Spurious regressions with stationary series

A spurious regression occurs when a pair of independent series, but with strong temporal properties, are found apparently to be related according to standard inference in an OLS regression. Although this is well known to occur with pairs of independent unit root processes, this paper finds evidence that similar results are found with positively autocorrelated autoregressive series or long moving averages. This occurs regardless of the sample size and for various distributions of the error terms.     

Developing country fisheries and technical efficiency: the Java Sea purse seine fishery

The analysis of technical efficiency in developing country agriculture is well established but has been overlooked for developing country commercial marine fisheries. Policies raising technical efficiency in agriculture are viewed as uniformly positive but are a mixed blessing in fisheries due to the open-access property right and common-pool resource. This study explores this contradiction and policies aimed to promote sustainable development and management of renewable common pool resources through a case study of the Java Sea purse seine fishery. Season of the year rather than fisher or vessel characteristics primarily determines technical efficiency. The results are contrasted with developing country agriculture and conclusions drawn for fisheries development strategies.     

Combining Revealed Preference Data with Stated Preference Data: A Latent Class Approach

A substantial literature exists combining data from revealed preference (RP) and stated preference (SP) sources, aimed either at testing for the convergent validity of the two approaches used in nonmarket valuation or as a means of drawing on their relative strengths to improve the ultimate estimates of value. In doing so, it is assumed that convergence of the two elicitation approaches is an “all or nothing” proposition; i.e., the RP and SP data are either consistent with each other or they are not. The purpose of this paper is to propose an alternative framework that allows for possible divergence among individuals in terms the consistency between their RP and SP responses. In particular, we suggest the use of a latent class approach to segment the population into two groups. The first group has RP and SP responses that are internally consistent, while the remaining group exhibits some form of inconsistent preferences. An EM algorithm is employed in an empirical application that draws on the Alberta and Saskatchewan moose hunting data sets used in earlier combined RP and SP exercises. The empirical results suggest that somewhere between one-third and one-half the sample exhibits consistent preferences. We also examine differences in welfare estimates drawn from the two classes.     

Social exchange approach,job satisfaction,and turnover intention in the airline industry

Service Business - This paper investigates the effects of social exchange relationships on job satisfaction and turnover intention in the airline industry. To this end, two constructs of social...     

The impact of tour quality and tourist satisfaction on tourist loyalty: The case of Chinese tourists in Korea

This study examines the causal relationship between tourist expectations, tourist motivations, tour quality, tourist satisfaction, tourist complaints and tourist loyalty of Chinese tourists in the Republic of Korea using path analysis. It was found that tourist expectations have a negative effect on the perceived experiential quality of the tour, yet tourist motivation has a positive effect on the perceived tour quality. In turn, the perceived tour quality has a positive effect on tourist satisfaction. Similarly there is an inverse relationship between satisfaction and tourist complaints, and a positive relationship exists between satisfaction and loyalty. Equally, the higher is the number of complaints, the lower are the loyalty levels. These results will provide potential guidelines for inbound tour agents who plan to attract Chinese tourists to Korea and enable them to formulate appropriate strategies. This study also seeks to contribute to conceptual and policy formation by understanding the determinants of tourist satisfaction and loyalty.     

Identifying the structure of knowledge networks in the US mobile ecosystems: patent citation analysis

With the emergence of smartphones, the paradigm of the mobile ecosystem has changed rapidly. In particular, global mobile firms focus on technological competition when jostling for market position in recognition of the strategic need to secure a strong mobile platform. In this paper, we analyse the network structure of technological knowledge flows in mobile ecosystems using US patent citation information. We find that two subsectors, platform providers and application and software providers, are at the centre of knowledge exchange activity and play a brokerage role as the key knowledge mediator. Then, we categorise mobile firms into five different groups based on the patterns of their network centrality: knowledge keystone players, knowledge-distributing mediators, knowledge-absorbing mediators, catch-up players, and pure knowledge receivers. The categorisation of firms demonstrates that knowledge flows in the mobile industry converge towards a few leading firms, and such patterns are shaping the mobile ecosystem with respect to technological knowledge. The firms categorised as catch-up players have played a brokerage role within their group, while the firms categorised as knowledge keystone players play a brokerage role across different groups.     

Labor Market Information Acquisition and Downsizing

We study the optimal mechanism for downsizing the public sector which takes into account different informational constraints (complete versus asymmetric information on each worker’s efficiency) and political constraints (mandatory versus voluntary downsizing). Under complete information, the optimal structure of downsizing (who is laid‐off and who is not) does not depend on the political constraint and is determined by the (marginal) cost of retaining a worker in the public sector. Since this cost includes his opportunity cost in the private sector, information acquisition on opportunity costs affects the structure of downsizing. Under asymmetric information, the political constraints determine which workers obtain information rents and therefore affect the structure of downsizing. An increase in the precision of the information on workers’ opportunity costs may increase or decrease social welfare depending on its impacts on the information rents.     

The Effects of Reversible Investment on Capital Structure and Credit Risks

We propose a structural model with an optimal switching of diffusion regimes that integrates a wide range of investment reversibility. The default boundary and switching thresholds are endogenously determined, and they enable us to comprehend the interrelated problems of the investment decision, capital structure, and credit risks. We examine not only the under/overinvestment but also the under/overdisinvestment. The leverage ratio decreases when the firm has an option to invest in a reversible project, which can alleviate the capital structure puzzle. Furthermore, the model significantly reduces the wide dispersion of yield spreads depending on the credit grade of bonds.     

Re-evaluation of global innovation index based on a structural equation model

The Global Innovation Index (GII) was proposed to observe the innovation capability and efficiency levels of individual countries using input and output factors. However, it does not consider potential structural relationships among factors affecting the innovation performance of a country. In this study, we proposed a structural equation model (SEM) based on the hypothesised national innovation structure among seven factors representing inputs (institution, human capital and research, infrastructure, market sophistication, and business sophistication) and outputs (knowledge and technology outputs, and creative outputs). Using GII data from 2013, we discovered that business sophistication and infrastructure have the strongest direct and indirect effects on creative output, respectively. In addition, a new ranking is obtained based on the fitted SEM. We provide feedback information to improve innovation capabilities.     

Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals

We propose a new way of selecting among model forms in automated exponential smoothing routines, consequently enhancing their predictive power. The procedure, here addressed as treating, operates by selectively subsetting the ensemble of competing models based on information from their prediction intervals. By the same token, we set forth a pruning strategy to improve the accuracy of both point forecasts and prediction intervals in forecast combination methods. The proposed approaches are respectively applied to automated exponential smoothing routines and Bagging algorithms, to demonstrate their potential. An empirical experiment is conducted on a wide range of series from the M-Competitions. The results attest that the proposed approaches are simple, without requiring much additional computational cost, but capable of substantially improving forecasting accuracy for both point forecasts and prediction intervals, outperforming important benchmarks and recently developed forecast combination methods.