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- 单位根与协整:单位根检验、协整、误差修正与长期关系。
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日期精度:到日 142 篇 · 到月 1051 篇 · 到年 30 篇
Cointegration and Government Borrowing Constraints: Evidence for the United States
Testable implications are derived in a present-value borrowing-constraint model for the U.S. federal government. Critical values for unit-root and cointegration tests are calculated with Monte Carlo studies. Cointegration techniques are employed to determine whether the government has been involved in perpetual debt financing in recent years. The data reject this assertion.
Asymptotic Distributions of Unit-Root Tests When the Process Is Nearly Stationary
Several test criteria are available for testing the hypothesis that the autoregressive polynomial of an autoregressive moving average process has a single unit root. Schwert (1989), using a Monte Carlo study, investigated the performance of some of the available test criteria. He concluded that the actual levels of the test criteria considered in his study are far from the specified levels when the moving average polynomial also has a root close to 1. This article studies…
The effect of parameter uncertainty on forecast variances and confidence intervals for unit root and trend stationary time‐series models
参数不确定性对单位根与趋势平稳模型预测方差和置信区间的影响
Abstract In this paper I describe the effect of parameter uncertainty on the way conditional forecast variances grow as the forecast horizon increases. Without parameter uncertainty, forecast variances for the unit root model grow linearly with the forecast horizon while with the trend stationary model they are bounded. With parameter uncertainty, however, I find that for both the unit root and the trend stationary models, forecast variances grow with the square of the…
An interpolation test for a unit root in the presence of drift
This paper considers tests of the null hypothesis of a unit root in an observed time series against the alternative that the series is level stationary. Interpolation tests whose critical values depend upon the value of the drift parameter are compared to the standard Dickey-Fuller tests in Monte Carlo simulations. The interpolation test performs quite well especially against one-sided alternatives.
Some Lagrange multiplier tests for seasonal differencing
季节差分的若干拉格朗日乘子检验
Determining whether a time series has a unit root is an important problem in many time series analyses. For seasonal time series the problem is more complicated as one has to decide whether both regular and seasonal differencing or just one of them would suffice to transform a series into stationarity. This important problem is addressed via the Lagrange multiplier test approach. The large sample representations of the test statistics in terms of integrals of Wiener…
Inference for Near-Integrated Time Series with Infinite Variance
无限方差近单位根时间序列的统计推断
An autoregressive time series is said to be near-integrated (nearly nonstationary) if some of its characteristic roots are close to the unit circle. Statistical inference for the least squares estimators of near-integrated AR(1) models has been under rigorous study recently both in the statistics and econometric literatures. Although classical asymptotics are no longer available, through the study of weak convergence of stochastic processes, one can establish the asymptotic…
Limiting power of unit-root tests in time-series regression
Testing Causality in an Autoregression with Cointegrated Regressors
Testing for a Moving Average Unit Root
移动平均单位根检验
Testing for a unit root in the moving average model is discussed. First, for the stationary MA(1) model, we suggest a score type test which is locally best invariant and unbiased. Performance of the test for finite samples is compared with the most powerful test. The asymptotic behavior of the test is also considered by computing the limiting power under a sequence of local alternatives. We then extend the model to an infinite order MA and suggest a test for this extended…
A Comparison of the Forecasting Ability of ECM and VAR Models
The results of forecasting experiments based on an error correction mechanism (ECM) model and various types of vector autoregressive (VAR) and Bayesian vector autoregressive (BVAR) models are presented. A Bayesian error correction mechanism (BECM) model is also tested. This model represents a hybrid of the BVAR and ECM models. The results from experiments using fifty industries and monthly Ohio labor market data demonstrate that the ECM model produces forecasts with much…
The Demand for Money in Argentina 1978–1987: Before and After the Austral Program
阿根廷 1978—1987 年货币需求:奥斯特拉尔计划前后
In this study, a monthly money-demand function for Argentina is estimated for a period that ends one month before the austral program (May 1985). The performance of the traditional econometric approach is compared with the new cointegration approach to time series econometrics. The comparison is carried out by a postsample forecast of the demand for money for a period of two years after the stabilization (until July 1987). The cointegration approach is found superior to the…
The Demand for Money in Argentina 1978-1987: Before and after the Austral Program
阿根廷1978—1987年的货币需求:奥斯特拉尔计划前后
In this study, a monthly money-demand function for Argentina is estimated for a period that ends one month before the austral program (May 1985). The performance of the traditional econometric approach is compared with the new cointegration approach to time series econometrics. The comparison is carried out by a postsample forecast of the demand for money for a period of two years after the stabilization (until July 1987). The cointegration approach is found superior to the…
Cointegration in a macroeconomic system
宏观经济系统中的协整
Abstract This paper investigates the long‐run relationships within a set of six quarterly time‐series on the Austrian economy by means of cointegration. After analysing the univariate properties, especially with respect to the appropriate seasonal filter, the maximum‐likelihood method proposed by Johansen (1988) is applied to estimate and test the cointegrating relationships. We found three such relations, implying that the system is driven by three independent stochastic…
Seasonal integration and cointegration
Testing for a Unit Root in a Time Series With a Changing Mean
均值发生变化的时间序列单位根检验
This study considers testing for a unit root in a time series characterized by a structural change in its mean level. My approach follows the “intervention analysis” of Box and Tiao (1975) in the sense that I consider the change as being exogenous and as occurring at a known date. Standard unit-root tests are shown to be biased toward nonrejection of the hypothesis of a unit root when the full sample is used. Since tests using split sample regressions usually have low power,…
Unit-Root Tests and the Statistical Pitfalls of Seasonal Adjustment: The Case of U.S. Postwar Real Gross National Product
单位根检验与季节调整的统计陷阱:美国战后实际国民生产总值的案例
Unit-root tests applied to the postwar seasonally adjusted quarterly gross national product series strongly support the null hypothesis of the presence of a unit root in the data-generating process. Evidence reported here with seasonally unadjusted data is far less conclusive. It is explained why seasonal-adjustment procedures may alter the outcome of conventional tests.
'Testing for a unit root In the presence of moving average errors'
The Fractional Unit Root Distribution
分数单位根分布
Asymptotic distributions are derived for the ordinary least squares estimate of a first order autoregression model when the series is fractionally integrated. The fractional unit root distribution is introduced to describe the limiting distribution. The unit root distribution is shown to be an atypical member of this family because its density is nonzero over the entire real line. For -1/2 Copyright 1990 by The Econometric Society.
Time Series Regression With a Unit Root and Infinite-Variance Errors
具有单位根和无限方差误差的时间序列回归
In [4] Chan and Tran give the limit theory for the least-squares coefficient in a random walk with i.i.d. (identically and independently distributed) errors that are in the domain of attraction of a stable law. This paper discusses their results and provides generalizations to the case of I (1) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. General unit root tests are also studied. It is shown that the…
A General Approach to the Limiting Distribution for Estimators in Time Series Regression with Nonstable Autoregressive Errors
非稳定自回归误差下时间序列回归估计量极限分布的一般方法
The authors consider the time series regression model where the error term follows a nonstable autoregressive process and present a general approach for delivering the limiting distribution of a normalized estimator for the autoregressive parameter. The present approach is quite straightforward and leads them to an accurate evaluation of the distribution function, unlike the other approaches suggested in the literature. The authors' methodology is illustrated and percent…
Asymptotic Properties of Residual Based Tests for Cointegration
基于残差的协整检验的渐近性质
This paper develops an asymptotic theory for residual based tests for cointegration. These tests involve procedures that are designed to detect the presence of a unit root in the residuals of (cointegrating) regressions among the levels of economic time series. Attention is given to the augmented Dickey-Fuller (ADF) test that is recommended by Engle-Granger (1987) and the Z(a) and Z(t) unit root tests recently proposed by Phillips (1987). Two new tests are also introduced,…
Inference in Linear Time Series Models with some Unit Roots
含部分单位根的线性时间序列模型中的推断
This paper considers estimation and hypothesis testing in linear time series when some or all of the variables have (possibly multiple) unit roots. The motivating example is a vector autoregression with some unit roots in the companion matrix, which might include polynomials in time as regressors. Parameters that can be written as coefficients on mean zero, nonintegrated regressors have jointly normal asymptotic distribution, converging at the rate of T(superscript…
Statistical Inference in Instrumental Variables Regression with I(1) Processes
This paper studies the asymptotic properties of instrumental variable (IV) estimates of multivariate cointegrating regressions and allows for deterministic and stochastic regressors as well as quite general deterministic processes in the data-generating mechanism. It is found that IV regressions are consistent even when the instruments are stochastically independent of the regressors. This phenomenon, which contrasts with traditional theory for stationary time series, is a…