Showing papers on "Cointegration published in 1987"
TL;DR: The authors used a long-run restriction implied by a large class of real-business-cycle models -identifying permanent productivity shocks as shocks to the common stochastic trend in output, consumption, and investment -to provide new evidence on this question.
Abstract: Are business cycles mainly the result of permanent shocks to productivity? This paper uses a long-run restriction implied by a large class of real-business-cycle models -identifying permanent productivity shocks as shocks to the common stochastic trend in output, consumption, and investment -to provide new evidence on this question. Econometric tests indicate that this common-stochastic-trend / cointegration implication is consistent with postwar U.S. data. However, in systems with nominal variables, the estimates of this common stochastic trend indicate that permanent productivity shocks typically explain less than half of the business-cycle variability in output, consumption, and investment. (JEL E32, C32) A central, surprising, and controversial result of some current research on real business cycles is the claim that a common stochastic trend-the cumulative effect of permanent shocks to productivity-underlies the bulk of economic fluctuations. If confirmed, this finding would imply that many other forces have been relatively unimportant over historical business cycles, including the monetary and fiscal policy shocks stressed in traditional macroeconomic analysis. This paper shows that the hypothesis of a common stochastic productivity trend has a set of econometric implications that allows us to test for its presence, measure its importance, and extract estimates of its realized value. Applying these procedures to consumption, investment, and output for the postwar United States, we find results that both support and contradict this claim in the real-businesscycle literature. The U.S. data are consistent with the presence of a common
1,437 citations
TL;DR: This paper found that the fundamental variables are integrated of different orders and there is a lack of cointegration between the exchange rate variables in the monetary model and relative prices, which indicated that it is not worthwhile to forecast from the pure monetary model.
243 citations
01 Sep 1987
TL;DR: This paper showed that the initial empirical suppor t enjoyed by the models was an illusion created by the failure to a count for exchange-rate nonstationarity and the arbitrary imposition of dynamic restrictions.
Abstract: Many explanations have been advanced for the apparent breakdown of monetary exchange-rate model s in the late 1970s. This paper shows that the initial empirical supp ort enjoyed by the models was an illusion created by the failure to a ccount for exchange-rate nonstationarity and the arbitrary imposition of dynamic restrictions. Furthermore, estimation of a more general, dynamic specification and cointegration tests both lead to rejection of a central proposition of the monetary approach, the long-run propo rtionality of the exchange rate to relative money supplies. Copyright 1987 by Royal Economic Society.
79 citations
TL;DR: In this article, the application of Granger-causality tests to macroeconomic time series frequently necessitates filtering the data to induce stationarity, and a common application is illustrated.
70 citations
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40 citations
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TL;DR: In this paper, the concept of near-integrated vector random processes is introduced and a limit theory for the sample moments of such time series is developed using weak convergence and is shown to involve a simple functionals of a vector diffusion.
Abstract: The concept of a near-integrated vector random process is introduced. Such processes help us to work towards a general asymptotic theory of regression for multiple time series in which some series may be integrated processes of the ARIMA type, others may be stable ARMA processes with near unit roots, and yet others may be mildly explosive. A limit theory for the sample moments of such time series is developed using weak convergence and is shown to involve a simple functionals of a vector diffusion. The results suggest finite sample approximations which in the stationary case correspond to conventional central limit theory. The theory is applied to the study of vector autoregressions and cointegrating regressions of the type recently advanced by Granger and Engle (1987). A noncentral limiting distribution theory is derived for some recently proposed multivariate unit root tests. This yields some interesting insights into the asymptotic power properties of the various tests. Models with drift and near integration are also studied. The asymptotic theory in this case helps to bridge the gap between the nonnormal asymptotics obtained by Phillips and Durlauf (1986) for regressions with integrated regressors and the normal asymptotics that usually apply in regressions with deterministic regressors.
15 citations
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13 citations
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TL;DR: In this article, the authors study cointegrated systems of multiple time series which are individually well described as integrated processes (with or without a drift) and give necessary and sufficient conditions for cointegration.
Abstract: This paper studies cointegrated systems of multiple time series which are individually well described as integrated processes (with or without a drift). Necessary and sufficient conditions for cointegration are given. These conditions form the basis for a new class of statistical procedures designed to test for cointegration. The new procedures rely on principal components methods. They are simple to employ and they involve only the standard normal distribution. Monte Carlo simulations reported in the paper indicate that the new procedures provide simple and apparently rather powerful diagnostics for the detection of cointegration. Some empirical applications to macroeconomic data are conducted.