What is nonlinear autoregressive distributed lag model?

We consider estimation of and inference on the nonlinear autoregressive distributed lag (NARDL) model, which is a single-equation error correction model that allows for asymmetry with respect to positive and negative changes in the explanatory variable(s).

What are the difference between standard Ardl and Nardl techniques to test the cointegration relationship?

All Answers (17) Standard ARDL assumes Linearity whereas NARDL assumes non-linearity so the former permits the effects of the variables to be same. however, in case the impact of segregated components of an explanatory variable is found to be same, then NARDL model boils down to the standard symmetric ARDL model.

What is the difference between Ardl and Ardl bounds test?

The main difference between ARDL and ARDL bound test is that ARDL model is applied only when the series are stationary, integrated of the same order and are co-integrated, or with appropriate differencing when they are integrated of the same order but not co-integrated, and can not be used when the series are …

Why is Ardl used?

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.

Can I use Ardl for panel data?

The model was applied to paddy producer price at the farmer level in Java from January 2016 to December 2019 where the explanatory variable was the Farmers’ Terms of Trade. Both variables were stationary in the first-difference I (1). The results showed that the ST-ARDL model was good for T > N panel data types.

Why 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 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.