The impact of external debt on total factor productivity and growth in HIPCs: non-linear regression approaches

Abstract

Purpose

The purpose of this study is to provide an empirical analysis of the impact of external debt on total factor productivity (TFP) and growth along with the TFP channel through which external debt affects the growth of heavily indebted poor countries (HIPCs).

Design/methodology/approach

This study uses panel data econometrics; basically, the seemingly unrelated regression (SUR) and alternative non-linear (panel threshold) models. For robustness check, it also uses panel-corrected standard errors, feasible generalized least squares and SUR (using alternative variables).

Findings

External debt significantly reduces both TFP and growth. Besides, it confirms that the relationship between external debt and TFP and gross domestic product growth is non-linear. Further external debt can affect the growth of HIPCs through the TFP channel. However, the threshold model result reveals weak evidence of threshold values although there are some threshold values of 67 and 54 for TFP and growth models, respectively.

Originality/value

To the best of the authors’ knowledge, this is the first study on most concerned countries (HIPCs) that shows a detailed and complete analysis of the TFP channel and the impact of external debt on growth. Thus, it provides appropriate and sound policies that consider the unique characteristics of the countries. Unlike most previous findings, this study does not support an inverted U-shape relationship between external debt and growth. Further, it provides insights into the relationships among TFP, external debt and growth. Moreover, it considers basic panel econometric tests like cross-sectional dependence, uses a non-linear simultaneous equations model along with the alternative non-linear model and is supported by different robustness checks.

Citation

Beyene, S.D. and Kotosz, B. (2022), "The impact of external debt on total factor productivity and growth in HIPCs: non-linear regression approaches", International Journal of Development Issues, Vol. 21 No. 2, pp. 173-194. https://doi.org/10.1108/IJDI-07-2021-0145