Social networks in the global banking sector

We show that banks with shared social connections partner more often in the global syndicated loan market and that central banks in the network play dominant roles in various interbank transactions, indicating that social connections facilitate business connections. However, more centralized banks in the network also contribute significantly to the global systemic risk. Moreover, we find the soft information generated by social networks is particularly valuable when potential partners operate under different accounting and regulatory standards. Finally, we show that the recent banking crisis significantly limited the positive soft information effects of social networks in the global banking system.     

财政补贴的竞争法审查及其改进——兼论《公平竞争审查制度实施细则（暂行）》

财政补贴是国家干预经济的重要手段,能够促进产业结构调整和转型升级、平衡和加速地区间的经济发展,但极易对市场公平竞争带来消极影响,例如破坏市场结构、误导市场行为、减损市场绩效,等等。《公平竞争审查制度实施细则（暂行）》对此予以重点关注,但缺乏全面性的制度构建。这方面,欧盟国家援助制度值得我们学习和借鉴。欲改进我国财政补贴的竞争法审查,必须落实公平竞争审查制度,坚持必要性原则、公平原则和透明度原则,同时要建立补贴评估机制、豁免机制、信息披露机制和异议机制,以规范财政补贴的实施,平衡财政补贴和竞争政策的冲突,确保市场竞争机制不被财政补贴所扭曲。     

Ownership concentration and bank risk: international study on acquisitions

This paper explores the effects of different types of bank ownership concentration on changes in bank risk during acquisition years. Using multi-country data from 2000 to 2006, during which market failures caused by various crises and government interventions are less influential to acquisition decisions, we collect 505 banking acquisition deals from 23 countries to examine which type of ownership concentration (such as financial intermediary, capital investor, non-financial, and state ownership) brings larger changes to an acquirer’s risk from pre-acquisition year to post-acquisition year (including non-performing loans, capital adequacy ratio, loan loss reserve, and credit rating). The empirical analyses show that acquirer banks with a concentration of shares owned by financial intermediaries and non-financial firms experience larger risk changes during acquisition years. In contrast, the risk changes of acquirer banks with a concentration of capital investors and state ownership are lower. Robustness checks from the random effect estimation, instrumental variables model, reverse causality, and different subsamples of (non-)U.S. or different levels of regulation enforcement confirm these results.     

On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks

Daily and weekly seasonalities are always taken into account in day-ahead electricity price forecasting, but the long-term seasonal component has long been believed to add unnecessary complexity, and hence, most studies have ignored it. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, this framework is based on linear models estimated using ordinary least squares. This paper shows that considering non-linear autoregressive (NARX) neural network-type models with the same inputs as the corresponding SCAR-type models can lead to yet better performances. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can outperform the latter significantly.     

Dynamical macroprudential stress testing using network theory

The increasing frequency and scope of financial crises have made global financial stability one of the major concerns of economic policy and decision makers. This has led to the understanding that financial and banking supervision has to be thought of as a systemic task, focusing on the interdependent relations among the institutions. Using network theory, we develop a dynamic model that uses a bipartite network of banks and their assets to analyze the system’s sensitivity to external shocks in individual asset classes and to evaluate the presence of features underlying the system that could lead to contagion. As a case study, we apply the model to stress test the Venezuelan banking system from 1998 to 2013. The introduced model was able to capture monthly changes in the structure of the system and the sensitivity of bank portfolios to different external shock scenarios and to identify systemic vulnerabilities and their time evolution. The model provides new tools for policy makers and supervision agencies to use for macroprudential dynamical stress testing.     

The impact of privatization on efficiency and profitability

Over the past three decades, China has undergone tremendous economic and social change as a consequence of the transition from a centrally planned to a market economy. This paper examines a key feature of this transition – the privatization of the state‐owned enterprises (SOEs) – through both a theoretical model and empirical analysis. Using newly collected primary data from a variety of sources, we study how privatization of listed SOEs affects employment, wages, profits and other aspects of economic performance at the firm level. Our major finding is that privatization results in substantial downsizing of employment, increased labour productivity and rising profitability.     

The effect of heterogeneous beliefs on mergers and acquisitions

This article investigates the effect of heterogeneous beliefs on firms’ mergers and acquisitions (M&A) decisions. Using data of China’s financial market, which is featured with great heterogeneity of belief, we find that heterogeneous beliefs are positively associated with the occurrence of M&A transactions, and firms with greater heterogeneous beliefs are more likely to pay the transactions with stock. Moreover, we show that government intervention, measured by state ownership, weakens the effect of heterogeneous beliefs on firms’ M&A decisions.     

国库最佳库底现金测算方法研究

随着国库集中收付管理制度改革的不断深入，我国国库库存现金余额呈现出快速增长的趋势。通过对确定最佳库底现金的主要模型进行介绍，以国家金库重庆市分库为对象进行了实证分析。以期为实际工作和相关研究提供一定参考。     

Neighbourhood Effects as Indirect Effects: Evidence from a Dutch Case Study on the Significance of Neighbourhood for Employment Trajectories

One of the key challenges in the study of neighbourhood effects on work is to understand the pathways through which disadvantaged neighbourhoods impact the employment opportunities of residents. Endogenous explanations for neighbourhood effects focus on social life in these neighbourhoods, identifying mechanisms of social isolation, deviant work ethics and neighbourhood disorder. This article studies these mechanisms in a low‐income neighbourhood in the Netherlands. The case study shows that unfavourable socioeconomic outcomes can be indirect and unintended consequences of actions and choices in everyday life that are not directly concerned with work. Nevertheless, these individual actions and choices reflect local social practices that are influenced by the marginalized context in which residents lead their lives.