Trade structure and industrial output: A disaggregated level analysis for Bangladesh

This study examines the effect of trade structure on the gross output of 10 industrial sectors in Bangladesh’s economy and focuses on analyzing it at a disaggregate level. The disaggregation is followed at a sector level, which includes all manufacturing industries for 26 years from 1995-2020. This paper explicitly focuses on five trade structure variables: (i) Intra-industry trade (IIT) (ii) Extra-trade and Intra-trade (EIT) (iii) Ratio of FDI to total trade (RFDIT) (iv) Number of trading partners (NTP), and (v) Revealed comparative advantage (RCA). By using the panel estimation technique, the study finds that IIT, RCA, and RFDIT positively influence industrial output, whereas EIT and NTP negatively influence the output levels. To better capture the Bangladesh government’s preferential trade promotion policy, the study further augments the model by adding a dummy variable called Highest Priority Sectors (HPS). Interactions between HPS and trade structure variables are made in order to investigate the varying effects of trade structure variables on Non-HPS and HPS. The findings of this study will open the path for future studies in this field as well as help policymakers and regulators to shed light on expected future policies related to trade structure and government trade policy.

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Publication Details

Journal
Asian Journal of Economic Modelling
Published
2024-12-13
DOI
https://doi.org/10.55493/5009.v12i4.5255
Primary Topic
Global trade and economics
Type
article
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article

Trade structure and industrial output: A disaggregated level analysis for Bangladesh

Nazmullah Bin Tariq
Asian Journal of Economic Modelling
Global trade and economics
article

Trade structure and industrial output: A disaggregated level analysis for Bangladesh

Nazmullah Bin Tariq
article en

Abstract

This study examines the effect of trade structure on the gross output of 10 industrial sectors in Bangladesh’s economy and focuses on analyzing it at a disaggregate level. The disaggregation is followed at a sector level, which includes all manufacturing industries for 26 years from 1995-2020. This paper explicitly focuses on five trade structure variables: (i) Intra-industry trade (IIT) (ii) Extra-trade and Intra-trade (EIT) (iii) Ratio of FDI to total trade (RFDIT) (iv) Number of trading partners (NTP), and (v) Revealed comparative advantage (RCA). By using the panel estimation technique, the study finds that IIT, RCA, and RFDIT positively influence industrial output, whereas EIT and NTP negatively influence the output levels. To better capture the Bangladesh government’s preferential trade promotion policy, the study further augments the model by adding a dummy variable called Highest Priority Sectors (HPS). Interactions between HPS and trade structure variables are made in order to investigate the varying effects of trade structure variables on Non-HPS and HPS. The findings of this study will open the path for future studies in this field as well as help policymakers and regulators to shed light on expected future policies related to trade structure and government trade policy.

Asian Journal of Economic ModellingVol. 12(4)
Chulalongkorn University (TH)
Partnerships for the goals
Openalex Percentile: Top 58%
Global trade and economics
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