ECM tests for cointegration in a single equation framework

1992

Statistics in Transition New Series, 2014

The Engle-Granger cointegration test is highly sensitive to the choice of lag length and the poor performance of conventional lag selection criteria such as standard information criteria in selecting appropriate optimal lag length for the implementation of the Engle-Granger cointegration test is well-established in the statistical literature. Testing for cointegration within the framework of the residual-based Engle-Granger cointegration methodology is the same as testing for the stationarity of the residual series via the augmented Dickey-Fuller test which is well known to be sensitive to the choice of lag length. Given an array of candidate optimal lag lengths that may be suggested by different standard information criteria, the applied researchers are faced with the problem of deciding the best optimal lag among the candidate optimal lag lengths suggested by different standard information criteria, which are often either underestimated or overestimated. In an attempt to address t...

Mathematics and Computers in Simulation, 1995

2015

This study examines the relationships between the employment and foreign direct investment (FDI) in Malaysia. The Malaysian government continues to put efforts in attracting more FDI inflows as it seems that FDI plays a major role in the economic development of Malaysia. Besides, there is general perception that the FDI inflow contributes to increase the employment opportunity in the country. Hence, we apply an empirical analysis to study the effect of FDI on the employment in Malaysia. The data span from 1970 to 2007. Several econometric models are applied including the bounds testing (ARDL) approach, and ECM-ARDL model. The results show that there is no cointegration relationship between employment and the FDI in the long-run. However, there is a causal

This paper proposes a new Hausman-like (H) test for the null of cointegration based on the efficient estimation of a cointegration regression and the subsequent consistent estimation of a regression in differences without making specific assumptions about the short-run dynamics of the data generating process. It is shown that, asymptotically, the H statistics are distributed as a standard chi-squared and are not affected by the inclusion of deterministic components in the regression, thus offering a simple way of testing for cointegration under the null. Besides, small sample critical values for these statistics are tabulated using Monte Carlo simulation and it is shown that these "not residual-based" tests exhibit appropriate size even for quite general error dynamics and good power against non-cointegrated alternatives. In fact, simulation results suggest that they perform quite reasonably when compared to some other -residual-basedtests of the null of cointegration.

Journal of Econometrics, 2002

We show that the conventional CUSUM test for structural change can be applied to cointegrating regression residuals leading to a consistent residual-based test for the null hypothesis of cointegration. The proposed tests are semiparametric and utilize fully modiÿed residuals to correct for endogeneity and serial correlation and to scale out nuisance parameters. The limit distribution of the test is derived under both the null and the alternative hypothesis. The tests are easy to use and are found to perform quite well in a Monte Carlo experiment.

2000

In this paper critical values for the Hausman-like and Variance-ratio tests statistics of the null of coin- tegration are presented. Besides the critical values, which are tabulated using simulation, the asymptotic distribution of these tests are derived. It is also shown that these tests substain good power against the independent random walks alternative and that they may do better in

2003

Part 1. Automated model selection Contents Chapter 2. Automatic identification of simultaneous equations models 2.1. Introduction 22. Results 2.3, Algorithm 2.4. An application 2.5. Conclusions 2;A. Proofs 2.B. Matlab program Chapter 3. Automatic identification and restriction of the cointegration space 3d. Introduction 3.2. The cointegrated VAR model 3.3. Identification and restriction of (3 3.4. Monte Carlo evidence 3.5. Use of the algorithm 3.6. Conclusions 3;A. Proofs Part 2. Small sample corrections Chapter 4. Bootstrapping and Bartlett corrections in the cointegrated VAR model 4.1. Introduction 4;2. Bartlett-corrected and bootstrap tests on cointegrating coefficients 4.3. Design of the Monte Carlo experiment 4.4. Results 4.5. Conclusions Chapter 5. A Bartlett correction in stationary autoregressive models Omtzigt, Pieter (2003), Essays on Cointegration Analysis

Journal of Time Series Analysis, 2002

In this paper we introduce a new test of the null hypothesis of no cointegration between a pair of time series. For a very simple generating model, our test compares favourably with the Engle-Granger/Dickey-Fuller test and the Johansen trace test. Indeed, shortcomings of the former motivated the development of our test.

Economics Letters, 1995

Journal of Statistical and Econometric Methods, 2016

Economic analysis suggests that there is a long run relationship between variables under consideration as stipulated by theory. This means that the long run relationship properties are intact. In other words, the means and variances are constant and not depending on time. However, most empirical researches have shown that the constancy of the means and variances are not satisfied in analyzing time series variables. In the event of resolving this problem most cointegration techniques are wrongly applied, estimated, and interpreted. One of these techniques is the Autoregressive Distributed Lag (ARDL) cointegration technique or bound cointegration technique. Hence, this study reviews the issues surrounding the way cointegration techniques are applied, estimated and interpreted within the context of ARDL cointegration framework. The study shows that the adoption of the ARDL cointegration technique does not require pretests for unit roots unlike other techniques. Consequently, ARDL coint...

Journal of Econometrics, 1994

An error correction model is specified having only exact identified parameters, some of which reflect a possible departure from a cointegration model. Wald, likelihood ratio, and Lagrange multiplier statistics are derived to test for the significance of these parameters. The construction of the Wald statistic only involves linear regression, and under certain conditions the limiting distribution of the Wald statistic differs from the limiting distributions of the likelihood ratio and Lagrange multiplier statistics. A special ordering of the variables is recommended so that equal limiting distributions of the three different test statistics are obtained. The applicability of the derived testing procedures is illustrated using real demand for money, real GNP, and bond and deposit interest rates from Denmark.

Journal of Econometrics, 1997

This paper studies test procedures which can be used to determine the cointegrating rank in infinite order vector autoregressive processes. The considered tests are analogs or close versions of previous likelihood ratio tests obtained for finite-order Gaussian vector autoregressive processes, it is shown that the use of the likelihood ratio tests is justified even when the data are generated by an infinite order non-Gaussian vector autoregressive process. New tests are also developed for cases where intercept terms are included in the cointegrating relations. These tests are based on a new approach of estimating the intercept terms. They have the property that, under the null hypothesis, the same asymptotic distribution theory applies as in the case where the values of the intercept terms are a priori known and not estimated. A limited simulation study indicates that the new tests can be considerably ntore powerful than their previous counterparts. © 1997 Elsevier Science S.A.

Research Memorandum, 1998

This paper provides an extensive Monte-Carlo comparison of sev-eral contemporary cointegration tests. Apart from the familiar Gaus-sian based tests of Johansen, we also consider tests based on non-Gaussian quasi-likelihoods. Moreover, we compare the performance ...

2000

We describe the concept of cointegration, its implications in modelling and forecasting, and discuss inference procedures appropriate in integrated-cointegrated vector autoregressive processes (VARs). Particular attention is paid to the properties of VARs, to the modelling of deterministic terms, and to the determination of the number of cointegration vectors. The analysis is illustrated by empirical examples.