We present an application of the recent CS-ARDL methodology in the context of a country's trade balance-exchange rate relationship. The trade balance is expected to deteriorate first before improving in response to currency depreciation and vice versa, widely known as the J-curve effect satisfying the Marshal-Learner condition in the long run. Combining bilateral and aggregate analysis in one setting by constructing specific panel data with one reference country, we find that aggregate analysis is sensitive to our allowance for heterogeneity. Estimates using the aggregate time-series data show evidence favouring the J-curve relation whereas, the aggregate analysis resulting from the panel time-series data shows that currency appreciation improves trade balance in Bangladesh in the long run, which goes against the Marshall-Lerner condition. With the reference of existing commodity level literature, we argue that this atypical scenario lines with the realities of a 'small' economy like Bangladesh, where her exporters attempt to maintain their market share with some government support. The study provides essential policy suggestions by identifying the significant contributors to Bangladesh's trade balance-exchange rate relationship: China, Japan, and Singapore.
Bibliographical noteFunding Information:
We would like to express our gratitude to the Bureau of Economic Research, University of Dhaka, Bangladesh, for funding the study. We are grateful to the anonymous referees and the associate editor for their valuable comments on an earlier version of the paper.
© 2021, The Author(s).
- ECON Macroeconomics
- exchange rates
- Trade Balance
- Cross-sectionally augmented Non-linear ARDL
- Panel time series
- Common Correlated Effects
- Aggregation bias