ARDL Bounds Test
The first step in the ARDL approach is to estimate Equation (2) using ordinary least
square (OLS). The F-test has a non-standard distribution which depends upon (i) whether
variables included in the ARDL model are I(0) or I( l ),(,i i) the number of regressors, and
(iii) whether the ARDL model contains an intercept and a trend. Critical values are
reported by Pesaran and Pesaran (1997) and Pesaran et al. (2001). However, these critical
values are generated for sample sizes of 500 and 1000 observations and 20,000 and
40,000 replications, respectively. Given the relatively small sample size in our study (36
observations), therefore we used of calculated critical values by Narayan(2004) using
small sample size between 30 and 80 observations.
If the computed F-statistics lies above the upper level of the band, the null is rejected,
indicating cointegration. If the computed F-statistics lies below the lower level band, the
null cannot be rejected, supporting the absence of cointegration. If the statistics fall
within the band, inference would be inconclusive.
The result of ARDL Bounds test (Table 5 shows that test statistic falls below the lower
critical value so the null hypothesis no long-run relationship cannot be rejected, therefore
there is not long-run relationship between FDI and GDP in Malaysia