Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments

The reproducibility crisis, that is, the fact that many scientific results are difficult to replicate, pointing to their unreliability or falsehood, is a hot topic in the recent scientific literature, and statistical methodologies, testing procedures and p‐values, in particular, are at the centre of the debate. Assessment of the extent of the problem–the reproducibility rate or the false discovery rate–and the role of contributing factors are still an open problem. Replication experiments, that is, systematic replications of existing results, may offer relevant information on these issues. We propose a statistical model to deal with such information, in particular to estimate the reproducibility rate and the effect of some study characteristics on its reliability. We analyse data from a recent replication experiment in psychology finding a reproducibility rate broadly coherent with other assessments from the same experiment. Our results also confirm the expected role of some contributing factor (unexpectedness of the result and room for bias) while they suggest that the similarity between original study and the replica is not so relevant, thus mitigating some criticism directed to replication experiments.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

延迟退休年龄下隔代抚育与劳动参与的抉择*——基于工资收入随机性假定的研究

隔代抚育会对延迟退休年龄政策在促进劳动力供给上产生挤出效应。为了对此进行验证，本文在工资收入随机性的假定及延迟退休5年的情景下，模拟了面临孙辈照护需求的女性临近退休者提前退休所产生的福利变化。进一步，本文采用CHIP和CHARLS的微观调查数据，对不同群组的收入增长率和收入风险进行了估计，继而分析了当面临孙辈照护需求时这些收入特征对退休决策者制度退休和退休后劳动参与抉择产生的影响。总体上，在延迟退休年龄政策下，隔代抚育将对女性劳动力供给产生挤出效应。当面临孙辈照护需求时，女性临近退休者的制度退休抉择主要受自身收入增长率和收入风险的影响，收入增长率越低，或收入风险越高，她们提前退休的意愿就越强烈；制度退休后的劳动参与则更多地受子女收入增长率的影响，子女收入增长率越高，劳动参与的概率越低。     

On the Current Situation and Problems of High Education Institutes Digital Libraries Development

The paper discusses the necessity and objective of digital library system, and analyzes the current situation of the high education institute digital libraries in China as well as some potential problems. Development plan is proposed for the digital library system for universities.     

构造信贷市场资金价格形成机制分析——对定南县贷款利率市场化改革的个案研究

文章通过对江西定南县利率改革试点进行个案研究，从宏观和微观两个层面探讨了如何构造信贷市场资金价格形成机制。     

Intraday Lead-Lag Relationships Between the Futures-, Options and Stock Market

In rational, efficiently functioning and complete markets, returns on derivative and underlying securities should be perfectly contemporaneously correlated. Due to market imperfections, one of these markets may reflect information faster. The use of high-frequency data and the choice for a small unit time interval to measure these lead-lag relations comes at the cost of some or many missing observations, causing traditional estimators to either under- or overestimate covariances and correlations. We use a new estimator to estimate lead-lag relationships between the cash AEX index, options and futures. We find that futures returns lead both options and cash index returns by approximately 10 minutes. The relationship between options and the cash market is not completely unidirectional.