*5.4. Co-Integration Tests*

The presence of cointegration among the series was tested by employing the bound test approach. Accordingly, the results presented in Table 5 show that the computed *F*-statistic (7.105) was greater than the *F*-critical value at 1%, 5%, and 10%, respectively. Consequently, the result supported the rejection of the null hypothesis, which indicated the existence of a long-run relationship between the variables. This implies that there is cointegration among the series in the model. The existence of cointegration among the series aids in analyzing the short-run and long-run relationship of the factors that affected the growth of horticulture exports in the country.

**Table 5.** ARDL bounds test results for Cointegration.


Note: \*\*\* is the significance level at 1%.

Using AIC, SIC, and Hannan-Quinn information criteria, ARDL (2, 2, 2, 0, 1, 0, 0, 2) was revealed as the best model for the series. The Breusch-Godfrey Serial Correlation LM Test results presented in Table 6 show that there were no problems of serial autocorrelation. In addition, the diagnostic test for heteroscedasticity also showed the absence of such problem (Table 7). This indicates that the model was good enough for the study of cointegration among the variables.



**Table 7.** Heteroskedasticity Test: Breusch-Pagan-Godfrey.

