Table of Contents

## 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 technique?

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 F bounds test?**

The ARDL F bounds test is a joint test that the coefficients of the error correction terms are not all zero. The ARDL bounds t-test is a test that the coefficient on the lagged dependent variable is zero. These are two different hypotheses and therefore may give rise to different results.

### What is bound cointegration 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.

### 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). So, before applying this test, we determine the order of integration of all variables using the unit root tests. The objective is to ensure that the variables are not I(2) so as to avoid spurious results.

**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 does ARDL mean?

Autoregressive-Distributed Lag

“ARDL” stands for “Autoregressive-Distributed Lag”. Regression models of this type have been in use for decades, but in more recent times they have been shown to provide a very valuable vehicle for testing for the presence of long-run relationships between economic time-series.

#### What does Ardl mean?

**What are the advantages of ARDL model?**

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.

## What are the advantages of Ardl model?

## Why is ARDL used?

**What is the ARDL bounds test?**

The ARDL bounds test is based on the assumption that the variables are I (0) or I (1). So, before applying this test, we determine the order of integration of all variables using the unit root tests.

### How to use the auto regressive distributive lag (ARDL) bounds test?

This will therefore make us estimate our model by making use of the Auto Regressive Distributive Lag (ARDL) bounds test. To perform the bounds test, you should follow the steps below: Hold the CTRL key and click on all the variables (let your dependent variable come first). Right click and open as an equation

### How do I perform the bounds test?

To perform the bounds test, you should follow the steps below: Hold the CTRL key and click on all the variables (let your dependent variable come first). Right click and open as an equation

**How do you estimate ARDL with lower bound F statistics?**

If the value of F-statistics is less than the lower bound (I0 Bound) of the chosen level of significance, proceed to estimating ARDL at first difference. Here, you click on “Estimate” and add D in front of each of the variables [for example: D (LRGDP) D (PLR) D (SR) D (MPR)] and then click OK.