经济开放与货币需求:国际金融风险及持币成本的测度

在中国开放经济体制下的基准货币需求模型中,本文将源于国际金融市场的持币成本设为遗漏潜变量,并构建特定的国际金融综合指数(CIFI)作为该潜变量的测度。借鉴机器学习与测度理论,本文利用对数误差修正模型提出了分步降维的CIFI构造算法,构造了长期CIFI和短期CIFI。结果表明,CIFI构造中的无监督降维步骤有助于减少高维金融数据中的冗余信息。实证分析发现,国际机会成本对中国货币需求具有规律性的前导影响,而在2007至2008年国际金融危机期间,央行的应急措施对长期CIFI所代表的非均衡冲击起到明显的阻截效果,对短期CIFI的影响基本是持续不变的。通过综合指数构造与宏观货币需求模型的算法连接,可以利用CIFI的构成结构从前导时间与影响强度两方面追踪冲击货币需求的国际金融风险的具体来源,这为宏观决策者监测国际金融市场提供了颇有规律的信息。在方法论上,本研究为如何利用模型监测国际金融市场影响宏观经济开辟了一条新路。     

A practical road map for assessing cyber risk

The increase in interconnectivity and developments in technology have caused cyber security to become a universal concern. This paper highlights the dangers of the evolution of cyber risk, the challenges of quantifying the impact of cyber-attacks and the feasibility of the traditional actuarial methodologies for quantifying cyber losses. In this paper, we present a practical roadmap for assessing cyber risk, a roadmap that emphasizes the importance of developing a company and culture-specific risk and resilience model. We develop a structure for a Bayesian network to model the financial loss as a function of the key drivers of risk and resilience. We use qualitative scorecard assessment to determine the level of cyber risk exposure and evaluate the effectiveness of resilience efforts in the organization. We highlight the importance of capitalizing on the knowledge of experts within the organization and discuss methods for aggregating multiple assessments. From an enterprise risk management perspective, impact on value should be the primary concern of managers. This paper uses a value-centric/reputational approach to risk management rather than a regulatory/capital-centric approach to risk.     

Simulated economic impacts in applied trade modelling: A comparison of tariff aggregation approaches

This paper assesses the performance of two recently developed tariff aggregators in reducing tariff aggregation bias by analysing Swiss beef market liberalisation scenarios. Specific relevant sources of bias are addressed: substitution effects on import demand, Tariff Rate Quotas and overprotection in tariffs. The aggregators are linked to a global large-scale partial equilibrium model and benchmarked against a standard aggregator. The choice of the aggregation method shows considerable effects on simulated economic impacts, specifically if the dispersion in tariffs or tariff cuts is large. A large bias is revealed in simulated gains from trade liberalisation using the standard aggregator. The impacts on traded quantities are found to be overestimated, while price and welfare effects can be higher or lower by switching to alternative aggregation methods. By reducing aggregation bias and depicting negotiated tariff schedules more directly, the proposed aggregators enhance the contribution of trade modelling to evidence-based policy making.     

Fixed costs and long-lived investments

Fixed costs models are difficult to analyze because they feature non-degenerate, time-varying distributions of capital across firms. If investments are sufficiently long-lived however then the cross-sectional distribution of capital holdings has virtually no bearing on the equilibrium and the aggregate behavior of fixed-cost models is essentially identical to neoclassical models. The findings are due to a near infinite elasticity of investment timing for long-lived investments – a feature shared by fixed-cost models and neoclassical models. “Irrelevance results” found in numerical studies of fixed-cost models are not parametric special cases but instead are fundamental properties of models with long-lived investment goods.     

Estimating firm-level and country-level effects in cross-sectional analyses: An application of hierarchical modeling in corporate disclosure studies

Researchers in the field of international accounting are often confronted with observations of firms clustered into higher-level units such as countries. Using data from a corporate disclosure study including 797 firm observations from 34 countries, we demonstrate that the inferences obtained from the most commonly used Ordinary Least Square (OLS) test, which pools the firm and country data either under the disaggregation or aggregation approach, are problematic and misleading. To overcome the methodological limitation, we subsequently employ hierarchical modeling to simultaneously estimate both firm-level (within-country) and country-level (cross-country) disclosure determinants. We find that the clustering effects are significant in almost all firm-level variables. Once such effects are adjusted, only three firm-specific variables are significantly associated with corporate disclosure. Evidence provided by this study has important implications for most international accounting studies conducted in cross-level contexts.     

中国金融集聚水平的现状与影响因素探析

金融集聚作为产业集聚的一种表现形式,在我国呈现出在曲折中缓慢上升的趋势,而且这种趋势有向东部发达地区延伸的迹象。为验证并进一步探究影响这种趋势的相关因素,一方面,引入空间基尼系数、HI指数和行业集中度三种测度方法,对我国金融集聚的现状作出分析;另一方面,通过回归分析考察我国金融集聚与工业化程度、货币化程度和经济发展水平之间的关系,认为经济的货币化程度和经济发展水平是影响这种集聚趋势的重要因素。     

基于科技型人才聚集的高等院校协同创新系统建模与仿真

高等院校是推进协同创新的重要力量,相关研究议题日益受到国内外学者关注。在对高等院校协同创新模式进行研究的基础上,以科技型人才聚集为视角,提出高等院校协同创新复杂系统。通过分析协同创新环境与高等院校协同创新系统的作用过程,基于系统动力学方法构建相应模型,运用Vensim PLE软件进行系统仿真,并利用拟合优度方法验证系统有效性。应用灵敏度分析方法,结合工作实际,得到高等院校协同创新管理启示如下：制定以科技型人才为主导的协同创新战略,强化高等院校协同创新的政策制度支撑,完善高等院校协同创新投入机制。     

Inferring Transactions from Financial Statements*

In this paper, we embed the double entry accounting structure in a simple belief revision (estimation) problem. We ask the following question: Presented with a set of financial statements (and priors), what is the reader's “best guess” of the underlying transactions that generated these statements? Two properties of accounting information facilitate a particularly simple closed form solution to this estimation problem. First, accounting information is the outcome of a linear aggregation process. Second, the aggregation rule is double entry.     

Biases in demand analysis due to variation in retail distribution

Aggregate demand models typically assume that consumers choose between all available products. Since consumers may be unwilling to search across every store in a given market for a particular item, this assumption is problematic when product assortments vary across stores. Using supermarket scanner data for five product categories we demonstrate that approximately one third of products have limited retail distribution, which account for one fourth of dollar sales. Monte Carlo analysis demonstrates that the level of limited product availability observed in the data can significantly bias the results of aggregate demand models that incorrectly assume all consumers in a given market face the same choice set.