Estimation of structural impulse responses: short-run versus long-run identifying restrictions

There is evidence that estimates of long-run impulse responses of structural vector autoregressive (VAR) models based on long-run identifying restrictions may not be very accurate. This finding suggests that using short-run identifying restrictions may be preferable. We compare structural VAR impulse response estimates based on long-run and short-run identifying restrictions and find that long-run identifying restrictions can result in much more precise estimates for the structural impulse responses than restrictions on the impact effects of the shocks.     

Reducing confidence bands for simulated impulse responses

It is emphasized that the shocks in structural vector autoregressions are only identified up to sign and it is pointed out that this feature can result in very misleading confidence intervals for impulse responses if simulation methods such as Bayesian or bootstrap methods are used. The confidence intervals heavily depend on which variable is used for fixing the signs of the responses. In particular, when the shocks are identified via long-run restrictions the problem can be severe. It is pointed out that a suitable choice of variable for fixing the signs of the responses and, hence, of the shocks, can result in substantial reductions in the confidence bands for impulse responses.     

Consumer Search Behavior in the Changing Credit Card Market

Many recent articles have identified behavioral disturbances in vector autoregressions by imposing restrictions on the long-run effects of shocks. This article demonstrates that this approach will be unreliable unless the underlying economy satisfies three types of strong restrictions. Although many aspects of these issues have been raised before, this article draws out and illustrates the implications for inferences under the long-run scheme. Furthermore, it provides strategies for dealing with the problems.     

Structural vector autoregressive analysis for cointegrated variables

Summary Vector autoregressive (VAR) models are capable of capturing the dynamic structure of many time series variables. Impulse response functions are typically used to investigate the relationships between the variables included in such models. In this context the relevant impulses or innovations or shocks to be traced out in an impulse response analysis have to be specified by imposing appropriate identifying restrictions. Taking into account the cointegration structure of the variables offers interesting possibilities for imposing identifying restrictions. Therefore VAR models which explicitly take into account the cointegration structure of the variables, so-called vector error correction models, are considered. Specification, estimation and validation of reduced form vector error correction models is briefly outlined and imposing structural short- and long-run restrictions within these models is discussed. I thank an anonymous reader for comments on an earlier draft of this paper that helped me to improve the exposition.     

Some Observations,a Suggestion,and Some Comments on the Conway-Roberts Article

This article provides new tools for the evaluation of dynamic stochastic general equilibrium (DSGE) models and applies them to a large-scale new Keynesian model. We approximate the DSGE model by a vector autoregression, and then systematically relax the implied cross-equation restrictions and document how the model fit changes. We also compare the DSGE model's impulse responses to structural shocks with those obtained after relaxing its restrictions. We find that the degree of misspecification in this large-scale DSGE model is no longer so large as to prevent its use in day-to-day policy analysis, yet is not small enough to be ignored.     

通货膨胀的宏观经济影响因素分析

本文首先利用贝叶斯向量自回归（BVAR）模型,分析了通货膨胀对宏观经济的冲击响应及其剧烈程度。然后,利用门限模型验证了通货膨胀在不同变量作为门限变量情况下的门限效应。结果表明：通货膨胀对六个因素冲击的反应程度各异,其中,对流动性过剩的反应程度最强,对股票价格、产出缺口和国际油价的反应适度,对实际有效汇率和房价的反应较弱;股票价格、汇率和国际油价具有明显的门限特征,它们分别将通货膨胀分为高低两种区制状态。以上结果有利于我们更好地认识通货膨胀的反应机制,采用合理的经济政策应对通货膨胀。     

Structural Vector Autoregressions With Nonnormal Residuals

In structural vector autoregressive (SVAR) modeling, sometimes the identifying restrictions are insufficient for a unique specification of all shocks. In this paper it is pointed out that specific distributional assumptions can help in identifying the structural shocks. In particular, a mixture of normal distributions is considered as a possible model that can be used in this context. Our model setup enables us to test restrictions which are just-identifying in a standard SVAR framework. The results are illustrated using a U.S. macro data set and a system of U.S. and European interest rates.     

Estimation of long-run inefficiency levels: a dynamic frontier approach

Cornwell, Schmidt, and Sickles (1990) and Kumbhakar (1990), among others, developed stochasticfrontier production models which allow firm specific inefficiency levels to change over time. These studies assumed arbitrary restrictions on the short-run dynamics of efficiency levels which have little theoretical justification. Further, the models are inappropriate for estimation of long-run efficiencies. We consider estimation of an alternative frontier model in which firmspecific technical inefficiency levels are autoregressive. This model is particularly useful to examine a potential dynamic link between technical innovations and production inefficiency levels. We apply our methodology to a panel of US airlines.     

Estimation of long-run inefficiency levels: a dynamic frontier approach

Cornwell, Schmidt, and Sickles (1990) and Kumbhakar (1990), among others, developed stochasticfrontier production models which allow firm specific inefficiency levels to change over time. These studies assumed arbitrary restrictions on the short-run dynamics of efficiency levels which have little theoretical justification. Further, the models are inappropriate for estimation of long-run efficiencies. We consider estimation of an alternative frontier model in which firmspecific technical inefficiency levels are autoregressive. This model is particularly useful to examine a potential dynamic link between technical innovations and production inefficiency levels. We apply our methodology to a panel of US airlines.     

Adaptive Shrinkage in Bayesian Vector Autoregressive Models

Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis. For both applications, shrinkage priors can help improving inference. In this article, we apply the Normal-Gamma shrinkage prior to the VAR with stochastic volatility case and derive its relevant conditional posterior distributions. This framework imposes a set of normally distributed priors on the autoregressive coefficients and the covariance parameters of the VAR along with Gamma priors on a set of local and global prior scaling parameters. In a second step, we modify this prior setup by introducing another layer of shrinkage with scaling parameters that push certain regions of the parameter space to zero. Two simulation exercises show that the proposed framework yields more precise estimates of model parameters and impulse response functions. In addition, a forecasting exercise applied to U.S. data shows that this prior performs well relative to other commonly used specifications in terms of point and density predictions. Finally, performing structural inference suggests that responses to monetary policy shocks appear to be reasonable.     

国际资本流动冲击有利于经济增长吗

本文估算并应用潜在产出描述经济增长,尝试从国际合作角度设定动态结构面板向量自回归模型,识别自发性国际资本流动的综合性结构冲击,并进一步分解为共同冲击和特有冲击,提出研究国际资本流动冲击对经济增长影响的计量思路,以金砖国家为例进行实证分析。研究发现：国际资本流动冲击对金砖各国经济增长的效应因资本账户开放进程而异,但对金砖整体经济增长存在正效应,且不为金砖各国之间的资本流动冲击所扰;将金砖国家视为以国际合作形式联合的整体进行计量分析是可行且有经济意义的。中国应推进包括金砖国家在内的全方位南南合作,不断完善资本账户开放条件,分散国际资本流动冲击并使其有利于长期共同发展。     

Do Flow Rates Respond Asymmetrically to Water Level? Evidence from the Edwards Aquifer

This research examines the time series relationship between the Comal Springs flow rate and the water level in the Edwards Aquifer (Well J-17). The empirical methodology utilizes threshold autoregression (TAR) and momentum-TAR models that allow for asymmetry in responses and adjustments to a disequilibrium in the long-run cointegrating relationship. Based on the results, an asymmetric error-correction model (AECM) is proposed to characterize the short-run and long-run dynamic relationship between spring flow and water level. The results have implications for the management of water resources, water demand, and ecosystems.     

对我国居民消费及其影响因素的动态分析——基于VAR模型的实证研究

我们利用1978—2006年的时间序列数据,基于宏观和动态的视角,对我国居民消费及其影响因素进行了实证分析。Johansen协整检验的结果说明我国居民消费行为与其影响因素之间存在一种长期均衡关系。向量自回归VAR模型的动态分析表明。我国居民消费对自身的冲击产生持续响应,居民消费呈现出一定程度的“惯性”特征;经济增长和人口增长对消费的短期冲击是正向的,居民消费对二者的中长期响应均为负;通货膨胀和政府支出对消费的冲击持续为负,其他因素对居民消费的短期和中长期影响各不相同,而居民消费对它们冲击的响应也呈现出不同的趋势。方差分解的结果说明,消费自身的波动是我国居民消费变异的主要原因,经济增长、贸易条件、政府支出、经常帐户余额对居民消费波动的贡献要高于其他因素的贡献。     

土地供给对通货膨胀的动态影响分析

通货膨胀是宏观经济学研究的一个热点问题,而土地供给对通货膨胀的影响又是当前非常现实的问题,特别对于中国这样的发展中国家,该问题的现实意义更为突出。利用AD-AS模型和面板VAR模型,研究土地供给对通货膨胀的动态影响,结果表明:从脉冲响应函数看,在受到土地供给冲击时,通货膨胀在同期没有发生变化,在第一年受到正的影响,但在第二年之后主要受到负的影响,并且累积响应为负;从方差分解看,土地供给对通货膨胀波动的解释程度较小。政府可以通过对土地供给的调控,使中国宏观经济处于"高增长,低膨胀"的平稳状态。     

江苏省电力消费量的影响因素及预测

为对影响江苏省电力消费量的因素进行分析,文章采用了单位根和协整分析技术,对江苏省三次产业与电力消费量之间的关系进行了实证分析,得到了有启示意义的结论;同时,还建立了VAR模型,对电力消费量进行了预测,其结果表明,该模型的精确度很高,具有较强的实用性。     

Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations

In this article, we investigate the effects of careful modeling the long-run dynamics of the volatilities of stock market returns on the conditional correlation structure. To this end, we allow the individual unconditional variances in conditional correlation generalized autoregressive conditional heteroscedasticity (CC-GARCH) models to change smoothly over time by incorporating a nonstationary component in the variance equations such as the spline-GARCH model and the time-varying (TV)-GARCH model. The variance equations combine the long-run and the short-run dynamic behavior of the volatilities. The structure of the conditional correlation matrix is assumed to be either time independent or to vary over time. We apply our model to pairs of seven daily stock returns belonging to the S&P 500 composite index and traded at the New York Stock Exchange. The results suggest that accounting for deterministic changes in the unconditional variances improves the fit of the multivariate CC-GARCH models to the data. The effect of careful specification of the variance equations on the estimated correlations is variable: in some cases rather small, in others more discernible. We also show empirically that the CC-GARCH models with time-varying unconditional variances using the TV-GARCH model outperform the other models under study in terms of out-of-sample forecasting performance. In addition, we find that portfolio volatility-timing strategies based on time-varying unconditional variances often outperform the unmodeled long-run variances strategy out-of-sample. As a by-product, we generalize news impact surfaces to the situation in which both the GARCH equations and the conditional correlations contain a deterministic component that is a function of time.     

OECD国家能源消费、经济增长与碳排放关系研究

基于面板数据模型,分析1971--2006年间28个OECD国家能源消费、经济增长和碳排放之间的关系,再根据面板数据的单位根检验和协整性检验,确定三者之间存在长期的均衡关系。通过固定影响变系数模型的估计发现：碳排放与能源消费呈显著的正相关关系,各国碳排放的能源消费弹性系数存在明显的差异;从长期看,部分国家碳排放与GDP的关系呈现倒“U”形,部分国家呈“U”形。     

Generalized linear mixed joint model for longitudinal and survival outcomes

Longitudinal studies often entail categorical outcomes as primary responses. When dropout occurs, non-ignorability is frequently accounted for through shared parameter models (SPMs). In this context, several extensions from Gaussian to non-Gaussian longitudinal processes have been proposed. In this paper, we formulate an approach for non-Gaussian longitudinal outcomes in the framework of joint models. As an extension of SPMs, based on shared latent effects, we assume that the history of the response up to current time may have an influence on the risk of dropout. This history is represented by the current, expected, value of the response. Since the time a subject spends in the study is continuous, we parametrize the dropout process through a proportional hazard model. The resulting model is referred to as Generalized Linear Mixed Joint Model (GLMJM). To estimate model parameters, we adopt a maximum likelihood approach via the EM algorithm. In this context, the maximization of the observed data log-likelihood requires numerical integration over the random effect posterior distribution, which is usually not straightforward; under the assumption of Gaussian random effects, we compare Gauss-Hermite and Pseudo-Adaptive Gaussian quadrature rules. We investigate in a simulation study the behaviour of parameter estimates in the case of Poisson and Binomial longitudinal responses, and apply the GLMJM to a benchmark dataset.     

Aliternative methods for estimating long-run responses with applications to australian import demand

This paper compares and contrasts a number of single-equation and systems estimators of long-run responses with application to a three-variable import demand model. Two variants of Box and Tiao's (1977) canonical estimator are developed and associated tests for the number of cointegrating vectors are introduced. A simulation study indicates that, while both Box-Tiao estimators have empirical distributions with fatter tails than the normal, there is evidence that the incidence of extreme values is even greater with Johansen's (1988) ML procedure.     

Aliternative methods for estimating long-run responses with applications to australian import demand

This paper compares and contrasts a number of single-equation and systems estimators of long-run responses with application to a three-variable import demand model. Two variants of Box and Tiao's (1977) canonical estimator are developed and associated tests for the number of cointegrating vectors are introduced. A simulation study indicates that, while both Box-Tiao estimators have empirical distributions with fatter tails than the normal, there is evidence that the incidence of extreme values is even greater with Johansen's (1988) ML procedure.