评价中心技术实践教学模式初探

评价中心是预测效度较高的有效的综合性测评系统,目前被越来越多的组织用来进行人员的选拔和配置,因此,在《人员素质测评理论与方法》课程中要求作为重点内容给学生讲授。由于评价中心高度的情境模拟性及较强的实践操作性,所以,对于这部分内容的讲授不应局限于理论知识,而应该综合使用案例教学与模拟教学模式,以便于人力资源管理专业的学生熟练掌握、运用和操作。     

A New Method for Identifying the Effects of Foreign Exchange Interventions

Central banks react even to intraday changes in the exchange rate; however, in most cases, intervention data are available only at a daily frequency. This temporal aggregation makes it difficult to identify the effects of interventions on the exchange rate. We apply the Bayesian Markov‐chain Monte Carlo (MCMC) approach to this endogeneity problem. We use “data augmentation” to obtain intraday intervention amounts and estimate the efficacy of interventions using the augmented data. Applying this new method to Japanese data, we find that an intervention of 1 trillion yen moves the yen/dollar rate by 1.8%, which is more than twice as much as the magnitude reported in previous studies applying ordinary least squares to daily observations. This shows the quantitative importance of the endogeneity problem due to temporal aggregation.     

农民工工伤保险模式设计与仿真

农民工工伤保险模式要求在政府统一的农民工社会保障体系下,实行缴费资金先由省市政府统一管理、再逐步发展为全国统一的管理体系,实行单位缴费,个人不承担。文章在重点调查研究农民工工伤保险现状基础上提出合理的工伤保险缴费和待遇新模式,并进行计算机仿真计算,检验设计的模式是否科学、合理和可操作的。     

Investigating the impact of demand amplification on freight transport

Despite freight transport operations being influenced by supply chain dynamics, there has been only a very limited investigation into the impact of demand amplification on this function, with almost no analytical research. This paper aims, through spreadsheet simulation of a generic production control system, to quantify the impact of demand amplification on transport performance. Performance measures evaluated include both transport cost and efficiency. The results in general find a negative relationship between transport performance and demand amplification. It is also found that the ratio of vehicle capacity to average demand affects these results.     

Nonlinearities in the real exchange rates: new evidence from developed and developing countries

This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we show that a modified nonlinearity test, which includes additional right-hand-side variables, performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange rate for both developed and developing countries using the modified test for the recent floating period. In general, the results find a greater incidence of nonlinear dynamics for developing country real exchange rates.     

Policies for managing peak stock of food grains for effective distribution: A case of the Indian food program

The Indian food program has encountered a significant shortfall in storage due to slow expansion of storage facilities in comparison with procurement. The open storage of food grains results in substantial loss and deterioration of quality. While increasing storage capacity is a viable but costly and time consuming option, the adoption of policies for peak storage reduction would go a long way towards effective food grains management. On this background, this study proposes policy adoption for peak storage reduction for effective inventory management. A dynamic simulation model was built by replicating the complex flow process and incorporating the process variability for finding the bottleneck and significant factors. It was found that steep wheat procurement is the critical bottleneck factor for peak storage requirements. Two practical and straightforward, yet effective policies are proposed from the few existing strategies for peak storage reduction owing to the constraints associated with the food program. With the actual data of the food program, reduction in peak stock was estimated for the recommended policies, including the operational cost saving in storage. The practical implications of these policies within the system were also discussed. Through peak reduction, the use of open storage can be significantly reduced, and this leads to better food grains management for effective food distribution.     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Optimal model averaging forecasting in high-dimensional survival analysis

This article considers ultrahigh-dimensional forecasting problems with survival response variables. We propose a two-step model averaging procedure for improving the forecasting accuracy of the true conditional mean of a survival response variable. The first step is to construct a class of candidate models, each with low-dimensional covariates. For this, a feature screening procedure is developed to separate the active and inactive predictors through a marginal Buckley–James index, and to group covariates with a similar index size together to form regression models with survival response variables. The proposed screening method can select active predictors under covariate-dependent censoring, and enjoys sure screening consistency under mild regularity conditions. The second step is to find the optimal model weights for averaging by adapting a delete-one cross-validation criterion, without the standard constraint that the weights sum to one. The theoretical results show that the delete-one cross-validation criterion achieves the lowest possible forecasting loss asymptotically. Numerical studies demonstrate the superior performance of the proposed variable screening and model averaging procedures over existing methods.     

Impact of walking speed on tourist carrying capacity: The case of Maiji Mountain Grottoes,China

This paper analyzes the impact of walking speed on tourist carrying capacity. To do so, a combination of simulation experimentation and on-the-ground experiment is suggested to work in a study case, Maiji Mountain Grottoes, China. The simulation findings indicate that walking speed has a negative impact on tourist carrying capacity and the correlation coefficient is 0.64, for the reason that walking takes up more space. The on-the-ground experiment shows that carrying capacity is not a unified limit all over a destination, but changeable temporally and spatially, and its estimation needs to be adjusted according to the minimum area required per tourist and tourist activity. The method applied in this paper and the simulation findings can serve as a methodological tool for further research about tourist carrying capacity where the main activity of tourists is walking while watching.     

Regime switching rough Heston model

This model combines two important stylized features of volatility, the rough behavior consistent with a Hurst parameter less than , and the regime switching property consistent with more long-term economic considerations. It is nevertheless highly tractable in the sense of semianalytic formulae for European options, and permits a partial Monte Carlo method of similar computational speed as the semianalytic formula (at an appropriate number of Monte Carlo simulations). While option prices are relatively insensitive to the choice of Hurst parameter, introducing rough volatility allows for a better fit to the at-the-money skew.