Effect of Trade Surplus on External Debt in Developing Countries: Evidence from General-to-Specific Model

This paper examines the impact of trade openness towards external debt levels in low- and middle-income countries from 1980-2021. Using panel estimation of Fixed Effects (FE) and the General-to-Specific (GETS), the researchers segregated into Model 1 and Model 2, which Model 2 purposely to identify the interaction of international reserves as a potential medium to relate the impact of trade openness and external debt. The finding suggests that independent variables such as GDP growth rate, current account balance, and trade openness are highly significant variables that influence the external debt in the 50 LMICs. The researchers also found a robust interaction between trade openness and international reserves in determining external debt. The result confirms that the positive direct relationship of trade openness increases its coefficient from 0.10% to 0.14% after incorporating the interaction of international reserves in Model 2. The statistical evidence suggests that the inverse interactions of international reserves on trade openness significantly negatively affect external debt. Moreover, the result prevails, continuing to be positive and highly significant. Hence, the researchers can relate that an inverse impact of trade openness on international reserves has negatively affected external debt.

Authors

Institutions

Publication Details

Journal
Gadjah Mada International Journal of Business
Published
2025-12-31
DOI
https://doi.org/10.22146/gamaijb.v28i1.18970
Primary Topic
Fiscal Policies and Political Economy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of Trade Surplus on External Debt in Developing Countries: Evidence from General-to-Specific Model

Taufik Abd Hakim, Abdul Aziz Karia
Gadjah Mada International Journal of Business
Fiscal Policies and Political Economy
article

Effect of Trade Surplus on External Debt in Developing Countries: Evidence from General-to-Specific Model

Taufik Abd Hakim, Abdul Aziz Karia
article en

Abstract

This paper examines the impact of trade openness towards external debt levels in low- and middle-income countries from 1980-2021. Using panel estimation of Fixed Effects (FE) and the General-to-Specific (GETS), the researchers segregated into Model 1 and Model 2, which Model 2 purposely to identify the interaction of international reserves as a potential medium to relate the impact of trade openness and external debt. The finding suggests that independent variables such as GDP growth rate, current account balance, and trade openness are highly significant variables that influence the external debt in the 50 LMICs. The researchers also found a robust interaction between trade openness and international reserves in determining external debt. The result confirms that the positive direct relationship of trade openness increases its coefficient from 0.10% to 0.14% after incorporating the interaction of international reserves in Model 2. The statistical evidence suggests that the inverse interactions of international reserves on trade openness significantly negatively affect external debt. Moreover, the result prevails, continuing to be positive and highly significant. Hence, the researchers can relate that an inverse impact of trade openness on international reserves has negatively affected external debt.

Gadjah Mada International Journal of BusinessVol. 28(1)
Universiti Teknologi MARA (MY)
Partnerships for the goals
Openalex Percentile: Top 16%
Fiscal Policies and Political Economy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.