资本回报率、人力资本投资与收入不平等——基于Galor-Zeira模型的扩展

资本回报率下降对人力资本投资、收入不平等程度有较大影响。本文将可变资本回报率加入Galor-Zeira模型,理论推导发现:收入不平等陷阱并非不可逾越的障碍。当技能劳动力工资高于受教育固定成本时,随着资本回报率下降,接受教育的遗赠临界水平将降低,更多家庭将发现投资人力资本是有利的,稳态的技能劳动力比例将提高。在当前资本回报率下降的大背景下,提高技能劳动力工资、降低受教育成本、对教育贷款实施财政减免优惠、为农村中等教育支出减负和提升农村教育质量、倡导节俭和重视遗赠的文化氛围在长期都有助于提高技能劳动力比重以及缓和收入不平等。     

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.     

Personal Income Tax Reform in China in 2018 and Its Impact on Income Distribution

In the context of personal income tax (PIT) reform in China in 2018, this paper examines some of the major issues of concern regarding the reform and income distribution. Using the China Personal Income Tax Micro‐simulation model, the paper compares the differences between the 2011 and 2018 PIT systems, and finds that residents relying on different income sources may face a large degree of real tax rate change. Once the tax system is altered to PIT 2018, the coverage of PIT for wage earners will decrease from 46.9 to 23.4 percent, the income redistributive effect will drop from 1.95 to 1.22 percent and the PIT's role in fiscal revenue will also be negatively affected. Nevertheless, if individual income continues to grow, the share of PIT in fiscal revenue is expected to return to the 2018 level in 2022, but its income redistribution function is difficult to recover in the short term. The paper finds that the effect of PIT on income distribution depends on the tax structure. Gradual transition to an “entirely comprehensive” tax system when conditions are appropriate will achieve better income redistribution results at a lower average tax rate.     

海南城乡居民消费水平差异性分析和预测

从1985-2018年海南城乡居民收入、消费数据出发，分别建立消费关于收入、消费差距关于收入差距的自回归模型，结果表明农村居民当期消费更易受近期收入和消费水平的影响，具有不稳定性。再利用GM(1,1)模型预测城乡居民收入差距，结合自回归模型，完成未来10年海南城乡消费差距的预测：收入差距和消费差距将呈直线递增趋势，收入差距的增幅高于消费差距增幅。缩小海南城乡居民消费差距的根本途径在于缩小收入差距，应因地制宜，切实提高农民收入水平。     

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.     

自然资源依赖对城乡收入差距的影响研究

［目的］针对全国31个省（市、区）（不含港澳台地区）、自然资源依赖度高的地区和自然资源依赖度低的地区，从整体和分区域研究自然资源依赖对城乡收入差距的影响，探究不同区域其影响程度的差异性，进而为弱化各区域城乡收入差距，解决由城乡收入差距拉大造成的各类社会矛盾具有重要的现实意义。［方法］从理论上分析了自然资源依赖对城乡收入差距的影响，并利用1999—2017年的省级面板数据，运用固定效应模型，从全国和分区域实证分析了自然资源依赖对城乡收入差距的影响。［结果］针对全国，自然资源依赖会拉大城乡收入差距； 分区域结果，针对自然资源依赖度高的地区，自然资源依赖拉大城乡收入差距； 针对自然资源依赖度低的地区，自然资源依赖对城乡收入差距影响不显著。［结论］为缩小城乡收入差距，需要降低经济体对自然资源的依赖，针对自然资源依赖度高的地区，政府通过将部分自然资源收益转化为农业创新基金和农村基础设施投入，促进自然资源收益向农村公共资本转化，完善现有的自然资源收益分配及转化制度； 鼓励资源型产业技术创新，加大研发投入，延长资源产业链； 加大农村教育投入、提升农村人力资本质量。     

The Great Recession,Austerity and Inequality: Lessons from Ireland

The advent of the Great Recession and the widespread adoption of fiscal austerity policies have heightened concern about inequality and its effects. We examine how the distribution of income in Ireland—a country which experienced one of the most severe economic contractions—has evolved over the years 2008 to 2013. Standard cross‐sectional analysis of the income distribution shows broad stability in the Gini coefficient and in decile shares, with one main exception: the share of the bottom decile fell sharply, with the largest fall in average incomes being for that group. Longitudinal analysis shows that the falls in the average income for the bottom decile were not due to decreasing income for those remaining in the bottom decile, but to falls in income from those initially located in higher deciles. The extent of redistribution through taxes and transfers increased strongly, as measured by the Reynolds‐Smolensky index, which rose from 0.20 before the onset of the crisis to 0.27 in 2013. Analysis indicates that about three‐quarters of this increased redistribution is due to automatic stabilisers and one‐quarter to discretionary policy changes.