Open AccessPosted Content
Common Trends and Common Cycles
Reads0
Chats0
TLDR
The existence of a serial correlation common feature among the first differences of a set of I(1) variables implies the existence of common cycle in the Beveridge-Nelson-Stock-Watson decomposition of those variables as mentioned in this paper.Abstract:
The existence of a serial correlation common feature among the first differences of a set of I(1) variables implies the existence of a common cycle in the Beveridge-Nelson-Stock-Watson decomposition of those variables. A test for the existence of common cycles among cointegrated variables is developed. The test is used to examine the validity of the common trend-common cycle structure implied by Flavin's excess sensitivity hypothesis and Campbell and Mankiw's mixture of rational expectations and rule-of-thumb hypothesis for consumption and income. Linear independence between the cointegration and the cofeature vectors is exploited to decompose consumption and income into their trend and cycle components. Copyright 1993 by John Wiley & Sons, Ltd.read more
Citations
More filters
Journal ArticleDOI
The econometrics of financial markets
TL;DR: The authors provides a survey of the work that has been done in financial econometrics in the past decade, establishing a set of stylized facts that are characteristics of financial series and then detailing the range of techniques that have been developed to model series which possess these characteristics.
ReportDOI
Testing for Common Features
Robert F. Engle,Sharon Kozicki +1 more
TL;DR: In this paper, the authors introduce a class of statistical tests for the hypothesis that some feature that is present in each of several variables is common to them, which are data properties such as serial correlation, trends, seasonality, heteroscedasticity, auto-regression, and excess kurtosis.
Journal ArticleDOI
A Measure of Comovement for Economic Variables: Theory and Empirics
TL;DR: In this article, a measure of dynamic comovement between (possibly many) time series and names it cohesion is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations.
Journal ArticleDOI
Some Consequences of Temporal Aggregation in Empirical Analysis
TL;DR: In this paper, the authors derive the generating mechanism of a temporally aggregated process when the disaggregated one belongs to the vector autoregressive integrated moving average class, and study the effects of temporal aggregation on a set of characteristics of usual interest such as exogeneity, causality, cointegration, and common features.
Journal ArticleDOI
7. The Econometric Modelling of Financial Time Series
Andrew T. Walden,T. C. Mills +1 more
TL;DR: The third edition of the Terence Mills' best-selling graduate textbook as mentioned in this paper contains a wealth of material reflecting the developments of the last decade, with particular attention paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series.
References
More filters
Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: 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.
Journal ArticleDOI
Statistical analysis of cointegration vectors
TL;DR: In this paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
Book
An Introduction to Multivariate Statistical Analysis
TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
Book
Elements of econometrics
TL;DR: The emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus, and Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases.
Journal ArticleDOI
Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence
TL;DR: In this article, the authors show that no variable apart from current consumption should be of any value in predicting future consumption, except real disposable income, which has no predictive power for consumption, but rejected for an index of stock prices.