







































American Research Journal of Economics, Finance and Management 

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EXPLORING THE NEXUS BETWEEN GOVERNMENT 
EFFICIENCY, REGULATORY QUALITY, AND ECONOMIC 

GROWTH IN TRADE 
 
 

1Dr. Philemon V. Tomsa, 2Dr. Charles B. Bitang and 3Dr. Christy Z. Mbala 
1Assistant, Department of Analyses and Economic Policy, University of Maroua 

2Associate Professor, Head of Department of Monetary Economics, University of Ngaoundère 
3Associate Professor, Department of Economics, University of Yaoundé II 

 
Abstract: The pivotal role of institutions in economic development has been well-established in the 
literature since the 1990s. Scholars like North (1990), Mauro (1995), Engerman and Sokoloff (2003), 
and Dollar and Kraay (2003) have underscored the significance of quality institutions in fostering 
economic growth and enabling effective economic policy measures. While prior research has 
extensively examined the connections between institutions and trade, their impact on economic 
growth remains relatively understudied. This study bridges this gap by exploring the relationship 
between institutions, trade openness, and economic growth, drawing upon the frameworks of 
endogenous growth theory and the new theory of international trade. It acknowledges that trade 
openness can be a catalyst for economic growth, offering economies of scale and facilitating 
technology transfer. However, recent decades have witnessed disparities in economic performance 
between developed and developing countries, prompting a reassessment of the presumed positive 
effects of trade openness. 
This research contends that the quality of national institutions plays a crucial role in shaping a 
country's economic growth trajectory, potentially acting as a determining factor for its successful 
integration into global trade networks. By delving into the nuanced interplay of institutions, trade, 
and economic growth, this study aims to provide valuable insights for policymakers and researchers 
alike. 
Keywords: Institutions, Trade Openness, Economic Growth, Endogenous Growth Theory, 
Developing Countries. 
 
  
1. Introduction   
During the 1990, literature gave institutions a primordial place. It provided a series of analyzes aimed 
at demonstrating the essential role of quality institutions in the process of economic development and 
in the effectiveness of economic policy measures. North (1990) was one of the first to demonstrate the 
importance of institutions in economic development. Mauro (1995) emphasizes the phenomenon of 
corruption which is harmful to investment and economic growth in developing countries; while 
Engerman and Sokoloff (2003) postulate that there are economies of scale due to good quality of 
institutionsand trade openness in determining economic development. In the same vein, Dollar and 
Kraay (2003) formulate that countries which have good institutions tend to trade more. However, most 

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of the work examines the links between institutions and trade ignoring their effect on economic growth 
(Lavallée, 2006; Levchenko, 2013; Avom and Gandjon, 2014; Gandjon, 2017).  
According to the theory of endogenous growth and the new theory of international trade, openness to 
international trade is a catalyst for economic growth insofar that it allows countries to benefit from 
economies of scale and promotes transfer of technology. However, the differences in economic 
performance observed between rich and developing countries over the past three decades have put the 
positive effects of trade openness on economic growth into perspective (Sachs and Warner, 1995). Thus, 
any poor quality of national institutions could further harm contributed to countries weakness 
economic growth that could truly miss it integration into world trade. 
In this background, using annual data, this paper analyses whether efficiency in terms of policy 
execution and the quality regulation matters on the relationship between trade and economic growth 
in Central African countries. Objective of this paper is to provide an overview of the role of regulation 
quality and government efficiency in the relationship between trade openness and economic growth, 
the question that could be raised here is why this research remains relevant for the economy of Central 
African countries.  
One reason mentioned, is the choice of the political dimension of institutions that is justified by 
controversies of the work and the scarcity of to our knowledges which analyzed the effectof the quality 
of political institutions especially the effectiveness of thegovernment efficiency and regulationqualityon 
trade and growth. Indeed, these two indicators seem mixed when compared to the statistics of the 
WorldGovernance Indicators (WGI, 2017) and in view of other countries with a quality institution 
appreciate (Tranparency, 2010). Moreover, considering these indices, these indicators in terms of 
political governance have progressed relatively compared to previous years (Transparancy, 2016).    
The rest of the paper is organized as follows: the second section reviews the existing literature. The third 
section shown the methodological framework used. The fourth section presents the various results and 
discussions obtained.The last partconcludes this work.   
2- Literature review  
Trade is a central concern in macroeconomics in view of the controversies existing literature. There is 
a growing and clear interest on the relationship between trade openness and economic growth. Some 
work works havebeen devoted to this analysis. The studies are divided into two categories.    
For the first category, trade openness has a positive effect on economic growth. It highlights the 
important role of trade openness as a factor that promotes long-term growth in improving well-being 
through increased productivity (Frankel and Romer, 1999; Abessolo, 2005; Busse and Koniger, 2012). 
Regard the second category, trade openness has no significant effect on economic growth if it is 
separated from quality institution (Constantinos and al, 2014; Vitola and Senfelde, 2015; Votsoma et 
al, 2020). Drawing on studies by Dollar and Kraay (2003), Balogoun (2016) assesses the effect of trade 
openness on poverty in developing countries. It shows that to a large extent trade openness reduces 
income inequalities. However, the growth channel, relayed by the theoretical literature, remains 
insignificant. He concludes that the analysis of the transmission channel, through nonlinear regressions 
suggests that the impact of trade openness on poverty does not come from the effects of the 
redistribution income on economic growth, but rather from otherinstitutionalvariable.    

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Conversely, Mathew and al (2014) separately analyze trade openness and the quality institution on 
economic growth in Sub-Saharan Africa using the Least Square Dummy Variables (LSDV) and the 
Generalized Moments Method (GMM) on the period 1985-2012. The study is significant considering 
the fact that trade openness and institutions exert to some extent a positive influence on the economic 
growth of African countries. The results indicate that the institutions had a positive and significant 
impact on economic growth but trade openness was not very significant on the economic growth of 
African countries.  
In Africa, Dinkneh and Yushi (2016) find that Africa-China trade openness has a positive and robust 
effect on the real GDP growth of African countries. This trade of Africa-China interacts with the political 
institutional and human capital of Africa. It effect is positive and significant. Therefore, it needs Africa 
strong domestic absorption capacity in order to reap the technology improving effect of trade with 
China. These results therefore provide evidence that trade openness and the quality of institutions are 
an important to economic growth for Africa.Hence, Niyongabo (2007) hypothesizes that openness 
policies can be more effective if they benefit from good quality political institution in developing 
countries. Using the Ordinary Least Squares (OLS), he concludes that good governance and the 
adoption of open trade policies act interactively and are positively associated with increasing income, 
reducing inequalities and the cushioning of trade shocks.  
Meanwhile,Krenz (2016) studies the two-way relationship between political institution and trade. To 
this end, itworks covers 87 countries and spans the period 1990-2007. Using the Co-integration 
method, the results conclude that the political institutional framework has a positive long-term effect 
on trade. This report is robust to different evaluation methods. The estimators report unbiased 
evaluations for cointegrating variable, even under the presence of endogenous repressors. In addition, 
the results confirmed a long-term causality from institutions to trade. He concludes that an improved 
political institutional framework is a cause of increased trade exchange.   
However,Mina and Ndikumana (2007) explore that one of the causes limiting the growth in the degree 
of trade in Africa may be weak institution. Their results of Arellano Bond method (GMM) assessments 
on panel data from African countries show that institutions play an important role.   
They find that the common effect of institutions and trade has a U shape, suggesting that while trade 
has the high levels of expansion institution play an important role in harnessing the trade engine that 
drives economic growth    
Whereas, Linh Bun (2009) uses a regression by the Least Squares Method (OLS) in panel.He examines 
the effect of openness on the growth of the ten countries of the Association of South-east Asian Nations. 
He also combines the quality institution and trade. Its results suggest that trade and the quality of 
political institutions positively affect economic growth and find that the good quality of institutions has 
a greater effect on economic growth.   
In contrast, using the GMM method, Kilishi and al (2013) first assess the quality of institutions and 
economic growth in Africa, addressing two questions: Do institutions matter in Africa? If so, what are 
the interaction effects of institutions on growth? To this end, it shows that political institutionis 
important in promoting growth. This improvement in the quality of institutions affects the growth rate 
through the quality of standardization, the legal framework and political stability. Thus, according to 
him, improving the standardization quality of trade agreements may have more of an effect on growth 

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than in isolating them. Finally, they find that institutional factors become much more important 
associated with trade openness on economic growth. 
3. Methodology   
This paragraph successively sets out the economic growth model to be estimated, the data and their 
sources as well as the model estimation strategy.  
3.1. Econometric specification 
The specification of the neoclassical growth model developed by Mankiw and al (1992) considers 
human capital and physical capital. The model can be expressed as follows:  
Y(t)  A(t)K(t) L(t)1  0 1  
The Cobb-Douglas production function (Y) depends on physical capital (K), labor force (L) and the level 
of technology (A). Inspired by this previous function, the neoclassical model of Mankiw and al (1992) 
is formulated as follows: The global functional form allows us to establish the following relation  
Direct relation: PIB it B0 B1 PIB it 1 B2 OUV it B3 X it it it  
Indirect relation: PIB it B0 B1 PIB it 1 B2 OUV B3 IP B3 X it 

B4 IP OUV it it it  
Or B 0 . B 4 are parameters of the model variable. X is the control variable; PI * OUV is the interactive 
variable between trade and the quality of political institutions (government efficiency and regulation 
quality), OUV is trade openness, u is the country specific, e is the error term.   
3.2. Variables  
The real economic growth rateis a percentage to take into account purchasing power parity to allow 
comparison between countries (Greenaway and al, 2012). Trade openness measures the proportion of 
a country total income that is linked to international trade. Government efficiency measures 
perceptions of the quality of public services, the quality of the civil service and the degree of its 
independence from policy, the quality of policy development and execution, and the credibility of 
government policies (Kaufmann and al, 2004). Regulatoin Quality captures perceptions of government 
capacities to formulate and enforce sound policies and regulation that enable and encourage the 
promotion of private sector development (Kaufmann et al, 2004; Koeniger, and Silberberger, 2015). 
Public expenditure measured by final public consumption as a percentage of GDP, this variable allows 
us to take into account the effect of fiscal policy in our analyses by virtue of Keynesian teachings (Levine 
and Renelt, 1992, Sachs and Warner, 1995; Edwards, 1998). The rate of inflation measures the annual 
growth rate of the consumer price index (CPI), the CPI is one of the best measures of inflation for 
economies heavily dependent on import prices. This variable takes into account macroeconomic 
stability.   
In the economic literature, we talk about the rate of inflation when the index is not specified (Romer, 
1991). Gross Fixed Capital Formation is the aggregate that measures, in national accounts, the 
investment (acquisition of production goods) in fixed capital of the various resident economic agents. 
Formerly called gross domestic investment, it consists of expenditures for additions to the tangible fixed 
assets of the economy plus the net changes in inventorie (Yanikkaya, 2003, Wacziarg and Welch, 
2008).Natural resource measures natural rent by the difference between the selling price of natural 
resources and their operating costs (Devarajan and Wolfgang, 2013; Mondjeli and Tsopmo, 2017). The 
active population measures the rate of increase of the active population. This variable takes into 

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account the role of the labor factor in economic activity. Indeed, a demographic expansion increase the 
proportion of the population considered as non-productive, mainly those of children and seniors. The 
table 1 shows summary variables.  
Table 1: variables  

 

Dependent  
variable   

Economic  
activity   

Economic growth  Real GDP rate in  
  annual%   

  WDI   

Gross fixed capital  (+)  WDI formation as% of GDP  
Total natural resource (+) WDI  as% of GDP  
Annual population  (-)  WDI   
growth rate in%  
Public expenditure rate  (+/-)  WDI   
Inflation rate in %  (+ /-)  WDI   
annual  

 
Source: the author  
3.3. Data and Study Area 
Data was acquired from several sources including: (i) the World Governance Indicator (WGI, 2018), 
(ii) World Bank Development Indicators (WDI, 2018); and (iii) data from the International Monetary 
Fund (WEO, 2018). The sample covers a few countries in Central Africa (Cameroon, Congo, Gabon, 
Guinea and Chad). The incorporation of these five countries in the same sample can be justified by their 
strong historical and cultural roots, in addition to the economicies of being part of the customs and 
monetary union.  
3.4. Estimation Methods  
The conclusions of Chang and al (2005) has marked the literature that examines how trade openness 
and institutions interact, seeking a possible role for policy complementarities. Although, they did not 
give the specific application, he asserts that the essence of the analyses can be extended for the analyzer 

expenditure   
  

as% of 
GDP  

  Trade  Sum of exports and 
imports of goods and 
services(%GDP)  

(+)  WDI  

Variable   Concept   Component   Measurement indicator   
  

S ign   So urce   

    Government  
Efficiency   

Government Efficiency   
Index    

(+)      WGI    

Q uality   regulation   Regulation   index   (+)   WGI    

    

  
  
  
Control variable    
  
  
  

I nvestment    

Natural resource    
  

Population    

Public  

Inflation    

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of complementarity between trade and other reforms. To achieve our objective of analyzing the effect 
of government efficiency and the quality of regulation in the relationship between trade and economic 
growth, this research uses an empirical methodology based on the method of instrumental variables 
(IV - GMM) over the period 1995-2017. The decision to use this method is justified by correcting for 
heteroscedasticity in order to best compensate for the endogeneity of certain improvement variables 
(Arellano and Bond, 1991; Arellano and Bover, 1995; Blundell and Blond, 1998; Roodman, 2009).   
4. Empirical results  
Table 2 below shows the result. Overall, the instrumental variable used in our regression are valid since 
the Hansen / Sargan test does not allow rejecting the null hypothesis of validity of the instrument in 
level and in difference (p-value> 0.05). In addition, we find that there is no second order 
autocorrelation of the errors of the difference equation AR (2), because Arellano and Bond second order 
autocorrelation test accepts the hypothesis no lack of second-order autocorrelation (p-value> 0.05). 
The arbitrage is done by comparing the value provided automatically by the conversion associated with 
the evaluated Wald value, which facilitates the analyses. It will therefore suffice to compare the 
discussion associated with the Wald-statistic with the 5% threshold used.    
If the conversation associated with W-Statistics was selected at 5%, then the H0 hypothesis will be 
rejected in favor of the alternative hypothesis according to which the regression is globally significant. 
In this case, the Wald statistic is less than 5%, so the null hypothesis is rejected and the model is globally 
significant.   
 Table 2: Estimation of interaction termsthe components of political institution andtrade on economic 
growth  
  

Dependent variable   
  

Real annual economic growth     
System dynamic panel-data estimation   
(GMM-type)   

  

Model  (1)   Model (2)   Model  (3)   Model (4)   
Lagged growth (-1)   0.007*  (0.34)   0.290**  (2.10)   0.322***  

(2.82)   
0.267**  
(1.69)   

Trade   0.154***  
(9.74)   

0.135***  (7.68)   0.148***  
(9.85)   

0.139***  
(7.32)   

Population   -1.973   
(-0.32)   

6.464  (1.52)   8.389**  (1.91)   9.027*  (1.72)   

Public expenditure   
  

-0.136***  (-
3.89)   

-0.601***  (-3.87)   -0.603***  (-
7.05)   

-0.429***  (-
3.84)   

Inflation   -0.298***  (-
3.37)   

-0.197***  (-4.57)   -0.188***  (-
3.53)   

-0.222***  (-
4.16)   

Natural resource   
  

-0.653   
(-0.89)   

0.191***  (2.66)   0.163  (1.51)   0.252**  
(2.04)   

Private investment   
  

-3.456   
(-0.98)   

2.800  (1.09)   2.974  (1.98)   0.861  (0.30)   

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Government efficiency   
  

0.069  (0.86)   0.066*  (1.61)   0.058  (1.49)   0.169*  (1.56)   

Regulation   
  

0.022  (0.66)   0.014  (0.42)   -0.011  (0.34)   0.149*  
(0.65)   

Government  
efficiency *Trade   

///   0.103***  (3.81)   //   1.559  (0.23)   

Regulation* Trade   //   //   0.098***  
(4.84)   

0.101  (2.92)   

Constant   4.161  (0.09)   -44.263  (-1.40)   -53.190**  (-
2.33)   

-57.011  (-
3.92)   

Interaction terms   (No)   (Yes)   (Yes)   (Yes)   
Observations   95   90   90   90   
AR(1) p-value   0.3296   0.4531   0.3488   0.0982   
AR(2) p-value   0.4096   0.3244   0.4927   0.574   
Wald p_value   0.0000   0.000   0.000   0.000   
Countries   5   5   5   5   

Note: ***: significant at the 1% level; **: significant at the 5% level; *: significant at the level of 10%  
In Table 2, column 1, 2, 3, 4, there are a positive relationship between trade openness and economic 
growth.  
Column (1) shows a positive impact of trade openness on economic growth. The coefficient associated 
with trade is  
0.154, which suggests that an increase of 1 unit in the trade openness rate leads to an increase economic 
growth of 0.154 unit. This result, which at first glance seems to join the conclusion of Frankel and 
Romer (1999) and Ho and Iyke (2018). Indeed, they highlight the important role of trade openness as 
a factor that promotes long-term growth. Among the effects favoring economic growth, several authors 
support the preponderant place that the process of trade openness plays in improving well-being by 
boosting productivity.  
We tested the validity of the interactive effect between trade and government efficiency on the one hand, 
and the quality of regulation on the other. The results show that the coefficients of the main interactive 
variable specified havepositive sign. Column (2) shows a positive effect of the interactive variable 
between trade openness and government efficiency on economic growth. The coefficient associated 
with the interactive variable is 0.103, which suggests that a unit increase in trade openness and 
government efficiency results in economic growth of 0.103 unit. Therefore, trade and government 
efficiency are complementary. In other words, perceptions of the quality of public services, the quality 
of the civil service, the degree of its political independence, the quality of policy formulation and 
execution, and the credibility of government policies reinforce the positive effect of trade openness on 
economic growth. This result is consistent with the conclusions of Zaouli and Zaouli (2015) and Bonnal 
(2015). Column (3) shows a positive effect of the interactive variable between trade openness and 
regulation on economic growth. The coefficient associated with the interactive variable is 0.098, which 
suggests that a 1unit increase in trade openness and regulation leads to economic growth of 0.098 unit. 
Consequently, trade openness and the quality of regulation are complementary. In other words, the 

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quality of perceptions of the government capacities to formulate and implement sound policies and 
regulations to encourage the promotion of private sector development enhances the positive effect of 
trade openness on the market. This result matches the work of Koeniger and Silberberger (2015) and 
Mina and Ndikumana (2007).  
Regarding the control variable, aunit increase in the population growth rate leads to 8,389 units of 
economic growth in column (3). This result is consistent with the work of Hanushek and Kimko (2000). 
However, the coefficient associated with public expenditure is negative. A unit increase in the public 
expenditure ratio leads to a decrease in growth respectively of 0.136 unit in column (1); 0.601 unit in 
column (2); 0.603 unit in column (3). These results corroborate with the conclusions of Levine and 
Renelt (1992) and Edwards (1998). Likewise, the coefficient associated with inflation is negative. Aunit 
increase in the public expenditure ratio leads to a decrease in growth by 0.238 unit respectively in 
column (1); 0.197 unit in column (2); 0.188 unit in column (3). These results corroborate with the 
conclusions of Romer (1991). On the other hand, the coefficient associated with the natural resource is 
positive. An increase of 1 unit of natural resource rent results in an increase of 0.191 unit of economic 
growth in column (2). These results corroborate with the conclusion ofMondjeli and Tsopmo (2017).  
5. Conclusion  
This article examined whether the quality of polical institution, espaciallygovernmentefficiency and the 
regulation quality, are likely to strengthen the effect of trade on the economic growth of five Central 
African countries, over the period from 1995 to 2017. To establish this result, we used the econometric 
model of Mankiw and al (1992). Using the dynamic panel GMM method. Firstly, trade openness 
positively affects economic growth. Secondly, government efficiency and the quality of regulation 
reinforce the positive effect of trade openness on economic growth.In order to benefit from growth 
driven by trade openness, government efficiency and the quality of regulation matter.   
References  

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Appendix   
Appendix 1:  Statistics   
Growth Economic  70  5.742603  7.495651  37.99873  

Gov efficiency  70  -1.136766  .3386584  -1.721875  -.394153  
Regulation  70  -.9982445  .3280813  -1.490816  -

.1646162  
Trade openness  70  101.5553  49.73676  37.06518  307.0159  

Population  70  2.794799  .4569652  2.204565  3.832788  

Public expenditure  70  11.11555  3.963983  2.736065  20.58012  

Natural resource  70  46.81607  20.87731  4.51427  80.69243  

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Inflation  70  3.523465  5.948757  -18.07454  20.47896  

Investment  70  29.41983  11.74087  14.298  64.852  

 
Source:Author by WDI and WGI data (2017)  

 
  
  

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