




































 
 

 

59 
© 2020 by the authors; licensee Asian Online Journal Publishing Group 
 

Economy 
Vol. 7, No. 1, 59-68, 2020 

ISSN(E) 2313-8181/ ISSN(P) 2518-0118 
DOI: 10.20448/journal.502.2020.71.59.68 

© 2020 by the authors; licensee Asian Online Journal Publishing Group 

    
 

 
 
 
An Analysis of the Relationship among Economic Growth, External Debt and 
Exports in India (1970-2018) 

 
Smita Nath   

 

 
 
Associate Professor in Economics, Scottish Church College (affiliated to the University of Calcutta), Kolkata, 
India. 

 

 
Abstract 

This paper attempts to examine the relationship among debt servicing, exports and GDP for 
India during 1970 – 2018 using co-integration test, error correction model and Granger causality 
test. In the bi-variate model with constant trend specification GDP and exports seem to have no 
long-term relationship. However, change in GDP Granger causes change in exports. For the 
restricted constant trend specification, in the short run, GDP affects exports positively and 
significantly. GDP and debt services seem to have a positive and significant long-term 
relationship in the bivariate model. The tri-variate model including GDP, Exports and debt 
service reveals a long term relationship among the variables where both exports and debt services 
affect GDP positively and significantly. GDP, exports and debt stocks do not have any long term 
relationship with constant trend specification, but change in GDP is found to Granger cause 
change in exports. For the restricted constant trend specification, however, there seems to be a 
long term relationship among them. In the short run GDP affects exports positively and 
significantly. In general, results indicate a positive and significant impact of GDP on exports. A 
significant positive long run impact of external debt on economic growth is also observed when 
debt service is the indicator of external debt. The short run impacts of external debt in terms of 
both debt servicing and debt stocks, however, produce diverse and insignificant results. 

 
Keywords: External debt, Economic growth, Exports, Co-integration, Granger-causality. 

JEL Classification: F34; 047. 
 

Citation | Smita Nath (2020). An Analysis of the Relationship 
among Economic Growth, External Debt and Exports in India 
(1970-2018). Economy, 7(1): 59-68. 
History:  
Received: 26 March 2020 
Revised: 28 April 2020 
Accepted: 4 June 2020 
Published: 2 July 2020 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Funding: This study received no specific financial support. 
Competing Interests: The author declares that there are no conflicts of 
interests regarding the publication of this paper. 
Transparency: The author confirms that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.   

 

 

Contents 
1. Introduction ...................................................................................................................................................................................... 60 
2. A Brief Survey of the Literature ................................................................................................................................................... 60 
3. Data and Methodology ................................................................................................................................................................... 62 
4. Trends in GDP, Exports and Various indicators of External Debt in India ....................................................................... 62 
5. Relationship among External Debt, Exports and Economic Growth ................................................................................... 63 
6. Concluding Remarks ....................................................................................................................................................................... 66 
References .............................................................................................................................................................................................. 67 
 

 
 

 

 

 

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Contribution of this paper to the literature 
This study contributes to exiting literature by examining the relationship among debt servicing, exports 
and GDP for India during 1970 – 2018 using co-integration test, error correction model and Granger 
causality test. 

 
1. Introduction 

The role of external debt on the economic development of a country is one of the widely discussed topics 
among the academicians and policy-makers. Essentially, foreign borrowing has an important contribution in the 
process of economic development of developing countries. It can promote growth by increasing investment and 
transfer of technology. Developing countries often borrow from the international capital market when they suffer 
from deficits in the current account. But sometimes the burden of foreign borrowing itself hampers the economic 
development of a country. This happens when foreign borrowing is not productively used by a country, and so, the 
debts go on increasing without a corresponding increase in the ability to service it.1  

Naturally, a strand of literature on external debt is developed where the authors seek to study the relationship 
between external debt and economic growth of countries. However, the studies on impact of external debt on 
economic growth of countries provide mixed results. Some studies show positive impact of external debt on 
economic growth while others show negative impact. A number of studies note that the impact is dependent upon 
the threshold level of debt of a country whereas some studies reveal no significant impact of debt.2    

A borrowing country faces an adverse situation due to the presence of external debt when it is unable to raise 
the amount to be repaid through its own resource raising methods and/or unable to find foreign exchange required 
to make payments.3 Different proposals are suggested in the literature. However, it is argued that since external 
debt has to be repaid in terms of foreign currency, debtor countries should opt for raising foreign exchange 
reserves. In this regard the importance of exports for a debtor country is emphasized as export performance 
primarily determines the debt servicing capacity of a country.4   

Again, it is believed that exports can affect economic growth which is embodied in the idea of export-led 
growth (ELG). The arguments in favour of this, as explained by the literature,5 are the following. First, exports 
can be considered as an instrument of technology transfer and through this productivity increases for an exporter 
country, and so, economic growth is enhanced. Second, since more foreign exchanges are available through 
exports, a country can import necessary capital goods for production which affects growth positively. Third, 
exports determine the debt servicing capacity of a borrowing country. Therefore, when export performance of a 
country is better, more external debts, and so, more resources for investment would be available. Economic growth 
can be improved then. Fourth, when exports are higher, demand for the country’s product will be higher and 
output will be higher. Finally, it is observed that countries with better export performance usually show better 
growth performance.    

Gabriele (2006) described the development of ELG hypothesis starting with Adam Smith and David Ricardo. 
The arguments given by the economists till modern time in favour of this theory are explained. As noted by the 
author a huge number of empirical studies are done to examine the validity of the hypothesis; but the results are 
mixed. Further, an opposite causality from economic growth to exports is also observed, which is mentioned as the 
growth-led export (GLE) hypothesis. The argument given in favour of GLE hypothesis is that economic growth 
leads to improvement in human capital and technology. This is followed by productivity increase and reduction in 
cost of production. Exports would increase for the country then.6 

There is another strand of literature that suggests that the role of debt servicing is to be incorporated in the 
analysis of relationship between exports and economic growth since export revenues are used to finance debt 
repayment of a borrowing country.7 It can be opined that in the external debt economic growth relationship also 
the role of exports is important because export performance determines debt servicing capacity of a country. The 
relationship between external debt and economic growth is examined for India by a number of authors and some 
studies focus on the relationship between exports and economic growth for India.8 However, the relationship 
among Economic growth, exports and debt servicing in India is not explored. 

The objective of the present study is to examine the relationship among economic growth, external debt and 
exports for the Indian economy. For the study period 1970-2018 we attempt to examine the relationship among 
GDP, exports and debt servicing considering all in real terms. 

The rest of the paper is organized as follows. Section II presents a brief survey of the literature.  Data and 
methodology are given in Section III. Section IV reveals the scenario of Indian economy regarding GDP, exports 
and various indicators of external debt during the study period. The analysis of the relationship among the 
variables is presented in Section V. Some concluding remarks are made in Section VI. 
 

2. A Brief Survey of the Literature 
There are both theoretical and empirical studies on the relationship between external debt and economic 

growth. But since our analysis is empirical in nature we review the empirical studies here.9  

                                                           
1 Mahmood, Arby, and Sherazi (2014) explained the debt situation of the SAARC countries by the vicious circle where a large fiscal deficit leads to large 
amount of external debt which requires large amount of debt servicing causing less domestic investment and economic growth leading to low resource 
mobilization and further expansion of fiscal deficit. 
2 For a survey of the studies see Abdelaziz, Rim, and Majdi (2019). 
3 See Woo and Nasution (1989). 
4 See for example Borensztein and Ghosh (1989); Chaudhary, Anwar, and Tahir (2000); Dhonte (1979); Diwan (1990);   Goel (1989); Hemmer (1990); Parai and 
Mohanty (1985)  etc. 
5 See for example Ajmi, Aye, Balcilar, and Gupta (2015). 
6 A list of empirical studies, comprising both cross section and time series analysis, done in the 1970s, 1980s and 1990s is available in Bahmani-Oskooee and 
Economidou (2009) where data, method used, variables included and findings are mentioned in each case. Ajmi et al. (2015)  also provided a survey of empirical 
works on ELG and GLE hypotheses. 
7 See for example Ahmed, Butt, Alam, and Kazmi (2000). 
8 See the next Section for examples of such studies. 
9 For examples of theoretical works see Otani and Villanueva (1989); Bhandari, Haque, and Turnovsky (1990) and Rodríguez-Arana and Zumaya (2012). 



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Siddiqui and Malik (2001) examined the debt growth relationship for South-Asian countries. The results 
indicate that the impact of foreign debt on economic growth is positive and significant. Considering panel data for 
sixty countries over the period 1969-98 (Pattillo, Poirson, Ricci, Kraay, & Rigobon, 2003) noted that when debt is 
higher than the threshold level its impact on economic growth is significantly negative; but, when debt is lower 
than the threshold level the impact is usually positive but insignificant.  

Dinneya (2006) addressed another aspect of the debt-growth relationship by exploring the roles of power 
change, quality of governance, political environment, and overall level of democratization etc. on this in the context 
of Nigerian economy.  Cordella, Ricci, and Ruiz-Arranz (2010)  examined how investment and growth are affected 
by the level of indebtedness of countries. Their study reveals that for highly indebted countries or for countries 
with low quality of policies and institutions investment does not seem to be affected by indebtedness whereas for 
less indebted countries or for countries with high quality of policies and institutions there is a negative relationship 
between them. Similar results are obtained between economic growth and debt of countries.  

Hwang, Chung, and Wang (2010) found a two-way causality between financial development and economic 
growth for twenty Asian and Latin American countries during the period 1982-2004; it is also revealed that 
excessive debt hinders financial sector development and thus lower economic growth. Reinhart and Rogoff (2010)  
showed that for the advanced countries no relationship between GDP growth and debt/GDP ratio is established 
unless the debt/GDP ratios exceed the threshold levels (90%) over the period 1946-2009. For the emerging 
countries also similar results are noted for the period 1970-2009. Butts, Mitchell, and Berkoh (2012) found a 
positive and significant long run relationship between short term external debt and economic growth of Thailand 
during 1970-2003 and a short run change in GDP Granger causes short term debt. Bal and Rath (2014)  from their 
study noted that central government debt, total factor productivity and debt services affected growth of the Indian 
economy in the short run during 1980-2011; in the long run also a relationship between economic growth and 
public debt is observed. 

Ciftçioğlu and Sokhanvar (2018) for twelve Central and Eastern European countries for 1995-2014 noted that 
for eight out of twelve countries studied there is unidirectional causation from external debt to economic growth. 
Kharusi and Ada (2018) noted a significant and negative impact of debt-GDP ratio on growth rate of GDP for the 
period 1990-2015 in Oman. Using ordinary least squares method Saxena and Shanker (2018)  found a negative 
impact of external debt on India’s economic growth during 1990-91 – 2015-16. Abdelaziz et al. (2019) examined 
the impact of debt on investment and growth separately for twelve less indebted and eleven highly indebted 
countries using SUR method. For the split models as well as for the entire sample the results indicate a negative 
impact of external debt on investment and growth.  

Now we focus on the empirical studies that examine the ELG and GLE hypotheses. Gyimah-Brempong (1991) 
examined the relationship between export instability and economic growth of the Sub-Saharan countries using 
cross-section data during the period 1960-86. For various indices of export instability a negative relationship is 
found between the variables. Kugler (1991) studying on six countries viz., France, Japan, Switzerland, UK, USA 
and West Germany for the period 1970-87 noted support in favour of export-led growth for France and West 
Germany only.Ghatak and Price (1997) examined the ELG hypothesis for India during the period 1960-1992 
incorporating various types of exports. It is found that at the aggregate level ELG hypothesis is not supported; but 
at the disaggregate level for non-traditional exports ELG hypothesis is supported whereas for traditional exports it 
is not supported. El-Sakka and Al-Mutairi (2000) examined the relationship for the Arab countries during the 
period 1970-99. The results indicate no long term relationship between exports and economic growth for any of 
the countries. In the short run countries show mixed results. 

Chandra (2003) examined ELG hypothesis for the Indian economy using terms of trade as a third variable in 
the period 1950-1996. It finds a long run relationship among the variables and a bi-directional causation between 
exports and GDP. Thus the study supports both ELG and GLE hypotheses. Gabriele (2006) noted a significant 
relationship between growth rate of GDP and growth rate of service exports in the period 1980-2000 in a study 
covering one hundred and fourteen developing countries. Kaushik and Klein (2008) found a long term relationship 
among export growth, export instability, investment and economic growth in case of India during 1971-2005 and a 
unidirectional Granger causality running from real exports to real GDP. 

Using human development as a third variable Afzal, Rehman, and Rehman (2009) noted support of GLE 
hypothesis in Pakistan for the period 1970-71 – 2008-09. Bahmani-Oskooee and Economidou (2009) studied the 
long run relationship among GDP, stock of capital and labour, export and import for sixty two developing 
countries during the period 1960-99 and note that the results are country specific. In a multi-variable model 
Sulaiman and Saad (2009) observed a positive relationship between exports and economic growth of Malaysia for 
the period 1960-2005. Guru-Gharana (2012)  used superior Granger causality test for the Indian economy and the 
results indicate support of ELG hypothesis for the period 1971-2008. The panel data analysis conducted by 
Ndoricimpa (2014) for seventeen COMESA countries during 1980-2011 showed support of ELG hypothesis for 
two countries and support of GLE hypothesis for two countries. It is also noted that ELG is not supported for the 
countries which export primary product.   

Sannassee, Seetanath, and Jugessur (2014) conducted a meta-analysis to find the reason behind mixed results 
among different empirical works. The study comprising eighty two studies with four hundred and forty seven 
observations notes that the impact of exports on growth is less for the countries with low development level. Ajmi 
et al. (2015)   studied the relationship for South African countries during 1911-2011. For linear Granger causality 
test no relationship is found. For non-linear Granger causality test using Hiemstra and Jones Test a unidirectional 
causation is found from GDP to Exports; again using Diks and Panchenko Test bi-directional causation is noted. 
Bastola and Sapkota (2015) working on Nepal for the period 1965-2011 found that in the short as well as long run 
exports affect GDP. Saleem and Sial (2015)  from their study on Pakistan find evidence of support of both ELG and 
GLE hypotheses during 1973-2013. Berasaluce and Romero (2017) found no causal relation of exports and FDI on 
GDP for the Korean economy during 1980-2015. 

The following studies examine relationship among economic growth, external debt and exports of countries. 
Ahmed et al. (2000) examined the causality between growth rates of economic growth and exports for each of eight 



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Asian countries over the period 1970-1997. It is found that export-led growth hypothesis is supported by their 
study but when growth rate of debt servicing is included in the model the results are not uniform for the countries. 
For the period 1970-71 – 2007-08 Afzal et al. (2009) studied the relationship among economic growth, external 
debt servicing and exports in Pakistan. Their study indicates unidirectional causalities running from GDP to 
exports and from debt servicing to GDP.  The study made by Saad (2012)  for Lebanon over the period 1970-2010  
indicates a bi-directional causality between economic growth and external debt servicing, a unidirectional causality 
running from exports to economic growth and a unidirectional causality running from external debt servicing to 
exports. Dritsaki (2013) observed that in the short run there is a unidirectional causation from exports to economic 
growth and from economic growth to external debt for Greece during the period 1960-2011 and there is no 
causation from exports to external debt. In the long run also external debt depends upon economic growth. 
 

3. Data and Methodology 
We consider four regression models. Models 1 and 2 are bi-variate models whereas models 3 and 4 are tri-

variate models. Model 1 studies the relationship between GDP and exports, model 2 examines the relationship 
between GDP and debt service. The relationship among GDP, exports and debt service is analyzed in model 3; 
model 4 explains the relationship among GDP, exports and debt stocks.  

Data on the four variables GDP, exports,  debt service and debt stocks for the period 1970 – 2018 are collected 
from World Bank’s World Development Indicators 2019. Data on GDP and exports at 2010 US dollars are 
available from World Bank. Since data on debt service and debt stocks are available at current US dollars, those are 
converted into 2010 US dollars using GDP deflators. 

First, logarithm of each variable is taken and then unit root test is conducted to determine the order of 
integration of each variable using augmented Dickey-Fuller (ADF) test and Philips-Perron (PP) Test where 
optimum lag length is determined by Hannan-Quinn information criterion (HQIC), Schwartz Bayesian information 
criterion (SBIC) and Akaike information criterion (AIC).  When the variables in a model are found to be stationary 
at first difference Johansen methodology is used to examine whether the variables are co-integrated i.e., to check 
whether there exists a long run relationship between the variables.  

For the cases where the variables are found to be co-integrated an error correction model (ECM) is applied to 
analyse the short run relationship between them. For the cases where the variables are not found to be co-
integrated a vector autoregressive (VAR) model in first difference is used and Granger causality test is done. Soft 
ware stata has been used for the econometric computations. 
 

4. Trends in GDP, Exports and Various indicators of External Debt in India 
Figure 1 reveals the condition of the Indian economy in terms of real GDP, real exports, debt service and total 

debt stocks during 1970 – 2018. Figure 2 and 3 show the observations made on various ratios used as debt 
indicators. 
 

 
Figure-1: Trends in GDP, Exports, Debt Stocks and External Debt Service (constant 2010 US$). 

 

 
India’s debt service as a percentage of GNI remain more or less same during this period; it is around 2 per cent. 

The ratio of debt service to exports was 15 per cent in 1975 and in 2018 it was 11 per cent of that. Not only that in 
some years this were very high as evident from Figure 2. Debt stocks as percentage of GNI does not show much 
fluctuations, it increases from 14 in 1970 to 19 in 2018. Debt-reserve ratio is also considered as an indicator of 
external debt. In terms of that also much fluctuation is observed during this period. Mahmood et al. (2014) also 
pointed out that according to the traditional criteria India was within threshold levels of external debt. 
 



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Figure-2. Trends in debt service ratios (%). 

 

 
Figure-3. Trends in debt stocks-GNI ratio and reserves-debt ratio 
(%). 
 

 

5. Relationship among External Debt, Exports and Economic Growth 
We first determine the order of integration of each variable considered in our study. Figures 4(a) – 1(h) 

indicate that each variable in non-stationary at level whereas stationary at first difference.  
 

 
Figure-4(a). lgdp. 

 
Figure-4(b). First Difference in lgdp. 

 
Figure-4(c). lexpotrs. Figure-4(d). First Difference in lexports. 

 
Figure-4(e). ldebetservice. Figure-4(f). First difference in ldebtservice. 

Figure-4(g). ldebtstocks. Figure-4(h). First difference in ldebtstocks. 

 



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Conducting Augmented Dickey-Fuller (ADF) Test and Philips-Perron (PP) Test from Table 1 we note that all 
the variables are in fact non-stationary at level but stationary at first difference,10 where optimum lag lengths are 
determined by Hannan-Quinn information criterion (HQIC), Schwartz Bayesian information criterion (SBIC) and 
Akaike information criterion (AIC).11  

 
Table-1. Unit root test results. 

Model Variable ADF Statistic (1% critical 
value) 

PP Statistic (1% critical value) 

Intercept lgdp 3.234 (-3.607) 4.138 (-3.594) 
 dlgdp -6.478 (-3.600) -6.478 (-3.600) 
    
 lexports 0.310 (-3.600) 0.588 (-3.594) 
 dlexports -5.693 (-3.600) -5.693 (-3.600) 
    
 ldebtservice -.974 (-3.607) -0.324 (-3.594) 
 dldebtservice -5.569 (-4.187) -10.320 (-3.600) 
    
 ldebtstocks -0.527 (-3.607) -0.201 (-3.594) 
 dldebtstocks -3.440 (-3.607)* -4.847 (-3.600) 
    
Intercept and Trend lgdp -1.649  (-4.187) -2.398 (-4.168) 
 dlgdp -8.211 (-4.178) -8.211(-4.178) 

    
 lexports -1.598 (-4.178) -1.684(-4.168) 
 dlexports -5.681 (-4.178) -5.681 (-4.178) 
    
 ldebtservice -2.302 (-4.187) -4.199 (-4.168) 
 dldebtservice -5.469 (-3.607) -10.176 (-4.178) 
    
 ldebtstocks -2.231 (-4.187) -1.792 (-4.168) 
 dldebtstocks -3.393 (-4.187) -4.794 (-4.178) 
 

      Note: *5% critical value is  -2.94       

 
5.1. Relationship between GDP and Exports 
Model 1:   lgdpt = α0 + α1lexportst + errort 
Where lgdp and lexports are logarithm of GDP and exports respectively. 

Table 2 presents the results of cointegration test between lgdp and lexports with constant trend specification.  
 

Table-2. Johansen tests for cointegration between lgdp and lexports  (Trend: constant). 

Maximum rank Trace statistic 5% critical value 

0 12.5812* 15.41 
1 1.9534 3.76 
2   

 
Since, Trace statistic = 12.5812 < 15.41 = critical value, we fail to reject the null hypothesis of no cointegration 

between the variables which indicates that lgdp and lexports are not cointegrated, that is, there is no long term 
relationship between them. The Granger causality test results following VAR in first differences of the variables 
(dlgdp and dlexports)  are shown in Table 3.  
 

Table-3. Granger causality Wald tests for dlgdp and dlexports. 

Null hypothesis Chi2 df Prob > chi2 

dlexports does not Granger-cause dlgdp 1.1046 2 0.576 
dlgdp does not Granger-cause dlexports 6.5669 2 0.037 

 
When we have the null hypothesis H0: dlexports does not Granger cause dlgdp, the p-value (0.576) is more 

than any pre-assigned level of significance, and so, we fail to reject the null hypothesis and conclude that dlexports 
does not Granger cause dlgdp. That is, the results indicate that dlexports will not be helpful for forecasting dlgdp. 
On the other hand, when the null hypothesis is dlgdp does not Granger cause dlexports, the p-value (0.3) is less 
than 5 per cent, and so, we reject the null hypothesis and conclude that dlgdp Granger causes dlexports. That is, 
the results indicate that dlgdp will be helpful for forecasting dlexports. 

Table 4 presents the results of cointegration test between lgdp and lexports with restricted constant trend 
specification.  

 
Table-4. Johansen tests for cointegration between lgdp and lexports (Trend: restricted constant). 

Maximum rank Trace statistic 5% critical value 

0 33.3854 19.96 
1 3.1104* 9.42 
2   

                                                           
10 For ldebtservice there is a contradiction because it is found to be stationary at level according to PP test but non-stationary at level according to ADF test. 
 
11 Tests are conducted for all lag lengths determined by different criteria and the results are same. However, the test statistics reported in Table 1 are those for 
the AIC criterion when SBIC, HQIC and AIC suggest different lag lengths.    



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It is observed that the null hypothesis H0: r = 0 (no cointegration) is rejected, whereas we fail to reject H0: r ≤ 

1. So, for restricted constant trend specification lgdp and lexports have a long term relationship. The estimated 
error correction model (ECM) for these cointegrated variables gives the following long run and short run 
relationships between the variables. The figures within brackets represent corresponding p-values. 
Long run relationship: ECTt-1 = lgdpt-1 – 0.19lexportst-1 – 20.25 
                                                                  (0.19)                   (0.0) 
Short run relationships:  
dlgdpt = 0.03ECTt-1 – 0.19lgdpt-1 + 0.05lexportst-1          

   (0.0)             (0.21)             (0.27) 
dlexports = 0.01ECTt-1 + 0.93lgdpt-1 + 0.19lexportst-1         
                    (0.48)            (0.04)            (0.18) 

When dlgdp is the dependent variable estimated adjustment coefficient (0.03) is positive and statistically 
significant, which implies that any deviation from equilibrium value in the short run is not corrected. The 
estimated coefficient of lagged lexports is positive but statistically insignificant. When dlexports is the dependent 
variable the estimated adjustment has expected sign but is statistically insignificant. In the short run lgdp affects 
lexports positively as the estimated coefficient (0.93) is positive and statistically significant.  

In the long run also exports positively affects gdp although the estimated coefficient is statistically 
insignificant. The estimated elasticity of gdp with respect to exports is 0.19.  
 
5.2. Relationship between GDP and Debtservice 

Model 2: lgdpt = β0 + β1 ldebtservicet + errort  
where ldebtservice is logarithm of debtservice.  

Table 5 reveals that the null hypothesis H0: r = 0 is rejected whereas we fail to reject H0: r ≤ 1 and conclude 
that there seems to be a long run relationship between lgdp and ldebtservice.  

 
Table-5. Johansen tests for cointegration between lgdp and ldebtservice  (Trend: constant). 

Maximum rank Trace statistic 5% critical value 

0 16.7825 15.41 
1 1.9844* 3.76 
2   

 
The long run and short relationships given by the estimated error correction model for these two variables are 

as follows: 
Long run relationship: ECTt-1 = lgdpt-1 – 2.38ldebtservicet-1 + 26.5 
                                                                   (0.0)  
Short run relationships: dlgdpt = - 0.01ECTt-1 – 0.19lgdpt-1  –  0.003ldebtservicet-1 + 0.05               

(0.0)         (0.2)                  (0.79)                            (0.0) 
                              dldebtservicet =  0.03ECTt-1 + 2.37lgdpt-1  –  0.26ldebtservicet-1 + 0.01  
                                                         (0.17)          (0.15)                 (0.04)                        (0.89) 

In this case the estimated adjustment coefficients have correct signs and it is statistically significant for dlgdp 
equation. Any short run deviation of lgdp from its equilibrium value is corrected at a speed  of one per cent. In the 
short run debtservice is negatively affected by lagged value of it (estimated coefficient is – 0.26 and it is statistically 
significant). Other estimated coefficients are not statistically significant in the short run. But, we get one 
interesting result. In the short run, lagged ldebtservice negatively affects lgdp (estimated coefficient – 0.003) 
whereas, in the long run, debtservice positively and significantly affects gdp (estimated coefficient 2.38).   
 

5.3. Relationship among GDP, Exports and Debtservice 
Model 3: lgdpt = γ0 + γ1lexportst + γ2ldebtservicet + errort 
Table 6 presents the cointegration test results for this model and it is found that It is clear that    
 

Table-6. Johansen tests for cointegration among lgdp, lexports and ldebtservice  (Trend: constant). 

Maximum rank Trace statistic 5% critical value 

0 30.5091 29.68 
1 10.7893* 15.41 
2 1.9519 3.76 

3   

 
lgdp, lexports and ldebtservice are cointegrated, that is, there is a long run relationship among them. 

The error correction model is estimated to analyse the short run and long run effects represented by the 
following equations: 
Long run relationship: ECTt-1 = lgdpt-1 – 0.42lexportst-1 – 0.30ldebtservicet-1 – 9.92 

(0.0)                 (0.0) 
Short-run relationships:  
dlgdpt =         –  0.09ECTt-1   – 0.12lgdpt-1    –  0.0008lexportst-1    – 0.008ldebtservicet-1   + 0.05  
                         (0.001)            (0.399)                (0.987)                      (0.502)                      (0.0) 
 
dlexportst =        0.01ECTt-1    + 0.92lgdpt-1    +  0.20lexportst-1      – 0.04ldebtservicet-1      + 0.03  
                          (0.89)              (0.03)                 (0.20)                      (0.25)                            (0.33)  
  
dldebtservicet =  0.55ECTt-1   + 2.40lgdpt-1    +   0.21lexportst-1     –  0.22ldebtservicet-1      + 0.01  



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                          (0.059)           (0.121)              (0.702)                    (0.093)                          (0.939) 
The results can be interpreted in the following way. The estimated adjustment coefficients have correct signs 

and for dlgdp it is statistically significant also. Any short run deviation in lgdp from its equilibrium value is 
corrected at a rate 9 per cent per year. All other estimated coefficients are statistically insignificant excepting the 
coefficient of lgdpt-1 for dlexports equation. It indicates a positive influence of lgdp on lexports in the short run. 

In the long run, however, both lexports and ldebtservice are found to be statistically significant factors 
determining lgdp and each one positively influences lgdp. 
 

5.4. Relationship among GDP, Exports and Debt Stocks 
Model 4: lgdpt = δ0 + δ1lexportst + δ2ldebtstockst + errort 
where ldebtstocks is logarithm of debtstocks. Table 7 presents the cointegration test results for this model. It is 
clear that H0: r = 0 is rejected and  
 

Table-7. Johansen tests for cointegration among lgdp, lexports and ldebtstocks  (Trend: constant). 

Maximum rank Trace statistic 5% critical value 

0 17.4826* 29.68 
1 5.1502 15.41 
2 1.3765 3.76 
3   

 
H0: r = 0 cannot be rejected. Therefore, lgdp, lexports and ldebtservice are not cointegrated, that is, no long 

run relationship exists among them. Thus, a VAR in first difference of the variables is conducted to study the 
Granger causality results. Table 8 presents the test results. It is noted that only dlgdp is helpful for forecasting 
dlexports.  

 
Table-8. Granger causality Wald tests for dlgdp, dlexports and dldebtstocks. 

Null Hypothesis (H0) Chi2 df p-value Decision 

dlexports does not Granger cause dlgdp 
dldebtstocks does not Granger cause dlgdp 
dlexports and dldebtstocks do not Granger cause dlgdp 

1.0389 
.10549 
1.2127 

2 
2 
4 

0.595 
0.949 
0.876 

H0 is not rejected 
H0 is not rejected 
H0 is not rejected 

dlgdp does not Granger cause dlexports 
dldebtstocks does not Granger cause dlexports 
dlgdp and dldebtstocks do not Granger cause dlexports 

6.7948 
2.202 

9.0833 

2 
2 
4 

0.033 
0.333 
0.059 

H0 is rejected 
H0 is not rejected 
H0 is not rejected 

dlgdp does not Granger cause dldebtstocks 
dlexports does not Granger cause dldebtstocks 
dlgdp and dlexports do not Granger cause dldebtstocks 

.29255 

.37891 
.8498 

2 
2 
4 

0.864 
0.827 
0.932 

H0 is not rejected 
H0 is not rejected 
H0 is not rejected 

 
Table 9 shows that with restricted constant trend specification lgdp, lexports and ldebtstocks are cointegrated. 

The ECM is then estimated to analyse the short run and long run effects represented by the following equations: 
 

Table-9. Johansen tests for cointegration among lgdp, lexports and ldebtstocks (Trend: restricted constant). 

 

                         
Long run relationship: ECTt-1 = lgdpt-1 – 0.47lexportst-1 – 0.68ldebtstockst-1 – 0.52 

(0.101)              (0.106)                     (0.915) 
Short-run relationships:  
dlgdpt =             –  0.03ECTt-1     – 0.16lgdpt-1    +  0.03lexportst-1    – 0.003ldebtstockst-1     
                              (0.0)                (0.27)                  (0.49)                      (0.94)                       
 
dlexportst =        – 0.015 ECTt-1    + 0.94lgdpt-1    +  0.15lexportst-1      – 0.19ldebtstockst-1        
                              (0.25)                (0.03)                 (0.29)                      (0.13)                             
  
dldebtstockst =   – 0.007ECTt-1   + 0.49lgdpt-1    –   0.04lexportst-1     + 0.32ldebtstockst-1        
                             (0.65)               (0.34)               (0.82)                       (0.03)                           
 

The results reveal that for dlgdp equation only the estimated adjustment coefficient has correct sign and is 
statistically significant. The speed of adjustment is 3 per cent. In the short run, lgdp positively affects lexports and 
the estimated coefficient is significant at 5 per cent level. All other estimated coefficients are statistically 
insignificant. The short run impact of ldebtstocks on both lgdp and lexports is negative. The impact of lgdp on 
both lexports and ldebtstocks is positive. The impact of exports on ldebtstocks is negative and on lgdp is positive. 

In the long run also the estimated coefficients are not statistically significant; however, the impact of both 
exports and debtstocks on gdp is positive. So, similar to model 3 we find that debtstocks affects GDP negatively in 
the short run but positively in the long run. The impact of exports on GDP is positive in the short as well as long 
run. 
 

6. Concluding Remarks 
This paper attempts to examine the relationship among external debt, exports and economic growth for the 

Indian economy during the period 1970 – 2018. Using the techniques like cointegration, error correction model 

Maximum rank Trace statistic 5% critical value 

0 108.7484 34.91 
1 6.8255* 19.96 
2 1.4957 9.42 
3   



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and Granger causality analysis our study considers four models. In the model with constant trend specification 
where GDP and exports are the variables, the results indicate that there is no long-term relationship between 
them. However, dlgdp Granger causes dlexports; in contrast to that for the restricted constant trend specification 
there is a positive long term relationship (although not significant) and in the short run lgdp affects lexports 
positively and significantly. Thus for both specifications we find a support of GLE hypothesis. 

For the second model where GDP and debt services are the variables, the results reveal a positive and 
significant long-term relationship between them; in the short run, however, debt services negatively affect GDP 
although it is not statistically significant. 

The third model includes GDP, Exports and debt service. The results indicate that a long term relationship 
exist among the variables where both exports and debt services affect GDP positively and significantly. In the 
short run, surprisingly, both exports and debt services affect GDP negatively although not significantly. The error 
correction terms have expected signs. GDP has a positive and significant impact on exports. Other coefficients are 
not statistically significant. 

The fourth model is a variant of the third model where debt stock is used as an indicator of external debt. In 
this case with constant trend specification there seems to be no long term relationship among the variables dlgdp is 
found to Granger cause dlexports. For the restricted constant trend specification, however, there seems to be a 
long term relationship among the variables. Here also exports and debt stock affect GDP positively although not 
significantly. In this case also short run impact of debt stocks on GDP is negative and that of exports is positive 
but not significant. GDP affects exports positively and significantly.  

External debt is often used to supplement investment which is expected to impact economic growth positively. 
However, it can upset the process of economic growth under certain situations. The idea of export-led growth 
suggests that by boosting exports countries can improve economic growth; again export revenues finance 
repayment of external debt to foreign countries. Higher levels of exports indicate better debt servicing capacity and 
more debts would be available from the lenders. There is a hypothesis of growth-led exports also which argues that 
economic growth affects exports positively. So, it can be said that external debt, exports and economic growth are 
inter-related in a country and it is both important and interesting to study the relationship for India. 

In general, results indicate that GDP has a positive and significant impact on exports in all models including 
exports. Hence it can be said the GLE hypothesis is supported in case of India for the period 1970-2018. ELG 
hypothesis is not supported in the short run in any of the model. For model 3, where debt servicing is included, in 
the long run also there is a significant positive relationship between GDP and exports. For model 2 and model 3 
there is a positive and significant relationship between economic growth and external debt in the long run. A 
significant positive long run impact of external debt on economic growth is observed in the Indian economy in both 
the bivariate as well as trivariate model where debt service is the indicator of external debt. Ahmed et al. (2000) 
also noted positive impact of exports and external debt on economic growth and negative impact of debt servicing 
on exports during 1970 -1997 where growth rates of the three variables are considered in their study.  

The short run impacts of external debt in terms of both debt servicing and debt stocks, however,  produce 
diverse results in our study and the effects are not statistically significant also. 
 

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