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                      American International Journal of Social Science Research; Vol. 4, No. 2; 2019 
                                       ISSN 2576-103X   E-ISSN 2576-1048 

Published by Centre for Research on Islamic Banking & Finance and Business, USA 
 

     14 
 

Public Debt Spiral in Nigeria: Can a Structural Gap Result From Pervasive 
Corruption? 

 
Fisayo Fagbemi 

Independent Researcher 
Nigeria 

E-mail: fisay4real@yahoo.com 
 

Olufemi Solomon Olatunde 
Independent Researcher 

Nigeria 
E-mail: olufemi.olatunde@gmail.com 

 
 
Abstract 
It is increasingly recognized that good understanding on the corruption-related causes and remedies of the modern fiscal crisis 
would bolster informed decisions and key governance standards. Many of the governance weaknesses have been exacerbated by 
ingrained fiscal indiscipline and lack of effective bureaucratic provisions.  These concerns necessitate ongoing research efforts 
aimed at galvanizing the best compilation of perspectives on the role of public institutions in debt accumulation process. Hence, 
this study examines the long run and short run effect of corruption on public debt in Nigeria over the period of 1996 to 2017 
using ARDL bound test to cointegration analysis. Empirical evidence reveals that both corruption index and control of 
corruption have an insignificant adverse effect on public debt in the long run, but with a significant influence in the short run. 
Considering the long-term implication, current anti-corruption efforts might be ineffective in enhancing strategic monitoring 
and sustainable fiscal standards. Nonetheless, it is emphasized that effective corruption control measures could mitigate 
spiralling incidence of government debt. Further findings indicate that there exists bi-directional causality between corruption 
index and public debt, whereas none is found between control of corruption and public debt. The study suggests that strong 
corruption-based control mechanisms are fundamentals to decreasing fiscal deficits and debt reduction. Overall, a significant 
insight distills from the study is that the goal of attaining global financial stability and fiscal sustainability through sound 
regulatory framework has embodied the provisions that enhance corruption-reducing measures and institutional standards to 
curb persistent debt accumulation. 

 

Keywords: Public debt, Corruption, Fiscal crisis, ARDL, Nigeria.  
 
1. Introduction 
The orthodox stance on the concept of structural gap is that when fiscal revenues of the state are insufficient to finance ever-
increasing public expenditures. With increasingly unsustainable government spending levels in the social and economic 
development process, the state faced a huge financing deficit. Hence, evolving empirical expositions reveal that structural gaps 
could lead to spiraling incidence of public borrowing and debt (Bailey, 2004). In this context, structural gap and ‘fiscal crisis’1 
are synonymous. In most developing economies, the public debt trajectory has approached unsustainable levels which threaten 
the fiscal health of countries. Many African countries, in particular, are struggling with a combination of rising public debt, 
budget deficits and poor growth.  Over the years, much of this debt upsurge is driven by an absence of fiscal discipline and 
sound corruption control measures. The injudicious choices for debt accumulation posed a problem to citizens of such indebted 
jurisdiction, since future servicing of public debt with no long-term development impact would exacerbate intergenerational 
inequity (Liu, 2017). Some economists (researchers), in general, have espoused to the adverse effect of government debt on 
economic growth and development in any economy (Kumar & Woo, 2010; Reinhart, Reinhart & Rogoff, 2012). Thus, debt 
deliberately amplified through corrupt actions may be inimical to fiscal performance and the economy as a whole. 
Recognizing that a robust fiscal state is a springboard for socio-economic development, in sub-Saharan Africa (SSA), recent 
years have witnessed a great deal of policy actions initiated to bolster the fiscal position of the central government across 
countries. Nonetheless, political leaders and economic actors often reinforce the formation of large structural gaps in SSA 

                                                             
1 Fiscal crisis occurs when there is a substantial increase in much-needed government expenditures over state revenues, which give rise to 
insufficient finance. 



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countries. In Africa, the culture of self-serving ethos and dishonest political control are ubiquitous. Due to high levels of 
corruption and inefficient resource utilization, public debt has turned out to be a new succession of slavery for most countries in 
the region. The biggest challenge confronting SSA is how the borrowed funds can be utilized. Nigeria, indeed, best fits this 
scenario, as pervasive corruption impedes strict adherence to fiscal rules and prudence in the country.  In Nigeria, the advent of 
civil rule in 1999 has led to the introduction of anti-corruption initiatives by the successive governments. Despite these, coupled 
with institutional control measures, corruption is festering. According to transparency international, Nigeria is one of the most 
corrupt countries in the world. The Corruption Perceptions Index (2018) shows that out of 175 countries ranked, Nigeria is the 
144 least corrupt nation — close to the bottom of the ranking. 
 The alarming proportion of Nigeria’s public debt which could have an adverse effect on the development path of the 
country has escalated debate among policymakers, in spite of the argument of government’s financial managers. Given the Debt 
Management Office (DMO) report, the country’s total debt stood at N22.43 trillion in 2018, a rise of 85.06 per cent when 
compared with what it was in June 2015 (Leadership Nigeria Newspaper, 2018). The percentage of public debt to GDP has 
been on the rising side vis-à-vis low corruption index (Figure 1). It is worrisome that Nigeria is approaching the pre-2005 Paris 
Club levels. The causes of and responsive approach to the fiscal crisis are being viewed by researchers. Following call for 
restraining the escalation of public debt, the goal of attaining global financial stability and fiscal sustainability through sound 
regulatory reform has embodied the provisions that enhance the institutional framework for addressing frail fiscal levels in 
developed and emerging economies. However, the literature on the role of political and bureaucratic factors in public debt 
accumulation process is sparse, perhaps still budding in developing countries. Thus, the question as to whether the high level of 
corruption magnifies the growing incidence of indebtedness of Nigeria’s government should be accorded considerable attention. 

 
Figure 1: corruption index and % of public debt to GDP (2012-2018) 

Source: Authors’ estimates based on data from transparency international and IMF 
World Economic Outlook database (2018) 
 
 Furthermore, most findings on the relationship between corruption and public debt are cross-country studies (Alfredo & 
Luca, 2015; Cooray et al., 2017; Benfratello et al., 2018), whereas, regarding Nigeria, major studies center on the nexus between 
corruption and economic performance (Obadan, 2002; Osunyikanmi, 2007; Adewale, 2011). Hence, like the way Grechyna 
(2012) opines that there is need for convincing empirical evidence of the effect of corruption on public debt for high-income 
countries, a study that will examine the influence of corruption on the rising debt profile in Nigeria is central. The main reason 
advanced for this study is the paucity of systematic analysis significant for enhancing holistic expositions that would drive robust 
regulatory response to escalating fiscal crisis. Specifically, the study’s key objective is to explore the long-run and short run 
relationship between corruption and public debt in Nigeria. 
The rest of the paper is organized as follows. In section 2, literature review is presented. Data description and detailed 
econometric techniques adopted are provided in section 3. Section 4 is the presentation of results and discussion, while the last 
section (section 5) gives the concluding remarks. 
2. Literature review 
2.1 Theoretical and conceptual discussion 
Over the years, many scholars have dealt with various institutional and economic factors that could navigate fiscal operations in 
any economy. The close nexus between feeble bureaucratic system and shadow economy2 has a substantial influence on the 
performance of fiscal institutions. For instance, (Friedman, Johnson, Kaufmann, & Zoido-Lobaton, 2000; Schneider, Buehn, & 
Montenegro, 2010) contend that a larger shadow economy results from high corruption. The two concepts are closely related 

                                                             
2 Although there seems to be no consensus exists as to the precise definition of the shadow economy, the concept can be viewed as an 
unobservable (unrecorded) economic phenomenon (Buehn & Schneider, 2009).  



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and analogous3, as both involve illegal activities such that the market-based production of goods and services remains elusive in 
official GDP estimates (Tanzi, 1998; Smith, 1994). Accordingly, by compromising the capacity of the government to collect 
taxes and fees, corruption gives rise to revenue shortfalls (Arusha & Friedrich, 2013). Given that a corrupt bureaucracy alters the 
design, structure and functionality of fiscal arrangement, the effectiveness of public investment and infrastructure is undermined 
by increasing opacity in the public sector (Dzhumashev, 2014a). In any case, the quality of institutions shapes the effect of 
government spending, and hence determines the growth rate of public debt. 

Another theoretical linkage in the literature is anchored on the elite theory. The theory emphasizes that, at the 
governance level, the perpetrators of corruption are mostly the elite class. Proponents of the theory assert that public policy is 
shaped by the preferences and values of the governing elite (Gaetano Mosca (1858-1941); Jose Ortega (1855-1983); Vilfredo 
Pareto (1923-1948)). They elucidate that every society is controlled by a group of persons enjoying superior intellectual or 
social and economic status necessary for its accession to full political and economic power. This group manipulate the structures 
and institutions of politics to suite their private ends (selfish purposes). Moreover, the ideological and philosophical direction of 
the society are determined by a minority. The development of governing class in most developing economies is strongly linked 
with their colonial background4. Specifically, in Nigeria, the elite group has features similar to its colonial progenitor — an 
instrument of exploitation and a means for primitive resource accumulation. Public policy is characterized by ill-informed 
decisions and sharp corrupt practices of the ruling class, which undermine fiscal performance, and in turn, the retardation of 
economic growth and development (Obialor, 2017). 
 The literature on rent-seeking theory which emphasizes the pursuit of private gains by public administrators at the 
expense of the common good also offers an explanation on corruption-fiscal nexus. Corruption which is often viewed as the 
“misuse of public office for private gain” (Mauro, 1995) could facilitate rent-seeking behavior in the public sector. A corrupt 
environment is characterized by an extreme case of violated legal rules and the pervasiveness of questionable illegal activities. 
Corruption is an unconstitutional pursuit of selfish goals by public officials (Liu, 2017). Previous studies have stressed that 
government officials are likely to espouse to large capital investments, as they engender maximum rent seeking. Owing to non-
transparent bureaucracy, the effectiveness of various financial assistance programs is hampered, because funds are often channeled 
away from the intended purposes. In such economies, prior evidence posits that it is rampant to bribe officials who can exert 
political leverage in public contracts and regulation-related industries (Kaufmann 2010; Liu and Mikesell, 2014).  Thus, public 
expenditure is deemed to be wasteful due to injudicious choices (Shleifer and Vishny 1993; Tanzi and Davoodi 1997). Overall, 
there is evidence that corruption exacerbates inequalities and poverty in a country through the distortion in the composition of 
public spending (Delavallade, 2006; Mauro, 1998). Historically, as most government projects are financed primarily through 
borrowed funds, some authors opine that presence of corruption will induce increased public debt, ceteris paribus (Butler, Fauver 
and Mortal, 2009; Liu, 2017). 
2.2 Empirical evidence 
With the expansion of public debt in most economies, establishing a convincing ground that could consolidate the role of 
institutional control measures in the economy is central. In light of this, empirical studies bolster up the ulterior reasons for 
supporting that a link between corruption and the level of public debt is tenable, as many researchers argue that corruption may 
affect government debt through various channels. For example, Tanzi and Davoodi (1997) support the notion that an increase 
in public spending could be reinforced by corruption. Similarly, Dzhumashev (2014b) corroborating this view with assertion 
that the perpetuation of large public expenditures may result from the interplay of high levels of corruption and public spending. 
Furthermore, given that the composition of public spending can be altered by corrupt elements, Mauro (1998); Wei (2001) 
indicate that more resources may be allocated to sectors which involve less transparency (like defense) against the vital sectors 
(such as health and education), because military expenditure is most often not subject to the usual auditing and frequent public 
legal scrutiny (Gupta, De Mello & Sharan, 2001). Thus, public debt would increase as large-scale investment projects and public 
expenditures (such as defense) are financed by both internal and external borrowing, (Kaufmann, 2010). 
 Moreover, using a panel of 166 countries between 1995 and 2013, Luigi, Alfredo & Luca (2015) examine the 
relationship between corruption and public debt. The authors show that high corruption in the public sector is found to increase 
government debt. Based on a large panel of countries between 1995 and 2015, Benfratello et al. (2018) assess the impact of 
corruption on public debt.  Results indicate that corruption leads to increased public debt, but the effect seems to be 
heterogeneous across income-related sample splits; such that in advanced economies, it is stronger, while in less-developed 
countries, it appears to be weaker and less statistically robust. Pani (1996) focuses on the effects of corruption on the macro-
economic variables of the public budget. The study analysis centers on the situation whereby the management of public 
expenditure is induced by public bribes, in the long term, it is stressed that these corrupt acts could accentuate an accumulation 

                                                             
3 For example, Arusha, Ratbek, & Friedrich (2017) posit that a larger shadow economy and high corruption in an economy trigger spiralling 
public debt. 
4 In Nigeria, with propensity for unbridled materialism, the culture of self-serving ethos was imbibed by the country’s elites who took over 
power from the erstwhile colonial administrations.  Their actions were mostly influenced by the exploitative tendencies (activities) of the 
colonial masters (Ojukwu and Shopeju, 2010:5). 



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of debt that might result to financial crisis in the country, although the outcome depends on some prevailing factors — the 
incentives with which it is confronted and preferences of the government. Cooray et al. (2017) using Ordinary Least Squares 
(OLS), fixed effects, system generalized method of moments (GMM) and instrumental variable estimation, examine the 
relationship between corruption, the shadow economy and public debt. With the use of two measures of corruption (the 
Transparency International Corruption Perceptions Index and the Kaufmann et al., 2010 —corruption index) for 126 countries 
over the period of 1996–2012, estimates reveal that increased corruption and a larger shadow economy result to a rise in public 
debt. Employing the system generalized method of moment (GMM) estimator, Njangang (2018) explores the impact of 
corruption on public debt with a panel of 29 Sub Saharan African countries (SSA) between 2000 and 2015. Although 
recognizing that a large literature concludes on the damaging effect of corruption on any economy, findings reveal that 
corruption positively influences public debt in the sample countries. 
 On the other hand, some authors argue that corruption adversely affect the economic performance as a whole (Hall & 
Jones, 1999; Kraay, Zoido-Lobaton, & Kaufmann, 1999). In particular, corruption retards the level of investment (Mauro 
1995), and it also undermines the quality of procurement services (Rose-Ackerman 1997). Other studies on the effect of 
corruption on most economies also corroborate these conclusions (Johnson, Kaufmann & Shleifer, 1997; Depken & LaFountain, 
2006). Analogously, with a focus on Nigeria, corrupt practices are found to be inimical to the economic system (Obadan, 2002; 
Osunyikanmi, 2007; Adewale, 2011). They further posit that corruption impairs hard work, accountability and efficiency.  In 
general, there exists a significant adverse relationship between corruption and output growth in Nigeria. However, the preceding 
review underscores that evidence on the influence of corruption on fiscal level is sparse. There is limited understand on how it 
accentuates fiscal impacts. By and large, a sufficient gap is left for a study assessing how corruption affects the spiralling 
incidence of public debt in Nigeria. 
3. Data and Methodology 
3.1 Data description 
Given the systematic significance of the main objective, the study employs annual time series data between 1996 and 2017. 
Based on the availability of data, the choice of scope is vital for establishing a robust ground on the role of public institutions in 
fiscal development process.  In the study, two indicators of corruption are used — the Transparency International Corruption 
Perceptions Index and the Kaufmann et al., 2010 (corruption index). The percentage of public debt to GDP is included as the 
dependent variable in the model. While taking into account the relevance of certain variables in governance-fiscal literature, GDP 
per capita, inflation rate, consumer prices (annual %) and gross national expenditure (% of GDP) are employed as control 
variables. Accordingly, detailed description and the corresponding data source are given in Table 1. 
Table 1: Variable description 

Variable Description Source 

Fiscal indicator   

% of debt to GDP It is the ratio of a country’s public debt to its 
gross domestic product (GDP). 

IMF historical public debt database 
(2018) 

Corruption indicator   

Transparency International 
Corruption Index 

It shows the perceived level of public sector 
corruption on a scale of 0 (highly corrupt) to 
100 (very clean). 

Transparency international (2018) 

Kaufmann et al., 2010 (control of 
corruption) 

It captures perceptions of the extent to which 
public power is exercised for private gain, 
including both petty and grand forms of 
corruption, as well as "capture" of the state 
by elites and private interests. Estimate gives 
the country's score on the aggregate 
indicator, in units of a standard normal 
distribution. The close the index to negative, 
the worse the institutional quality (-2.5 to 
2.5). 

World governance indicators (2018 
edition) 

Macroeconomic indicator   

GDP per capita GDP per capital (constant 2010 US$), It is 
expected to be indirectly linked to public 
debt. 

World development indicators (2018 
edition) 

Inflation rate Inflation rate is measured by consumer price 
index (annual %). It is expected to positively 

World development indicators  (2018 
edition) 



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affect public debt. 

Gross national expenditure (% of 
GDP) 

It represents the sum of household final 
consumption spending, general public final 
consumption expenditure and gross capital 
formation. Theoretically, it is positively 
correlated with public debt. 

World development indicators (2018 
edition) 

 
3.2 Methodological framework 
Following the preceding theoretical linkage between corruption and fiscal levels (Butler, Fauver and Mortal, 2009; Liu and 
Mikesell, 2014), a linear regression model is formulated in a functional form as; 

 
Where  is defined as % of debt to GDP.  represents corruption index.  is the GDP per capita.  connotes 

inflation rate while  is the Gross national expenditure (% of GDP).   indicates the time period. 
3.2.1 Cointegration technique 
As many econometric techniques exist for finding the long run relationship among variables, Autoregressive Distributed Lag 
(ARDL) model has been viewed to be more efficient and reliable given its numerous advantages over others (Engle-Granger, 
1987; Johansen and Juselius, 1990; Johansen, 1991). Unlike other cointegration methods, where the order of integration matters 
and the requirement for large sample size, ARDL approach developed by Peseran and shin (1997); Pesaran, et al. (2001) is 
applicable irrespective of the order of integration (i.e. whether it I (0) or I (1), it does not matter). It is also effective for small 
sample5. With ARDL, long run and short run relationship can be allowed for within the same model. In view of these, and 
considering the small sample size of the study, ARDL bound test to cointegration is applied. Hence the model is stated as 
follows: 

 
The white noise error is represented by .  is the log of variables while the difference operator is defined as . 

In Eq. (2), ……,  indicate the optimal lag length determined by information criterion. Using bound test approach 

(Pesaran et al., 2001), the cointegration relationship between  and other variables (explanatory) can be found with the 
placing of restriction on the whole estimated parameters of lagged level variables to be equal to zero. In this case, the null 

hypothesis is stated as;  =   = 0, against alternative hypothesis; : 

. In this model, the null hypothesis states that there is no long run relationship among the 
variables. On the other hand, the alternative hypothesis implies the presence of long run relationship among the variables. 

Decision rule: if the computed F-test exceeds the upper bound critical value,  is rejected. However, if the calculated F-

statistics is less that the lower critical value,   cannot be rejected, while the decision remains inconclusive, if the calculated F-
statistics lie between the lower and upper bounds. After confirming the existence of cointegration among the variables, an error 
correction model is specified from Eq. (2) as; 

 
 is the speed of adjustment, which is expected to be negative and significant.  indicates the residuals that obtained from 

the estimation of Eq. (2). Following a shock in the short-run, the negative sign of  parameters implies that   adjusts 
back to its equilibrium value. 
4. Empirical Results and Discussion 
Taking into account the ineffectiveness and the spurious outcome that may occur when the order of integration in any of the 
series is I (2), Augmented Dickey Fuller (ADF) and Phillip Peron (PP) unit root tests are performed. Although, in ARDL 
model, no pre-test is required to ascertain the order of integration, if the level of stationarity is above I (1), the estimates could 

                                                             
5 The use of ARDL approach circumvents the problem of biasness that often associated with small sample size (see Haug, 2002; Narayan, 
2005). 



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be inefficient and unreliable. Essentially, results of the tests in Table 2 confirm that no variable is not found to be stationary at 
first difference. ADF and PP indicate a mixture of I (0) and I (1) in the series. With no I (2) variable in the model, the use of 
ARDL offers an adequate basis for the study. Also, in Table 3, bounds F-tests are applied to determine the cointegration 
relationship among the variables. Following Pesaran et al. (2001), the null hypothesis of no cointegration is rejected at 1% 
significant level in model (i) & (ii), as the computed F-statistics in both models6 are greater than the upper bound critical value. 
The stability of the parameters in the model is established by Cumulative Sum of Recursive Residuals (CUSUM) and 
Cumulative Sum of Squares of Recursive Residuals (CUSUMSQ) — in Figure 1, the two tests fall within the critical 
boundaries. The diagnostic tests conducted further verify the validity and robustness of the estimated results. 
Table 2. Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) unit root test results 

Variable Augmented Dickey Fuller Phillips-Perron 

 Level First difference Level First difference 

Public debt -3.69 (4)** -3.95 (0)*** -1.11 -3.95** 

Corruption index -2.15 (0) -5.20 (1)*** -2.17 -10.43*** 

Control of corruption -1.91 (0) -4.65 (0)*** -2.09 -4.64 

GDP -0.80 (0) -3.47 (0)** -0.82 -3.47** 

Inflation -5.93 (0)*** -7.07 (0)*** -5.70*** -11.35*** 

National expenditure -3.77 (0)** -5.14 (4)** -3.77** -11.47*** 

***, **, & * indicates the level of significance at 1%, 5% & 10% respectively. Figures in (.) represents 
lag length selected by AIC criterion. The PP length was selected by Newey-West Band Width. 

Table 3. Bounds F-tests for cointegration relationship 

Model F-
statistics 

Level of 
Significance 

Critical value 

   Lower bound Upper bound 
 
Corruption index 
Model (i) 
(1, 2, 1, 2, 1) 

 
7.28*** 

 
1% 
5% 
10% 

 
3.74 
2.86 
2.45 

 
5.06 
4.01 
3.52 

Control of 
corruption Model 
(ii) 
(2, 2, 2, 2, 2) 

18.80*** 

*** represents statistical significance at 1% level. 
In assessing the long run and short run effect of corruption on public debt, Table 4 is presented, and the regression 

results regarding main measures (corruption indicators) mostly correspond to the apriori expectations. Starting with long run 
estimates, corruption index (model (i)) has an adverse effect on public debt, suggesting that the higher the index, the lesser the 
level of public debt. Also, in model (ii), control of corruption is negatively related with the public debt. This implies that an 
effective corruption control measure could mitigate a high incidence of government debt. Further findings indicate that in both 
models, the estimated parameters of the two indicators are not significant. A plausible justification for this is that the current 
ant-corruption efforts might not be well suited to the improvement of public debt management strategy. In another way, it can 
be stressed that it has a shallow effect on the fiscal management process. In terms of entrenched corrupt bureaucracy and 
structural gap relations, it is difficult for states with greater fiscal crisis to curb wasteful expenditures and levels of debt. 
However, given these results, it is evident that, in practice, debt accumulation is restricted with lower levels of public corruption. 
This empirical assertion is consistent with previous studies on corruption-public debt nexus (Cooray et al., 2017; Liu, 2017). 
On the hand, with respect to short run relationship, the estimated parameters of two indicators are significant, while the negative 
signs are retained. This suggest that, in the short run, the level of corruption substantially navigates the direction of government 
debt. 
Table 4. ARDL long run and short run estimates 

Variable Model (i) Variable                                       Model (ii) 

 Long run Short run  Long run Short run 
Constant 0.20* 0.25** Constant 1.03** -1.44*** 

                                                             
6 In this study, model (i) indicates the inclusion of corruption index computed by the Transparency international, whereas model (ii) represents 
the use of control of corruption developed by Kaufmann et al. (2010) as an institutional indicator in the model. 



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[1.99] [-2.89] [2.79] [-12.99] 

Corruption index -0.79 
[-1.03] 

-0.03** 
[-4.29] 

Control of 
corruption 

-1.71 
[-0.53] 

-0.84** 
[-2.78] 

GDP -1.27** 
[-2.95] 

1.01* 
[2.15] 

GDP -0.89 
[-0.32] 

-0.85** 
[-2.83] 

Inflation 0.12 
[0.57 

0.02*** 
[3.26] 

Inflation 0.47* 
[1.69] 

0.01* 
[2.04] 

National expenditure 0.68* 
[1.96] 

1.49** 
[4.85] 

National 
expenditure 

4.86* 
[1.77] 

1.98*** 
[9.89] 

ECM (-1)  -0.11*** 
[-8.42] 

ECM (-1)  -0.12*** 
[-13.01] 

D.W 1.94 D.W 2.02 

Ramsey reset test 0.58 Ramsey reset test 0.51 

Normality test 0.53 Normality test 0.58 

Serial correlation 0.91 Serial correlation 0.32 

*, ** & *** indicate statistical significance at 10%, 5% and 1% respectively, whilst 
figures in (-) are t-values. 
On the control variables, signs of the estimated parameters also marry up with the theoretical expectation. The results 

reveal that, in the long run, the effect of GDP per capita remains substantial and statistically significant, indicating that in the 
period of economic boom, government tends to borrow less compared with the financial crisis period. Similarly, the assertion is 
also retained in the short run. In contrast, inflation and national expenditure have a direct significant association with public 
debt in the long run as well as in the short run. Although inflation is insignificant in model (i), high inflation rate and excessive 
public spending are the fundamental causes of spiralling levels of public debt in Nigeria. In buttressing this empirical ground, 
large – scale government expenditures on unsustainable projects could exacerbate fiscal imprudence and the rising incidence of 
indebtedness in the economy (Gupta, De Mello & Sharan, 2001; Kaufmann, 2010). Moreover, the speed of adjustment of 
government debt to shocks in exogenous variables is shown by the estimated coefficients of the Error Correction Term (ECM (-
1)). The negative statistical significance of the estimated parameters of Error Correction Term in the two models indicates a 
stable process of adjustment to the long run equilibrium. Essentially, the validity of the Error Correction Term (ECM (-1)) is 
established by the estimated values respectively. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Model (i) — Corruption index 

-10.0

-7.5

-5.0

-2.5

0.0

2.5

5.0

7.5

10.0

2010 2011 2012 2013 2014 2015 2016 2017

CUSUM 5% Significance        

-0.4

0.0

0.4

0.8

1.2

1.6

2010 2011 2012 2013 2014 2015 2016 2017

CUSUM of Squares 5% Significance  
 

Model (i) — Control of corruption 

-8

-6

-4

-2

0

2

4

6

8

2013 2014 2015 2016 2017

CUSUM 5% Significance         

-0.4

0.0

0.4

0.8

1.2

1.6

2013 2014 2015 2016 2017

CUSUM of Squares 5% Significance  

Figure 2: cusum (left) & cusumsq (right) 



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Table 5.Pairwise Granger Causality Test 

Model Hull hypothesis F-
statistic 

Prob. 

Model 
(i) 

CORRUPTION_INDEX does not Granger Cause 
LOGPUB 

2.80 0.09* 

 LOGPUB does not Granger Cause 
CORRUPTION_INDEX 

3.01 0.07* 

Model 
(ii) 

CONTROL_OF_CORRUPTION does not Granger 
Cause LOGPUB 

1.65 0.22 

 LOGPUB does not Granger Cause 
CONTROL_OF_CORRUPTION 

1.57 0.23 

* indicates statistical significance at 10% 
 
 In Table 5, the Granger causality results show that corruption index as the tendency to induce the rate of debt in the 
country, while the causality is also run in opposite direction. This implies that, in model (i), there is bi-directional causality 
between corruption index and public debt. However, both control of corruption and government debt do not Granger cause 
each other in model (ii).  These findings depict little effectiveness on the part of corruption-based control mechanisms, 
including bureaucratic and fiscal adjustment mechanisms. One of the main factors that could be responsible for such 
ineffectiveness is that public policies’ enforcement rate may be too low. Furthermore, the entrenchment of corruption in the 
public sector and social misalignment have led to a litany of compromising corrupt officials in the system, which undermine the 
application of  governance principles and support for long-term strategic monitoring. 
5. Concluding Remarks 
It is increasingly recognized that good understanding on the corruption-related causes and remedies of the modern fiscal crisis 
would bolster informed decisions and key governance standards. Many of the governance weaknesses have been exacerbated by 
ingrained fiscal indiscipline and lack of effective bureaucratic provisions. These concerns necessitate ongoing research efforts 
aimed at galvanizing the best compilation of perspectives on the role of public institutions in debt accumulation process. Hence, 
this study examines the long run and short run effect of corruption on public debt in Nigeria over the period of 1996 to 2017 
using ARDL bound test to cointegration analysis. While pairwise Granger causality test was applied to know the causal 
direction between corruption indicators (corruption index and control of corruption) public debt, other significant tests were 
also checked for. 
 New empirical evidence documented reveals that both corruption index and control of corruption have an insignificant 
adverse effect on public debt in the long run, but with a significant influence in the short run. Considering the long-term 
implication, the current anti-corruption efforts might not be well suited to the improvement of public debt management strategy 
or perhaps ineffective in enhancing strategic monitoring and sustainable fiscal standards. Thus, entrenched corruption in the 
public sector may widen the structural gaps. Nonetheless, it is emphasized that effective corruption control measures could 
mitigate spiralling incidence of government debt. More findings from the analysis indicate that there exists bi-directional 
causality between corruption index and public debt, whereas none is found between control of corruption and public debt. The 
study suggests that strong corruption-based control mechanisms are fundamentals to decreasing fiscal deficits and debt 
reduction. On the contrary, fiscal imprudence and the rising incidence of indebtedness could be worsened by large – scale 
government expenditures on unsustainable projects. Overall, a significant insight distills from the findings is that the goal  of 
attaining global financial stability and fiscal sustainability through sound regulatory framework has embodied the provisions that 
enhance corruption-reducing measures and institutional standards to curb persistent debt accumulation. 
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