The 7th Asia-Pacific CHRIE Conference

Despite the increase in use of user-generated electronic content as an information source by tourists, its influence in destination image formation is not yet fully understood. This research aimed to explore the communicated destination image held by tourists to Zanzibar Island (Tanzania) by utilizing communications in Lonely Planet. Content analysis of 214 posts using TextSTAT yielded 13 destination attributes. Comparatively, functional attributes were dominant in potential tourists whereas post-travel image perception was dominated by psychological attributes. Those who have visited tended to have a positive image of the island compared with those who are planning to visit the island. The results necessitate the differential use of the functional- and psychological-based information in communicating with tourists at different information-search stages. Studies to capture communications in another language are recommended as well as the employment of methodologies that might reveal hidden images held by tourists.     

Structural effects of cognitive and affective reponses to web advertisements,website and brand attitudes,and purchase intentions: The case of casual-dining restaurants

This study investigates the structural relationships among responses to website advertisements, website attitudes, brand attitudes, and purchase intentions in the case of web advertisements for casual-dining restaurants. Responses toward advertising (Rad) factors were categorized as cognitive responses and affective responses. The SEM model in LISREL was used to examine the interrelationships among the proposed hypothesized constructs. Several empirical results were obtained. First, Rad had a positive effect on website attitudes. Second, website attitudes had a positive effect on brand attitudes. Third, brand attitudes had a positive effect on purchase intentions. Finally, some discussion and implications of the study are provided.     

A logistic regression point of view toward loss given default distribution estimation

We propose a new procedure to estimate the loss given default (LGD) distribution. Owing to the complicated shape of the LGD distribution, using a smooth density function as a driver to estimate it may result in a decline in model fit. To overcome this problem, we first apply the logistic regression to estimate the LGD cumulative distribution function. Then, we convert the result into the LGD distribution estimate. To implement the newly proposed estimation procedure, we collect a sample of 5269 defaulted debts from Moody’s Default and Recovery Database. A performance study is performed using 2000 pairs of in-sample and out-of-sample data-sets with different sizes that are randomly selected from the entire sample. Our results show that the newly proposed procedure has better and more robust performance than its alternatives, in the sense of yielding more accurate in-sample and out-of-sample LGD distribution estimates. Thus, it is useful for studying the LGD distribution.     

Predicting issuer credit ratings using a semiparametric method

This paper proposes a prediction method based on an ordered semiparametric probit model for credit risk forecast. The proposed prediction model is constructed by replacing the linear regression function in the usual ordered probit model with a semiparametric function, thus it allows for more flexible choice of regression function. The unknown parameters in the proposed prediction model are estimated by maximizing a local (weighted) log-likelihood function, and the resulting estimators are analyzed through their asymptotic biases and variances. A real data example for predicting issuer credit ratings is used to illustrate the proposed prediction method. The empirical result confirms that the new model compares favorably with the usual ordered probit model.     

Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality

Journal of Financial Services Research - We propose a new procedure to predict the loss given default (LGD) distribution. Studies find empirical evidence that LGD values have a high concentration...     

Competitive Effects of Disclosure in a Strategic Entry Model

We investigate the welfare consequences of incumbent firms' mutual disclosure of cost information when there is a threat of entry from a firm not required to disclose its private cost information. New effects of disclosure are observed relative to no-entry models, with the result that incumbents' expected output is a decreasing function of the disclosure level. However, further analysis shows that increased disclosure usually increases incumbent expected profits and decreases expected consumer surplus, despite the additional entry effect of disclosure. Such analytical derivations provide objective input to the FASB as they attempt to predict the competitive effects of changing mandated disclosure requirements.     

Heterogeneity and netting efficiency under central clearing: A stochastic network analysis

This paper examines the effect of heterogeneity in clearing members’ exposure management practices under central clearing. Our network model specifies the dynamics of prenetted interbank exposures to shape interdependent exposure distributions beyond normality. Employing over-the-counter derivatives market data from the U.S. Office of the Comptroller of the Currency, our simulation results indicate that heterogeneity in bank-to-bank exposure dynamics is systemically desirable, while the entire system benefits more from the central clearing in more homogeneous environments. Policymakers should incentivize individual clearing members to enhance resiliency and stability in counterparty exposure management to maximize netting efficiency under central clearing.