What is ARDL bounds testing approach to cointegration?
ARDL bounds testing approach is a cointegration method developed by Pesaran et al. ( 2001) to test presence of the long run relationship between the variables. This procedure, relatively new method, has many advantages over the classical cointegration tests.
What is the ARDL model?
An autoregressive distributed lag (ARDL) model is an ordinary least square (OLS) based model which is applicable for both non-stationary time series as well as for times series with mixed order of integration.
What are the advantages of using ARDL methods in time series data?
One of the advantages of ARDL test is that it is more robust and performs better for small sample size of data which suitable for this research. The sample size is 43 years for each country. The annual time series data of saving and investment ratio as percentage of GDP in each country were utilized in this study.
Why do we use ARDL bound test?
The ARDL bounds test is based on the assumption that the variables are I(0) or I(1). The objective is to ensure that the variables are not I(2) so as to avoid spurious results. In the presence of variables integrated of order two, we cannot interpret the values of F statistics provided by Pesaran (2001).
What is the purpose of ARDL?
The ARDL / EC model is useful for forecasting and to disentangle long-run relationships from short-run dynamics. Long-run relationship: Some time series are bound together due to equilibrium forces even though the individual time series might move considerably.
What is ARDL cointegration?
The ARDL cointegration technique is used in determining the long run relationship between series with different order of integration (Pesaran and Shin, 1999, and Pesaran et al. 2001). The reparameterized result gives the short-run dynamics and long run relationship of the considered variables.
What is bound cointegration test?
An augmented autoregressive distributed lag (ARDL) bounds test for cointegration involves an extra F-test on the lagged levels of the independent variable(s) in the ARDL equation. The augmented ARDL bounds test is demonstrated using an empirical study on government taxation and expenditures.
Are there parametric single-equation cointegration estimators for ADL models?
This paper deals with a family of parametric, single-equation cointegration estimators that arise in the context of the autoregressive distributed lag (ADL) models. We particularly focus on a… Expand We present a new Stata package for the estimation of autoregressive distributed lag (ARDL) models in a time-series context.
Is there an autoregressive distributed lag modelling approach to cointegration analysis?
An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Introduction Econometric analysis of long-run relations has been the focus of much theoretical and empirical research in economics. In cases in which the variables in the long-run relation of interest are trend-stationary, the general practice has been to de-trend
What is ARDL Bounds Testing?
What is ARDL Bounds Testing 1. ARDL bounds testing approach is a cointegration method developed by Pesaran et al. (2001) to test presence of the long run relationship between the variables. This procedure, relatively new method, has many advantages over the classical cointegration tests.
What does ARDL stand for?
Autoregressive distributed lag (ARDL) models are often used to analyse dynamic relationships with time series data in a single-equation framework. The current value of the dependent variable is…