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Financial Deepening and Economic Growth in Nigeria (1986 – 2022)
- Faith Okete
- Okuma N. Camillus, PhD, LLB
- 204-216
- Nov 27, 2024
- Finance
Financial Deepening and Economic Growth in Nigeria (1986 – 2022)
Faith Okete and Okuma N. Camillus, PhD, LLB
Department of Banking and Finance, Madonna University Nigeria
DOI: https://dx.doi.org/10.47772/IJRISS.2024.81100017
Received: 14 October 2024; Accepted: 22 October 2024; Published: 27 November 2024
ABSTRACT
This paper examined the financial deepening on economic growth in Nigeria. Adopting the supply-leading hypothesis using variables such as money supply, credit to private sector, inflation rate, market capitalization and prime lending rate as proxies for financial deepening and real gross domestic product growth rate for economic growth, we found that credit to private sector and market capitalization promote economic growth in Nigeria while money supply, inflation rate and prime lending rate did not within the period studied (1986-2022). Expanding the financial sector allows financial intermediaries to carry out functionalities of deploying, aggregating and directing a country’s savings into an investment which contributes to domestic progression. Data was obtained from CBN bulletin different issues and analyzed using Autoregressive Distributed Lag. From the result of analysis, we found out that long run relationship existed but no regressor was found to be significant. Credit to the private sector and market capitalization to RGDP had positive relations with economic growth, whereas money supply, inflation rate and prime lending rate to GDP had positive relations with economic growth rate. Government policy should therefore be geared towards strategically increasing money supply and promoting efficient capital market that will enhance overall economic efficiency, create and expand liquidity, mobilize savings, enhance capital accumulation, transfer resources from traditional sectors to growth inducing sectors (such as manufacturing and industry, agriculture and the services sectors) and also promote competent entrepreneurial response in various sectors of the economy. Policies favoring credit lending to the private sector should be encouraged by stakeholders in the economy, for instance, higher savings interest rates would encourage more savings. Raising the interest provided to depositors on their savings will serve as a perk to attract customers to save more money with commercial banks, savings and borrowing for investments will be encouraged as a result.
Keywords: Real Gross Domestic Product, Money Supply, Credit to Private Sector, Inflation Rate and Prime Lending Rate
INTRODUCTION
Background of The Study
Financial deepening is the term for a rise in an economy’s supply of financial assets. Due to the undeniable importance of the development of the financial sector for economic growth, the relationship between financial deepening and economic growth has received attention in financial literature and has been widely acknowledged. Financial deepening implies that financial organizations can efficiently utilize savings for investments through financial intermediation by enhancing the competitive efficacy of financial markets. It is a comprehensive process that involves the intersection of primary, secondary and retail markets, as well as financial instruments (Ademola and Marshal, 2018).
Economic growth and development is the sole desire of every economy. Economic growth can be defined as thecontinuous process through which the productive capacity of the economy is increased over a period time toachieve rising degrees of publicly yield and pay (Anachedo 2021).
Undoubtedly, the degree of financial system development affects how much money can be raised from surplus economic units and channeled to productive deficit units. The financial organizations assume this intermediation role and draw in the pool of savings and non-performing funds, channeling them to business owners, consumers, governments, and other essential endeavors in the hopes of making a profit (profit). This helps in improving economic circumstances through increased financial market competition and, as a result, indirectly benefits non-financial sectors of the economy. Since the contributions of financial deepening to the Nigerian economy include expanding the base of available resources and providing the capital needed to promote savings and credit investment, it has led to the implementation of efficient mediations and programmes in the Nigerian banking industry and as posited by Nwanna and Chiwundu (2016), these programmes have contributed directly to the ongoing improvement of financial assets
Disinvestment in the financial and real sectors due to frequent policy changes has had a negative impact on macroeconomic performance. This calls for a heightened focus on financial inclusion and accessibility and the need to assess the financial sector’s deepening impact on economic performance in Nigeria becomes necessary taking into account the fact that financial deepening measures intended to improve bank performance have remained pale and are still the subject of continued debate. This has not been helped by the recent downturn in the financial market, distress of banks, global economic and financial meltdown, and fluctuating economic growth over years. Therefore, the goal of this study is to assess the relationship between financial deepening and economic growth from 1986-2022. However, the choice of this period was basically a result of the SAP liberalization policy implemented in 1986.
RESEARCH OBJECTIVES
The main objective of this study is to examine the impact of financial deepening indicators on the economic growth of Nigeria. The specific objectives are as follows to;
- Examine the impact of broad money supply on the economic growth.
- Determine the impact of credit to private sector on the economic growth.
- Find out the impact of market capitalization on the economic growth.
- Analyze the impact of inflation rate on the economic growth.
- Explore the impact of prime lending rate on the economic growth.
LITERATURE REVIEW
This section looks at relevant literature, theoretical framework and empirical studies surrounding the relationship between financial deepening and economic growth in Nigeria.
Theoretical Framework
Mckinnon/Shaw Theory
The McKinnon (1973) and Shaw (1973) frameworks, popularized the idea of financial deepening and the need to ease financial repression by, among other things, removing credit controls and allowing market-determined real interest rates to be set. Low savings, high consumption, low investments, and suppressed economic growth are the results of repression. According to McKinnon and Shaw models, any restriction or distortion of the banking industry, such as reserve and liquidity requirements, interest rate regulations impede financial expansion primarily by driving down interest rates (Capannelli, Lee and Petri, 2009). The models contend that the increase in real interest rates brought on by interest rate liberalization will increase savings, stimulate investment, and ultimately lead to an expansion of the economy. Therefore, the McKinnon-Shaw approach is focused on market distortions brought on by financial repression which has a disadvantageous effect on financial development and subsequently on bank performance. Mckinnon and Shaw thus advocated for financial deepening as a tool needed by emerging countries to expand their financial sector in order to boost their real growth (Orji 2015).
Financial deepening will encourage economic growth by increasing savings through a rise in the real deposit rate and by increasing private investment in important economic sectors. As a result, the McKinnon and Shaw framework contends that removing interest rate and credit control restrictions as well as other restrictive financial laws is necessary for an economy to enjoy economic growth through more effective capital accumulation and allocation.
Based on these theoretical views and following Khan (2005) and Khan and Qayyum (2006), the relationship between economic growth and financial development can be specified as:
RGDP = f (MS,CPS,MC,INF,PLR)
EMPIRICAL REVIEWS
OzohandMounanu (2012) explored financial deepening influences on Nigeria’s growth from 1992 to 2008 using supply-leading hypothesis and variables of broad money velocity, money stock diversity, market liquidity, economic volatility and market capitalization. It was affirmed that market liquidity and broad money velocity aid Nigerian growth whereas market capitalisation, economic volatility and money stock diversification had reverse effects. Therefore, it was proffered that government policies should aim to increase money supply and boost efficient capital markets for general economic effectiveness, creation and expansion of liquidity, savings mobilization, higher capital accumulation and greater transferred finances from stereotyped to growth-stimulating industries.
Chukwu and Agu (2009) adopted a multivariate Vector Error Correction Model (VECM) in ascertaining the direction of causality between four indicators of financial depth and economic growth in Nigeria from 1971 to 2008. Financial deepening proxies utilised included the ratio of broad money supply (M2) to RGDP, the ratio of private sector credit to RGDP, loan to deposits ratio and the ratio of bank deposit liabilities to RGDP. Findings from this study showed that, using private sector credit and real broad money supply as proxies, the demand-following hypothesis was supported. Also, supply-leading hypothesis was supported when the ratio of loan to total deposits, and bank deposit liabilities, were used. The study, therefore, underscored that the choice of financial depth indicator/proxy determines the direction of causality with economic growth.
Marbuah and Mensah (2013) researched long run influences of financial deepening on Ghanaian economy via dataset from 1998 to 2011. Private sector credit ratio to RGDP, total domestic credit ration, aggregate bank liabilities ratio, money supply ratio to RGDP were utilized in measuring financial deepening with control variables of real gross government expenditure, trade openness and inflation rate. Despite using several variables measures, the observation/data time frame is inadequate to yield statistically significance for each variable, and this questions their findings, which could be spurious as a result.
The study by Nzotta and Okereke (2009) concluded that the level of financial deepening in Nigerian has remained relatively low in spite of the various reforms and institutional changes put in place by the monetary authorities. To them, it is also evident that the low level of monetization of the economy, the high rate of inflation and the level of private sector credits has negatively affected the level of financial deepening in Nigerian. They observed that although the level of interest rates has remained very high, the level of private sector credits has not sustained the desired level of new investments necessary to facilitate growth in the economy.
While investigating the impact of financial deepening from the stock market perspective using the Generalized Autoregressive Conditional Heteroscedasticity (GACH) model, Nwezeaku and Okpara (2010) found out that a high degree of financial deepening reduces significantly the level of risk (volatility) in the stock market.
Ghildiyal, Pokhriyal and Mohan (2015) investigated the causal effect of financial deepening on Indian economic growth using the Autoregressive Distributed Lag (ARDL) Bound testing strategy and the Granger Error Correction Model (ECM) technique. The study found that there is a long-term relationship between financial development and economic growth. Additionally, the study demonstrated that financial deepening promotes economic growth both in the long run and the short run, and suggested improvement in the financial deepening.
Kibet and Agbelenko (2015) evaluated the relationship between financial development and economic growth in the West African Economic and Monetary Union using time series data from 1981–2010 while applying the General Moment Method (GMM). They came to the conclusion that there is a bidirectional causal relationship between financial development and economic growth that is positive and statistically significant. They recommended pursuing policies that would manage inflation and promote trade openness while luring foreign direct investments. In their study, Karimo and Ogbonna (2017) examined the relationship between financial deepening and economic growth in Nigeria between 1970 and 2013.
Herman and Klemm (2019) examined financial deepening effects in Mexico from 2007 to 2015 through disequilibrium regression approach. The study discovered that supply influences are specifically vital in determining Mexican loans. Contemporary policies tackle most supply limitations although their degree of successful outcomes is contingent upon proper enactment. The major issue future-wise is with facilitating financial deepening and simultaneously restricting the riskiness of monetary stabilization.
Vipin and Arvind (2015) researched on the dimension to which financial deepening affects India’s growth from 1990-2014. Autoregressive distributed lag and bound test was utilized to analyse the long-term relations between the variables. Granger Error Correction Model (ECM) approach was also implemented to approximate short-run causal effect. Results imply that long run equilibrium connection is existent. Additionally, financial deepness was seen to trigger national growth both on short and long run basis. Thus, it was inferred that governmental bodies must consciously endeavor to enhance financial deepening so as to spur societal progression. Specialized attempts should be made to supply stress-free lending to private enterprises, advancing stock markets and fostering international trade.
RESEARCH METHODOLOGY
The study examines the impact of macroeconomic variables on the performance of capital market in Nigeria.
The ex-post factor research method was employed using quantitative secondary data obtained from various sources like the Nigerian Stock Exchange (NSE) Bulletin, Securities and Exchange Commission (SEC) bulletin and Central Bank of Nigeria (CBN) Statistical bulletin. The unit root tests were conducted on the data obtained to confirm stationarity of the variables at levels. This was a preliminary test meant to ascertain data stability.
Model Specification
Regression model using ordinary least square technique (OLS) is an essential econometric technique as it can be used in a wide range of applications to examine the various variables used. The theory on which the study was anchored is Mckinnon/Shaw Theory. Log transpose form was adopted in the analysis using Excel software. This study has adopted a growth model which specifies that growth is a function of; money supply, credit to private sector, market capitalization, inflation rate and prime lending rate.
RGDP = F (MS, CPS, MC, INF, PLR)
Where:
RGDP = Real Gross Domestic Product
MS = Money Supply
CPS = Credit to Private Sector
MC = Market Capitalization
INF = Inflation
PLR = Prime Lending Rate
In clear terms, the econometric model is specified below:
D(LGDP) C D(LRGDP(-1)) D(LRGDP(-2)) D(LMS(-1)) D(LMS(-2)) D(LCPS(-1)) D(LCPS(-2)) D(LMC(-1)) D(LMC(-2)) D(LIFR(-1)) D(LIFR(-2)) D(LPLR(-1)) D(LPLR(-2)) LRGDP(-1) LMS(-1) LCPS(-1) LMC(-1) LIFR(-1) LPLR(-1)
Where:
RGDP = Real Gross Domestic Product
b0 = Regression Constant
b1, b2, b3, b4, b5 = Regression parameters
U = error term
Method of Data Analysis
The study employs econometric analyses such as Unit root, OLS regression, co-integration and Error Correction Model (ECM).
Data Presentation and Analysis
Real Gross Domestic Product, Money Supply, Credit to Private Sector, Inflation Rate and Prime Lending Rate Data for Nigeria in N’bn (1999-2021)
Table 4.1: Array of Data for the Dependent And Independent Variables
Year | RGDP | MS | CPS | MC | IFR | PLR |
1986 | 198.12 | 23.81 | 15.25 | 6.8 | 5.73 | 10.5 |
1987 | 244.68 | 27.57 | 21.08 | 8.2 | 11.29 | 17.5 |
1988 | 315.62 | 38.36 | 27.33 | 10 | 54.51 | 16.5 |
1989 | 414.86 | 45.9 | 30.4 | 12.8 | 50.47 | 26.8 |
1990 | 494.64 | 47.42 | 33.55 | 16.3 | 7.36 | 25.5 |
1991 | 590.06 | 75.4 | 41.35 | 23.1 | 13.01 | 20.01 |
1992 | 906.03 | 111.11 | 58.12 | 31.2 | 44.59 | 29.8 |
1993 | 1,257.17 | 165.34 | 127.12 | 47.5 | 57.17 | 18.32 |
1994 | 1,768.79 | 230.29 | 143.42 | 66.3 | 57.03 | 21 |
1995 | 3,100.24 | 289.09 | 180 | 180.4 | 72.84 | 20.18 |
1996 | 4,086.07 | 345.85 | 238.6 | 285.8 | 29.27 | 19.74 |
1997 | 4,418.71 | 413.28 | 316.21 | 281.9 | 8.53 | 13.54 |
1998 | 4,805.16 | 488.15 | 351.96 | 262.6 | 10 | 18.29 |
1999 | 5,482.35 | 628.95 | 431.17 | 300 | 6.62 | 21.32 |
2000 | 7,062.75 | 878.46 | 530.37 | 472.3 | 6.93 | 17.98 |
2001 | 8,234.49 | 1,269.32 | 764.96 | 662.5 | 18.87 | 18.29 |
2002 | 11,501.45 | 1,505.96 | 930.49 | 764.9 | 12.88 | 24.85 |
2003 | 13,556.97 | 1,952.92 | 1,096.54 | 1,359.30 | 14.03 | 20.71 |
2004 | 18,124.06 | 2,131.82 | 1,421.66 | 2,112.50 | 15 | 19.18 |
2005 | 23,121.88 | 2,637.91 | 1,838.39 | 2,900.06 | 17.86 | 17.95 |
2006 | 30,375.18 | 3,797.91 | 2,290.62 | 5,120.90 | 8.23 | 17.26 |
2007 | 34,675.94 | 5,127.40 | 3,668.66 | 13,181.69 | 5.39 | 16.94 |
2008 | 39,954.21 | 8,643.43 | 7,899.14 | 9,562.97 | 11.58 | 15.14 |
2009 | 43,461.46 | 9,687.51 | 9,889.58 | 7,030.84 | 12.54 | 18.99 |
2010 | 55,469.35 | 11,101.46 | 10,518.17 | 9,918.21 | 13.74 | 17.59 |
2011 | 63,713.36 | 12,628.32 | 9,600.02 | 10,275.34 | 10.83 | 16.02 |
2012 | 72,599.63 | 15,503.41 | 13,293.64 | 14,800.94 | 12.22 | 16.79 |
2013 | 81,009.96 | 18,743.07 | 14,461.41 | 19,077.42 | 8.5 | 16.72 |
2014 | 90,136.98 | 20,415.61 | 16,753.00 | 16,875.10 | 8.05 | 16.55 |
2015 | 95,177.74 | 20,885.52 | 18,688.42 | 17,003.39 | 9.01 | 16.85 |
2016 | 102,575.42 | 24,259.00 | 21,025.24 | 16,185.73 | 15.7 | 16.87 |
2017 | 114,899.25 | 28,604.47 | 22,459.18 | 21,128.90 | 16.5 | 17.56 |
2018 | 129,086.91 | 29,774.43 | 22,646.33 | 21,904.04 | 12.1 | 19.33 |
2019 | 145,639.14 | 34,257.90 | 25,676.87 | 25,890.22 | 11.4 | 15.53 |
2020 | 154,252.32 | 36,038.01 | 29,030.01 | 38,589.58 | 13.25 | 12.32 |
2021 | 176,075.50 | 40,318.29 | 32,868.49 | 42,054.50 | 16.95 | 11.48 |
2022 | 202,365.03 | 48,462.07 | 38,952.43 | 51,188.87 | 18.85 | 12.34 |
Source: CBN Statistical Bulletin various years
Table 4.2: Log Transpose
Year | LOGRGDP | LOGMS | LOGCPS | LOGMC | LOGIFR | LOGPLR |
1986 | 2.296928 | 1.376759 | 1.18327 | 0.832509 | 0.758155 | 1.021189 |
1987 | 2.388598 | 1.440437 | 1.323871 | 0.913814 | 1.052694 | 1.243038 |
1988 | 2.499165 | 1.583879 | 1.43664 | 1 | 1.736476 | 1.217484 |
1989 | 2.617902 | 1.661813 | 1.482874 | 1.10721 | 1.703033 | 1.428135 |
1990 | 2.694289 | 1.675962 | 1.525693 | 1.212188 | 0.866878 | 1.40654 |
1991 | 2.770896 | 1.877371 | 1.616476 | 1.363612 | 1.114277 | 1.301247 |
1992 | 2.957143 | 2.045753 | 1.764326 | 1.494155 | 1.649237 | 1.474216 |
1993 | 3.099394 | 2.218378 | 2.104214 | 1.676694 | 1.757168 | 1.262925 |
1994 | 3.247676 | 2.362275 | 2.15661 | 1.821514 | 1.756103 | 1.322219 |
1995 | 3.491395 | 2.461033 | 2.255273 | 2.256237 | 1.86237 | 1.304921 |
1996 | 3.611306 | 2.538888 | 2.37767 | 2.456062 | 1.466423 | 1.295347 |
1997 | 3.645295 | 2.616244 | 2.499976 | 2.450095 | 0.930949 | 1.131619 |
1998 | 3.681708 | 2.688553 | 2.546493 | 2.419295 | 1 | 1.262214 |
1999 | 3.738967 | 2.798616 | 2.634649 | 2.477121 | 0.820858 | 1.328787 |
2000 | 3.848974 | 2.943722 | 2.724579 | 2.674218 | 0.840733 | 1.25479 |
2001 | 3.915637 | 3.103571 | 2.883639 | 2.821186 | 1.275772 | 1.262214 |
2002 | 4.060753 | 3.177813 | 2.968712 | 2.883605 | 1.109916 | 1.395326 |
2003 | 4.132163 | 3.290684 | 3.040024 | 3.133315 | 1.147058 | 1.31618 |
2004 | 4.258255 | 3.328751 | 3.152796 | 3.324797 | 1.176091 | 1.282849 |
2005 | 4.364023 | 3.42126 | 3.264438 | 3.462407 | 1.251881 | 1.254064 |
2006 | 4.482519 | 3.579545 | 3.359953 | 3.709346 | 0.9154 | 1.237041 |
2007 | 4.540028 | 3.709897 | 3.564507 | 4.119971 | 0.731589 | 1.228913 |
2008 | 4.601563 | 3.936686 | 3.89758 | 3.980593 | 1.063709 | 1.180126 |
2009 | 4.638104 | 3.986212 | 3.995178 | 3.847007 | 1.098298 | 1.278525 |
2010 | 4.744053 | 4.04538 | 4.02194 | 3.996433 | 1.137987 | 1.245266 |
2011 | 4.804231 | 4.101346 | 3.982272 | 4.011796 | 1.034628 | 1.204663 |
2012 | 4.860934 | 4.190427 | 4.123644 | 4.170289 | 1.087071 | 1.225051 |
2013 | 4.908538 | 4.272841 | 4.160211 | 4.28052 | 0.929419 | 1.223236 |
2014 | 4.954903 | 4.309962 | 4.224093 | 4.227246 | 0.905796 | 1.218798 |
2015 | 4.978535 | 4.319845 | 4.271573 | 4.230536 | 0.954725 | 1.2266 |
2016 | 5.011043 | 4.384873 | 4.322741 | 4.209132 | 1.1959 | 1.227115 |
2017 | 5.060317 | 4.456434 | 4.351394 | 4.324877 | 1.217484 | 1.244525 |
2018 | 5.110882 | 4.473843 | 4.354998 | 4.340524 | 1.082785 | 1.286232 |
2019 | 5.163278 | 4.534761 | 4.409542 | 4.413136 | 1.056905 | 1.191171 |
2020 | 5.188232 | 4.556761 | 4.462847 | 4.58647 | 1.122216 | 1.090611 |
2021 | 5.245699 | 4.605502 | 4.51678 | 4.623812 | 1.22917 | 1.059942 |
2022 | 5.306135 | 4.685402 | 4.590535 | 4.709176 | 1.275311 | 1.091315 |
Source: Excel software
Data of The Descriptive Statistics
The data presented above was analyzed using multiple regressions with the aid of E-view because of the volume of data and to ensure accuracy in computation. The attempt to study the relationship between financial deepening and economic growth in Nigeria led the researcher to subject the data collected to Unit Root test, Johansen Cointegration test and Vector Error Correction Model. The variables considered in this research work are: Real Gross Domestic Product (RGDP) which is the dependent variable and the independent variables are money supply (MS), credit to private sector (CPS), market capitalization (MC), prime lending rate (PLR) and inflation rate (IR). The empirical results are presented below as generated from the analysis:
Result of Unit Root Test
VARIABLES | ADF TEST STATISTICS AT LEVEL | 5% CRITICAL VALUES | LEVEL OF INTEGRATION | REMARKS |
RGDP | -4.0595 | -2.9458 | I (0) | Stationary @ Level |
MS | -4.0956 | -2.9484 | I (1) | Stationary @ 1st Diff. |
CPS | -4.4068 | -2.9484 | I (1) | Stationary @ 1st Diff. |
MC | -4.6816 | -2.9484 | I (1) | Stationary @ 1st Diff. |
IFR | -3.9031 | -2.9484 | I (0) | Stationary @ Level |
PLR | -3.8442 | -2.9458 | I (0) | Stationary @ Level |
Source: E-view Output
In the unit root test result above, the ADF statistics reveals RGDP, IFR and PLR are stationary at level (Order one) while MS, CPS and MC were stationary at first difference. This implies that the series are integrated (stationary) at different order of integration (i.e order I(0) and I(1). We therefore affirm that the variables have statistical properties that are constant and do not change over the time period under study. Based on the above result, ARDL model is deemed appropriate for analyzing the data set since all the variable were stationary at different order of integration.
Result for Ardl Model
Table 4.5: Ardl Modelestimates
Dependent Variable: D(LRGDP) | ||||
Method: Least Squares | ||||
Date: 07/16/24 Time: 06:26 | ||||
Sample (adjusted): 1989-2022 | ||||
Included observations: 34 after adjustments | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | -0.256181 | 0.452752 | -0.565832 | 0.5799 |
D(LRGDP(-1)) | -0.092095 | 0.382359 | -0.240861 | 0.8129 |
D(LRGDP(-2)) | -0.008064 | 0.355581 | -0.022680 | 0.9822 |
D(LMS(-1)) | -0.047300 | 0.297145 | -0.159182 | 0.8756 |
D(LMS(-2)) | -0.167127 | 0.278978 | -0.599069 | 0.5581 |
D(LCPS(-1)) | 0.019350 | 0.226091 | 2.485585 | 0.0329 |
D(LCPS(-2)) | 0.344260 | 0.144841 | 2.376812 | 0.0312 |
D(LMC(-1)) | 0.165501 | 0.138183 | 1.197693 | 0.2496 |
D(LMC(-2)) | -0.027913 | 0.108550 | -0.257139 | 0.8006 |
D(LIFR(-1)) | 0.050731 | 0.048675 | 1.042233 | 0.3138 |
D(LIFR(-2)) | -0.002088 | 0.040340 | -0.051765 | 0.9594 |
D(LPLR(-1)) | -0.235827 | 0.209256 | -1.126980 | 0.2775 |
D(LPLR(-2)) | -0.163225 | 0.115593 | -1.412072 | 0.1783 |
LRGDP(-1) | -0.030420 | 0.198904 | -0.152936 | 0.8805 |
LMS(-1) | 0.217535 | 0.367760 | 0.591515 | 0.5630 |
LCPS(-1) | -0.104540 | 0.297499 | -0.351396 | 0.7302 |
LMC(-1) | -0.085392 | 0.128100 | -0.666601 | 0.5152 |
LIFR(-1) | -0.003649 | 0.084496 | -0.043182 | 0.9661 |
LPLR(-1) | 0.257165 | 0.216858 | 1.185867 | 0.2541 |
R-squared | 0.802814 | Mean dependent var | 0.082558 | |
Adjusted R-squared | 0.566191 | S.D. dependent var | 0.049901 | |
S.E. of regression | 0.032867 | Akaike info criterion | -3.693371 | |
Sum squared resid | 0.016203 | Schwarz criterion | -2.840405 | |
Log likelihood | 81.78731 | Hannan-Quinn criter. | -3.402485 | |
F-statistic | 3.392795 | Durbin-Watson stat | 2.648090 | |
Prob(F-statistic) | 0.010423 |
INTERPRETATION AND DISCUSSION OF MODEL RESULTS
The relationship between money supply and Economic Growth
Money supply (MS) has negative and insignificant effect on economic growth rate (GDP) in Lag 1 & 2. This inverse relationship implies that a percentage increase in the slope of MS will result to a corresponding decrease in economic growth to the tune of –0.047300 and -0.167127 for lag 1&2 respectively.
The relationship between Credit to private sector and Economic Growth
Credit to private sector was found to be (CPS) positive and has significant effect on economic growth (GDP) in lag 2. This direct relationship implies that a percentage increase in the slope of CPS will result to a corresponding increase in economic growth to the tune of 0.019350 and 0.344260 for lag 1 and 2 respectively
The relationship between MC and Economic Growth
MC revealed a positive coefficient in lag 1 and negative coefficient in lag 2. MC was found to be statistically insignificant with economic growth (GDP). This inverse relationship implies that a percentage increase in the slope of MC will result to a corresponding decrease in economic growth to the tune of -0.027913 in lag 2 while reverse is the case with lag 1
The relationship between Inflation rate and Economic Growth
Inflation rate revealed a positive coefficient in lag 1 and negative coefficient in lag 2. Inflation rate was found to be statistically insignificant with economic growth (GDP). This inverse relationship implies that a percentage increase in the slope of IFR will result to a corresponding decrease in economic growth to the tune of -0.002088 in lag 2 while reverse is the case with lag 1
The relationship between Prime lending rate and Economic Growth
Prime lending rate was found to be (PLR) negative and has insignificant effect on economic growth (GDP). This inverse relationship implies that a percentage increase in the slope of prime lending rate will result to a corresponding decrease in economic growth to the tune of -0.163225 and -0.030420 for lag 1 and 2 respectively
TEST OF HYPOTHESES
Test of hypothesis one
Ho1: There is no significant relationship between broad money supply and economic growth in Nigeria.
From table 4.5, the P-value of MS was obtained as 0.8756 and 0.5581 for lag 1 & 2, which is greater than the critical value at 5% (0.05). this implies that money supply has no significant effect on Nigeria’s economic growth
Test of hypothesis two
Ho2: There is no significant relationship between credit to private sector and economic growth in Nigeria.
From table 4.5, the P-value of CPS was obtained as 0.0329 and 0.0312 which is less than the critical value at 5% (0.05). this implies credit to private sector has a significant effect on Nigeria’s economic growth
Test of hypothesis three
Ho3: There is no significant relationship between market capitalization and economic growth in Nigeria.
From table 4.5, the P-value of market capitalization was obtained as 0.2496 and 0.8006 for lag 1 & 2 respectively, which is greater than the critical value at 5% (0.05). this implies market capitalization has no significant effect on Nigeria’s economic growth.
Test of hypothesis four
Ho4: There is no significant relationship between inflation rate and economic growth in Nigeria.
From table 4.5, the P-value of inflation rate was obtained as 0.3138 and 0.9594 for lag 1 & 2 respectively, which is greater than the critical value at 5% (0.05). this implies inflation rate has no significant effect on Nigeria’s economic growth.
Test of hypothesis five
Ho5: There is no significant relationship between prime lending rate and economic growth in Nigeria.
From table 4.5, the P-value of prime lending rate was obtained as 0.2775 and 0.1783 for lag 1 & 2 respectively, which is greater than the critical value at 5% (0.05). this implies prime lending rate has no significant effect on Nigeria’s economic growth.
CONCLUSION AND RECOMMENDATIONS
Conclusion
This paper intended to analyze the influences of financial deepening on Nigeria’s growth. Key objectives were to ascertain the relationship between money supply to GDP and economic growth; impact of credit to the private sector to GDP on economic growth; and effects of time deposit and savings of commercial banks on Nigerian growth. In chapter two, literatures were reviewed on conceptual issues of financial deepening and economic growth as well as their linkages. Afterward, the theory of mckinnon/shaw 1973 on financial deepening was adopted. Empirical works were reviewed of which both negative and positive relationships were discovered for different measures of financial deepening and RGDP. The third section introduced the methodology which constituted yearly time series secondary data from CBN Statistics.
Financial deepening is an imperative for frontier and developing Nigeria for several reasons. First, financial development can drive economic growth in the economy. Second, better financial services will allow firms and households to reduce transaction costs and provide opportunities for smoothing income, thus reducing poverty and income inequality. Third, financial deepening can help strengthen the economy resilience and capacity to cope with shocks and mitigate macroeconomic volatility.
Recommendations
Nigeria has deepened by more than would have been expected from their structural characteristics alone, implying risks to stability. Rapid deepening can fuel credit and asset price booms and destabilize an economy, particularly absent appropriate financial oversight and policies.
To maximize the benefits, Nigeria efforts and actions to deepen and broaden the financial system and increase access to financial services should be centered around three interrelated pillars:
(1) Policies to ensure stable macroeconomic environments. Policies favoring credit lending to the private sector should be encouraged by Nigerian economy, for instance, higher lending interest rates would encourage savings. More importantly, policies should be enacted to make sure that savings are transmitted into productive investments that can yield financial deepening. Savings and time deposits should also be encouraged in commercial banks to motivate cashless banking and economy. This will aid financial intermediation that will eventually translate into economic growth.
(2) Institutional and infrastructure reforms to create enabling frameworks for markets and private initiatives.
(3) Regulatory and oversight policies to address inefficiencies and risks generated by markets and market players.
(4) Government policies should also be geared towards increasing money supply and efficient capital market that will enhance overall economic efficiency, increase investor confidence, create and expand liquidity, mobilize savings, enhance capital accumulation, transfer resources from traditional sectors to growth inducing sectors and also to promote competent entrepreneurial response in various sectors of the economy.
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