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LOCAL POWER OF LIKELIHOOD RATIO TESTS FOR THE COINTEGRATING RANK OF A VAR PROCESS

VAR 过程协整秩似然比检验的局部功效

Likelihood ratio (LR) tests for the cointegrating rank of a vector autoregressive process have been developed under different assumptions regarding deterministic terms. For instance, nonzero mean terms and linear trends have been accounted for in some of the tests. In this paper we provide a general framework for deriving the local power properties of these tests. Thereby it is possible to assess the virtue of utilizing varying amounts of prior information by making…

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The Influence of VAR Dimensions on Estimator Biases

VAR 维度对估计量偏误的影响

Vector AutoRegressions (VARs) have now become the most popular tool of Time Series analysis amongst econometricians. Unfortunately, little is known about the analytic finite-sample properties of parameter estimators for such systems. The asymptotic analysis of VARs published to date does not address questions regarding the influence of the number and nature of the system's variates on parameter estimates. Clearly, both questions will have repercussions on the way VARs are…

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Some Consequences of Temporal Aggregation in Empirical Analysis

时间聚合对实证分析的若干影响

The author derives the generating mechanism of a temporally aggregated process when the disaggregated one belongs to the vector autoregressive integrated moving average class. He then studies the effects of temporal aggregation on a set of characteristics of usual interest such as exogeneity, causality, cointegration, and common features. An empirical example with Canadian interest rates illustrates the main issues.

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On The Size and Power of System Tests for Cointegration

协整系统检验的尺寸与功效

System tests for cointegration proposed by Stock and Watson (1988), Johansen (1988), and Bewley and Yang (1995) are compared using Monte Carlo experiments that include overspecification of the lag length and data-generating processes with moving average disturbances. Both AIC and SIC are used to select the lag length of the approximating vector autoregressions. The three tests considered are found to have very different characteristics, and each dominates in some portion of…

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Exogeneity, Cointegration, and Economic Policy Analysis

外生性、协整与经济政策分析

This overview examines conditions for reliable economic policy analysis based on econometric models, focusing on the econometric concepts of exogeneity, cointegration, causality, and invariance. Weak, strong, and super exogeneity are discussed in general and these concepts are then applied to the use of econometric models in policy analysis when the variables are cointegrated. Implications follow for model constancy, the Lucas critique, equation inversion, and impulse…

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Asymptotic Inference on Cointegrating Rank in Partial Systems

部分系统中协整秩的渐近推断

The likelihood ratio test for cointegrating rank is analyzed for partial (or conditional) systems in the vector autoregressive error-correction model. Under the assumption of weak exogeneity for the cointegrating parameters, the asymptotic distributions are given and tables of critical values are provided. A discussion is given of some of the assumptions of the model, why they are needed, and how they are tested.

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Short Run and Long Run Causality in Time Series: Theory

时间序列中的短期与长期因果性:理论

Causality in Granger's sense is defined in terms of predictibility one period ahead. The notion of causality is generalized by considering causality at any given horizon 1 <= h <= inifinity, providing a rigorous formalization of indirect causal effects and causality chains in (possibly) nonstationary time series. The authors derive necessary and sufficient conditions for noncausality between vectors up to any given horizon. They observe that coefficients of lagged variables…

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Fully Modified Vector Autoregressive Inference in Partially Nonstationary Models

部分非平稳模型中完全修正向量自回归的推断

The likelihood ratio (LR) test for ranks is commonly used to test for the number of cointegrating relationships among multivariate time series. The distribution of the LR test in partially nonstationary models is nonstandard and contains nuisance parameters in the presence of non-iid errors and misspecified lags. In contrast, I show that under less-restrictive assumptions on the errors, the fully modified (FM) vector autoregressive (VAR) rank test has a chi-squared…

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Structural Models of the Liquidity Effect

流动性效应的结构模型

In this paper we examine a number of recent studies that claim to have obtained a well-defined liquidity effect using structural VAR models based on broad measures of money. These studies can be distinguished in terms of the identifying restrictions, sample periods, and frequency of data used. We show that estimation of the structural coefficients of all these models can be achieved by instrumental-variable methods, where the instruments are predetermined variables and the…

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Small-sample Confidence Intervals for Impulse Response Functions

脉冲响应函数的小样本置信区间

Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend to be more accurate than delta method intervals, standard bootstrap intervals, and Monte Carlo integration intervals. This…

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A PARAMETRIC CHARACTERIZATION OF INTEGRATED VECTOR AUTOREGRESSIVE (VAR) PROCESSES

单整向量自回归过程的参数化刻画

This paper provides a polynomial factorization theorem that is then used to extend the characterization parts of the parametric representation theorems of Johansen (1992, Econometric Theory 8, 188–202) for vector autoregressive processes integrated of up to order 2. A characterization theorem is provided in the general case of an I ( d ) process. For the discussion of the complicated polynomial cointegration properties of such processes, the case of an I (3) process is…

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Impulse response and forecast error variance asymptotics in nonstationary VARs

非平稳 VAR 中脉冲响应与预测误差方差的渐近性质

Estimated impulse responses and forecast error decompositions are shown to be inconsistent at long horizons in unrestricted VARs with some unit roots. Predictions from unrestricted VARs also do not converge to the optimal predictors over long forecast horizons. In contrast, reduced rank regressions produce impulse responses and forecast error variance estimates that are consistent and predictions that are asymptotically optimal, provided the cointegrating rank is correctly…

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Business cycle analysis without much theory A look at structural VARs

少量理论约束下的商业周期分析:审视结构 VAR

This paper examines the usefulness of applying structural vector autoregressions (SVARs) to the study of business cycles. The SVAR approach aims to provide robust inferences, by imposing only weak theoretical restrictions. We illustrate that the robustness of conclusions drawn from SVAR exercises are questionable. We also examine the problem of identification failure in structural VAR models.

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Generalizing the Bayesian Vector Autoregression Approach for Regional Interindustry Employment Forecasting

推广用于区域行业间就业预测的贝叶斯向量自回归方法

The Bayesian vector autoregression (BVAR) employment-forecast approach is generalized using data for the state of Georgia. This study advances previous regional BVAR approaches by (1) incorporating regional input-output coefficients, (2) using the coefficients both to specify the prior means in one model and to weight the variances of a Minnesota-type prior in a second model, and (3) including final-demand effects and links to national and world economies. Out-of-sample…

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Empirical econometric modelling of food consumption using a new informational complexity approach

采用新信息复杂度方法的食品消费实证计量建模

This paper is concerned with empirical econometric modeling of food consumption in the USA and the Netherlands. Using autoregressive distributed lag models (ADLs) selected via the Informational Complexity (ICOMP) criterion, we study the relationship between food consumption and income. Whether food consumption obeys the homogeneity postulate is tested using information criteria. Using information-theoretic techniques, we identify the optimal information set and lag order for…

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Inference in Cointegrated VAR Systems

This note examines the asymptotic properties of the Wald statistic in vector autoregressions (VAR) that may have unit roots. Within this framework we extend the theoretical results to nonlinear restrictions. As an example we study constraints derived from linear(ized) rational expectations models focusing on the expectations hypothesis using U.S. term structure data. For such cross-equation restrictions the statistic has a nonstandard distribution because the restrictions…

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When Do Long-Run Identifying Restrictions Give Reliable Results?

长期识别限制何时能够给出可靠结果?

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…

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Miscellanea. Estimation of missing values in possible partially nonstationary vector time series

可能部分非平稳向量时间序列的缺失值估计

Ljung's (1989) method for estimating missing values and evaluating the corresponding likelihood function in scalar time series is extended to the vector case. The series is assumed to be generated by a possibly partially nonstationary and noninvertible vector autoregressive-moving average process. No particular pattern of missing data is assumed. Future and past values are special cases of missing data that can be estimated in the same way. The method does not use Kalman…

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On biases in tests of the expectations hypothesis of the term structure of interest rates

We document extreme bias and dispersion in the small-sample distributions of four standard regression-based tests of the expectations hypothesis of the term structure of interest rates. The biases arise because of the extreme persistence in short interest rates. We derive approximate analytic expressions for the biases under a simple first-order autoregressive data generating process for the short rate. We then conduct Monte Carlo experiments based on a bias-adjusted…

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