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Impact of Disaggregated External Debt on Economic Growth: Evidence from Asian Developing Economies

  • Muhammad Dawood ORCID logo , Zhao Rui Feng EMAIL logo and Muhammad Ilyas
Published/Copyright: October 10, 2024
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Abstract

This study investigate the impact of total and disaggregated external debt on economic growth, across 32 Asian developing economies (ADE) from 1995 to 2020. The study applied the generalized method of moments (GMM) and dynamic common correlated estimator (DCCE) with interaction terms of institutional quality and macroeconomic policy to address the non-linearity, across-country heterogeneity, cross-sectional dependence and endogneity. The empirical results indicate that total external debt and its types initially harm economic growth, except for commercial creditors’ debt, which has positive effects. Short-term, private, and multilateral debt show weaker negative associations compared to long-term, public, and bilateral debt. Incorporating interaction terms in non-linear models reveal a shift from negative to positive impacts, highlighting the importance of robust institutional quality and stable macroeconomic policy in mitigating adverse debt effects. Our findings underline the necessity of tailored policies accounting for specific impacts of different debt types on economic growth. Moreover, highlight the significance of institutional quality and macroeconomic policy standards to manage risks, optimize debt management practices, adjust fiscal policies, and foster sustainable economic growth. Future research should further investigate the broad impact of domestic debt in conjunction with external debt across different countries, time periods, and methodological approaches.

JEL Classification: C23; F34; F43; N35; O4

Corresponding author: Zhao Rui Feng , Management and Economics, Kunming University of Science and Technology, Kunming, 650000, China, E-mail:

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This research was supported by the Yunnan Provincial Philosophy and Social Science Innovation Team, `Learning from Tens of Millions of Countries' Construction Experience to Build a Livable, Viable, and Beautiful Countryside' (2024CX12), and the National Social Science Fund Project, `Research on Measurement and Promotion Strategy of Rural Digital Governance Efficiency in Southwest China' (23BZZ091).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix
Table A1:

Definitions, measurement, and sources.

Variables Definition and measurement units Source
Economic growth – RYPC Percentage change in real gross domestic product per head WB (2020), IMF (2020), EIU (2020)
Total debt/GDP – TDPY Comprising public and publicly guaranteed long-term debt, private non-guaranteed private debt, use of IMF credit, and short-term debt at end-period as a percentage of GDP WB (2020), IMF (2020), EIU (2020)
Short term external debt/TDPY-STDTTD Disbursed external debt owed by all sectors, having an original maturity of up to one year, including capitalized interest arrears, at the end period as a percentage of total external debt EIU (2020)
Long term external debt/TDPY-MLTDTTD Total debt has a maturity of more than one year owed to both official and commercial creditors at the end-period as a percentage of total external debt EIU (2020)
Public external debt/TDPY-GFDTTD Disbursed external debt owed by the public sector or with a public guarantee, having an original or extended maturity of more than one year, at the end-period as a percentage of total external debt EIU (2020)
Private external debt/TDPY-PFDTTD Disbursed external debt owed by the private sector with no public guarantee, having an original or extended maturity of more than one year, at the end-period as a percentage of total external debt EIU (2020)
Commercial external debt/TDPY-TPRCTD Public and private debt owed to commercial creditors as a percentage of total external debt EIU (2020)
Official external debt/TDPY-OFFCTD Medium- and long-term debt owed to official creditors at the end-period as a percentage of total external debt EIU (2020)
Bilateral external debt/TDPY-BILCTD Official medium- and long-term debt owed to foreign governments, notably Paris Club members of official creditors, at the end-period as a percentage of total external debt EIU (2020)
Multilateral external debt/TDPY-MULCTD Official medium- and long-term debt owed to multilateral institutions, excluding the IMF, at the end-period as a percentage of total external debt EIU (2020)
Investment-PFIN Gross public fixed investment expenditure at current market prices, as a percentage of GDP WB (2020), EIU (2020)
Population growth- DPOP Percentage change in mid-year population estimate over the previous year IMF (2020), EIU (2020)
Total factor productivity growth-FAPG Total factor productivity is the part of economic output growth not accounted for by the growth in inputs (labor and capital) EIU (2020)
Institutional quality-IQ The composite index of institutional quality calculated by principal component factor analysis of six governance indicators such as control of corruption, voice and accountability, political stability, government effectiveness, regulatory quality, and the rule of law By author using WGI (Oppong, Salifu Atchulo, and Fatia Oman 2023; WB 2020)
Financial development-FD Domestic credit of the private sector (share of GDP) WB (2020)
Macroeconomic policy-MEP The composite index of macroeconomic policy is calculated by principal components factor analysis of three indicators of fiscal policy (inflation rate), monetary policy (real interest rate), and trade policy (trade openness) By author using WDI
  1. Note: Sources of the data: WDI: world developing indicators; WEO: world economic outlook; EIU: economic intelligence unit; WGI: worldwide governance indicators.

Table A2:

Descriptive statistics.

Variable Obs Mean Std. dev. Min Max
RYPC 832 3.633 4.852 −20.6 22.29
TDPY 832 50.945 36.384 0.5 251.826
GFDTTD 832 64.218 36.122 0.09 764.063
PFDTTD 832 21.46 18.455 0.026 90.878
STDTTD 832 14.354 13.496 0.004 73.168
MLTDTTD 832 81.15 15.639 4.131 174.639
BILCTD 832 26.991 21.612 −0.985 90.713
MULCTD 832 22.404 19.584 0.07 87.845
OFFCTD 832 49.396 29.804 0.155 143.818
TPRCTD 832 32.76 24.719 0.01 91.865
PFIN 832 24.785 8.938 2.345 69.673
FAPG 832 1.856 3.129 −16.002 29.4
DPOP 832 1.44 1.222 −2.85 9.25
IQ 832 7.45e-09 1.601 −4.039 3.974
FD 832 40.409 35.231 1.166 182.433
MEP 832 4.33e-09 0.777 −4.042 2.098
  1. Note: Source: Author’s calculations. This table shows the descriptive statistics of the variables with mean values, standard deviation, and minimum and maximum values.

Table A3:

Matrix of correlation.

Variables RYPC TDPY GFDTTD PFDTTD STDTTD LMDTTD BILCTD MULCTD OFFCTD TRPCTD PFIN FAPG DPOP IQ FD MEP
RYPC 1.000
TDPY −0.097 1.000
GFDTTD −0.038 −0.083 1.000
PFDTTD −0.019 0.264 −0.534 1.000
STDTTD −0.008 −0.194 −0.376 0.074 1.000
LMDTTD 0.010 0.278 0.344 0.023 −0.814 1.000
BILCTD 0.083 0.031 0.466 −0.527 −0.382 0.366 1.000
MULCTD 0.066 −0.080 0.386 −0.385 −0.426 0.342 0.044 1.000
OFFCTD 0.104 −0.031 0.592 −0.635 −0.557 0.490 0.754 0.689 1.000
TRPCTD −0.105 0.216 −0.480 0.772 0.154 −0.006 −0.621 −0.587 −0.836 1.000
PFIN 0.170 −0.075 −0.050 0.099 0.201 −0.142 −0.107 −0.036 −0.101 0.084 1.000
FAPG 0.420 −0.197 0.068 −0.112 0.062 −0.021 0.035 0.104 0.093 −0.133 0.076 1.000
DPOP −0.283 0.147 0.105 −0.126 0.062 0.081 0.130 −0.036 0.070 −0.051 −0.104 −0.023 1.000
IQ −0.027 0.123 −0.233 0.177 0.267 −0.142 −0.293 −0.049 −0.245 0.269 0.359 −0.097 −0.054 1.000
FD −0.100 −0.017 −0.364 0.251 0.612 −0.408 −0.409 −0.279 −0.480 0.324 0.223 0.012 0.032 0.513 1.000
MEP 0.055 0.255 −0.115 0.099 0.089 0.002 −0.065 0.026 −0.030 0.060 0.112 0.017 0.169 0.389 0.309 1.00
  1. Note: Source: Author’s construction. This table shows the correlation of the variables.

Table A4:

Cross-sectional dependence of variables.

Variable CD-test p-value Average joint T Mean ρ Mean abs (ρ)
RYPC 33.832 0.000 26.00 0.30 0.32
TDPY 15.207 0.000 26.00 0.13 0.43
GFDTTD 33.867 0.000 26.00 0.30 0.46
PFDTTD 24.613 0.000 26.00 0.22 0.43
STDTTD 13.213 0.000 26.00 0.12 0.34
MLTDTTD 2.622 0.000 26.00 0.02 0.43
BILCTD 33.226 0.000 26.00 0.29 0.59
MULCTD 12.226 0.000 26.00 0.11 0.50
OFFCTD 41.676 0.000 26.00 0.37 0.57
TPRCTD 20.321 0.000 26.00 0.18 0.49
PFIN 10.308 0.000 26.00 0.09 0.37
FAPG 10.864 0.000 26.00 0.10 0.31
DPOP 7.644 0.000 26.00 0.07 0.47
IQ 13.939 0.000 26.00 0.12 0.42
FD 42.304 0.000 26.00 0.37 0.58
MEP 20.293 0.000 26.00 0.18 0.30
  1. Notes: Under the null hypothesis of cross-section independence, CD ∼ N(0,1)P-values close to zero indicate data are correlated across panel groups.

Table A5:

Unit root tests.

Variable Maddala and Wu (1999) panel unit root test (MW) Pesaran (2007) panel unit root test (CIPS)
Without-trend chi_sq, lags (2) With-trend chi_sq, lags (2) Decision Without-trend Zt-bar lags (2) With-trend Zt-bar lags (2) Decision
RYPC 124.119*** 133.517*** 1(0) −2.937*** −2.317*** 1(0)
TDPY 72.489* 50.978 1(1) 0.256 −4.152*** 1(1)
GFDTTD 80.241 50.722 l(1) 1.031 4.827*** l(1)
PFDTTD 74.009 65.916 l(1) −2.967*** −0.189 l(0)
STDTTD 89.939** 69.983 1(0) −3.932*** −1.169 1(0)
LMDTTD 184.321*** 190.469*** 1(0) −3.554*** −1.840** 1(0)
BILCTD 102.614*** 78.393 1(0) −1.461* 2.745 1(1)
MULCTD 55.409 67.484 l(1) −0.170 1.144 l(1)
OFFCTD 77.491 86.698** l(1) −4.161*** −1.415* l(0)
TRPCTD 74.454 67.871 l(1) −1.712** 2.251 l(1)
PFIN 155.712*** 127.377*** l(0) −3.238*** −1.899** l(0)
FAPG 87.917** 64.145 l(0) 0.199 2.161 l(1)
DPOP 203.162*** 77.577 l(0) −2.394*** 4.574*** l(0)
IQ 42.091 57.239 l(1) 0.493 −2.851*** l(1)
FD 62.226 71.788 l(1) −0.624 1.449 l(1)
MEP 124.782*** 102.668*** l(0) −0.956 −1.316* l(1)
  1. Null for MW and CIPS tests: series is I (1). MW test assumes cross-section independence. CIPS test assumes cross-section dependence is in the form of a single unobserved common factor. Multipart- uses Scott Merryman’s – xtfisher – and Piotr Lewandowski’s – pescadf. Asterisks denote statistical significance at the 10% (*), 5% (**), and 1% (***) levels. Variables are stationary at level (I (0)) if no unit root is present; if stationary at first difference (I (1)), they become stable only after differencing.

Table A6:

Linearity tests.

Statistics P-values
Ramsey’s retest 16.39 0.0000
White’s test 101.60 0.0000
  1. Note: H0: relationship is linear. Hi: the relationship is non-linear.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/snde-2024-0040).


Received: 2023-12-29
Accepted: 2024-08-19
Published Online: 2024-10-10

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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