Intensity of preferences for bivariate risk apportionment

Bivariate risk apportionment is the preference for dispersing risks associated with two aspects of individuals’ well-being into different states of the world. In this paper, we propose an intensity measure of this preference by extending to the bivariate case the concept of marginal rate of substitution between risks of different orders introduced in the univariate case by Liu and Meyer (2013). We show that the intensity measure of the preference for bivariate risk apportionment is characterized by bivariate risk attitudes in the sense of Ross. The usefulness of our measures to understand economic choices is illustrated by the analysis of two specific decisions: savings under environmental risk and medical treatment in the presence of diagnostic risks.     

The impact of national macro-environment exogenous variables on airport efficiency

Our paper tests the extent to which airport efficiency is affected by national macro-environmental factors. The literature on airport performance measurement is extensive but has tended to focus mainly on estimating the effects on efficiency from what are mostly endogenous variables. We undertake a two-stage analysis of 59 international airports observations in the Europe and Asia-Pacific regions. The first stage involves the use of Data Envelopment Analysis (DEA) to measure the efficiency of these airports. This is followed by a second stage, where we use a Truncated Regression model that incorporates the Simar and Wilson bootstrapping technique to test the extent to which a set of macro-environmental factors affect airport efficiency. Results reveal that a state's air transport sector output, institutional quality and robustness, the macro-economic environment, safety and security, and human development, all have a significant influence on the performance of airports. The result of this study fills the gap in the literature related to the non-discretionary variables affecting the performance of airports. It also suggests that policymakers and airport managers consider the identified factors when benchmarking airports.     

Estimation of willingness-to-pay for premium economy class by type of service

This study aims to estimate the willingness-to-pay (WTP) to upgrade from economy to premium economy class by six types of services and to identify the socioeconomic and travel characteristics of international travelers affecting the WTP using the Tobit model assumed to be censored at zero. The results confirm that the travelers' WTP for the premium economy class in the long-haul travel is higher than those in the medium and the short-haul travels. However, the ratio of additional WTP to the economy class fare in the long-haul route is slightly lower than that in the medium-haul route. The results also present that international travelers have the highest WTP for increased seat width in the premium economy class service attribute, followed by increased seat pitch and upgraded in-flight meal service. Finally, the results indicate that the WTP to upgrade to premium economy class are proportional to the age or the income level of travelers. Furthermore, international travel frequency and the experience of premium economy class have a positive impact as well. This research can be a useful resource for analyzing international travelers’ WTP concerning the type of service and this information will be useful to policy makers in their efforts to determine their fare policies and the target audience for marketing premium economy class.     

Impact of off-farm labor supply on food expenditures of the farm household

Farm households diversify their income sources by working off the farm. This is a risk management strategy that is used by farm households in both developed and developing countries. Income diversification via off-farm work is associated with higher incomes and food consumption. However, little is known about the association between off-farm work and farm household food expenditures. In an effort to bridge this gap, this study attempts to assess the impact of off-farm work decisions by the operator and/or the spouse on the food expenditures of the farm household. Using a nationwide farm household survey in the United States and new econometric method, we find that the decisions of the operator and/or the spouse to work off the farm are significantly interrelated (29%). However, these two decisions affect food expenditures in different ways. The operator’s off-farm work decision is positively related to food expenditures, while the spouse’s decision is negatively associated with expenditures on food by the farm household.     

Entry Mode Choice and Performance: Evidence from Taiwanese FDI in China

This paper examines entry mode choices between wholly owned subsidiaries (WOSs) and joint ventures (JVs) and the impact on performance for Taiwanese foreign direct investment in China. Taiwan and China share common cultural traits, so Taiwanese investors inherently prefer WOSs because these investors are acquainted with local conditions in China. This paper shows that even if WOSs are a natural choice, transaction cost theory is applicable in explaining the adoption of JVs by Taiwanese firms when investing in China. Firms that choose WOSs generally have higher sales growth and superior profitability. However, the smaller the subsidiary and the less experienced the firm, the more likely that JVs will have better performance.     

A posteriori ratemaking using bivariate Poisson models

Recently, different bivariate Poisson regression models have been used in the actuarial literature to make an a priori ratemaking taking into account the dependence between two types of claims. A natural extension for these models is to consider a posteriori ratemaking (i.e. experience rating models) that also relaxes the independence assumption. We introduce here two bivariate experience rating models that integrate the a priori ratemaking based on the bivariate Poisson regression models, extending the existing literature for the univariate case to the bivariate case. These bivariate experience rating models are applied to an automobile insurance claims data-set to analyse the consequences for posterior premiums when the independence assumption is relaxed. The main finding is that the a posteriori risk factors obtained with the bivariate experience rating models are significantly lower than those factors derived under the independence assumption.     

Nonparametric estimators of the bivariate survival function under random censoring

A large number of proposals for estimating the bivariate survival function under random censoring have been made. In this paper we discuss the most prominent estimators, where prominent is meant in the sense that they are best for practical use; Dabrowska's estimator, the Prentice–Cai estimator, Pruitt's modified EM-estimator, and the reduced data NPMLE of van der Laan. We show how these estimators are computed and present their intuitive background. The asymptotic results are summarized. Furthermore, we give a summary of the practical performance of the estimators under different levels of dependence and censoring based on extensive simulation results. This leads also to a practical advise.     

Goodness-of-fit tests for Poisson count time series based on the Stein–Chen identity

To test the null hypothesis of a Poisson marginal distribution, test statistics based on the Stein–Chen identity are proposed. For a wide class of Poisson count time series, the asymptotic distribution of different types of Stein–Chen statistics is derived, also if multiple statistics are jointly applied. The performance of the tests is analyzed with simulations, as well as the question which Stein–Chen functions should be used for which alternative. Illustrative data examples are presented, and possible extensions of the novel Stein–Chen approach are discussed as well.     

PORTFOLIO SELECTION PROBLEMS VIA THE BIVARIATE CHARACTERIZATION OF STOCHASTIC DOMINANCE RELATIONS1

Stochastic dominance (SD) is a very useful tool in various areas of economics and finance. the purpose of this paper is to provide the results of SD relations developed in other areas such as applied probability which, we believe, are useful for many portfolio selection problems. In particular, the bivariate characterization of SD relations given by Shanthikumar and Yao (1991) is a powerful tool for the demand and the shift effect problems in optimal portfolios. the method enables one to extend many results that hold for the case where the underlying lying assets are statistically independent to the dependent case directly.