流动性、银行间市场摩擦与借贷便利类货币政策工具

通过内生引入流动性短缺银行(拆入行)对流动性盈余银行(拆出行)的流动性需求机制,本文构建了一个包含银行间市场的DSGE模型,对借贷便利类货币政策工具的传导机制和传导效果进行了理论和实证研究。研究表明:(1)负向冲击会同时增加拆入行和拆出行对流动性的预防性需求,在经济形势不确定的情形下,拆出行不会很快恢复对拆入行的流动性供给,引起银行间市场流动性缺口放大和市场失灵。(2)由于仅依赖银行间市场自发回归稳态的过程太过缓慢,需要央行进行流动性干预。借贷便利类工具可以通过引导贷款市场定价和流动性效应这两个渠道来影响银行融资可得性,进而降低银行间市场流动性风险对宏观经济的负面影响。(3)借贷便利类货币政策工具的影响效果边际递减,央行可根据借贷便利操作的收益和成本,制定最佳的反应程度参数。     

房价波动、金融稳定与最优宏观审慎政策

本文通过构建包含家庭住房抵押借款摩擦和银行贷款摩擦的动态随机一般均衡模型,重点考察了异质性冲击下房价波动对金融稳定的影响。研究发现,房价上涨会导致银行风险溢价及杠杆率显著上升,进而加剧金融体系的内在不稳定。为降低房价波动及维护金融稳定,选取两类宏观审慎政策工具进行逆周期调控实验,结果表明,在住房需求冲击下,金融管理部门应选取贷款价值比政策,且应对房贷积极调控,而对房价进行中性调控。在最终产品部门生产率冲击、房地产部门生产率冲击及跨期偏好冲击下,应选取资本充足率政策,但对房贷和房价调控力度的把握则存在差异。本研究为厘清房价波动对金融稳定的动态传导机制,以及金融管理部门如何选取宏观审慎政策工具以稳定房价并降低系统性金融风险提供了启示。     

China’s monetary policy: Quantity versus price rules

Two monetary policy rules, the money supply (quantity) rule and interest rate (price) rule, are explored for China in a dynamic stochastic general equilibrium model. The empirical results seem to indicate that the price rule is likely to be more effective in managing the macroeconomy than the quantity rule, favoring the government’s intention of liberalizing interest rates and making a more active use of the price instrument. Moreover, the economy would have experienced less fluctuations had interest rate responded more aggressively to inflation.     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.     

土地供给市场化后的出让总收入及预测模型设计

国有土地出让招拍挂制度的实施开启了我国土地供给的市场化,更公平、透明地揭示了土地的市场价值,同时为地方政府带来了一定的城市发展建设资金。然而,现行财税制度却加剧了地方财政对土地出让收入的依赖,由此滋生的种种问题导致土地出让收入成为舆论焦点。本文采用格兰杰因果分析、脉冲检验、自回归滞后分布模型等方法,通过实证研究寻找宏观经济变量与土地出让总收入的相互影响及数量关系,并据此推导建立土地出让收入模型,预测土地出让收入的数量及变化趋势,为各界真正了解土地财政以及政府把握土地供给与经济发展之间的关系提供一个理论途径。     

General equilibrium impact of an energy-saving policy in the public sector

We analyse a disregarded environmental policy instrument: a switch in government expenditure away from energy (or other natural resources) and toward a composite good which includes energy-saving expenditure. We first develop two variants of an analytical general equilibrium model. A composite good is produced with constant returns to scale, and energy is imported or produced domestically with diminishing returns, yielding a differential rent to its owners. The government purchases energy and composite goods from private firms. Such a policy unambiguously increases employment. It also raises private consumption and welfare under two conditions: (i) it is not too costly and (ii) the initial share of the resource is smaller in public spending than in private consumption, or the difference is small enough. We then run numerically a model featuring both importation and domestic production of energy (oil, gas and electricity), for the OECD as a whole. Simulations show that employment, welfare and private consumption rise. We provide magnitudes for different parameter values. Earlier versions of this paper have benefited from conference participants at the European Council for an Energy-Efficient Economy, International Society for Ecological Economics World Congress, CIRED seminar and EUREQua environmental economics seminar. We especially thank Michèle Sadoun and two anonymous referees. The usual disclaimer applies.     

实体经济低迷与房地产繁荣之“困”*

本文以实体经济低迷和房地产行业繁荣的困局为切入点,研究了困局产生的原因,并从房产税的视角探讨了如何走出这一困局。本文发现：第一,经济进入新常态后,宽松的货币政策导致增加的货币流向了房地产行业,资源的错配使投资和产出长期无法走出“L”型区间;第二,本文通过三次模拟实验证明,政府可以考虑适当地通过对代表性家庭征房产税进行宏观调控,解决资源错配问题。     

Learning in an estimated medium-scale DSGE model

We evaluate the empirical relevance of learning by private agents in an estimated medium-scale DSGE model. We replace the standard rational expectations assumption in the Smets and Wouters (2007) model by a constant-gain learning mechanism. If agents know the correct structure of the model and only learn about the parameters, both expectation mechanisms produce very similar results, and only the transition dynamics that are generated by specific initial beliefs seem to improve the fit. If, instead, agents use only a reduced information set in forming the perceived law of motion, the implied model dynamics change and, depending on the specification of the initial beliefs, the marginal likelihood of the model can improve significantly. These best-fitting models add additional persistence to the dynamics and this reduces the gap between the IRFs of the DSGE model and the more data-driven DSGE-VAR model. However, the learning dynamics do not systematically alter the estimated structural parameters related to the nominal and real frictions in the DSGE model.     

供求冲击与我国经济外部失衡——基于DSGE两国模型的模拟分析

文章为分析我国经济外部失衡问题,运用当前国际经济学领域先进的动态随机一般均衡(DSGE)两国模型研究方法,模拟了在不同消费替代弹性下以技术冲击为代表的供给冲击和以货币冲击为代表的需求冲击对一国经济外部失衡的影响。研究结果表明这两种冲击发生后该国的外部资产和汇率水平会从初始的0均衡状态偏离,而到最终收敛大约需要10年到15年的时间。这可以很好地解释当前我国的经济外部失衡,文章也依此提出了相应的政策建议。     

European systemic credit risk transmission using Bayesian networks

The analysis of systemic credit risk is one of the most important concerns within the financial system. Its complexity lies in adequately measuring how the transmission of systemic default spreads through assets or financial markets. The transmission structure of systemic credit risk across several European sectoral CDS is studied by dynamic Bayesian networks. The new approach allows for a more advanced analysis of systemic risk transmission, including long-term and more complex relationships. The modelling reveals as relevant only relationships between the original series and one- and two-lagged series. Network structure learning displays a robust and stationary underlying risk transmission structure, pointing to a consolidated transmission mechanism of systemic credit risk between CDSs. Between 5 % and 40 % of sectoral CDS series variances are explained by the network relationships. The modelling allows us to ascertain which relationships between the CDS series show positive (amplifier) and negative (reducer) effects of systemic risk transmission.