Cointegration and error correction: representation
01 Jan 1987-Vol. 55, Iss: 2, pp 251-276
About: The article was published on 1987-01-01 and is currently open access. It has received 3983 citations till now. The article focuses on the topics: Representation (systemics) & Error correction model.
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TL;DR: This article examined the use of autoregressive distributed lag (ARDL) models for the analysis of long-run relations when the underlying variables are I(1) and I(0) regressors.
Abstract: This paper examines the use of autoregressive distributed lag (ARDL) models for the analysis of long-run relations when the underlying variables are I(1). It shows that after appropriate augmentation of the order of the ARDL model, the OLS estimators of the short-run parameters are p T -consistent with the asymptotically singular covariance matrix, and the ARDL-based estimators of the long-run coe¢cients are super-consistent, and valid inferences on the long-run parameters can be made using standard normal asymptotic theory. The paper also examines the relationship between the ARDL procedure and the fully modi
ed OLS approach of Phillips and Hansen to estimation of cointegrating relations, and compares the small sample performance of these two approaches via Monte Carlo experiments. These results provide strong evidence in favour of a rehabilitation of the traditional ARDL approach to time series econometric modelling. The ARDL approach has the additional advantage of yielding consistent estimates of the long-run coe¢cients that are asymptotically normal irrespective of whether the underlying regressors are I(1) or I(0). JEL Classi
cations: C12, C13, C15, C22. Key Words: Autoregressive distributed lag model, Cointegration, I(1) and I(0) regressors, Model selection, Monte Carlo simulation. ¤This is a revised version of a paper presented at the Symposium at the Centennial of Ragnar Frisch, The Norwegian Academy of Science and Letters, Oslo, March 3-5, 1995. We are grateful to Peter Boswijk, Clive Granger, Alberto Holly, Kyung So Im, Brendan McCabe, Steve Satchell, Richard Smith, Ron Smith and an anonymous referee for helpful comments. Partial
nancial support from the ESRC (Grant No. R000233608) and the Isaac Newton Trust of Trinity College, Cambridge is gratefully acknowledged.
4,711 citations
TL;DR: This article proposed new error correction-based cointegration tests for panel data, which have good small-sample properties with small size distortions and high power relative to other popular residual-based panel coIntegration tests.
Abstract: This paper proposes new error correction-based cointegration tests for panel data. The limiting distributions of the tests are derived and critical values provided. Our simulation results suggest that the tests have good small-sample properties with small size distortions and high power relative to other popular residual-based panel cointegration tests. In our empirical application, we present evidence suggesting that international healthcare expenditures and GDP are cointegrated once the possibility of an invalid common factor restriction has been accounted for.
3,136 citations
TL;DR: In this paper, the authors examined the role of tourism in the Spanish long-run economic development and confirmed the tourism-led growth hypothesis through cointegration and causality testing.
Abstract: This paper examines the role of tourism in the Spanish long-run economic development. The tourism-led growth hypothesis is confirmed through cointegration and causality testing. The results indicate that, at least, during the last three decades, economic growth in Spain has been sensible to persistent expansion of international tourism. The increase of this activity has produced multiplier effects over time. External competitivity has also been proved in the model to be a fundamental variable for Spanish economic growth. From the empirical analysis it can be inferred the positive effects on income that government policy, in the adequacy of supply as well as in the promotion of tourist activity, may bring about.
1,225 citations
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TL;DR: A survey of advances in this area since the publication of Hodrick's (1987) survey is presented in this paper, with a focus on the relationship between uncovered interest parity and real interest parity.
Abstract: Forward exchange rate unbiasedness is rejected in tests from the current floating exchange rate era. This paper surveys advances in this area since the publication of Hodrick's (1987) survey. It documents that the change in the future exchange rate is generally negatively related to the forward discount. Properties of the expected forward forecast error are reviewed. Issues such as the relation of uncovered interest parity to real interest parity, and the implications of uncovered interest parity for cointegration of various quantities are discussed. The modeling and testing for risk premiums is surveyed. Included in this area are tests of the consumption CAPM, tests of the latent variable model, and portfolio-balance models of risk premiums. General equilibrium models of the risk premium are examined and their empirical implications explored. The survey does not cover the important areas of learning and peso problems, tests of rational expectations based on survey data, or the models of irrational expectations and speculative bubbles.
1,137 citations
TL;DR: The authors fit nonlinearly mean-reverting models to real dollar exchange rates over the post-Bretton Woods period, consistent with a theoretical literature on transactions costs in international arbitrage.
Abstract: We fit nonlinearly mean-reverting models to real dollar exchange rates over the post-Bretton Woods period, consistent with a theoretical literature on transactions costs in international arbitrage. The half lives of real exchange rate shocks, calculated through Monte Carlo integration, imply faster adjustment speeds than hitherto recorded. Monte Carlo simulations reconcile our results with the large empirical literature on unit roots in real exchange rates by showing that when the real exchange rate is nonlinearly mean reverting, standard univariate unit root tests have low power, while multivariate tests have much higher power to reject a false null hypothesis.
1,122 citations