Does Twitter chatter matter? Online reviews and box office revenues

ABSTRACT

With a rapid rise of text-based social media and online Word-of-Mouth (WOM) activity, millions of people express their thoughts and opinions on a variety of topics. Considering that nowadays WOM is a most influential source of information when guiding consumers’ choice and purchase decisions, in this paper we look at the relationship between Twitter messages (tweets) and cinema box office revenues. Using static and dynamic panel data regression approaches, we show that the frequency, sentiment and timing of tweets posted about a film are correlated to different extent with the movie’s box office revenues, with negative tweets being particularly damaging to the box office revenues. From a managerial perspective, this is important to know, such that film production companies and distributors can adjust their strategy accordingly.     

中国地区间经济发展不平衡——水平测度和成因探究

在测度中国省区间经济发展不平衡程度的基础上,揭示了不平衡的影响因素:1989年至2008年间,中国省区间经济发展不平衡的状况不断加剧,加权变异系数、基尼系数和泰尔指数(II)增长了30%左右,泰尔指数(I)的增幅更是高达67%;人均GDP、国内资本存量、贸易开放度和第三产业增加值等因素显著加剧了地区间不平衡,教育水平的提高则显著抑制了地区间不平衡的扩大;失业率和城市化水平也对地区间不平衡产生了一定的影响,而外商直接投资对不平衡的影响作用是不确定的。     

地方政府住宅用地出让价格跨区域联动模式研究

研究目的:刻画、解构地方政府住宅用地出让价格跨区域联动系统。研究方法:全局向量自回归(GVAR)模型与网络分析工具。研究结果:(1)地方政府住宅用地出让价格跨区域联动系统呈现出高聚类、短路径的"小世界网络"特性。(2)地方政府住宅用地出让价格跨区域联动网络分为3个板块:板块1为"领导人"角色,板块2为"经纪人"角色,板块3为"谄媚人"角色。(3)地方政府住宅用地出让价格跨区域联动表现出明显的空间异质性。研究结论:应该从跨区域联动视角,深化对地方政府住宅用地出让价格形成机制的认识,有效管控地方政府住宅用地出让价格的跨区域影响。     

Pricing a rural development program: uncertainty,indifference, and protest behaviors

This article presents an econometric approach to modeling uncertainty, unwillingness to pay, and protest behavior in contingent valuation studies. For that purpose, a mixture model with sample selection is developed for a multiple‐bounded uncertainty elicitation format. The proposed theoretical framework is applied to evaluate the social welfare impact of implementing a sustainable rural development program. Results show that a “naive” analytical approach that excludes protesters from the analysis would result in significantly higher willingness to pay estimates for those individuals who favor the implementation of the program and agree to reveal their true reservation prices.     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

Nonparametric fixed effects model for panel data with locally stationary regressors

We develop methods for inference in nonparametric time-varying fixed effects panel data models that allow for locally stationary regressors and for the time series length $T$ and cross-section size $N$ both being large. We first develop a pooled nonparametric profile least squares dummy variable approach to estimate the nonparametric function, and establish the optimal convergence rate and asymptotic normality of the resultant estimator. We then propose a test statistic to check whether the bivariate nonparametric function is time-varying or the time effect is separable, and derive the asymptotic distribution of the proposed test statistic. We present several simulated examples and two real data analyses to illustrate the finite sample performance of the proposed methods.     

Where to vacation? An agent-based approach to modelling tourist decision-making process

Agent-based models (ABMs) are becoming more relevant in social simulation due to the potential to model complex phenomena that emerge from individual interactions. In tourism research, complexity is a subject of growing interest and researchers start to analyse the tourism system as a complex phenomenon. However, there is little application of ABMs as a tool to explore and predict tourism patterns. The purpose of the paper is to develop an ABM that increases knowledge in tourism research by (i) considering the complexity of tourism phenomenon, (ii) providing tools to explore the complex relations between system components and (iii) giving insights on the functioning of the system and the tourist decision-making process. A theoretical ABM is developed to improve knowledge on tourist decision-making in the selection of a destination to vacation. Tourists’ behaviour, such as individual motivation, and social network influence in the vacation decision-making process are hereby discussed.     

Impact of financial/economic crisis on demand for hotel rooms in Hong Kong

The main objectives of this study are (1) to identify the factors that influence the demand for hotel rooms in Hong Kong and (2) to generate quarterly forecasts of that demand to assess the impact of the ongoing financial/economic crisis. The demand for four types of hotel room from the residents of nine major origin countries is considered, and forecasts are generated from the first quarter of 2009 to the fourth quarter of 2015. Econometric approaches are employed to calculate the demand elasticities and their corresponding confidence intervals, which are then used to generate interval demand predictions. The empirical results reveal that the most important factors in determining the demand for hotel rooms in Hong Kong are the economic conditions (measured by income level) in the origin markets, the price of the hotel rooms and the ‘word of mouth’ effect. Demand for High Tariff A and Medium Tariff hotel rooms is estimated to have experienced negative annual growth in 2009 due to the influence of the financial/economic crisis, whereas that for High Tariff B hotel rooms is thought to have grown in 2009 after having decreased in 2008. The demand for tourist guesthouse rooms is expected to be the least affected by the crisis. Overall demand is predicted to recover gradually from 2010 onwards.     

矿区地质条件对农村居民点整理模式选取的影响分析——以山东省肥城煤矿区为例

研究目的：通过分析不同农村居民点整理模式集中分布区域的地质条件,找出影响整理模式选取的各种地质环境。研究方法：综合分析法、归纳法。研究结论：地质条件是矿区选取农村居民点整理模式的根本依据。近年来,中国农村居民点整理范围不断扩大,但对复杂地质环境区域,尤其是地质环境复杂的矿区的农村居民点整理研究还比较少,应加大对特殊地质条件下农村居民点整理的研究。     

Serial Nonparticipation in Repeated Discrete Choice Models

We consider alternative econometric strategies for addressing serial nonparticipation, that is, repeated choice of the same alternative or same type of alternative across a series of choice occasions, in data typically analyzed within the repeated discrete choice framework. Single and double hurdle variants of the repeated discrete choice model are developed and applied to choice experiment and multisite seasonal recreation demand data. Our results suggest that hurdle models can generate significant improvements in statistical fit and qualitatively different policy implications, particularly in choice experiment applications where the proper treatment of serial nonparticipation is relatively more ambiguous.