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.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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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).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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 |
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Note: Sources of the data: WDI: world developing indicators; WEO: world economic outlook; EIU: economic intelligence unit; WGI: worldwide governance indicators.
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 |
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Note: Source: Author’s calculations. This table shows the descriptive statistics of the variables with mean values, standard deviation, and minimum and maximum values.
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 |
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Note: Source: Author’s construction. This table shows the correlation of the variables.
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 |
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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.
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) |
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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.
Linearity tests.
Statistics | P-values |
---|---|
Ramsey’s retest 16.39 | 0.0000 |
White’s test 101.60 | 0.0000 |
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Note: H0: relationship is linear. Hi: the relationship is non-linear.
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