银行信贷与中国经济波动：1993-2005

基于1993--2005年的季度数据,本文在一个包含银行部门的动态随机一般均衡模型中,讨论了银行信贷和中国经济波动的关系。模拟结果和实际数据的对比表明,引入银行贷款渠道和价格粘性的经济周期模型对中国经济波动有很好的解释力。脉）中响应和方差分解的结果表明：（1）技术冲击解释了大部分产出、投资以及长期消费的波动;（2）信贷冲击解释了大部分短期消费、贷款以及货币余额的波动,对产出、投资的波动有一定解释力;（3）货币需求冲击影响不显著,仅对通货膨胀、贷款以及货币余额波动有一定的解释力;（4）货币政策冲击解释了通货膨胀的大部分波动。     

宏观政策对中国经济波动的影响模拟

文章通过建立一个包含货币政策、具有自动稳定机制的财政政策、金融中介机构以及粘性价格、粘性工资等特性的新凯恩斯主义动态随机一般均衡模型(DSGE),在校准模型结构参数的基础上,运用脉冲响应技术手段分析了财政政策、货币政策以及贷款、消费偏好等8个外生随机冲击对我国经济波动的影响。研究发现：货币供应量、消费偏好和政府购买支出等冲击均导致我国经济上升,即产出和通货膨胀均上升,贷款和技术冲击导致产出增加而通货膨胀下降,投资调整成本冲击导致产出和通货膨胀均下降,价格加成和工资加成冲击均导致产出下降、通货膨胀上升;货币供应量、技术和投资调整成本冲击是我国经济波动的主要来源,财政政策对中国经济波动的影响相对较小。     

资本市场的市场化与中国的实际经济周期

本文在RBC模型框架下引入垄断竞争,来解释宏观经济的周期波动和考察市场化进程冲击对经济波动的影响,并利用中国改革开放以来的经济数据,对该模型进行了实证检验。研究发现该模型能够更好地解释资本市场的波动特征,更好地解释各变量与劳动生产率之间的协动关系;能够合理地解释中国居民消费波动大于产出波动的特征事实,说明该模型对中国经济的解释力比传统的RBC模型更好。另外,还发现市场化进程冲击是中国经济波动的重要冲击来源,可以解释约23%的产出波动,53%的消费波动,33%的就业与投资波动,40%的资本存量与劳动生产率波动,说明其是中国宏观经济波动不可忽略的重要影响因素。     

货币冲击与中国经济波动——基于DSGE模型的数量分析

基于1993~2008年的季度数据,本文在一个包含Calvo价格粘性的新凯恩斯主义模型中,讨论了中国货币冲击与经济增长的关系。在假定货币政策通过调整货币供给增长实施的前提下,本文根据模型模拟和实际数据的对比以及脉冲响应函数分析得出以下结论:(1)货币并非我国经济波动根源,实际产出对货币供给具有一定反馈作用。(2)通货膨胀的顺周期性和领先增长表明中国经济周期存在总需求拉动的特性。物价波动在中短期主要由货币供应量波动引起。(3)货币政策对实体经济有效但效果有限,货币供给变动对投资的作用效力更大,对消费需求刺激有限。     

我国宏观经济波动中的随机冲击效应:经验事实与理论解读

本文首先利用一个施加长期约束的SVAR框架,考察了供给、需求与货币冲击对我国产出、通货膨胀影响的经验事实。结果显示,需求冲击对产出和通货膨胀均存在较大影响力,供给冲击偏重于影响产出,货币冲击则偏重于通货膨胀。随后,基于动态随机一般均衡理论框架,引入技术、偏好等七种典型的外生随机冲击,详细刻画随机冲击对我国宏观经济的影响机制,其脉冲模拟结果与SVAR经验事实基本一致。DSGE方差分解进一步显示,在多数年份,供给需求冲击与财政政策冲击能够解释大部分产出波动,供需、财政货币政策等随机冲击对通货膨胀波动的解释比例较为均衡。近期,受经济转型以及政策转向的影响,以消费、投资为代表的需求冲击构成我国当前宏观经济波动的最主要因素。     

随机货币冲击下的中国经济波动研究——基于RBC模型

中国居民消费存在明显的现金先行约束.在真实经济周期(RBC)模型中通过现金先行约束引入货币冲击符合中国经济运行特征.笔者在真实经济周期理论框架内分析了外生货币冲击对中国经济波动产生的影响.研究表明,货币发行冲击主要影响消费、投资和通胀率的波动,而其他主要经济变量(产出、就业等)的波幅基本不变.     

中国经济波动——基于新凯恩斯主义垄断竞争模型的分析

本文运用新凯恩斯主义垄断竞争模型来研究中国经济波动问题。模型校准的结果表明,就暂时冲击而言,消费偏好冲击、投资边际效率冲击、技术冲击、名义货币供给增长冲击和政府支出冲击都能产生明显的暂时经济波动;就冲击的持久性而言,只有消费偏好冲击和技术冲击的持久性对经济波动变化具有较明显的影响。但技术冲击对产出波动的影响不如RBC类模型那样大,而持久的正向消费偏好冲击对稳定经济增长非常重要。     

劳动份额在经济周期中的波动性及其影响效应

中国劳动份额波动与生产率波动、产出波动之间存在较强的关联性,中国劳动份额具有逆周期波动特征。本文构建了一个同时包含生产率冲击与要素收入份额冲击的动态随机一般均衡(DSGE)模型,研究中国劳动份额波动在经济周期中的影响效应,结果表明:中国劳动份额具有较大的波动性、较强的持续性以及逆周期性;本文的理论模型能够较好地模拟实际经济波动特征,在产出和消费波动上的Kydland-Prescott比率分别高达93%和91%,分别解释了投资、资本存量与劳动投入68%、58%和34%的波动,并较好地预测了消费、投资、资本存量的顺周期特征;面对劳动份额冲击,产出、投资、资本存量、生产率均会产生负向效应,消费表现出先提升后下降的动态效应,劳动投入则有所上升。     

产业结构升级与中国经济波动平稳化

本文将产业结构升级因素引入动态随机一般均衡模型并对其进行扩展,较好地模拟和分析了产业结构升级对中国经济波动的影响及其机制。敏感度分析表明,产业结构升级在增加了投资需求的同时相对减少了消费需求,但消费需求的波动缓和了产出波动而投资需求的波动加剧了产出波动,二者产生了一定程度的"抵消效应",这可能是近些年来中国经济在高投资、高增长的同时并没有出现高波动的重要原因。反映动态冲击机制的脉冲响应分析发现,产业结构升级冲击使得投资产生较大的正向波动,但同时使得消费产生负向波动,这两种波动共同作用,最终使得总产出的波动不是很大,可见产业结构升级对中国经济波动的冲击总体上表现为"熨平效应"。     

预期到的与未预期到的货币供给冲击及其宏观影响

本文尝试建立一个包含预期到的与未预期到的货币供给冲击的动态随机一般均衡(DSGE)模型,通过贝叶斯技术估计模型,并基于估计后的模型考察了预期到的与未预期到的货币供给冲击对产出和通货膨胀波动的影响。结论表明:预期到的与未预期到的货币供给冲击对通货膨胀波动有显著影响,二者均可以解释28%以上的通货膨胀波动,但对产出波动的影响偏小。因此,央行政策选择上可以积极运用数量型货币政策工具调控通胀,同时应注重提高货币政策的透明度,合理引导公众预期,增强货币政策的有效性。     

Observed expectations,news shocks,and the business cycle

This paper exploits information from the term structure of survey expectations to identify news shocks in a DSGE model with rational expectations.We estimate a structural business-cycle model with price and wage stickiness. We allow for both unanticipated and anticipated components (“news”) in each structural disturbance: neutral and investment-specific technology shocks, government spending shocks, risk premium, price and wage markup shocks, and monetary policy shocks.We show that the estimation of a standard DSGE model with realized data obfuscates the identification of news shocks and yields weakly or non-identified parameters pertaining to such shocks. The identification of news shocks greatly improves when we re-estimate the model using data on observed expectations regarding future output, consumption, investment, government spending, inflation, and interest rates - at horizons ranging from one-period to five-periods ahead.The news series thus obtained largely differ from their counterparts that are estimated using only data on realized variables. Moreover, the results suggest that the identified news shocks explain a sizable portion of aggregate fluctuations. News about investment-specific technology and risk premium shocks play the largest role, followed by news about labor supply (wage markup) and monetary policy.     

Investment-specific shocks and real business cycles in emerging economies: Evidence from Brazil

This paper investigates the role of the RBC (Real Business Cycle) model with investment-specific technology shocks in explaining business cycle fluctuations in Brazil. I consider the role of transitory and permanent components of neutral and investment-specific technology shocks. I fit the model to the data using Bayesian techniques to show that the investment-specific shocks are important sources of fluctuations in the estimated model. In fact, in the context of the model, investment-specific shocks can account for remarkable percentages of fluctuations in consumption growth, GDP growth, investment growth and trade balance to GDP ratio. Furthermore, I present simulation evidence showing that the RBC model cannot account for some important features of the data.     

Understanding the effects of technology shocks

The research led by Gali (AER 1999) and Basu et al. (AER 2006) raises two important questions regarding the validity of the RBC theory: (i) How important are technology shocks in explaining the business cycle? (ii) Do impulse responses to technology shocks found in the data reject the assumption of flexible prices? Using an RBC model, this paper argues that the conditional impulse responses of the U.S. economy to technology shocks are not grounds to reject the notion that technology shocks are the main driving force of the business cycle and the assumption of flexible prices, in contrast with the conclusions reached by the literature.     

Did monetary or technology shocks move euro area stock prices?

Using a Bayesian vector autoregressive (VAR) model, I investigate the impact of monetary and technology shocks on the euro area stock market. I find an important role for technology surprise shocks, but not monetary shocks, in explaining variations in real stock prices. Specifically, the pronounced boom?Cbust cycle of 1995?C2003 is largely due to technology surprise shocks. The identification method allows me to study the effects of technology news shocks. The responses are consistent with the idea that news on technology improvements has an immediate impact on stock prices. These findings are robust to several modelling choices, including the productivity measure, the specification of the VAR model, and the identifying restrictions.     

Avoiding pitfalls in using structural VARs to estimate economic models

Structural Vector Autoregressions with a differenced specification of hours (DSVAR) suggest that productivity shocks identified using long-run restrictions lead to a persistent and significant decline in hours worked. Economists have interpreted this evidence as showing that standard business cycle models in which a positive technology shock leads to a rise in hours are inconsistent with the data. In this paper we argue that such a conclusion is unwarranted because model's data and actual data are not treated symmetrically. To illustrate this problem, we estimate and test a flexible-price DSGE model with non-stationary hours using Indirect Inference on impulse responses of hours and output after technology and non-technology shocks. We find that, once augmented with a moderate amount of real frictions, the model can mimic well impulse responses obtained from a DSVAR on actual data. Using this model as a data generating process, we show that our estimation method is less subject to bias than a method that would directly compare theoretical responses with responses from the DSVAR.     

Sources of business fluctuations: Financial or technology shocks?

Despite the widespread belief that technology shocks are the main source of business fluctuations, recent empirical studies indicate that in the absence of financial frictions, a shock to the marginal efficiency of investment is the main source and is closely related to financial conditions for investment. We incorporate a financial accelerator mechanism and two types of financial shocks to the external finance premium and net worth in a dynamic stochastic general equilibrium model with shocks to the marginal efficiency of investment, the investment-good price markup, and the rates of neutral and investment-specific technological changes. This model is estimated using eleven US time series that include data on loan, net worth, the loan rate, and the relative price of investment. Our estimation results show that the (non-stationary) neutral and investment-specific technology shocks primarily drive output and investment fluctuations, while the external finance premium shock plays an important role for investment fluctuations. This financial shock induced substantial falls and subsequent sharp hikes in the external finance premium and caused boom–bust cycles over the past two decades.     

Stability of M2 money demand function in industrial countries

In this article, we set out a model of labour productivity which distinguishes between shocks which change productivity permanently and shocks which have transient affects on productivity. We show that this model is a type of unobserved components model – a random walk with drift plus noise model. The advantage of this approach is that it provides a coherent framework to identify the deterministic trend growth component and also the productivity enhancing (or technology related) stochastic components. The model is applied to aggregate labour productivity in Australia and the time series of technology shocks extracted is used to shed some light on the contributions of policy reforms to productivity.     

The role of financial shocks in business cycles with a liability side financial friction

The paper investigates the role of investment specific technology shock within the particular type of financial friction of Gertler and Karadi (2011) and the impact of direct financial shock into this, such as a net worth shock, using US data. The paper explicitly shows how the bank balance sheet effect of counter cyclical movement of capital price attenuates such investment shocks and the extent depends on the type of financial shocks included in the model. Because of the construction of capital quality shock in such financial friction model, we need to incorporate a direct net worth shock while analysing the role of financial shock. This highlights finance sector as a fundamental source of shocks apart from amplifier of shocks originating in elsewhere of the economy.     

Manufacturing Wage Differentials and Employment in Some Scandinavian Countries, the U.S. and the U.K.: An Analysis of Variance Approach

This paper presents some empirical evidence on the factors determining changes in wage differentials between skilled and unskilled workers and in their employment. An ``analysis of variance' (ANOVA) model is estimated using UN data for five OECD countries in order to assess the relative importance of industry-specific, country-specific and international shocks (as well as interactions between industry and country effects). It is found that both international shocks and national policies affect wage differentials over the whole sample, whilst skill-biased technical change (SBTC) was a significant factor in the seventies. Employment responds mainly to international shocks, although national policies and SBTC were important determinants in the seventies and eighties respectively. Some of the results are found to be sensitive to the technology level of the industries considered.     

Sources of fluctuations in hours worked for Canada,Germany, Japan and the U.S.: a sign restriction VAR approach

This study empirically examines the sources of fluctuations in hours worked in Canada, Germany, Japan and the U.S. It is particularly motivated by Galí’s (1999) VAR study, which demonstrates that a positive technology shock reduces hours worked, at least in the short run. However, in the present study, a technology shock is identified without recourse to Galí’s long-run restriction, which has been subject to active controversy. Furthermore, this study uncovers other important sources of fluctuations in hours worked to reflect the concern, raised by numerous studies, that technology shocks leave most variations in hours worked unexplained. Specifically, there are six shocks underlying our model, and they are identified using a set of sign restrictions. The empirical results confirm that in all four countries, a positive technology shock significantly reduces hours worked. This technology shock, along with labor supply and demand shocks, accounts for most of the short-term variations in hours worked. As the forecasting horizon increases, technology and demand shocks become less important, whereas labor supply shocks contribute to explaining the bulk of long-run variations in hours worked. Finally, the empirical relevance of Galí’s long-run identification restriction is tested and the results are related to those obtained using the sign restriction model.