股票价格、货币政策和宏观经济波动

本文对包含股票价格在内的新凯恩斯模型的结构方程进行估计,分析了股票价格和货币政策与宏观经济波动之间的关系,认为股票价格与宏观经济波动密切相连,货币政策调整可以平滑经济波动。在此基础上,比较了不同的货币政策规则的宏观调控效果,得到的结论是,将股票价格波动纳入货币政策的调控范围会改善货币政策效果,有助于稳定宏观经济。     

中国影子银行的货币供给补充与替代效应——来自货币乘数的证据

本文将影子银行引入银行存款乘数模型,分析影子银行通过分流银行存款、扩大社会信用供给对于货币供给的补充与替代效应,运用向量误差修正模型和状态空间模型及2002~2013年的月度数据进行实证分析。结果表明,影子银行规模扩张总体上扩大了货币乘数,但因经济周期和货币政策立场不同而具有明显"非对称性";在社会总需求扩张阶段,影子银行可以有效补充银行信贷供给不足,而在货币政策紧缩时期,影子银行信用扩张对银行信贷形成替代;影子银行顺周期变化与货币政策逆周期调控之间的矛盾弱化了货币政策效果。     

股票市场对货币政策传导机制影响的实证研究——基于脉冲响应函数和方差分解的技术分析

随着股票市场的蓬勃发展及其与国民经济的联系日益密切,货币政策的传导机制和效应必然受到股票市场发展的影响,同时股票市场也逐渐成为货币政策传导的重要渠道之一。本文首先对货币政策的传导机制与股票市场的关联机制进行分析,然后运用协整分析、向量自回归模型(VAR)、向量误差修正模型(VECM)、脉冲响应函数、方差分解技术等计量方法对我国股票市场对货币政策传导机制的影响进行了实证分析。结果显示股票市场已经成为传导货币政策的一个主要渠道,中央银行制定货币政策时必须要考虑股票市场。     

我国房地产价格对货币政策响应的区域异质性研究

本文通过构建HAVAR模型,尝试将我国省级房地产市场对货币政策响应的区域异质性纳入分析框架,对比分析了传统宏观VAR模型和HAVAR模型中房地产住宅价格和房地产住宅投资对货币政策的响应情况。模型脉冲响应结果显示:HAVAR模型在货币政策冲击的动态响应程度和持续时间上与传统宏观VAR模型表现出显著的差异,证明了区域异质性对货币政策冲击的响应具有重要影响。短期来看,中央银行在调控房地产住宅价格和房地产住宅投资的过程中需要重视区域异质性对货币政策总体效率的影响。长期来看,区域异质性会导致货币政策的调控能力下降,中央银行应重视加强对房地产金融市场的宏观审慎管理,综合运用贷款价值比、债务收入比等工具对房地产信贷市场进行逆周期调节。     

政策性冲击、货币政策操作目标：基于准备金市场模型的实证研究

对于我国货币政策操作目标,并没有一个明确的说法。为了对相对稳定、有效的货币政策操作目标进行实证判断,本文建立了宏观经济变量和准备金市场变量的结构性向量自回归模型(SVAR),通过识别假设把SVAR模型转化为包含政策变量和非政策变量新息(innovation)的关于政策变量的半结构性向量自回归模型(Semi-SVAR)。通过准备金市场模型,界定了可观察残差项与结构扰动项之间的黑箱,对我国货币政策操作目标进行识别。实证结果显示,1998年以来,我国相对稳定、有效的货币政策操作目标是准备金总额,也可以说是基础货币,并不是超额准备金和货币市场利率。识别的政策冲击反映了货币政策调控事件对货币供求的冲击,与我国货币政策的操作实际很吻合。     

我国利率期限结构的货币政策含义

本文从理论上考察了利率期限结构在货币政策制定和实施中的作用:利率期限结构的变化可以体现货币政策态势,可以预测未来的GDP,可以预测未来通货膨胀。进一步地,本文利用无约束VAR模型对我国利率期限结构中货币政策含义进行了实证检验,结果表明,在2002年1月至2009年7月这一时期内,我国利率期限结构对货币政策态势的反应比较迅速;利率期限结构的变化可以预测大约半年后国内生产总值的变化,但对未来通货膨胀的预测能力受到较大限制。由此,我国利率期限结构的变化可以为评估货币政策调控的效果、提高货币政策制定的前瞻性和灵活性提供有价值的信息。     

货币政策工具运用对吉林省银行业资金流动的影响—基于支付清算数据的实证分析

货币政策工具的运用影响着银行业的资金流动,进而影响着地区的金融及经济发展。本文以资金清算的视角对二者关系进行实证分析。首先对吉林省支付清算历史数据与同时期货币政策工具指标变量建立VAR模型,对其进行脉冲响应分析和方差分解,确定了货币政策工具指标变量对吉林省资金流动的冲击程度。在此基础上,对省内不同类型银行的支付清算历史数据与货币政策工具指标变量进行了线形回归分析,得到货币政策工具对各类型银行资金流动的不同影响。最后结合当前货币政策,给出合理化建议。     

货币政策拉动就业增长的有效性研究 ——基于系统GMM估计与面板门槛模型的实证分析

本文基于31个省(市、自治区)2010—2019年的面板数据,对数量型货币政策和价格型货币政策的就业拉动效果进行了实证检验,在检验中运用系统GMM模型剔除内生性,运用面板门槛模型验证阶段性.实证分析发现,总体而言,提高实体经济融资总量和降低利率的货币政策均可以拉动总体就业规模的增长,以社会融资规模衡量的数量型货币政策工具对就业的拉动作用存在门槛特征,拉动效应随货币政策规模的扩张而下降,LPR下降对私营主体就业的拉动作用不显著.据此,建议引导社会融资规模合理增加,加快LPR改革进程,制定差异化的货币信贷政策工具.     

影子银行对货币政策影响的理论与实证分析北大核心CSSCISSCI

本文通过引入银行和影子银行的信用创造和流动性创造功能,对传统的IS-LM模型进行修正来分析影子银行对货币政策的影响,并基于向量自回归模型(SVAR)选用我国2003年1月至2013年6月的月度数据进行实证分析影子银行对货币政策的影响。理论和实证分析结果表明,影子银行的发展对货币政策传导机制如信贷、利率的传导效果造成影响;中央银行货币政策调控难度加大,应执行更为谨慎的货币政策;影子银行的发展对经济具有扩张作用,但也存在影子银行资金不具有长期效应等问题,应客观对待,注意防控其风险。     

解析货币政策非对称性与惰性区域的识别和检验

在我国经济政策中,货币政策一种扮演者无可替代的角色,是我国对经济展开宏观调控的非常重要的途径,它的作用非对称性特征受到各界的广泛关注。识别与检验货币政策的非对称性与惰性,对加强我国货币政策机制的分析与研究具有重要意义。本文在简述了我国货币政策操作的规则性的基础上,已线性指数损失函数为依托,并增加通胀与产出缺口两项指数项参数,基本构建了一种货币政策的反应模型,并对这一模型参数进行了约束,进而对货币政策的惰性行为以及非线性规则性进行识别,以期对货币政策的有效调整提供参考。     

Simple Monetary Policy Rules Under Model Uncertainty

Using stochastic simulations and stability analysis, the paper compares how different monetary policy rules perform in a moderately nonlinear model with a time-varying NAIRU. Rules that perform well in linear models but implicitly embody backward-looking measures of real interest rates (such as conventional Taylor rules) or substantial interest rate smoothing perform very poorly in models with moderate nonlinearities, particularly when policymakers tend to make serially-correlated errors in estimating the NAIRU. This challenges the practice of evaluating policy rules within linear models, in which the consequences of responding myopically to significant overheating are extremely unrealistic.     

In search of the liquidity effect in a modern monetary model

This paper examines the impact of a monetary policy shock in a dynamic stochastic general equilibrium model with sticky prices and financial market frictions. First, we examine the shortcomings of monetary models emphasizing these frictions individually. The model then is specified to limit the response of prices and savings to a current period monetary disturbance. Our results show that this model can account for the following key responses to an expansionary monetary policy shock: a fall in the nominal interest rate; a rise in output, consumption, and investment; and a gradual increase in the price level. Finally, a detailed sensitivity analysis shows the model's results depend on the parameters assigned to critical structural features.     

An optimum-currency-area odyssey

The theory of optimum-currency-areas was conceived and developed in three highly influential papers, written by (Mundell, 1961) and (McKinnon, 1963) and Kenen (1969). Those authors identified characteristics that potential members of a monetary union should ideally possess in order to make it feasible to surrender a nationally-tailored monetary policy and the adjustment of an exchange rate of a national currency. We trace the development of optimum-currency-area theory, which, after a flurry of research into the subject in the 1960s, was relegated to intellectual purgatory for about 20 years. We then discuss factors that led to a renewed interest into the subject, beginning in the early 1990s. Milton Friedman plays a pivotal role in our narrative; Friedman's work on monetary integration in the early 1950s presaged subsequent optimum-currency-area contributions; Mundell's classic formulation of an optimal currency area was aimed, in part, at refuting Friedman's “strong” case for floating exchange rates; and Friedman's work on the role of monetary policy had the effect of helping to revive interest in optimum-currency-area analysis. The paper concludes with a discussion of recent analytical work, using New Keynesian models, which has the promise of fulfilling the unfinished agenda set-out by the original contributors to the optimum-currency-area literature, that is, providing a consistent framework in which a country's characteristics can be used to determine its optimal exchange-rate regime.     

Are Indexed Bonds Really Inflation Proof? A Model of Real and Nominal Term Structures when Money has Real Effects

This paper studies the general behavior of the nominal and real term structures of interest rates in a general equilibrium framework. A central bank is introduced in the model as an agent facing a tradeoff between inflation and output and choosing a monetary policy variable. Prices and output are jointly determined in our model endogenously. Two multi-factor nominal and real term structure models are given as examples to illustrate the general model. In our economies, inflation indexed bonds are not completely inflation proof, but are still subject to the influence of inflation uncertainties. The models offer us an empirical framework that can be studied with indexed bond data and nominal bond data together in a single estimation.     

The Skewness of the Price Change Distribution: A New Touchstone for Sticky Price Models

We present a new way of empirically evaluating various sticky price models that are used to assess the degree of monetary nonneutrality. While menu cost models uniformly predict that price change skewness and dispersion fall with inflation, in the Calvo model, both rise. However, the U.S. Consumer Price Index (CPI) data from the late 1970s onward show that skewness does not fall with inflation, while dispersion does. We present a random menu cost model that, with a menu cost distribution that has a strong Calvo flavor, can match the empirical patterns. The model exhibits much more monetary nonneutrality than existing menu cost models.     

A ‘rational’ explanation for ‘irrational’ forecasts of inflation

This paper analyzes professionals' forecasts of nominal income and the inflation rate. The analysis indicates that both monetary and fiscal policy data was used efficiently to forecast income, but the monetary policy data was not used efficiently to forecast the inflation rate. Further analysis suggests that the apparent inefficient use of the monetary data results from the non-stationary money-inflation relationship predicted by rational expectations models. These models then provide an explanation for the inconsistent conclusions regarding the income forecasts and the inflation rate forecasts.     

The Impact of the Volatility of Monetary Policy Shocks

This paper studies the impact of the volatility of monetary policy using a structural vector auroregression (SVAR) model enriched along two dimensions. First, it allows for time‐varying variance of monetary policy shocks via a stochastic volatility specification. Second, it allows a dynamic interaction between the level of the endogenous variables in the VAR and the time‐varying volatility. The analysis establishes that the nominal interest rate, output growth, and inflation fall in reaction to an increase in the volatility of monetary policy. The analysis also develops a dynamic stochastic general equilibrium model enriched with stochastic volatility to monetary policy that generates similar responses and provides a theoretical underpinning of these findings.     

A tractable yield-curve model that guarantees positive interest rates

Yield-curve models suggested previously in the literature seem always to make a tradeoff between analytical tractability and a realistic behavior of the interest rates. In this paper we analyze a model that combines both features into one model: the interest rates are always positive and the model has a rich analytical structure. Not only is our model theoretically appealing, we also provide empirical evidence that our model can fit observed cap and floor prices better than the Hull-White model.The author is grateful to Stephen Figlewski, Ton Vorst, Carien Dam, Douglas Bongartz-Renaud, participants of the Second International Conference on Computing in Finance and Economics in Geneva and especially Marti Subrahmanyam and two anonymous referees for comments and helpful suggestions.     

Local identification in DSGE models

The issue of identification arises whenever structural models are estimated. Lack of identification means that the empirical implications of some model parameters are either undetectable or indistinguishable from the implications of other parameters. Therefore, identifiability must be verified prior to estimation. This paper provides a simple method for conducting local identification analysis in linearized DSGE models, estimated in both full and limited information settings. In addition to establishing which parameters are locally identified and which are not, researchers can determine whether the identification failures are due to data limitations, such as lack of observations for some variables, or whether they are intrinsic to the structure of the model. The methodology is illustrated using a medium-scale DSGE model.