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https://doi.org/10.56556/gssr.v2i4.689 

                                                                  

 
 

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RESEARCH ARTICLE  

Empirical Investigation of Bank Survival and Agro-Production on Economic 

Resilience  

Aroghene Kparobo Gloria1*, Onuorah Anastasia Chi-Chi1  

1Department of Banking and Finance, Delta State University, Abraka, Nigeria   

Corresponding Author: Aroghene Kparobo Gloria: Kparobo-aroghene@delsu.edu.ng  

Received: 05 November, 2023, Accepted: 03 December, 2023, Published: 11 December, 2023  

  

Abstract  

The interaction between bank survival and agro production was used to investigate the extent of economic 

resilience. To achieve the general objectives of the study times series, data from the world bank data base and 

macro trends .net was sorted for the independent variables (bank survival, agro-production and capital formation) 

and the dependent variable (economic resilience) from 2013 through 2021. Different statistical test was conducted 

through the aid of econometric views version 9.0. The study found that BASU, AGPR, and CAPF has an 

insignificant influence on ECRE but only CAPF seem to have a positive relationship with ECRE. The study 

recommended that government authorities should facilitate additions to the fixed assets of the economy plus net 

changes in the level of inventories. The study suggested amongst others that: the variables of the study for further 

research should include other factors like inflation, exchange rate so on that impacts economic resilience; the time 

frame for subsequent research should be adjusted to reflect contemporary events and comparative analysis should 

be embark on say empirical analysis between Nigeria and some other west Africa or Africa countries.  

Key Words:  Bank survival; Agro-production; economic resilience  

  

Introduction  

Nigeria as an open economy is engaged in foreign trade. In its foreign transactions (import & export) of finished 

goods adequate finance is required. Financial institutions, banks in particular offers credits to various economy 

agent comprising individual, firms and government which they invest on productive activities. By providing credit 

to private enterprises and small firms, the banking industry in emerging nations contributes significantly to 

economic growth (Beck & Demirguc-Kunt, 2006; Hoang et al., 2022). The lack of necessary funds for corporate 

operations has a negative impact on output and, as a result, the economy. Economic development and growth, 

according to Aroghene and Akpoyibo (2023), are assessed by increases in the market value of products and 

services produced within a specific economy, as well as income per capita GNP. According to Obamuyi, Edun, 

and Kayode (2009), the sector's poor performance in Nigeria is primarily due to massive imports of finished goods 

and insufficient financial support for the manufacturing sector, which has contributed to a reduction in capacity 

utilization in the country.  

Agricultural sector on the other hand has the potentials to   provide benefits such as conservation, rural 

development as well as management of renewable natural resources. Despite the significant role played by the 

sector in an economy it is still without challenges like every other sector in the economy.  

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Years of poor management, inconsistent and poorly implemented government policies, government indifference, 

and a lack of basic infrastructure have all harmed the agricultural sector. Years of poor management, inconsistent 

and poorly implemented government policies, government indifference, and a lack of basic infrastructure have all 

harmed the agricultural sector. In view of Sabasi et al. (2021), the aforementioned would contribute to 

underproduction of food.  

The role played by banks in any economy together with agriculture cannot be undermined. It is against this 

backdrop that the study investigated the interaction of bank survival BASU measured by Z score, Agro- production 

(AGPR) measured by Agriculture, forestry, and fishing, value added (% of GDP) and  capital formation(CAPF) 

measured by gross capital formation (% of GDP) and economic resilience (ECRE) measured by per capita GDP 

growth   in Nigeria.  

  

For the purpose of the study the following research questions was raised:  

1. Does bank survival (BASU) affects economic resilience (ECRE) in Nigeria?  

2. Does Agro- production (AGPR) affects economic resilience (ECRE) in Nigeria?  

3. Does capital formation (CAPF) affects economic resilience (ECRE) in Nigeria?  

The research questions asked necessitated the following hypothesis in the null form:  

HO1: Bank survival (BASU) does not have effect on economic resilience (ECRE) in Nigeria.  

HO2: Agro- production (AGPR) does not have effect on economic resilience (ECRE) in Nigeria.  

HO3: Capital formation (CAPF) does not have effect on economic resilience (ECRE) in Nigeria.  

  

Literature Review  

Conceptual framework  

Bank Survival and Economic Resilience  

Banks enhance a country's monetary advancement by facilitating the pace of capital arrangement, money and 

credit, and satisfaction of financial goals needed for economic growth.  Access to finance is essential to set up a 

favourable atmosphere for the rate of development of enterprises. Economic growth is the sustained increase in 

per capita national output or net national product over a long period of time (Jones  & Ndubuisi, 2023a). The 

objective of facilitating economy growth would not be achieved if there are disruption in the provision of financial 

activities in the economy. Hence the survival of bank operation is vital to the growth and development of any 

economy. Ehiedu, Onuorah, and Mbagwu (2022) described commercial survival as means of achieving an 

organization mission and vision.  

  

Agro-Production and Economic Resilience  

When the production possibility frontier of an economy shifts outward it is said to be experiencing economic 

growth of which accumulates in a country’s resilience. Jones  and Ndubuisi (2023b) asserted that economic growth 

is the increase in a country’s productive capacity . Imene and Udjo-Onovughakpo (2023) opined that productivity 

in most firm has fallen as a result of recurrent conflict within an organization. Imene (2023) also acclaimed that 



 

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poor productivity and performance is as a result of inadequate evaluation system. As noted by Tochukwu (2012), 

Nigeria's economic future is not looking good due to the country's disregard for the agricultural sector and reliance 

on a monocultural economy centered around crude oil. In a similar vein, the agricultural sector is ideally situated 

to influence any country's pursuit of socioeconomic and industrial growth through its domains of activity at both 

the macro and micro levels. Low productivity levels and the agricultural sector's sluggish growth are thought to 

be the primary reasons behind emerging nations' low incomes and sluggish economic growth (Alston and Pardey, 

2014).  

Gross Capital Formation and Economic Resilience  

Any nation's gross capital formation is made up of expenditures that indicate increases to the economy's fixed 

assets as well as net changes in the amount of inventories. Land improvements (fences, ditches, drains, and the 

like), the acquisition of plant, machinery, and equipment, and the building of roads, railroads, and similar 

structures, such as offices, hospitals, schools, and private residences, are examples of fixed assets. Stocks of goods 

kept by businesses to accommodate sporadic or unforeseen swings in production are known as inventories (World 

Bank, 2023). With adequate amount of capital, productivity of an economic would increase resultant in economic 

resilience of a country.  

Empirical Review  

Gardner (2000)  found a significant positive relation between the growth in the value added per agricultural worker 

and national GDP per capita. Onuorah and Ebimobowei in 2012 affirmed that accountability and public sector 

financial management enhance growth. Spanos and Lioukas (2001) contributed that the focus of performance has 

shifted from industry to firm specific assets . Tsakok and Gardner (2007) examined four distinct nations over four 

distinct time periods to investigate if agricultural development has consistently been a prerequisite for additional 

economic transformation of a nation. They come to the conclusion that economies can change and grow without 

the need for a sophisticated and modern agriculture sector. Gollin et al. (2007) and Self and Grabowski (2007) 

contended that there is proof of a positive correlation between rising agricultural productivity and economic 

expansion.  Musah (2008) indicates that organizational performance should be measured through various 

indicators depending on the organizational structure. Onuorah, Arubayi and Egbule (2020) stressed that employee 

relationship management has become imperative for competitive advantage and improves performance.  Existant 

literatures has showed that certain strategies should be applied by firms/ organisation to boast their return on assets 

which will also impact inclusive growth (Onuorah, 2009; Onuorah, 2010 ; Anayochukwu & Onuorah, 2016; 

Ehiedu, Onuorah & Mbagwu, 2022).  

Awokuse et al. (2009) used real export, agriculture value added per worker, gross capital formation per worker, 

and real GDP per capita as proxies in an effort to study the dynamic interaction between agricultural productivity 

and economic growth.  They said that agriculture functions as an engine for economic development and is a key 

component of economic growth.  People living in poverty can have better access to food and a better quality of 

life thanks to innovations in rural and agricultural finance (Kloeppinger-Todd & Sharma, 2010). Fatima, Khan and 

Arif (2017) opined that in emerging economies, the most influential side is the banking sector because banks 

providing the role of intermediary for trade and business transactions. Qamruzzaman (2017) assessed the 

relationship between institutional innovation and economic growth of Bangladesh and found   that innovation 

either in a financial institution or financial market can    influence economic growth. In order to measure 

organizational performance, Rezaei et al. (2018) proposed using a variety of indicators, including both financial 

and non-financial measurements. Finance is rooted on how well an institution uses financial assets to maximize 

value (Osiegbu, Onuorah & Nnmadi, 2010; Onuorah, 2011; Osiegbu & Onuorah, 2011).  

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According to earlier studies (Asaleye et al., 2020; Kaya & Kadanalı, 2022; Onyiriuba et al., 2020), financing for 

agriculture increases productivity. While the disruption caused by cash shortages affected consumer and corporate 

moods, financial development (FD) can boost industrial activity (Khemani & Kumar, 2022; Aroghene & Imene, 

2023). Furthermore, green FD and green FD development (ED) have a positive correlation (Sadiq et al., 2022).  

Better financial systems are essential for effective economic growth (Wen et al., 2022).  some studies examined 

foreign direct investment, gross capital formation and trade openness as  factors that determine economic resilience 

(Dritsakis ,Varelas and Adamopoulos, 2006; Erhijakpor & Aroghene, 2023), of which was proxied by some 

researchers  by  Per capita GDP (Gardner ,2000; Awokuse et al , 2009)  while some studies proxied bank survival  

by Z-score (Aroghene & Ikeora, 2022; Aroghene, 2022a; Aroghene, 2022b; Aroghene, 2023c).   

From critical investigation of the aforementioned studies, each researcher used variables of particular interest and  

not  all the  investigation were done in Nigeria using specifically the present study variables. This study filled the 

gap in literature by using specifically per capita GDP  as the dependent variable and Agriculture, forestry, and 

fishing, value added (% of GDP) and  gross capital formation (% of GDP) to measure the independent variables.   

Methodology  

In order to account for the interaction between bank survival and Agro- production on economic resilience in 

Nigeria, the study employed  Z- score, Agriculture, forestry, and fishing, value added (% of GDP) and  gross 

capital formation (% of GDP) to measure the independent variables  while per capita  GDP  annual growth rate  

was used to measure the dependent variable. Time series data for Nigeria was obtain  from the world bank data 

base for the period of 2013 through 2021. Different statistical analysis was carried out to investigate the influence 

of the independent variable on the dependent variable using the statistical package Econometric Views version 

9.0. The study  model is stated as ; 

 

ECRE  =  F(BASU, AGPR, CAPF)                                               eqn  (1) 

ECRE  =  b0+b1BASU+b2 AGPR+b3 CAPF+Ut                           eqn  (2)  

  

  

Where;  

ECRE      = Economic Resilience  

b0                     = the intercept  

BASU      = Bank Survival  

AGPR      = Agro- Production 

CAPF       = Capital Formation b1- 

b3              = the coefficient  

Ut               = the error term  

  

  

Results and Discussion  

The data for BASU, AGPR, and CAPF were obtained from World Bank data base while ECRE was obtained from 

macro trends.net are presented below;  

  



 

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   Table 1:   Data presentation: Data for BASU, AGPR ,CAPF and ECRE  

YEAR  BASU   AGPR  CAPF  ECRE  

2013  16.3  20.8  14.9  9.12  

2014  16.4  20  15.8  7.53  

2015  16.8  20.6  15.5  -16.29  

2016  16.4  21  15.4  -19.96  

2017  18.4  20.8  15.5  -9.46  

2018  14.8  21.2  19.8  9.47  

2019  15.4  21.9  25.4  9.79  

2020  13.6  24.1  27.5  -11.11  

2021  12.2  23.4  33.8  -0.43  

  

The results are presented and discussed as follows:  

Table 2:  Summary of Descriptive Statistics  

Variables  Mean   Median  Maximum  Minimum  Std.Dev   Skewness  Kurtosis  JarqueBera  

Prob.  

ECRE  -2.3711  -0.4300  9.7900  -19.9600  11.9983  -0.2462  1.4263   0.6006  

BASU  15.5888  16.3000  18.4000  12.2000  1.8469  -0.4602  2.5821   0.8257  

AGPR  21.5333  21.0000  24.1000  20.0000  1.3647   0.9424  2.5343  0.4933  

CAPF  20.4000  15.8000   33.8000  14.9000   6.8898   0.9181   2.4057  0.4974  

Source: Eviews Extract (2023)  

From the summarised descriptive statistics in table 2, ECRE has a negative mean of 2.3711, max. , min., and Std. 

Dev. value of 9.7900 , -19.9600 and 11.9983 respectively. BASU has mean, max. , mini. and Std. Dev. value of  

15.5888, 18.4000, 12.2000 and 1.8469. More so, AGPR has mean, max. , mini. and Std. Dev. value of 21.5333,  

24.1000, 20.0000 and 1.3647. Likewise, CAPF, AGPR has mean, max. , mini. and Std. Dev. value of20.4000, 

33.8000,  14.9000, and   6.8898. The values for the skewness shows that ECRE and BASU are negatively skewed 

but AGPR and CAPF are positively skewed. The value for the kurtosis showed that the variables are platokurtic. 

The Jarque- Bera Prob. values for all the variables indicated that the data set are normally distributed.  

 

Table 3: Correlation Analysis  

  ECRE  BASU  AGPR  CAPF  

ECRE   1.000000        

BASU  -0.201293   1.000000      

AGPR  -0.109413  -0.824554   1.000000   0.893217  

CAPF   0.150911  -0.897938   0.893217   1.000000  

Source: Eviews Extract (2023).  

Table 3 showed values of correlation of the variables. BASU and  AGPR showed negative correlation with ECRE. 

While CAPF had a positive correlation with ECRE. The correlation values indicates that there existed weak 

correlation between the study variable.  



 

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Table 4: Heteroskedasticity Test: Breusch-Pagan-Godfrey  

    
       

 F-statistic 0.545840      Prob. F(3,5)  0.6721  

 Obs*R-squared  2.220359      Prob. Chi-Square(3)  0.5279  

 Scaled explained SS  0.289769      Prob. Chi-Square(3)  0.9619  

    
       

Source: Eviews Extract (2023).  

The Prob. Chi-square (3) value  of 0.5279 greater than 0.05 indicated that the variables of the study is 

homoscedastic. Hence the assumption of heteroskedascity of the variables is therefore refuted.  

 

Table 5: Summary of Augumented Dicker-Fuller Unit Root Test  

Variables  T-Statistics  Order of Intergration Probability  Decision  

ECRE  -3.284560  1(0)  0.0578  Stationary  

BASU  0.591554  1(0)  0.9746  Non-Stationary  

AGPR  -0.450937  1(0)  0.8533  Non-Stationary  

CAPF  1.951757  1(0)  0.9985  Non-Stationary  

                                                                  @ First Difference   

ECRE  -3.707583  1(1)   0.0036  Stationary  

BASU  -3.953141  1(1)    0.0260  Stationary  

AGPR  -3.259319  1(1)  0.0596  Stationary  

CAPF  -0.276254  1(1)  0.5497  Non-Stationary  

Source: Eviews Extract (2023).  

 

Table 5 showed the values for the summarised Augumented Dicker-Fuller unit root test. In the table only ECRE  

was stationary at level and at first difference. BASU, AGPRand CAPF were stationary at first difference only  

CAPF was non stationary but at level and at first difference.  

From the summarised regressed result, BASU has a negative coefficient value of 3.1586, t-Statistic of -0.595636 

with prob. value of 0.5774. The coefficient depicts an inverse relationship whereas the prob. value confirm that 

BASU has an insignificant impact on ECRE. Similarly, AGPR, has a   negative coefficient value of 11.0959, 

tStatistic of -1.5795 prob. value of 0.1751. The relationship is converse while the influence is insignificant. Also, 

CAPF possessed positive relationship with coefficient value of 1.4657 and an insignificant value of 0.4498. The 

R-square showed that 36% change in ECRE is explained by BASU, AGPR, and CAPF. The remainder of 64% 

could be accounted for by other factors that influence ECRE not included in the study model.  

      

      



 

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Table 6: Summary of Regression Results  

Dependent Variable: ECRE        

  

Variable  

  

  

Coefficient  

  

  

Std. Error  

  

  

t-Statistic  

  

  

Prob.    

  

  

C  

  

255.9004  

  

175.9584  

  

1.454324  

  

0.2056  

BASU  -3.158628  5.302953  -0.595636  0.5774  

AGPR  -11.09591  7.024894  -1.579512  0.1751  

CAPF  

  

1.465678  

  

1.788770  

  

0.819377  

  

0.4498  

  

  

R-squared  

  

  

  

0.362973  

  

  

    

         Adjusted R-squared  

    

    

  

-0.019242  

  

  

Source: Eviews Extract (2023).  

  

 

Conclusion and Recommendation  

  

From the analysis of the influence of BASU, AGPR, and CAPF on ECRE, the results showed that the regressors 

had an insignificant effect on the regress and only CAPF had a positive relationship with ECRE. The study 

recommend that government should facilitate additions to the fixed assets of the economy plus net changes in the 

level of inventories.  

  

Declaration  

 

Authors declared that this work is as a result of their research efforts.  

  

Acknowledgment: All members of staff of the department of banking and  finance Delta State University are 

acknowledged  

  

Funding: No funding received 

  

Conflict of interest: No conflict of interest   

  

Authors contribution: All the authors contributed meaningfully to the actualization of the work  

  

Data availability:  To be provided on request 

   

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https://www.researchgate.net/publication/320329665
https://www.researchgate.net/publication/320329665

