The economy of Pakistan has been facing instability and downward trends due to several factors, such as rising foreign debt and goods and services prices. The regression and ARDL models are applied by using R software. Adding lag values of variables become necessary to measure the long-run relationship. Using an ARDL model with GDP as response variable, inflation rate and debt service as explanatory variables, it is found that GDP has significant negative relationship with lagged values of GDP at t-2, t-4, inflation rate at t-2, and debt service. The multiple linear regression explains 24.5% of the variation, whereas the ARDL fits well and explains 82.9% of the variation. Utilizing Bayesian analysis with ABC-MCMC provides more precise estimates of model parameters than the ARDL model, as evidence by smaller posterior standard deviations compared to ARDL standard deviations. This approach yields a comprehensive posterior distribution of unknown parameters, encompassing both point estimates and credible intervals. In light of this, it can be inferred that Pakistan's GDP growth from 2000 to 2021 has been impeded by escalating rates of debt service and inflation rate. It is recommended that the government and policymakers prioritize sustainable economic growth, implement measures to manage inflation, and effectively address the issue of debt burden.
Iqbal et al. (Fri,) studied this question.