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Unit-Root Tests and Asymmetric Adjustment With an Example Using the Term Structure of Interest Rates

单位根检验与非对称调整:利率期限结构示例

This article develops critical values to test the null hypothesis of a unit root against the alternative of stationarity with asymmetric adjustment. Specific attention is paid to threshold and momentum threshold autoregressive processes. The standard Dickey–Fuller tests emerge as a special case. Within a reasonable range of adjustment parameters, the power of the new tests is shown to be greater than that of the corresponding Dickey–Fuller test. The use of the tests is…

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Modelling Nonlinear Relationships between Extended-Memory Variables

扩展记忆变量之间非线性关系的建模

A definition of extended memory is provided, generalizing the ideas of long memory and persistence, based on the properties of forecasts over long horizons. Specification of nonlinear models with variables having extended memory is considered in terms of the balance of an equation and it is suggested that many more types of misspecification can occur than with usual situations and could produce important specification errors. Tests of linearity and standard methods of…

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Using the correlation exponent to decide whether an economic series is chaotic

利用相关指数判断经济序列是否具有混沌

We consider two ways of distinguishing deterministic time-series from stochastic white noise; the Grassberger-Procaccia correlation exponent test and the Brock, Dechert, Scheinkman (or BDS) test. Using simulated data to test the power of these tests, the correlation exponent test can distinguish white noise from chaos. It cannot distinguish white noise from chaos mixed with a small amount of white noise. With i.i.d. as the null, the BDS correctly rejects the null when the…

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Investigation of production, sales and inventory relationships using multicointegration and non-symmetric error correction models

利用多重协整与非对称误差修正模型研究生产、销售和库存关系

The accumulated sum of a stationary series is called integrated. If a linear combination of some of the integrated series is stationary, it is said to be cointegrated. This paper presents empirical results on inventories to consider the possibility of a deeper form of cointegration called multicointegration, which is introduced in Granger and Lee (1989). A vector integrated series is multicointegrated if the accumulated sum of its stationary (cointegrated) linear combination…

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Implications of Aggregation with Common Factors

含共同因子的聚合所产生的含义

Many observed macrovariables are simple aggregates over a large number of microunits. It is pointed out that the generating process of the macrovariables is largely determined by the common factors in the generating mechanisms of the microvariables, even though these factors may be very unimportant at the microlevel. It follows that macrorelationships are simpler than the complete microrelationships, but that empirical investigations of microrelationships may not catch those…

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Co-Integration and Error Correction: Representation, Estimation, and Testing

协整与误差修正:表示、估计与检验

The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples. If each element of a vector of time series x first achieves stationarity after differencing, but a linear combination a'x is already stationary, the time series x are said to be co-integrated with co-integrating vector a. There may be several such co-integrating vectors so that a…

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Semiparametric Estimates of the Relation between Weather and Electricity Sales

天气与售电量关系的半参数估计

A nonlinear relationship between electricity sales and temperature is estimated using a semiparametric regression procedure that easily allows linear transformations of the data. This accommodates introduction of covariates, timing adjustments due to the actual billing schedules, and serial correlation. The procedure is an extension of smoothing splines with the smoothness parameter estimated from minimization of the generalized cross-validation criterion introduced by…

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[Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts]: Comment

不同技术的预测准确性:美国宏观经济预测比较——Granger 评论

C. W. J. Granger, [Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts]: Comment, Journal of Business & Economic Statistics, Vol. 4, No. 1 (Jan., 1986), pp. 16-17

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Advertising and Aggregate Consumption: An Analysis of Causality

广告与总消费:Granger 因果关系分析

This paper is concerned with testing for causation, using the Granger definition, in a bivariate time-series context. It is argued that a sound and natural approach to such tests must rely primarily on the out-of-sample forecasting performance of models relating the original (non-prewhitened) series of interest. A specific technique of this sort is presented and employed to investigate the relation between aggregate advertising and aggregate consumption spending. The null…

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Investigating Causal Relations by Econometric Models and Cross-spectral Methods

There occurs on some occasions a difficulty in deciding the direction of causality between two related variables and also whether or not feedback is occurring. Testable definitions of causality and feedback are proposed and illustrated by use of simple two-variable models. The important problem of apparent instantaneous causality is discussed and it is suggested that the problem often arises due to slowness in recording information or because a sufficiently wide class of…

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The Typical Spectral Shape of an Economic Variable

In recent years, a number of power spectra have been estimated from economic data and the majority have been found to be of a similar shape. A number of implications of this shape are discussed, particular attention being paid to the reality of business cycles, stability and control problems, and model building.

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A Quick Test for Serial Correlation Suitable for Use with Non-Stationary Time Series

适用于非平稳时间序列的快速序列相关检验

Goodman's simplified runs test is examined as a test for serial correlation and is found to be both much quicker to apply than other available tests and to be appropriate for use with non-stationary data provided that the series has no trend in mean. Approximations to the power of the test are discussed and it is found that the power is acceptable for samples of size 100 or more. Particular consideration is given to the application of the test to economic data.

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A Quick Test for Serial Correlation Suitable for Use with Non-Stationary Time Series

适用于非平稳时间序列的快速序列相关检验

Goodman's simplified runs test is examined as a test for serial correlation and is found to be both much quicker to apply than other available tests and to be appropriate for use with non-stationary data provided that the series has no trend in mean. Approximations to the power of the test are discussed and it is found that the power is acceptable for samples of size 100 or more. Particular consideration is given to the application of the test to economic data.

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