School of Busniess, Zhengzhou University, Henan, China. School of Economics, Quaid I Azam University Islamabad. School of Economics, University of Chakwal, Pakistan.
A plethora of literature on nexus between exchange rate volatility and trade is available in the context of Pakistan; however, the majority of studies suffer from the exigency of aggregation bias on account of using aggregated level data. To tackle the issue of aggregation bias, the current research deploys disaggregated level (commodity-wise) data to explore the effects of oscillations in the exchange rate on bilateral trade between Pakistan and its major trading partner Saudi Arabia. Employing the annual data from 1981 to 2018, ARDL bound testing approach confirms the long-run association among the modeled variables. The application of the ARDL approach reveals the following results. First, exchange rate volatility exhibits the dynamic effects on 72% of total exporting industries in the short-run, while this impact reduces to 51% of exporting industries in the long-run. Second, 56% of total importing industries demonstrate a significant response to the volatility in the short-run, while these effects expand to 73% importing industries in the long-run. Third, the current study's unique finding is that three big industries of exports function coded as 42, 66, and 75 with a share of 35%, 7% & 6%, respectively, enjoy the positive effects of the volatility in the long-run. Also, the current work suggests some appropriate policy recommendations.