续集电影的片名策略及其市场效应研究

以续集电影为研究情境,探讨了电影制作经营方如何通过科学的电影续集片名策略,来提升观众的观影意愿和电影的市场表现.通过两个消费者实验和美国电影市场1960年～2017年的电影数据,研究发现,续集电影采用文字片名策略(vs.数字片名策略)会促使消费者有更高的观影意愿,想象可达性发挥中介作用.但是这一关系受到电影题材的调节,前瞻性题材的续集电影使用文字片名策略会产生更高的观影意愿,而回溯性题材的续集电影使用数字片名策略会产生更高的观影意愿.对影视产业如何采取不同的续集影视片名策略,从而打造影视知名品牌提供了战略启示;为更广泛的文化产业的品牌营销也具有战略借鉴意义.     

Marriage,Labor Supply,and Home Production

We develop a search model of marriage where men and women draw utility from private consumption and leisure, and from a non‐market good that is produced in the home using time resources. We condition individual decisions on wages, education, and an index of family attitudes. A match‐specific, stochastic bliss shock induces variation in matching given wages, education, and family values, and triggers renegotiation and divorce. Using BHPS (1991–2008) data, we take as given changes in wages, education, and family values by gender, and study their impact on marriage decisions and intrahousehold resource allocation. The model allows to evaluate how much of the observed gender differences in labor supply results from wages, education, and family attitudes. We find that family attitudes are a strong determinant of comparative advantages in home production of men and women, whereas education complementarities induce assortative mating through preferences.     

EXcess Idle Time

We introduce a novel economic indicator, named excess idle time (EXIT), measuring the extent of sluggishness in financial prices. Under a null and an alternative hypothesis grounded in no‐arbitrage (the null) and market microstructure (the alternative) theories of price determination, we derive a limit theory for EXIT leading to formal tests for staleness in the price adjustments. Empirical implementation of the theory indicates that financial prices are often more sluggish than implied by the (ubiquitous, in frictionless continuous‐time asset pricing) semimartingale assumption. EXIT is interpretable as an illiquidity proxy and is easily implementable, for each trading day, using transaction prices only. By using EXIT, we show how to estimate structurally market microstructure models with asymmetric information.     

A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding

Floods are a natural hazard evolving in space and time according to meteorological and river basin dynamics, so that a single flood event can affect different regions over the event duration. This physical mechanism introduces spatio‐temporal relationships between flood records and losses at different locations over a given time window that should be taken into account for an effective assessment of the collective flood risk. However, since extreme floods are rare events, the limited number of historical records usually prevents a reliable frequency analysis. To overcome this limit, we move from the analysis of extreme events to the modeling of continuous stream flow records preserving spatio‐temporal correlation structures of the entire process, and making a more efficient use of the information provided by continuous flow records. The approach is based on the dynamic copula framework, which allows for splitting the modeling of spatio‐temporal properties by coupling suitable time series models accounting for temporal dynamics, and multivariate distributions describing spatial dependence. The model is applied to 490 stream flow sequences recorded across 10 of the largest river basins in central and eastern Europe (Danube, Rhine, Elbe, Oder, Waser, Meuse, Rhone, Seine, Loire, and Garonne). Using available proxy data to quantify local flood exposure and vulnerability, we show that the temporal dependence exerts a key role in reproducing interannual persistence, and thus magnitude and frequency of annual proxy flood losses aggregated at a basin‐wide scale, while copulas allow the preservation of the spatial dependence of losses at weekly and annual time scales.     

Control‐based imputation for sensitivity analyses in informative censoring for recurrent event data

In clinical trials, missing data commonly arise through nonadherence to the randomized treatment or to study procedure. For trials in which recurrent event endpoints are of interests, conventional analyses using the proportional intensity model or the count model assume that the data are missing at random, which cannot be tested using the observed data alone. Thus, sensitivity analyses are recommended. We implement the control‐based multiple imputation as sensitivity analyses for the recurrent event data. We model the recurrent event using a piecewise exponential proportional intensity model with frailty and sample the parameters from the posterior distribution. We impute the number of events after dropped out and correct the variance estimation using a bootstrap procedure. We apply the method to an application of sitagliptin study.     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

现代性时间问题初探

通过对现代、现代性概念的词源考察,分析了蕴含在其中的时间意识.在对启蒙现代性、审美现代性的产生及类型的考察的基础上,分析了存在于两者之间与生俱来的悖论,指出产生这种悖论的深层原因,并分析了一些现代、后现代之间存在的时间概念.     

解放战争时期党在解放区的土地政策探析

解放战争时期中国共产党在解放区的土地政策,是我们党的一项重要政策.根据当时的背景变化,党在解放区的土地政策经历了一个历史的演变过程,在中国革命和建设中做出了巨大历史贡献.     

Nonparametric estimation of waiting time distributions in a Markov model based on current status data

We construct nonparametric estimators of state waiting time distribution functions in a Markov multistate model using current status data. This is a particularly difficult problem since neither the entry nor the exit times of a given state are directly observed. These estimators are obtained, using the Markov property, from estimators of counting processes of state entry and exit times, as well as, the size of “at risk” sets of state entry and transitions out of that state. Consistency of our estimators is established. Finite-sample behavior of our estimators is studied by simulation, in which we show that our estimators based on current status data compare well with those based on complete data. We also illustrate our method using a pubertal development data set obtained from the NHANES III [1997. NHANES III Reference Manuals and Reports (CD-ROM). Analytic and Reporting Guidelines: The Third National Health and Nutrition Examination Survey (1988–94). National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD] study.     

A comparison of nonparametric priors in hierarchical mixture modelling for AFT regression

We will pursue a Bayesian nonparametric approach in the hierarchical mixture modelling of lifetime data in two situations: density estimation, when the distribution is a mixture of parametric densities with a nonparametric mixing measure, and accelerated failure time (AFT) regression modelling, when the same type of mixture is used for the distribution of the error term. The Dirichlet process is a popular choice for the mixing measure, yielding a Dirichlet process mixture model for the error; as an alternative, we also allow the mixing measure to be equal to a normalized inverse-Gaussian prior, built from normalized inverse-Gaussian finite dimensional distributions, as recently proposed in the literature. Markov chain Monte Carlo techniques will be used to estimate the predictive distribution of the survival time, along with the posterior distribution of the regression parameters. A comparison between the two models will be carried out on the grounds of their predictive power and their ability to identify the number of components in a given mixture density.