scholarly journals A Residual-Based Cointegration Test for Near Unit Root Variables

2007 ◽  
Vol 2007 (907) ◽  
pp. 1-31 ◽  
Author(s):  
Erik Hjalmarsson ◽  
◽  
Pär Österholm
Keyword(s):  
Unit Root ◽  
Cointegration Test ◽  
Near Unit Root

scholarly journals ANALISIS HUBUNGAN PENDAPATAN WISATAWAN DAN HARGA PARIWISATA TERHADAP PERMINTAAN PARIWISATA DENGAN VECM

2016 ◽  
Vol 5 (2) ◽  
pp. 44
Author(s):  
MERARY SIANIPAR ◽  
NI LUH PUTU SUCIPTAWATI ◽  
KOMANG DHARMAWAN
Keyword(s):  
Unit Root ◽  
Unit Root Test ◽  
Cointegration Test ◽  
Tourism Demand ◽  
Long Run ◽  
Negative Effect ◽  
Short Run ◽  
The Relationship ◽  
Positive Effect

Tourism demand is focused on estimating variables which influence tourist visit. The tourism demand that we discuss on this research is the tourism demand to Bali of the major tourism-generating country was Australia. The aim of this research is to analyze the relationship between tourist income and tourism price to tourism demand using VECM. VECM requires that the variables in the model must be stationary and fulfilled a cointegration condition. In order to make it valid, the stationarity of variables in the model have to be checked using ADF unit root test. In additon, cointegration between these variables are examined using Johansen’s cointegration test. The results of ADF unit root test show that indicated the tourist income, the tourism price and the tourism demand for Australia data are stationary in first lag or I(1). Cointegration test shows that all variables are cointegrated, i.e. have a long-run relationship. In the long-run, the tourist income and tourism price give positive effect to the tourism demand. This means, the increase of tourist income and tourism price will contribute to the increase in tourism demand. In addition, in the short-run, the tourist income and the tourism price give negative effect to the tourism demand. This means, the increase of tourist income and tourism price will contribute to the decrease in tourism demand.

scholarly journals EXPLOITING INFINITE VARIANCE THROUGH DUMMY VARIABLES IN NONSTATIONARY AUTOREGRESSIONS

2013 ◽  
Vol 29 (6) ◽  
pp. 1162-1195 ◽  
Author(s):  
Giuseppe Cavaliere ◽  
Iliyan Georgiev
Keyword(s):  
Unit Root ◽  
Asymptotic Properties ◽  
Ordinary Least Squares ◽  
Infinite Variance ◽  
Local Power ◽  
Test Statistic ◽  
Asymptotically Normal ◽  
Normal Test ◽  
Order Of Magnitude ◽  
Near Unit Root

We consider estimation and testing in finite-order autoregressive models with a (near) unit root and infinite-variance innovations. We study the asymptotic properties of estimators obtained by dummying out “large” innovations, i.e., those exceeding a given threshold. These estimators reflect the common practice of dealing with large residuals by including impulse dummies in the estimated regression. Iterative versions of the dummy-variable estimator are also discussed. We provide conditions on the preliminary parameter estimator and on the threshold that ensure that (i) the dummy-based estimator is consistent at higher rates than the ordinary least squares estimator, (ii) an asymptotically normal test statistic for the unit root hypothesis can be derived, and (iii) order of magnitude gains of local power are obtained.

scholarly journals On the Distribution of the Nearly Unstable AR(1) Process with Heavy Tails

2010 ◽  
Vol 42 (01) ◽  
pp. 106-136 ◽  
Author(s):  
Mariana Olvera-Cravioto
Keyword(s):  
Real Line ◽  
Uniform Approximation ◽  
Unit Root ◽  
Heavy Tails ◽  
Gaussian Approximation ◽  
Heavy Tail ◽  
Tail Asymptotics ◽  
Precise Description ◽  
Entire Real Line ◽  
Near Unit Root

We consider a nearly unstable, or near unit root, AR(1) process with regularly varying innovations. Two different approximations for the stationary distribution of such processes exist: a Gaussian approximation arising from the nearly unstable nature of the process and a heavy-tail approximation related to the tail asymptotics of the innovations. We combine these two approximations to obtain a new uniform approximation that is valid on the entire real line. As a corollary, we obtain a precise description of the regions where each of the Gaussian and heavy-tail approximations should be used.

Cointegration between stock market indices: the case of the slovak and czech stock price indices

1999 ◽  
Vol 8 (1) ◽  
Author(s):  
Dawit Alemu Bemerew
Keyword(s):  
Stock Market ◽  
Unit Root ◽  
Stock Price ◽  
Empirical Investigation ◽  
Slovak Republic ◽  
Empirical Work ◽  
Policy Coordination ◽  
Unit Root Tests ◽  
Cointegration Test

This paper provides an empirical investigation of long-term relationship between the stock market indices of the Czech and Slovak Republic. The empirical work applies log of weekly average data on the Czech PX - 50 and the Slovak SAX from September 1995 to December 1997. Empirical investigation is conducted by means of unit root tests and the EngleGranger methodology of cointegration test. The result from the unit root tests shows that individual stock indices are nonstationary - I(1). The result from the cointegration test shows that there is no long-term relationship between the two indices, even though, the strong economic ties and policy coordination between the two republics seem to be in favor of some cointegration.

Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances

2014 ◽  
Vol 35 (5) ◽  
pp. 751-781 ◽  
Author(s):  
Matei Demetrescu ◽  
Christoph Hanck
Keyword(s):  
Unit Root ◽  
Robust Inference ◽  
Time Varying ◽  
Near Unit Root

Weak convergence in the near unit root setting

2013 ◽  
Vol 83 (5) ◽  
pp. 1411-1415
Author(s):  
N. Bailey ◽  
L. Giraitis
Keyword(s):  
Weak Convergence ◽  
Unit Root ◽  
Near Unit Root

Asymptotic Distributions of the Least-Squares Estimators and Test Statistics in the Near Unit Root Model with Non-Zero Initial Value and Local Drift and Trend

1994 ◽  
Vol 10 (5) ◽  
pp. 937-966 ◽  
Author(s):  
Seiji Nabeya ◽  
Bent E. Sørensen
Keyword(s):  
Characteristic Function ◽  
Asymptotic Distribution ◽  
Unit Root ◽  
Stochastic Integral ◽  
Integral Representations ◽  
Characteristic Functions ◽  
General Interest ◽  
Initial Value ◽  
Stochastic Integral Representations ◽  
Near Unit Root

This paper considers the distribution of the Dickey-Fuller test in a model with non-zero initial value and drift and trend. We show how stochastic integral representations for the limiting distribution can be derived either from the local to unity approach with local drift and trend or from the continuous record asymptotic results of Sørensen [29]. We also show how the stochastic integral representations can be utilized as the basis for finding the corresponding characteristic functions via the Fredholm approach of Nabeya and Tanaka [16,17], This “link” between those two approaches may be of general interest. We further tabulate the asymptotic distribution by inverting the characteristic function. Using the same methods, we also find the characteristic function for the asymptotic distribution for the Schmidt-Phillips [26] unit root test. Our results show very clearly the dependence of the various tests on the initial value of the time series.

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