Multicategory Purchase Incidence Models for Partitions of Product Categories

We analyze multicategory purchases of households by means of heterogeneous multivariate probit models that relate to partitions formed from a total of 25 product categories. We investigate both prior and post hoc partitions. We search model structures by a stochastic algorithm and estimate models by Markov chain Monte Carlo simulation. The best model in terms of cross‐validated log‐likelihood refers to a post hoc partition with two groups; the second‐best model considers all categories as one group. Among prior partitions with at least two category groups a five‐group model performs best. Effects on average basket value differ for the model with five prior category groups from those for the best‐performing model in 40% and 24% of the investigated categories for features and displays, respectively. In addition, the model with five prior category groups also underestimates total sales revenue across all categories by about 28%. Copyright © 2016 John Wiley & Sons, Ltd.     

出行链与出行方式相互影响模式

通过居民出行调查数据分析,建立递归联立离散选择模型,从出行链至出行方式和出行方式至出行链2个方向,重点分析了工作出行链和出行方式间的相互作用.研究表明,模型通过直接量化出行链和出行方式之间的相互作用,加强了行为机制对预测分析的指导.分析结果表明,出行链至出行方式的影响模式在工作出行决策过程中占主导地位,出行者首先根据个人和家庭的需要将一日的活动和出行组织成以出行链为单位的片段,然后在出行链各种性质的约束下考虑选择何种交通方式.研究结果对出行需求预测和管理有指导意义.     

Detecting and Predicting Economic Accelerations,Recessions, and Normal Growth Periods in Real‐Time

The dichotomous characterization of the business cycle in recessions and expansions has been central in the literature over the last 50 years. However, there are various reasons to question the adequacy of this dichotomous, recession/expansion approach for our understanding of the business cycle dynamics, as well as for the prediction of future business cycle developments. In this context, the contribution of this paper to the literature is twofold. First, since a positive rate of growth at the level of economic activity can be considered as the normal scenario in modern economies due to both population and technological growth, it proposes a new non‐parametric algorithm for the detection and dating of economic acceleration periods, trend or normal growth periods, and economic recessions. Second, it uses an ordered probit framework for the estimation and forecasting of these three business cycle phases, applying an automatized model selection approach using monthly macroeconomic and financial data on the German economy. The empirical results show that this approach has superior out‐of‐sample properties under real‐time conditions compared to alternative probit models specified individually for the prediction of recessions and/or economic accelerations. Copyright © 2016 John Wiley & Sons, Ltd.     

中国证券市场成交指令积极性及成交持续期的影响因素研究

对成交指令按成交价和成交量进行分类作为指令提交积极性的指示变量,本文依据上海证券市场的分笔高频交易数据,采用有序probit模型研究市场分笔行情如何影响投资者提交指令的积极性,采取LOG-ACD模型研究分笔行情如何影响成交持续期,并分析分笔行情中影响二者的关键信息因素.实证研究表明,短期报价波动增加、价差减小、与成交发起方相同方向的最优报价深度增加、与成交发起方相反方向的最优报价深度减小,都会降低成交指令属于积极性低类型的概率,提高成交指令属于积极性高类型的概率,即指令提交整体积极性提高,反之则相反;最优报价信息集合为影响指令提交积极性的关键信息因素.短期报价波动增加、价差减小、前三个报价买卖深度的增加均使成交持续期变短,反之则相反;同时,最优报价信息集合和最优报价外信息集合都不是影响成交持续期的关键信息因素.     

Forecasting US Recessions with a Large Set of Predictors

In this paper, I use a large set of macroeconomic and financial predictors to forecast US recession periods. I adopt Bayesian methodology with shrinkage in the parameters of the probit model for the binary time series tracking the state of the economy. The in‐sample and out‐of‐sample results show that utilizing a large cross‐section of indicators yields superior US recession forecasts in comparison to a number of parsimonious benchmark models. Moreover, the data‐rich probit model gives similar accuracy to the factor‐based model for the 1‐month‐ahead forecasts, while it provides superior performance for 1‐year‐ahead predictions. Finally, in a pseudo‐real‐time application for the Great Recession, I find that the large probit model with shrinkage is able to pick up the recession signals in a timely fashion and does well in comparison to the more parsimonious specification and to nonparametric alternatives. Copyright © 2016 John Wiley & Sons, Ltd.     

21世纪生物统计学教材建设初探

概括了生物统计学现行教材中存在的四个主要问题,逐个提出了相应的解决办法,其中包括首次提出的“概率尺”概念。21世纪的教材建设重点应在增加概率论内容和衔接现代生物统计技术的基础上突出新编教材的通用性。     

大学教育与国家人力资本积累——基于probit模型的问卷调查研究

在第一手数据的基础上,本研究运用probit模型探索了大学教育对于文化资本、经济与教育资本、社会资本、认知资本和抱负资本等五类人力资本的积累效应。本文在大学教学、大学管理、科学研究、大学氛围、努力程度、父母影响、就业压力等七个维度识别出了16个显著影响积累效应的微观变量,并计算了这些变量对于国家人力资本积累的边际效应。     

广州大学城外环路交叉口的黄灯困境问题研究

信号交叉口是关乎交通安全的重要区域,而黄灯困境区的存在大大增加了交叉口冲突的可能。目标是通过对广州大学城外环路交叉口两类困境情况的分析提出相应的改善措施。研究基于无人机技术进行实地数据采集,利用第一类黄灯困境模型完成对驾驶员驾驶风格的评定;并据此对似然函数稍作修正,实现probit驾驶行为模型的求解和第二类困境区的计算。分析结果表明,与第二类困境区相比,第一类困境区总长度较小、分布更离散。最后,针对其黄灯困境问题提出改善措施,以减少现存的交通安全隐患。     

Onsetof Emerging Market Crises with Probit Model

1　IntroductionSince 1 990 ,there have been several dramatic international financial crises involvingemerging economies,including Mexico,Turkey and Venezuela in1 994 ,Argentina in early1 995,and Indonesia,Korea,Malaysia,the Philippines and Thailand in 1 997.Each ofthese incidents displays elements of self-fulfilling crises,in which capital withdraws bycreditors cascade into a financial panic and resultin an unnecessary deep contraction.Mostanalysts have tried to explain these crises,and an…     

Using a heterogeneous multinomial probit model with a neural net extension to model brand choice

The multinomial probit model introduced here combines heterogeneity across households with flexibility of the (deterministic) utility function. To achieve flexibility deterministic utility is approximated by a neural net of the multilayer perceptron type. A Markov Chain Monte Carlo method serves to estimate heterogeneous multinomial probit models which fulfill economic restrictions on signs of (marginal) effects of predictors (e.g., negative for price). For empirical choice data the heterogeneous multinomial probit model extended by a multilayer perceptron clearly outperforms all the other models studied. Moreover, replacing homogeneous by heterogeneous reference price mechanisms and thus allowing price expectations to be formed differently across households also leads to better model performance. Mean utility differences and mean elasticities w.r.t. price and price deviation from reference price demonstrate that models with linear utility and nonlinear utility approximated by a multilayer perceptron lead to very different implications for managerial decision making. Copyright © 2007 John Wiley & Sons, Ltd.