Insurance activity,real output,and geopolitical risk: Fresh evidence from BRICS

This paper fills some empirical gaps by evaluating the causal associations among insurance premiums, real output, and geopolitical risk in BRICS (Brazil, Russia, India, China, South Africa) from 1985 to 2017. We utilize a newly-developed Granger-causality quantile analysis to assess the causal relationships among the series under consideration in each distribution quantile. Our empirical results reveal unidirectional causality that runs from real output and geopolitical risk to insurance activities in Brazil and South Africa. We also observe bi-directional lower-tail causality among real output, insurance premiums, and geopolitical risk in Russia. Findings also present bi-directional causality among real output, insurance premiums, and geopolitical risk at different quantiles. Knowledge of these causal relationships can prevent governments from conducting a ‘one-size-fits-all’ policy.     

Return of the inoperability

There has been unrest in the research community investigating the inoperability of an economic system under disaster situations. The inoperability input–output model (IIM), which is very popular in the risk management field, has become a center of argument, particularly from the input–output researchers, that IIM is a straightforward application of the standard Leontief input–output model. This paper revisits the concept of inoperability, rather than IIM, and proposes its new role in disaster impact analysis using a conventional tool, i.e. the RAS method, for illustrating how the inoperability of an economic system in the aftermath of disaster can be evaluated. The proposed framework is employed to examine the inoperability of industries resulting from the 1995 Kobe earthquake. The findings of the analysis reveal the usefulness of inoperability concept that can even incorporate resilience (gained operability) using the proposed framework of this paper.     

Measuring industrial upgrading: applying factor analysis in a global value chain framework

ABSTRACT

A key question for promoting international competition is how to improve the position of countries and industries in global value chains (GVCs). The first step is to properly measure industrial upgrading in GVCs. This is not a trivial issue because upgrading has not been defined unambiguously. Several authors have used different (and sometimes related) measures, all of which indicate certain aspects of upgrading. Rather than trying to find the single, ultimate measure of upgrading, we propose a different approach. We examine the multidimensionality of industrial upgrading, using eight indicators in factor analysis. Four of the eight indicators adopt the GVC perspective and include, for example, the growth of the share in value-added exports. We provide three quantitative dimensions of industrial upgrading: process upgrading, product upgrading, and skill upgrading. With these dimensions, we compare and analyze the upgrading of different countries and industries using the World Input–Output Database.     

The Effect of Foreign Entry Regulation on Downstream Productivity: Microeconomic Evidence from China*

We examine the cross‐industry influence of foreign entry regulation (based on a novel measure) on the productivity outcomes of downstream firms through input–output linkages in China. In contrast to the significant liberalization of the manufacturing sector, restrictions on the service sector remained stringent over the period 1997–2007. We find a powerful depressant effect of foreign entry barriers imposed on the upstream manufacturing and service industries on the productivity of downstream manufacturers, and this effect depends on a number of industry‐ and firm‐specific features. Our research calls for further investment liberalization (particularly in the service sector) in China.     

基于引力模型的省域创新产出空间联系研究

基于引力模型，结合社会网络分析法的凝聚子群分析，对31个省（区、市）的创新产出空间联系进行探究，研究发现：我国省域创新产出空间联系主要集中于京津冀和长三角一带，呈现出严重的分布不均状况，具有较强的区域集中性和空间依赖性；北京、天津、上海、浙江、江苏作为区域创新产出引力较强的节点省（区、市），对周边区域的创新产出具有较强的辐射作用；总体来看，省域创新产出空间联系并没有形成贯穿东西南北的交叉网状结构，中心省（区、市）数量较少且分布不均，辐射范围有限。基于此，提出加大区域创新投入、减少区域创新产出联系的政策性障碍、营造区域创新产出联系的良好环境等政策建议。     

Capital flows and growth dynamics in Central and Eastern Europe

This article assesses the importance of capital flows as measured by the current account balance for the growth dynamics of the EU countries from Central and Eastern Europe. Economic growth in these countries was on average relatively high before the global financial crisis but markedly lower after the crisis. Panel data econometrics using annual data for 1997–2015 point to the contemporaneous current account balance having a sizeable negative effect on annual GDP growth. Estimations using many control variables and instrumental variables suggest that the negative effect is mainly demand driven. Counterfactual simulations show that growth rates in all CEE countries would have been lower in the absence of capital flows, and this applies particularly to the countries with the most disadvantageous starting points.     

Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height

We develop a method for forecasting the distribution of the daily surface wind speed at timescales from 15-days to 3-months in France. On such long-term timescales, ensemble predictions of the surface wind speed have poor performance, however, the wind speed distribution may be related to the large-scale circulation of the atmosphere, for which the ensemble forecasts have better skill. The information from the large-scale circulation, represented by the 500 hPa geopotential height, is summarized into a single index by first running a PCA and then a polynomial regression. We estimate, over 20 years of daily data, the conditional probability density of the wind speed at a specific location given the index. We then use the ECMWF seasonal forecast ensemble to predict the index for horizons from 15-days to 3-months. These predictions are plugged into the conditional density to obtain a distributional forecast of surface wind. These probabilistic forecasts remain sharper than the climatology up to 1-month forecast horizon. Using a statistical postprocessing method to recalibrate the ensemble leads to further improvement of our probabilistic forecast, which then remains calibrated and sharper than the climatology up to 3-months horizon, particularly in the north of France in winter and fall.     

产业政策对企业研发创新的影响研究——基于促进创新型产业政策"信心效应"的视角

信心是影响产业政策实施效果背后的重要无形因素。本文从“信心效应”的新视角出发，基于2012—2017年中国A股上市公司面板数据，以《中国制造2025》为一项准自然实验，使用双重差分法研究促进创新型产业政策对企业研发创新的影响。研究结果表明：促进创新型产业政策的颁布能够通过“外部信心效应”和“内部信心效应”促进受支持企业研发投入增加；通过与受支持企业自身的营运性信心和社会性信心叠加，信心效应的影响分别出现U型与倒U型的差异；信心效应在促进创新型产业政策对受支持企业研发产出数量和实质性的影响中都发挥了作用。研究结论不仅丰富了相关文献，也为新时期产业政策的制定与实践以及企业行为调整提供了有益的启示。     

房价上涨如何影响了工业产出

为探究房价上涨对工业生产的作用机制,首先基于理论视角对房价如何影响房地产投资、劳动力成本进而影响工业产出进行了论证,基于2003年~2017年全国时间序列数据,构建VAR模型实证检验了房价上涨对工业产出的影响机理。结果表明:房价上涨对工业产出具有"先促进,后抑制"的作用;房价上涨,一方面通过促进房地产投资增长抑制工业产出,另一方面通过提高工业企业劳动力成本抑制工业产出;短期内工业产出对房价的冲击响应较为灵敏且强烈,但长期来看房地产投资、劳动力成本的影响力会逐渐显现,且房地产投资最终成为了解释工业产出的主导因素。     

政府审计、内部控制与企业创新

利用手工收集的政府审计公告数据，以2013—2017年的国有上市公司为样本，采用PSM+DID方法检验政府审计对国有上市公司创新活动的影响，并进一步根据内部控制质量和是否存在内部控制缺陷对样本进行分组检验两者之间的关系。研究结果表明：政府审计显著增加了国有上市公司的创新投入和创新产出；在内部控制质量高和不存在内部控制缺陷的样本企业中，政府审计对企业创新活动的促进作用更加显著。