


































In ternationa l
Scholars
Journa ls

                                                                                                               
African Journal of Agricultural Marketing ISSN: 2375-1061 Vol. 3 (8), pp. 232-240, August, 2015. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 

 

 

 

 

Full Length Research Paper 
 

A survey on the Effects of foreign debt servicing on per 
capita revenue growth rate in Pakistan 

 

Fazlur Al Hasan 
 

Department of Marketing, Faculty of Management Sciences, University of Karachi, Karachi, Pakistan. 
E-mail: fazlurhasan12@gmail.com 

 

Accepted 30 July, 2015 
 

Among the wide array of macroeconomic problems confronted by Pakistan, foreign debt servicing, has 

occupied a substantial place. Persistent fiscal deficit since the independence, turned out to be the ground 
for various governments to rely on the internal or external borrowings. The acquisition of more external 

debt instead of internal resource mobilization results in higher level of debt stock. Due to soaring level of 

debt, Pakistan has been allocating a major chunk of resources to debt repayment, which is tarnishing its 

economic growth. The present study has been conducted to discover the impact of foreign debt servicing 

on per capita income growth rate of Pakistan for the period 1981 to 2010 by applying relatively new 

technique, called auto-regressive distributed lag (ARDL) of co-integration. The results confirm that the 
foreign debt servicing has adversely and significantly affected the per capita income growth rate of 

Pakistan in both short-run and long-run in the specified period. There is an ardent need for 

comprehensive policy on part of the government of Pakistan to salvage the economy of such a financial 

loss. 
 

Key words: Per capita income, growth rate, debt, debt servicing, ARDL and co –integration. 

 
INTRODUCTION 
 
Pakistan is currently facing many economic and social 
issues  which  are  collectively  affecting  the  economic 
growth. The public debt and its servicing are the most 
crucial problems that Pakistan has been facing in recent 
years. Domestic and foreign borrowings are considered 
as normal phenomenon because countries at the initial 
stages of development need capital stock (Malik and 
Siddiqui 2001). Apparently, foreign debt increases the 
economic growth but if it gets accumulated beyond a 
specific  limit,  it  can  have  devastating  effects  upon 
economic growth as proved by (Hasan 1999).The poor 
countries like Pakistan are getting more and more loans 
just to survive but it creates dependency on donors. More   
 
 
 

debt is  being  acquired  just to  repay previous  debt  and  
it  is  neither  being  used  for  the development purposes 
nor for the human capital formation. Pakistan is spending 
its export revenues on debt servicing  instead  of  utilizing  
it  on  human  capital, investment in real assets and 
scientific research and development. Debt servicing is 
severely affecting economic growth of Pakistan by eating 
up major share of resources. The high level of debt 
leaves no incentives for the government to carry out the 
macroeconomics reforms and good effective policies 
because returns from these reforms will only be used to 
pay back outstanding debt and its services. The history of 
Pakistan has remained caught in the debt trap. Debt trap 



Fazlur       232 
 
 
 
is a situation where a country takes debt and to pay 
interest payments, it acquires more debt due to 
unavailability of resource. Foreign debt amount increased 
from US $37.24 billion as of June, 2006 to US $57.21 
billion as of June, 2010, which shows an increase of 
53.63%. In fiscal year 2009 to 2010, the elected 
government of Pakistan spent a large amount of US $ 
3.112 billion on debt servicing out of which US $ 2.3 
billion was paid as principal amount. 

There are a host of factors, which have contributed 
towards this dependence on foreign debt including 
unbalanced and wrong economic policies, inefficient 
governments and misappropriation by the political and 
administrative elite of the country during many succes-
sive regimes in Pakistan. The current account deficits, 
fiscal account deficit, macroeconomic mismanagement, 
non-development expenditures of the successive gover-
nments are largely responsible for this high level of debt 
servicing.  

According to former president of state bank of Pakistan 
Mr. Syed Salim Raza (2009), fiscal deficit is almost half of 
the total budget, which is the result of non-development 
expenditures and considered as the biggest problem of 

Pakistan after inflation
1
. The main heads of non-

development expenditures include general administration 
expenditure on various departments of federal govern-
ment, Law and order, defence expenditure, subsidies and 
debt servicing. Among all these, defence expenditures of 
Pakistan has been increasing in every budget with a 
constant rate and consuming a large share of income.  

The fiscal deficit of Pakistan is around 5.4% of gross 
domestic product (GDP) and it has to rely again on 
foreign debt to fulfill this deficit. Most of the other 
countries around the globe fulfill their fiscal and current 
account deficit by mobilizing the internal resources or 
foreign direct investment but Pakistan always relies on 
foreign debt, which results in high debt accumulations. 
Debt servicing takes large benefits from the domestic 
economy as a large amount of foreign exchange reserve 
has been transferred to the lender countries. It reduces 
the country‟s ability to grow itself rather it raises its 
dependence on the lender countries. 

The effects of the high debt can easily be observed by 

the budget allocation of Pakistan every year. Keeping in 

mind the severe effects of the debt repayments of the 

external debt, the present study investigates the impact of 

debt serving on the economic growth of Pakistan. The 

present study is organized as follows: 
 
Following the strong background of Pakistan debt 

problem, review of the literature is discussed in second 

section, theoretical frame work and model specification is 

discussed in third section, methodology and estimation is 

discussed in forth section and estimation results and 

 
 
 

 
findings are discussed in section five and section six 

contains conclusion followed by policy recommendations. 

 
Review of literature 
 
There are voluminous studies in the literature in which the 
effect of debt on economic growth has been high-lighted. 
Some studies discussed the debt overhang conditions 
and some showed significant and negative effect of debt 
and debt servicing on economic growth. Sinha (1999) 
examines the relationship between invest-ment, export 

stability and growth for nine Asian countries
2
. Generalized 

Johansen framework of co-integration was used to carry 
out results. Results suggest investment in these countries 
was positive and significant for the economic growth. 
 

Dijkstra and Hermes (2001) concluded, by applying 
orthogonal least-squares (OLS) technique that uncertainty 
measure of total debt and long-term debt servicing 
payments by 104 HIPCs has negative and statistically 
significant relation with economic growth for the period of 
1970 to 1998. Serieux and Samy (2001) analyzed how 
debt burden affects economic growth of 53 lower and 
middle income countries both directly and indirectly in the 
period of 1970 to 1999. The author also concludes that 
debt servicing negatively affects investment and economic 
growth. Karagol (2002) undertakes an empirical study to 
analyze the effect of debt servicing on economic growth 
of Turkey by applying Johansen co-integration technique. 
The author proves that debt servicing has negative 
relation with economic growth in short-run and long-run. 
Same is confirmed by Adesola (2009) for Nigeria and 
Malik et al (2010) for Pakistan.  

Gupta et al. (2005) checks the expenditure composition 
and fiscal consolidation effect on the economic growth. 
Panel data was used for 39 underdeveloped countries by 
applying generalized method of moments. The results 
explore that reduction of 1% point in fiscal deficit to gross 
domestic product ratio led to average increase of 0.5% 
point in per capita growth. Wijeweera et al. (2005) 
empirically studies the checked relationship between 
external debt and GNP for Sri Lanka by applying Engle 
and Granger (1987) co-integration and extracellular 
matrix (ECM). Results suggests that the sign of debt 
servicing coefficient was negative and capital stock and 
human capital were having positive relation in short-run 
and long-run.  

McGrath (2006) analyzes the impact of industrial 

development and financial deregulation on economic 

growth of Czech Republic, Hungary and Poland. Industrial 

development was found significant and positively affects 

economic growth in three countries. Industrial production 

unidirectional caused GDP for all three countries. Osinubi 

 
1
http://www.nation.com.pk/pakistan-news-newspaper-daily-english-   

 

2
  Indian, Japan, Malaysia, Myanmar, Pakistan, Philippines, Sri Lanka, South 

 

online/Politics/05-Feb-2009/Nondevelopment-expenditure-biggest-problem- 
 

SBP Korea and Thailand 
 



 
 
 

 
et al. (2006) empirically examines how the budget deficit 
led to accumulation of external debt which affects the 
economic growth of Nigeria for the period of 1970 to 
2003. The author explains the need for Nigeria to finance 
its fiscal deficit. Complete evasion of external debt as a 
means of financing budget deficits will not help the 
economy as debt at sustainable level leads to develop-
ment. Hameed et al. (2008) verifies the debt overhang 
situation in Pakistan. Sultan (2008) empirically confirms 
the positive impact of industry value added on economic 
growth of Bangladesh by applying simple OLS for the 
period of 1965 to 2004.  

After reviewing the literature, it can easily be evaluated 

that most of the studies have been conducted to check 
the effect of debt on economic growth. A fewer studies 
have been conducted to grasp the effect of debt servicing 

on single country‟s economic growth. The present study 
is conducted to fill the gap by checking the effect of 

foreign debt servicing along with some allied variables 
affecting on economic growth (in terms of per capita 

income growth) of Pakistan by using relatively new 
technique. 
 
 
Theoretical frame work 
 
The Pakistan economy has been undergoing severe 
economic pressure throughout the history. Pakistan has 
relied on the foreign debt to finance its deficit. The debt 
taken in the early decades was used appropriately which 
resulted in high growth and development of the economy. 
The situation started worsening after 1970‟s when the 
debt was not being used properly. The debt has 
devastating effect on the economic growth of Pakistan as 
its servicing is far more than its capacity. There are two 
main theories which elaborate the debt situation of an 
economy that is, debt overhang hypothesis and debt 
laffer curve. If the debt burden of an economy becomes 
so large that a country does not remain in a position to 
take additional debt to finance its future projects and even 
though these projects would be profitable enough to 
reduce indebtedness of a country over time. The debt laffer 
curve theory states that the higher level of debt stock is 
associated with the lower probabilities of the debt 
repayment. Debt overhang hypothesis seems to be in the 
sight for the case of Pakistan. The current capacity of the 
economy to repay its debt indicates that economy is in 
the second part of the debt laffer curve where expected 
repayments are decreasing with increasing debt stock. 
The effect of debt servicing can be interesting study to 
validate the above stated hypothesis for the case of 
Pakistan. 
 
 
Model specification 
 
The model is designed to investigate the effect of debt 

servicing  on  per  capita  income  growth  rate.  The  debt 

 

233      Afr. J. Agric. Mark. 
 
 
 
servicing variable has been taken as the main variable 

along with other potential variables which affects the per 

capita economic growth rate. 
 
GrPCY=β0 +β1 DSt +β2 DIt +β3 GrSECt+β4 GrINDt +β5 

FDt + Єt 
Where, 
 
GrPCY= Growth rate of Per Capita Income 
DS= Foreign Debt Servicing  
DI= Gross Domestic Investment as percentage of GDP 

GrSEC= Growth rate of Secondary School Enrolment 

GrIND= Growth rate of Industry Value added  
FD= Fiscal Deficit as percentage of GDP 

Єt= Error Term 
 
In the model foreign debt servicing has been taken as 
main variable which includes debt servicing payments of 
foreign medium and long term loans. The expected 
relationship between debt servicing variable and the 
economic growth is negative. Karagol (2002) proved the 
same negative relation for Turkey and Hameed et al. 
(2008) and Malik et al. (2010) for Pakistan. Gross 
domestic investment is defined as increase in stock of 
capital in an economy and it does not include deduction 
for depreciation which is previously produced. Here the 
ratio of gross domestic investment to GDP has been 
taken and a significant and positive relation is expected 
between gross domestic investment as a percentage of 
GDP and economic growth. The positive relation between 
domestic investment and economic growth for China was 
confirmed by Tang et al. (2008).  

Growth rate of secondary school enrolment has been 
taken as proxy for the quality of human capital as used by 
Serieux and Samy (2001) and Clements et al. (2003). 
The positive and significant relation is expected between 
secondary school enrolment and economic growth as 
proved by Skipton (2007) and Afzal et al. (2010). The 
industry value added is the GDP share by industry or 
contribution of the industry to overall GDP. A positive and 
significant relation is expected between industrial value 
added and economic growth as industry is sharing major 
portion in the total production. The positive and significant 
relation between industrial development and economic 
growth was found by McGrath (2006) and confirmed by 
Sultan (2008). Fiscal deficit does always have a negative 
effect on the economic growth. Fiscal deficit increases 
the amount of debt and its repayment, which slows down 
the economic growth process. Expected sign of the 
coefficient of fiscal deficit is negative as proved by Gupta 
et al. (2005) for 39 underdeveloped countries. 
 
 

DATA AND METHODOLOGY 
 
Data set used in this study is comprised of last three 

decades (1981 to 2010). Annual data has been used and 

data up to the year 2008 has been taken from the world 

development indicators  (WDI)  CD-ROM (2008)  and  the 



Fazlur       234 
 
 

 
remaining two years data has been taken from the World Bank 
website. Data on few variables has also been taken from, 
various issues of economic survey of Pakistan. After the 
collection of data the next mandatory task is the test, to check 
the stationarity of the variables in order to apply an appropriate 
econometric technique. In the present study, two tests 
Augmented Dickey Fuller (ADF) and Kwiatkowski-Phillips- 
Schmidt-Shin (KPSS) (1992) have been applied to check the 
stationarity.For the test of existence of long-run relationship (co-
integration) among the variables, a number of techniques are 
available. A relatively new technique ARDL bound testing approach 
has been used in this study due to the shortcomings of others 
techniques, covered by this technique. This technique is based on 
the general to specific modeling and has been developed by 
Pesaran and Pesaran (1997), Pesaran and Smith (1998), Pesaran 
and Shin (1999) and Pesaran at el (2001). ARDL technique of co-
integration has been used due to the problems with other 
techniques of co-integration like Engel-Granger (1987) and 
maximum likelihood based Johansen (1988) and Johansen and 
Juselius (1990). 

ARDL has the advantage that it can be applied irrespective of the 
order of integration of the variables used in study. “ARDL can be 
used whether the variable is I (0), I (1) or fractionally co-integrated” 
(Pesaran and Pesaran 1997). An advantage of using ARDL 
approach of co-integration is that the relationship can be estimated 
by simple OLS once the order of ARDL is recognized. The ARDL 
approach is suitable for small sample size. Another advantage of 
using ARDL bound testing approach is that “it takes satisfactory 
number of lags to confine the data generating process within the 
general-to-specific framework” (Laurenceson and Chai, 2003). In 
comparison with other vector autoregressive (VAR) models, the 
ARDL model accommodates greater number of variables. Moreover, 
“a dynamic error correction model (ECM) can be obtained from 
ARDL through simple linear transformation” (Banerjee et al. 1993).  

To apply ARDL bound testing approach first of all stationarity 
level of the variables has been checked through unit root tests. The 
variables must be I (0) or I (1) for the application of ARDL bound 
testing approach. After checking the order of integration of 
variables, existence of the long-run relationship between the 
variables has been checked by applying the F-test. The F-test has 
been carried out by the imposition of the restriction on the 
coefficients with null hypothesis that is, there exists no long run 
relationship among the variables and with alternative hypothesis 
that is, there exists long run relationship among the variables. If the 
F- statistics lies below the lower bound then null hypothesis is not 
rejected and if the value of F-statistics is greater than the upper 
bound then the null hypothesis is rejected. The results remain 
inconclusive if the value of F-statistics lies between the lower and 
upper bound then.In the next stage ARDL equation is estimated 
where optimal lag length is chosen according to one of the Akaike 
information or Schwartz Bayesian, which are considered standard 
criterion for choosing the maximum lag length. After that long-run 
solution has been obtained for the selected lag length. Diagnostic 
tests have been applied to check the validity of the model. 
Lagrange multiplier test has been applied to check either problem of 
serial correlation exists or not. Ramsey's reset test has been used 

for the functional form, Skewness and Kurtosis test has been 
used for the normality and lagrangian multiplier test has been 
used to check the problem of heteroscedasticity in the data. The 
equation for the model is given as under. 
 

 m m 
∆ GrPCYt = a +    b i  ∆ (GrPCY)t - i +    c i  ∆ (DS)t - i 
 i= 1 i= 0 

m m m 
+ d i  ∆ (DI)t - i + e i  ∆(GrSEC)t –i +k i  ∆ (FD)t - i 

i= 0 i= 0 i= 0  
m 

+ p i  ∆(GrIND)t - i +δ1 (GRPCY)t – 1 +δ2(DS )t - 1 + δ3 (DI)t - 1  
i= 0 

+ δ4 (GrSEC)t -1+ δ5 (FD)t - 1+ δ6 (GrIND)t - 1 + µt 

 
 
 

 
Where „i‟ to „m‟ shows the selected lag length. 
 
In the next stage the error correction model has been estimated by 

using the differences of the variables and the lagged long-run 

solution. The coefficient of the error correction term shows at which 

speed the variables return to the new equilibrium. 
 
  m m 

∆ GrPCYt  = β0 +    αi ∆GrPCYt - i +   βi ∆DS t - i 
  i=0 i=1 
 m m m 

+γ
i ∆DI t - i +    δi ∆GrSEC t – i+    ηi ∆FD t - i 

 i=1 i=1 i=1 
 m   

+  ∆GrIND t - i + φ ECM t - 1 + vt 
 i   

i=1 
 

Finally the cumulative recursive sum (CUSUM) and cumulative 

recursive sum of squares (CUSUMSQ) tests are employed to check 

the stability of the short-run and long-run coefficients. 
 
 
RESULTS 
 
Estimation results and findings 
 
Table 1, 2, 3 and 4 shows the results

3
 of the augmented 

Dickey-Fuller and Kwiatkowski–Phillips–Schmidt–Shin 
(KPSS) unit root tests at level. 

The unit root results at level suggested that DI and 
GSE were stationary at level. Other variables were 
checked at first difference and the results are given. 

The table suggests that ARDL bound testing approach 
can be applied here because all the variables were 
stationary at level or at first difference. None of the 
included variable in the model were stationary at level two 
or at second difference.  
After checking the stationarity level of the variables, the 
next step was to select the maximum lag length. Most 
widely used criterions to select the maximum lag length 
are Akaike Information and Schwarz Bayesian. The 
Schwarz Bayesian criterion had been used for this study 
for the selection of lag length. 

The optimum lag length of 1 has minimized the values 
of AIC and SCH criterions. The SBC criterion had been 
chosen to select the lag order for ARDL bound testing 
approach over the AIC as it has low prediction error (Ma 
and Jalil 2008). The partial F-test had been applied in the 
study to check the long-run relationship among the 
variables. The null hypothesis for the test was that no 
long-run relationship exists among variables with 
alternative hypothesis that long-run relationship exists. 
The following table shows the long-run relationship 
results of bound test for the economic growth model. 

Table 4. 
The results show that F-value was greater than the UB 

at 5 and 10 %t level of significance. This test provided the 
 
 
3
 Eviews 7, econometric software has been used to obtain results. 



       
 

Table 1. Results of unit root tests at Level     
 

      
 

 
Variables 

Augmented Dickey- Fuller(ADF) Kwiatkowski-Phillips-Schmidt-Shin (KPSS)   
 

 
Intercept Intercept and trend Intercept Intercept and trend  

 

   
 

 DS -1.2742 -2.9135 1.2214 0.1083   
 

 FD -1.6878 -2.9288 0.6704 0.1574   
 

 DI -2.8824*** -2.8752 0.1145 0.0555*   
 

 GrSEC -3.2729** -3.3966 0.1742 0.0645*   
 

 GrPCY -2.6873 -2.7982 0.6214 0.1917   
 

 GrIND -2.5847 -2.8048 0.2963 0.0739   
 

 Significance Level      
 

1% -3.6891 -4.3239 .73900 0.2160   
 

5 % -2.9718 -3.5906 0.4630 0.1460   
 

10% -2.6251 -3.2253 .34700 0.1190   
  

Note. * Shows significance of the variable at 1% and ** shows at 5% ** and *** shows at 10% 
 
 

 
Table 2. Results of unit root tests at first difference 
 

Variables 
 Augmented Dickey- Fuller (ADF) Kwiatkowski-Phillips-Schmidt-Shin (KPSS) 

 

 
Intercept Intercept and trend Intercept Intercept and trend  

  
 

DS -5.6463* -5.5255 0.0412* 0.0416 
 

FD -4.0226* -3.9493 0.1615* 0.0954 
 

GrPCY -4.5288* -4.4183 0.1494* 0.0727 
 

GrIND -5.6257* -5.6156 0.0588* 0.0527 
 

Significance level     
 

1%  -3.6998 -4.3393 0.7390 0.2160 
 

5%  -2.9762 -3.5875 0.4630 0.1460 
 

10%  -2.6274 -3.2292 0.3470 0.1190 
  

Note. * shows significance of the variable at 1% and ** shows at 5% ** and *** shows at 10% 
 
 

 
base to apply ARDL technique of co-integration as it 
showed the existence of long-run relationship among the 
variables. As shown in table 5.  

All the variables of the models had expected signs. The 
debt servicing coefficient showed that one million dollar 
increase in debt servicing results in 0.12% decrease in 
the economic growth. The logic behind this inverse 
relationship is that although Pakistani government takes 
debt to finance its projects or to retreat its deficit in 
balance of payment but as we know the whole amount of 
debt is not utilized for such purposes rather a very big 
chunk is paid back in shape of debt repayment. So such 
money being out of the flow (Leakage) of Pakistani 
economy, cast negative effect on economic growth. 
Question arises here is that, why debt is taken on some 
part of the developing countries like Pakistan? The 
answer lies in the fact that internal sources of revenue 
generation are not enough.  So  the  developing countries 

 
 

 
should wake up from this ignorance and must avoid the 
horrors of debt and its repayment and try indigenous 
resource generation. These results were consistent with 
the results of study by Kargaol (2002) that also showed 
the negative effect of debt servicing on economic growth.  

The fiscal deficit as percentage of GDP negatively 
affected the economic growth; one percent increase in 
fiscal deficit as percentage of GDP leads to 40 % 
decrease in the economic growth. A country does 
financial deficit due to short of revenue. So the purpose of 
fiscal deficit continue to use such capital for economic 
growth. But unfortunately, the capital so collected cannot 
avert the decree of the fate of developing countries 
unless they avoid mismanagement or corruption. It 
means no use of making fiscal deficit. Rather it causes 
harms to the growth rate of country like Pakistan. 
Industrial growth has played significant role in the 
economic growth of Pakistan. In the present study industrial

235      Afr. J. Agric. Mark. 



 Fazlur       236  

 Table 3. Lag selection criteria  
      

   Lags Akaike information criterion (AIC) Schwarz Bayesian criterion (SBC) 
 1 41.36181

*
 43.34203

*
 

  2 41.54019 45.25134 
 

Note. * Shows minimum lag length 
 
 

 
Table 4. Bound test for long-run relationship 

 
 

F-statistics value 
95% Confidence level 90% Confidence level 

 

 
Lower bound (LB) Upper bound (UB) Lower bound (LB) Upper bound (UB)  

  
 

 6.2771 3.1474 4.6350 2.5902 3.8808 
 

 
 

 
Table 5. ARDL estimates, ARDL (1, 0, 0, 1, 0, and 0) selected based on Schwarz  
Bayesian Criterion GrPCY is Dependent Variable 

 
Regressors Coefficients Standard Errors T-Ratios  Probabilities 
GrPCY(-1) .23679 .11585 2.0440 .054 
DS -.0011592 .5599E-3 -2.0702 .051 
DI .0035118 .038510 .091193 .928 
GrSEC .084527 .051344 1.6463 .115 
GrSEC(-1) .11861 .054222 2.1874 .040 
FD -.40049 .20041 -1.9983 .059 
GrIND .24554 .085556 2.8699 .009 
INPT 5.6117 2.0974 2.6756 .014 

Summary Statistics    
R-Squared .78830 R-Bar-Squared .7172 
S.E. of Regression   1.4247 F-Stat.  F(7,21)  11.1709 [.000] 
DW-statistic 2.0207 Durbin's h-statistic -.071263 [.943] 

 
 

 
industrial value added growth had been found highly 
significant. One percent increase in the growth rate of 
industry value added leads to 24% increase in the 
economic growth of Pakistan. Such result is also shown 
by McGrath (2006) and Sultan (2008). The industrial 
growth as the theories suggests is one of the strong 
indicators of economic growth. As we know when any 
industry promotes, it creates economic activities in the 
economy that is, other allied industries also get boost up. 
Hence employment is generated and demand for goods 
services, further increases, total national income increa-
ses and causes GDP per capita to increase.  

Growth rate of secondary school enrolment in this study 

had has been taken as a proxy of human capital. The 

study has revealed that secondary school enrollment also 

influences the economics growth of Pakistan positively in 

the long run, as it had has been found highly significant. 
The background reason is that human capital can be tapped 

 
 

 
only through education, skill and training. An educated 
person becomes resourceful and finds ways to be 
productive. Hence as secondary school enrolment 
increases, it also causes an escalation in economic 
growth of Pakistan  

The domestic investment coefficient had has been 
found positive but insignificant for the economic growth. 
Domestic investment means a step toward prosperity 
because investment is also accompanied by employment 
and twin increase in employment and output accelerates 
the pace of economic growth of a country. The value of 
R-square showed that 79 % of total variation in the 
economic growth had been explained by the independent 
variables. The value of R-bar-square shows the goodness 
fit of the model adjusted to the degree of freedom and it 
had a value of 0.72 in this model.  

The Durbin's h-statistic had been used to check the 

problem of auto correlation. From the results, it can safely 



237      Afr. J. Agric. Mark. 
 
 
 
Table 6. Diagnostic tests results 
 
 Problems Applicable tests Chi-square(Χ

2
)/F statistics Probabilities 

 Serial Correlation Lagrange multiplier .033738 .854 
 Functional Form Ramsey's RESET .83957 .360 
 Normality Skewness and kurtosis of Residuals .071453 .965 
 Heteroscedasticity White 1.1993 .273 
 
 
 

Table 7. Estimated long run Coefficients, ARDL (1, 0, 0, 1, 0, 0) selected based 

on Schwarz Bayesian criterion, GrPCY is dependent variable 
 

Regressors Coefficient Standard errors T-ratios Probabilities 
DS -.0015188 .6818E-3 -2.2276 .037 
DI .0046014 .050267 .091540 .928 
GrSEC .26616 .10768 2.4717 .022 
FD -.52474 .27276 -1.9238 .068 
GrIND .32172 .11030 2.9169 .008 
INPT 7.3528 2.5222 2.9153 .008 

 
 
 

Table 8. Error Correction Representation For The Selected ARDL Model, ARDL 

(1,0,0,1,0,0) selected based on Schwarz Bayesian Criterio, GrPCY is Dependent 

Variable 
 

Regressors Coefficients Standard Errors T-Ratios Probabilities 
dDS -.0011592 .5599E-3 -2.0702 .050 
dDI .0035118 .038510 .091193 .928 
dGrSEC .084527 .051344 1.6463 .114 
dFD -.40049 .20041 -1.9983 .058 
dGrIND .24554 .085556 2.8699 .009 
Ecm(-1) -.76321 .11585 -6.5882 .000 
R-Squared .74026 R-Bar-Squared  .65368 
DW-statistic 2.0207    

 
 
 
be said that problem of auto correlation does not exist in 
the data. As shown in table 6.The diagnostic tests had 
been applied for the robustness of results. The results, 
indicates that the data is not suffering from the problem of 
serial correlation. The results confirmed the normality of 
the data set and correct functional form of the model. The 
white test showed that the error terms had constant 
variance, which confirmed the absence of hetero 
scedasticity.  

Table 7, shows the long-run coefficients of the variables 

by applying ARDL. All the coefficients had expected 
signs. One million dollar increase in debt servicing leads 
to 0.2 % decrease in economic growth in the long-run. As 

expected, the school enrolment had long-run positive 
effect on the economic growth. The positive and 

significant relationship between growth rate of secondary 
enrolment and economic growth was also confirmed by 
Skipton (2007) and Afzal et al (2010). 

 
 
 

Fiscal deficit as percentage of GDP had long-run 
significant and negative effect on the economic growth. In 
the long-run, one percent increase in the fiscal deficit as 
percentage of GDP leads to 52 % decrease in growth 
rate. Gupta et al. (2005) also confirms the same in his 
panel study. Growth rate of domestic investment had 
been found insignificant in the long-run. The industrial 
value added had been found to have a positive and highly 
significant relation with the economic growth, which was 
also confirmed by Sultan (2008) . One percent increase in 
the growth rate of industrial value added caused causes 
32 percent increase in the economic growth. 
 

Table 8, reveal that error correction term had been 

found highly significant. The negative sign with ECM 

shows the convergence of the dependent variable general 

practitioner for children and the young (GPCY) towards 

long-run  equilibrium  path  in  response to the changes in 



Fazlur       238 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Figure 1. Plot of cumulative sum of recursive residuals 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Figure 2. Plot of cumulative sum of squares of recursive residuals 
 
 
 
the independent variables in the model. The ECM (-1) 
had been found significant at 1% level with coefficient 
equal to -.76321. The coefficient of ECM (-1) confirmed 
the co-integration among variables and deviation from the 
equilibrium level of economic growth during current 
period will be corrected by 76.32 % in the next period.  

The CUSUM and CUSUMSQ tests confirmed the 

stability of the model if the test representing line stays 

within the critical bounds at 5% level of significance. The 

graphs of the CUSUM and CUSUMSQ tests had been 

presented in Figure 1 and 2. The results of both tests 

confirmed the correctness of parameters of short-run and 

 
 
 
long-run variables for growth rate and also verified the 

structural stability of the model. 

 
CONCLUSION AND RECOMMENDED POLICIES 
 
In the literature, most of the studies on Pakistan have 

tried to explain the effects of the debt on economic 

growth. A few numbers of studies have been conducted 

to check the effects of debt servicing on the economic 

growth of Pakistan. High levels of debt repayments are 

negatively affecting the growth process in Pakistan. High 



 
 
 

 
levels of debt accumulation over the last few decades 
and its repayments have become a burning issue in 
recent times. The paper aimed to check the impact of 
debt servicing on the economics growth of Pakistan by 
taking data of last three decades. The ARDL bound 
testing has been applied and results showed that debt 
servicing has affected economic growth in the long-run 
more than the short-run. The reduction in economic 
growth had been found to be 0.12 and 0.15 % in the 
short-run and long-run respectively due to one million 
dollar increase in the debt servicing. The results highlight 
the need of less reliance on the foreign resources and the 
importance of domestic resource mobilization. The 
industrial value added growth had been found positive 
and significant in both short-run and long-run in the 
economic growth model, which needs special attention in 
policy making.  

The growth rate of secondary school enrolment had 
been found highly significant for growth model in the long-
run. The fiscal deficit impact had been found negative and 
significant on economic growth of Pakistan. The fiscal 
deficit in Pakistan is due to non-development expen-
diture, the defense expenditures and interest payments, 
which are more than the development expenditures. The 
debt dependence policy always put extra pressure on the 
domestic resources. By acquiring more and more foreign 

debt with strict conditionalities
4
, the economy is falling 

into a debt trap
5
.Keeping in view the results of the 

present study following policy recommendations can be 
helpful to enhance the growth rate and to tackle the rising 
problem of the debt.  

The government of Pakistan has been spending major 
share of its revenues for the non-development expendi-
tures which has brought fiscal deficit to the level of 50% 
of the total budget for the year 2010 to 2011. The 
government has to finance its projects by printing new 
money which not only creates inflation but also crowds 
out investment due to increase in the interest rate. The 
proper resource utilization is need of the time in 
education and health sector and institution building and 
reconstruction.  

Pakistan is blessed with affluent human capital which 

can be used for the self-dependent macro- economic 
performance. The quality education, training, research 

and development (R & D) facilities can enhance effi-
ciency of the labor force and help to increase productivity, 
which will ultimately lead to the higher growth with lower 

costs of production. The industry value added of Pakistan 
is 25% of its GDP; this sector has great potential to 

contribute more in the GDP of the economy. Proper 
attention and policies are needed to give it a boost. 
 
Conflict of Interests 
 
The authors have not declared any conflict of interests. 
 
4 The conditions related to the acquisition of debt especially from IMF 

 

5 The accusation of more debt to repay the previous debt 
 

 

239      Afr. J. Agric. Mark. 
 
 
 
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