appraisal and hedonic pricing models

Both statistical appraisal and hedonic pricing models decompose houses into a set of individual characteristics. Regression estimates yield the contribution of each characteristic to total value. Unfortunately, straightforward application of OLS may produce untenable results such as implausible coefficient magnitudes or incorrect signs. Often the suspected cause is multicollinearity. This article examines the effect on estimation efficiency of differing levels of multicollinearity, R², and a priori information in the form of sub-market cost data, by comparing inequality restricted least squares (IRLS) with OLS in a series of Monte Carlo experiments. The IRLS procedure investigated here hybridizes the statistical market approach implemented by OLS, and the more traditional cost approach. The experiments show dramatic gains in estimation efficiency from exploiting a priori information through IRLS.     

企业统计如何迎接新挑战

随着我国《统计法实施细则》的颁布,在这一新的形势下,企业统计应如何发挥其作用,值得我们每一位统计工作者深思,本文对此进行了探讨。