Small system dynamics model for alleviating the general practitioners rural care gap in Ontario,Canada

The disproportionate concentration of healthcare professionals in urban areas is a concern in many countries, including Canada. A need to address this rural care gap has driven a large number of government led initiatives worldwide over the years. This paper presents a model that can be used as a tool to examine the efficacy of such policies on the workforce distribution in the long term. A small system dynamics model is employed to simulate the current and future distribution of general physicians at a jurisdictional level. The model represents the transition of general practitioners to provide insight into the dynamics of care provision over time. The movement, and competition, between rural and urban areas is modeled to enable detailed exploration of the ability for proposed measures to alleviate the care gap in the future. Among the tested policies are such commonly used initiatives as financial incentives to rural professionals, promotion of medical education in rural areas, expansion of rural education programs and the engagement of international medical graduates etc. We demonstrate how the model can be used as a tool to determine an efficient and well-chosen combination of policies which can help alleviate the rural care gap in the future, given that some policies are more effective than others alone but also combined with other initiatives. The presented small system dynamics model is tested on Canada's reality, but its simple nature lends itself to easy application to other countries that experience a similar problem.     

Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies

This study examines the dependence and contagion risk between Bitcoin (BTC), Litecoin (LTC) and Ripple (XRP) using non-parametric mixture copulas (developed by Zimmer, 2012) and recently proposed methods of full-range tail dependence copulas (advanced by Hua, 2017, Su and Hua, 2017), for the period from 04-08-2013 to 17-06-2018. The Chi-plots and Kendall plots results show heavy tail dependence between each pairs of the cryptocurrencies. Evidence from the mixture copula indicates that for the BTC-LTC pair the upper-tail dependence is both stronger and more prevalent, while for the other pairs of cryptocurrencies the lower-tail dependence is very strong and more prevalent. However, the results of the full-range tail dependence copulas reveal a strong and prevalent upper and lower-tail dependence of each pairs of cryptocurrencies. These results provide evidence of significant risk contagion among price returns of major cryptocurrencies, both in bull and bear markets.     

The effect of controversial global sourcing practices on the ethical judgments and intentions of U.S. consumers

Global sourcing has led to lower cost and more effective supply chains for many companies. However, when the cost-driven practices of many suppliers in these chains come to light there is often considerable debate over the ethics of these practices. This research uses the well-known Hunt–Vitell framework as the theoretical foundation for a structural equation model of the deontological and teleological evaluations used by consumers when making ethical judgments of a firm's controversial cost-driven global sourcing practices. Data from a large-scale U.S. consumer survey show the importance of deontological and teleological evaluations in forming consumers’ ethical judgments of global sourcing practices, and establish a strong relationship between ethical judgment and the intention of consumers to alter consumption of a firm's products. Extensions to the framework and demographic analyses for age, gender, and income provide insights as to how perceptions of these practices affect consumer evaluations of a company involved in global sourcing and how consumers actualize their resultant intentions.     

Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates

We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton copula is estimated via Canonical Maximum-Likelihood. The superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine-dimensional financial portfolio. A comparison of the out-of-sample forecasting accuracy of both models confirms that our model yields economically significantly better Value-at-Risk forecasts than the competing parametric calibration strategy.     

Model Comparison for Temperature-Based Weather Derivatives in Mainland China

Abstract:

In this paper, we provide a comparison of two models of temperature-based weather derivatives. The Alaton et al. model (2002) and the continuous-time autoregressive (CAR) model of Benth et al. (2007) are applied to temperature data from twelve cities in China. The objective is to determine which is the better model for temperature derivative modeling in Chinese cities. We found the CAR model to be more accurate in terms of normality of residuals and smaller relative errors. However, the shortcomings of both the Alaton et al. model and the CAR model are revealed in this study as well.     

A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region

Bogotá and the 17 neighboring municipalities make up one of the biggest metropolitan areas in Latin America. However, despite strong functional interactions within the area, there is no official government body at this level in charge of coordinating authorities and providing solutions to the wide variety of issues arising in the regional urban land system. Aiming at providing an insight on future land-use developments linked to new transport infrastructures and at offering a tool to support territorial decision-making, this paper presents a cellular automata-based (CA) model based in Metronamica® software, that allows testing different scenarios based on potential land-use policies, environmental suitability and transport alternatives.There has not been, so far, an urban planning tool that accounts for the complexities of this region. CA-based land-use simulations constitute a useful approach to understanding the impacts of urban planning policies and regulations. This tool can help to improve inter-territorial and inter-institutional coordination, which through planning and management policies seek a spatially integrated development, with a long-term perspective.The CA-based model proposed was calibrated to reproduce land-use changes between 2007 and 2016 using different methods and indicators. The model was used to simulate and analyze eight scenarios with different policy directions of transport infrastructure in the future of the region. The results of the simulations reflect the dynamics of territorial occupation. The calibration indices in the experiment indicate a high degree of suitability for the CA Bogotá model, proving its effectiveness and potential as a useful tool for decision-making. The results show that occupation scenarios with restricted developable zones within the city, tend to have the greater dispersion rate in the study area, compared to scenarios where land development plans are promoted in Bogotá, which representing a more compact development.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

Partial least squares structural equation modeling in HRM research

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields.     

Stock market reactions to domestic sentiment: Panel CS-ARDL evidence

This study sets out to explore the effects of business and consumer sentiment on stock market performance, within the separate contexts of advanced and emerging markets. The empirical analysis is carried out using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) modeling approach, which considers time dynamics, cross-sectional heterogeneity, and cross-sectional dependence. The findings for developed markets suggest that business sentiment has positive leading effects on stock returns, across short- and long-term time horizons, while for emerging markets, the price impact of business sentiment turns out to be short-lived. On the other hand, consumer sentiment tends to affect positively both market types, albeit only in the short run. Furthermore, the influence of sentiment indicators seems to be stronger in emerging- than in developed-market countries. The results remain robust, even after controlling for a rich range of potential predictors of stock returns. Generally, such evidence highlights the relevance of psychological factors, such as business and consumer sentiment, in determining the future trajectory of asset prices.     

The effects of board structure on corporate performance: Evidence from East African frontier markets

The effectiveness of the well-known corporate governance practices may not be universal due to fundamental differences in the environments under which firms operate. By using hand-collected data from all the non-financial firms listed on the unexplored East African frontier markets (i.e., Kenya, Tanzania and Uganda), we examine the effect of board characteristics on the performance of firms. Our results show that board size has a negative and significant effect on firm performance. The presences of foreigners and civil servants on the board play positive roles on financial performance, where the agency and resource dependence theories apply. Further, we find that board members with higher education also contribute to firm performance. These findings still hold when we consider the 2008–2009 financial crisis period. Overall, we show that in a business climate where ownership is largely dominated by few shareholders, the conventional governance mechanisms do not work effectively.