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What is ARDL bounds testing approach?
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 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.
Why do we use 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.
When can we use ARDL?
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 a bound test?
The bounds tests suggest that the variables of interest are bound together in the long-run when foreign direct investment is the dependent variable. The associated equilibrium correction was also significant confirming the existence of long-run relationship.
Which is bounds testing method does ARDL use?
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.
Which is an advantage of the ARDL approach?
ARDL approach assumes that only a single reduced form equation relationship exists between the dependent variable and the exogenous variables (Pesaran, Smith, and Shin, 2001). The major advantage of this approach lies in its identification of the cointegrating vectors where there are multiple cointegrating vectors.
Which is ARDL model has a lag of the dependent variable?
We can see from the form of the generic ARDL model given in equation (1) above, that such models are characterised by having lags of the dependent variable, as well as lags (and perhaps the current value) of other variables, as the regressors.
Where do I get the data for ARDL?
All data are sourced from the statistical database of the Central Bank of Nigeria (CBN). Monthly data from 2004 to 2014 were extracted and analysed by building ARDL ( p, p1, p2) model. All data were transformed to log so that they have same magnitude and to improve the data analysis.