Identifying cycling-inducing neighborhoods: A latent class approach

Understanding how spatial attributes of cities and neighborhoods induce cycling is relevant for urban planning and policy making. In this work, ordered logit and latent class models are specified and estimated to analyze how the built environment affects bicycle-commuting frequency. Data come from a survey to 1,487 people in the city of Santiago, Chile, including sociodemographic information, travel behavior patterns and place of residence and work. Using geographic information systems tools, the built environment was characterized with variables calculated for a 500-m-radius buffer around the residential and work locations of each individual. Two models are estimated, first an ordered logit model confirms that built environment variables effect on cycling is similar to what has been reported in the literature, with some new findings such as an increase in cycling when public transport accessibility is low and the role of built environment attributes at the destination. Second, a latent class ordered logit is used to identify two classes of neighborhood in term of their cycling patterns, as a function of their density, presence of cycling infrastructure and distance to the main activity center of the city. This result allows to map the class membership probabilities, potentially helping to identify neighborhoods that encourage cycling and providing relevant information for policy making and infrastructure decisions.     

Public and private healthcare services: What drives the choice?

This paper has explored patients' propensity to consume private healthcare services. We based our analysis on the typical tangible and intangible (for instance, responsiveness, reliability, assurance and staff empathy) domains of the SERVQUAL and SERVPERF methods. These variables may influence patients' decision-making when they choose between the public and private sectors. We combined factor analysis (to obtain a set of latent factors related to perceived quality) and a partial proportional ordered logit model to estimate the probability that a patient would access private healthcare services. To test the main hypotheses, we used data from a stratified sample in Sardinia, a peripheral region of Italy. Findings revealed that private and public healthcare are substitutes, especially for primary/specialised services. Patients who used public healthcare frequently and had a low income were unlikely to change to private healthcare or to recommend private services. ‘Responsiveness’ and perceptions on ‘tangibles’ were key in determining the probability that a patient would choose and recommend private services. This paper offers a multifaceted framework that can be used in future research to generalise these findings, especially in insular regions that are constrained by mobility.     

郊区农村劳动力乡城迁移意愿研究——以广州市为例

依据农户抽样调查数据,运用逻辑回归模型,对特大城市郊区农村劳动力迁移决策的主要影响因素进行分析。     

Cash Management, Payment Patterns and the Demand for Money

We analyse cash management and payments behaviour using 1990–1994 panel data for Dutch households. The results largely confirm the transactions demand for money theory, including an income elasticity of substantially less than one, and they are consistent with the hypothesis of technology resulting in households' economizing on currency balances. The results indicate up to 40 per cent lower transactions balances in the future, which is affirmed by direct questioning on future expectations. The effect on total money outstanding is considerably lower, due to significant amounts of missing money in hoards, which are insensitive to new developments in the payments system.     

A GPS data-based analysis of built environment influences on bicyclist route preferences

This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named “CycleTracks.” The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.     

Free-Agency and the Competitiveness of Major League Baseball

I investigate whether the removal of the reserve clause in professional baseball affected the competitive nature of the industry in the context of whether the distribution of team wins has been affected by free-agency. Unlike previous studies which use the standard deviation of winning percentage, I use a more sensitive measure of parity. I calculate the deviations of the Herfindahl-Hirschman Index of team wins from the competitive ideal during 1920 to 1996 and relate them to player-talent distribution and structural changes in the industry. I isolate the structural effect of free-agency and find that it has adversely affected the parity of the American League but that it has had no statistical influence on the parity of the National League.     

基于Logit模型的视频流媒体用户付费意愿及其影响因素研究——以爱奇艺为例

爱奇艺作为国内头部视频流媒体之一,面临用户付费意愿薄弱的困境。基于整合型技术接受模型(UTAUT)和感知价值理论(CPV)的相关变量提出假设,构建研究模型。通过Logit模型展开实证研究,结果显示感知有用性、感知成本、社会影响、个人付费意识对爱奇艺用户的付费意愿有显著影响。对此,提出深耕优质内容IP、丰富价格体系、打造口碑营销、聚焦年轻人的情绪价值四点建议,为爱奇艺探索新的战略提供有针对性的对策建议。     

Consumer willingness to pay for in-flight service and comfort levels: A choice experiment

In the competitive aviation market as a result of the emergence of low cost carriers, charter airlines have had to reconsider their approach to service provision. Specifically, the reduction in service and comfort levels offered by the low cost airlines provides charter carriers with an opportunity to differentiate their product based on the quality of the offering. To consider this strategic option we employ an on-line choice experiment to examine consumer choices with respect to the bundle of services on offer when deciding to purchase a flight. With these data we use the Bayesian methods to estimate a mixed logit specification. Our results reveal that in principle passengers are willing to pay a relatively large amount for enhanced service quality.     

Liberalization,Regulatory Delays and Vulnerability to Systemic Banking Crisis

This work aims at contributing to the improvement of the early warning systems of banking crises using a new approach accounting for model uncertainty. We show that a multinomial logit model based on Bayesian model averaging (BMA) is a good strategy to predict banking crisis. To do this, we argue that differences in vulnerability to banking crisis can be largely explained by an asymmetry between financial market evolution and regulation update on a sample of 49 developed and developing countries between 1980 and 2010. When markets are liberalized, competition pushes bankers to take more risks and take advantage of regulatory delays thus increasing crises probabilities. Our empirical evidence supports that crisis probability is higher in country liberalizing their banking system when regulation is not updated. We developed an early warning system for systemic banking crises based on the multinomial logit model. Its main difference to existing prediction models and its contribution to the literature is that it is intended to identify and resolve what is called by Bussiere and Fratzscher [(2006). Towards a new early warning system of financial crises. Journal of International Money and Finance, 25(6), 953–973] as post-crisis bias in binomial models and to develop a new methodology of leading indicators selection based on BMA. Overall, our model predicts all banking crises during our sample period.