This research plan is prepared to find out the impact of savings deposit rate on security market capitalization in Nigeria. The inquiry plan employed monthly data between January 2016 and December 2019. The data were collected from the publications of the National Bureau of Statistics (NBS) and Central Bank of Nigeria (CBN). Variables on which data were sourced are stock market capitalization (MCAP), savings deposit rate (SDR) and bank lending rate (BLR) as a control variable. The data analysis was done via descriptive tools, Johansen cointegration test, ADF test of unit root and regression procedure. The investigation discovered a significant inverse association among savings deposit rate and security market capitalization. The research also discovered insignificant negative link between bank lending rate and stock market capitalization in Nigeria. The overall equation judging from the R2, Durbin-Watson statistics and F-statistics is significant. It is thus recommended that, at anytime the country intend to raise the level of stock market capitalization, government should formulate and implement policies to reduce savings deposit rate in Nigeria. Government should also implement policies to reduce bank lending rate to boast economic growth and as well raise the level of stock market capitalization in Nigeria.
Keywords: Stock market capitalization, Savings deposit rate, Bank lending rate, Descriptive statistics, Johansen cointegration test, ADF unit root test, Regression method.
JEL Classification: G10, G12, G18, G19, G20.
Received: 5 March 2020 / Revised: 9 April 2020 / Accepted: 11 May 2020/ Published: 1 June 2020
This study is one of very few studies which have investigated the effect of savings deposit rate on stock market capitalization in Nigeria. This study contributes in the existing literature is to be a reference for further researchers who want to deepen or re-examine the effect of savings deposit rate on stock market capitalization.
Security market capitalization has been considered to be the value of an entity that is traded on the stock exchange market. Security market capitalization disclose the size of a firm which is vital since firm size is considered to be an essential determinant of various investment characteristics in which investment decision makers are concerned, comprising risk; it is one of the best measures of a firm size (Agu Bertram, 2018). The strength of the quoted firms in the security market in terms of size could determine the strength of the market. To achieve a desire economic improvement, the stock market must be given serious attention. Studies have affirmed close positive link among market capitalization and economic improvement (Najaf & Najaf, 2016; Nazir, Nawaz, & Gilani, 2010; Obubu, Konwe, Nwabenu, Omokri, & Chijioke, 2016).
The machinery of capital market occupies the central position to the development of the economy (Tile, Aime, & Kase, 2018). The market stand to play intermediary role by providing needed fund to the deficit unit servicing from the surplus unit and such units could be individuals, companies and government (Ugherughe & MaryAnn, 2019). The Nigerian capital market since has been a meeting location for sellers and buyers of stocks for the aim of raising fund for the operations of different businesses (Abina & Maria, 2019). Several studies have shown that, any effective or proper running capital market can propel economic improvement (Acha & Akpan, 2019; Njemcevic, 2017; Nwaolisa, Kasie, & Egbunike, 2013; Pavone, 2019; Sharif & Afshan, 2016; Ubesie & Ude, 2019; Ugbogbo & Aisien, 2019).
Over the years, the Nigerian stock market has been in a fluctuating state and the performance in the market has not been impressive. Some scholars have attributed this ugly trend to crude oil price fluctuation, political influences and exchange rate (Abraham, 2016; Asaolu & Ilo, 2012; Demir, 2019; Olufisayo, 2014; Utile, Okwori, & Ipkambese, 2018).
Despite the efforts made in formulating and implementing programs based on recommendations from previous studies, the Nigerian market capitalization continue to record decline in recent time. Report from Nigerian stock exchange (NSE) in December 2019 indicated that, the Nigerian equities market closed on a negative line, thereby recording the second consecutive yearly decline. The Nigerian stock exchange All-Share Index, which is the benchmark barometer, measuring the performance of the market reduces by 14.5 percent at 26,842.842 from 31,430.500. The decline is lower than the 17.8 percent fall posted in 2018. In 2018, the NSE equities market capitalization fell by 13.8 percent. In 2019, MTN Nigeria communications Plc and Airtel Africa Plc assisted; excluding the above two companies, the market capitalization would have dipped by 17.3 percent, but the two companies boasted it to 10.5 percent which is undesired news for the market.
The objective of improving NSE market capitalization has drawn the attention of scholars to find out the determinants of market capitalization in Nigeria (Eriemo, 2014; Etale & Tabowei, 2019; Tsaurai, 2014). The studies made effort to examine the link between return on investment, inflation rate, value traded, exchange rate, GDP and FDI. The reviewed studies have did not examined the relative impact of savings deposit rate on the Nigerian market capitalization.
Savings deposit is interest bearing deposit account held with financial institutions. The increase or decrease of savings deposit rate could influence the attention of investors to either buy or not to buy stock traded which could determine the value of market capitalization. CBN has given directive that effective from May 1, 2017 for banks to pay savings account holders 30% on saved amount where the customers did not make a withdrawal up to four times and above in a month. Contrary to the guideline, the maximum savings deposit rate has been 9.69 percent per annum. There is need to know if this trend has influence on market capitalization in Nigerian stock market. From our extensive investigation and review of epistles in the subject, studies have not measured the relative link between savings deposit rate and Nigerian market capitalization. Only few studies have examined interest rate with market capitalization, where (Etale & Tabowei, 2019; Farooq, Anwar, & Chaudhry, 2016) found an inverse link among market capitalization and interest rate, while (Khrawish, Siam, & Jaradat, 2016; Priscilla & Ezeanyeji, 2019) found a positive link between market capitalization and interest rate, therefore creating room for further investigation. This study therefore set to seal the gap by using recent data to check the influence of savings deposit rate on market capitalization in Nigeria.
Total market volume is considered as key economic indicators of a nation. Savings deposit rate could have influence on stock market capitalization. Theoretically, savings deposit rate (SDR) has great significant influence in describing several economic phenomena, including stock market capitalization (Raza, Hena, & Saeed, 2017). Financial institutions savings deposit rates are the results of the people’s savings habit or savings behavior. The savings deposit rate has been introduced as a key factor. To the classical economist, savings habit will be enhance if the SDR increases; with higher SDR, investors would like to sacrifice their current consumptions. Modern theories of consumer behavior also consider the savings deposit rate as a vital factor that has influence on the present value of long-term assets which is based on utility maximization. It means that, if financial institutions increase savings deposit rate, in order to make more income in the future, individuals and others can save. To a great extent, investors would like to shift from other investment avenue; including buying of stock to financial institutions savings deposit.
Some studies have empirically researched on factors that could have impact on security market capitalization. Edirin and Ekwueme (2015) investigate capital market attainment and interest rate regime in Nigeria between 1981 and 2013. The research utilized the OLS method in measuring the link among interest rate, market capitalization and minimum rediscount rate for the study. The evidence shows that, interest rate had an inverse positive association with market capitalization while minimum rediscount rate had negative significant association with market capitalization.
Eriemo (2014) empirically analyzed the determinants of market capitalization in Nigeria between 1980 and 2010 with parsimonious ECM and ordinary least square technique. The outcome from the parsimonious ECM indicates that, value traded and return on investment has a great influence on the level of market capitalization.
Etale and Tabowei (2019) ascertain the connection among economic growth and interest rate in Nigeria by measuring inflation rate, GDP, interest rate and exchange rate in Nigeria between 1980 and 2014 with the application of error correction mechanism approach. Insignificant and inverse link was found among the variables measured in the study.
Priscilla and Ezeanyeji (2019) researched the existing link in financial growth and economic expansion in Nigeria. The research employed var Granger causality and block wald test to measure RGDP, credit to private sector, security market capitalization, liquidity ratio and real interest ratio from 1986 to 2017. The outcome revealed a positive association among market capitalization and interest rate.
Akpansung and Babalola (2011) empirically evaluated banking subdivision credit and economic expansion in Nigeria. Two-stage least square method was used in analyzing the linkage among GDP, lending rate, industrial production index and private sector credit from 1970 to 2008. It was revealed from the study that, lending rate impedes economic expansion while private subdivision credit promotes economic expansion for the research period.
Adekunle, Adodo, and Akindutire (2018) examined economic growth and interest rate nexus in Nigeria between 1981 and 2016. Interest rate was used as a predictor while GDP was used as predicted variable. The research applied ARDL approach. Inverse association exists among the variables in consideration.
Etale and Tabowei (2019) analyzed macroeconomic forces that could have influence on stock market capitalization in Nigeria between 2001 and 2018. Method of regression was utilized to find out the connection between GDP, exchange rate, interest rate, inflation rate and security market capitalization. The study revealed that, GDP had a positive significant influence on security market capitalization; exchange rate had a significant inverse effect on market capitalization while inflation rate and interest rate have insignificant downbeat influence on market capitalization.
Azeez and Obalade (2019) ascertained macroeconomic forces influence on security market development in Nigeria by measuring banking subsector improvement, security market liquidity, FDI and income level between 1981 and 2017. With the aid of autoregressive distributed lag cointegration technique, it was revealed that stock market improvement was not explained by the predictor variables.
Demir (2019) investigated macroeconomic influences on stock market fluctuations in Borsa Istanbul in Turkey stock market from 2003 to 2017 with autoregressive distributed lag bound test. The study tests the relationship between domestic currency, portfolio investment, FDI, interest rate, crude oil prices and security market attainment. Domestic currency, portfolio investment and FDI were responsible in raising the stock market achievement while interest rate and crude oil prices were found inversely associated with security market attainment.
Tsaurai (2014) researched on the affiliation existing among security market and FDI in Zimbabwe from 1988 to 2012. Granger causality test tool was utilized to ascertain the link among the security market performance and foreign direct investment. No causal link was found between the two for the examined period.
Farooq et al. (2016) examined the existing link between interest rate differentials and market capitalization in the case of Pakistan from 1975 to 2013. The study used autoregressive distributed lag method to measure the link among interest rate, savings rate, investment, and market capitalization. The study found that, interest rate differential had an inverse association with market capitalization however it is related positively with investment and savings rate.
Khrawish et al. (2016) employed a regression technique to investigate the existing link among security market capitalization rate and the interest rate in Jordan. Government prevailing interest rate and security market capitalization rate were used between 1999 and 2008. The study showed a positive significant relationship among the variables in Jordan for the research period.
Most of the studies (Adekunle et al., 2018; Azeez & Obalade, 2019; Demir, 2019; Etale & Tabowei, 2019; Farooq et al., 2016) came out with outcome that interest rate had a negative link with market capitalization, while studies such as Khrawish et al. (2016); Edirin and Ekwueme (2015); Priscilla and Ezeanyeji (2019) showed a positive association between interest rate and market capitalization. Existing studies focused on interest rate and stock market development, to the best of our length of research on this subject, no study has find out the link among savings deposit rate and market capitalization. The research as a result stands to fill the available gap with recent data.
3.1. Empirical Design and Source of Data
In this research, expo facto study design was adopted to ascertain the persuasion of savings deposit rate on security market capitalization in Nigeria. This is because the data were primarily historical and is not controlling type. The research adopted time series regression investigation to look at the link connecting savings deposit rate and market capitalization, while lending rate is employed as a control variable. The frequency of data is kept at monthly level while the time scope of the study is taken from January 2016 to December 2019. The data were collected from NBS and CBN publications. The variables on which data were collected were market capitalization (MCAP), savings deposit rate (SDR) and bank lending rate (BLR).
3.2. Models Specification
Econometric experts construct models as a system of streamlining the features of actual life, thus a model is a thought of realism. This study intends to adopt on empirical model build by Khrawish et al. (2016) with minor modification. It is thus constructed below;
MCAP = f (SDR, BLR) 1
Where: MCAP = Market capitalization.
SDR = Savings deposit rate.
BLR = Bank lending rate.
The model is precisely specified in its linear arrangement as follows:
MCAP = α0 + α1SDR + α2BLR + e 2
Where α0, α1 and α2 are parameters to be estimated
e is the error term or stochastic terms
3.3. Method of Data Analysis
Table-1. Descriptive statistics.
MCAP |
SDR |
BLR |
|
Mean |
22.29072 |
9.006667 |
16.72222 |
Median |
22.29950 |
8.9 5000 |
16.87000 |
Maximum |
26.28800 |
9.690000 |
18.23000 |
Minimum |
16.10000 |
8.240000 |
14.92000 |
Std. Dv. |
3.115975 |
0.344533 |
0.966266 |
Skew. |
-0.568102 |
0.262657 |
-0.443268 |
Kurt. |
2.386293 |
2.760402 |
1.921762 |
Jarque Bera |
2.501391 |
0.500042 |
2.922818 |
Prob. |
0.286306 |
0.778784 |
0.231909 |
Sum |
802.4660 |
324.2400 |
602.0000 |
Sum Sq. Dev. |
339.8256 |
4.154600 |
32.67842 |
Observations |
36 |
36 |
36 |
Source: Eviews 10 software output, 2020.
Table-2. Johansen cointegration test.
Hypothesized |
Trace |
0.05 |
||
No. of CE(s) |
Eigen val. |
Stat. |
Crit. Val. |
Prob.** |
None * |
0.705920 |
69.37113 |
29.797 |
0.0000 |
At most 1 * |
0.460650 |
28.98230 |
15.495 |
0.0003 |
At most 2 * |
0.229612 |
8.608418 |
3.8415 |
0.0033 |
Hypothesized |
Max-Eigen |
0.05 |
||
No. of CE(s) |
Eigenvalue |
Statistic |
Critical Value |
Prob.** |
None * |
0.705920 |
40.38883 |
21.132 |
0.0000 |
At most 1 * |
0.460650 |
20.37388 |
14.265 |
0.0048 |
At most 2 * |
0.229612 |
8.608418 |
3.8415 |
0.0033 |
DLNMCAP |
DLNSDR |
DLNBLR |
||
-5.286507 |
-11.28247 |
47.67902 |
||
-6.123787 |
-69.44284 |
-16.32414 |
||
-29.88128 |
-3.013693 |
-17.33195 |
||
D(DLNMCAP) |
0.016771 |
0.001532 |
0.022068 |
|
D(DLNSDR) |
0.003840 |
0.018932 |
-0.001469 |
|
D(DLNBLR) |
-0.045901 |
-0.000284 |
-0.001786 |
|
1 Cointegrating Equation(s): |
Log likelihood |
196.1890 |
||
DLNMCAP |
DLNSDR |
DLNBLR |
||
1.000000 |
2.134201 |
-9.019002 |
||
(1.56723) |
(1.19903) |
|||
D(DLNMCAP) |
-0.088659 |
|||
(0.04732) |
||||
D(DLNSDR) |
-0.020298 |
|||
(0.02815) |
||||
D(DLNBLR) |
0.242655 |
|||
(0.02983) |
||||
2 Cointegrating Equation(s): |
Log likelihood |
206.3759 |
||
DLNMCAP |
DLNSDR |
DLNBLR |
||
1.000000 |
0.000000 |
-11.72794 |
||
(1.51950) |
||||
0.000000 |
1.000000 |
1.269296 |
||
(0.22743) |
||||
D(DLNMCAP) |
-0.098040 |
-0.295600 |
||
(0.07237) |
(0.62939) |
|||
D(DLNSDR) |
-0.136236 |
-1.358036 |
||
(0.03189) |
(0.27737) |
|||
D(DLNBLR) |
0.244393 |
0.537582 |
||
(0.04565) |
(0.39702) |
|||
Source: Eviews 10 software output, 2020.
The descriptive statistics on Table 1 indicates that, the stock market capitalization (MCAP) has an expected value of 22.29072, savings deposit rate (SDR) has a mean value of 9.006667, and bank lending rate (BLR) has an expected value of 16.72222. The peak and smallest values of MCAP are 26.28800 and 16.10000 respectively. The peak and smallest values of SDR are 9.69000 and 8.240000 respectively. The peak and smallest values of BLR are 18.23000 and 14.92000 respectively. Jarq. Bera statistic indicates that, all variables used are normally dispersed; MCAP with a Prob. Val. of 0.286306; SDR with a Prob. Val. of 0.778784 and BLR with a Prob. Val. of 0.231909.
Both maximum Eigenvalue and trace test on Table 2 indicated three co-integrating equation existing among the predicted and predictable variables. This shows a long-run equilibrium link connecting the outcome and stimulus variables.
Table-3. ADF unit root test summary.
Variables |
Sig. Ls |
ADF @ level series |
ADF @ 1st diff |
||||
ADF test val. |
Crit. val. |
P. val. |
ADF test val. |
Crit. val. |
P. val. |
||
MCAP |
1% 5% 10% |
-1.082943 |
-4.243644 -3.544284 -3.204699 |
0.9177 |
-4.803771 |
-4.252879 -3.548490 -3.207094 |
0.0025 |
SDR |
1% 5% 10% |
-2.421119 |
-4.243644 -3.544284 -3.204699 |
0.3630 |
-6.037592 |
-4.252879 -3.548490 -3.207094 |
0.0001 |
BLR |
1% 5% 10% |
-0.071393 |
-4.284580 -3.562882 -3.215267 |
0.9931 |
-7.629595 |
-4.262735 -3.552973 -3.209642 |
0.0000 |
Source: Eviews 10 software output, 2020
From the ADF test outcome in Table 3, the three variables (MCAP, SDR and BLR) are not stationary at level series but are stationary at first difference.
Dependent Variable: DLNMCAP
Method: Least Squares
Date: 02/04/20 Time: 21:14
Sample (adjusted): 5 36
Included observations: 32 after adjustments
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
C |
-0.014063 |
0.007744 |
-1.815923 |
0.0801 |
DLNSDR |
-0.230426 |
0.095174 |
-2.421119 |
0.0213 |
DLNBLR |
-0.416487 |
0.217295 |
-1.916688 |
0.0655 |
ECM(-1) |
-0.353259 |
0.163472 |
-2.160975 |
0.0391 |
R-sq. |
0.543448 |
Mn dep. var |
-0.000949 |
|
Adj. R-sq. |
0.513993 |
S.D. dep.t var |
0.031618 |
|
S.E. of regr. |
0.022042 |
Akaike info crit. |
-4.707159 |
|
Sum sq. res. |
0.015062 |
Schwarz crit. |
-4.576942 |
|
Log lik. |
83.02954 |
Han-Quin crit. |
-4.661427 |
|
F-stat. |
18.45014 |
Durb.-Wat. stat |
1.969491 |
|
Prob(F-stat.) |
0.000005 |
|||
Source: Eviews 10 software output, 2020.
The outcome from the estimate in Table 4 above discovered that, SDR has a coefficient of -0.230426 which reveals that a percentage change in savings deposit rate leads to 23.04% change in stock market capitalization in the negative path and this is significant statistically at 5% acceptable level. BLR has a coefficient of -0.416487 which also reveals that a percentage change in bank lending rate leads to 41.64% change in stock market capitalization, also in the negative path but is not statistically significant at 5% acceptable level.
The outcome from the estimate further exposed that r-squared is 0.543448 while adjusted r-squared is 0.513993 signifying that 51.3993% of changes in stock market capitalization is believed to have been caused by the combined effect of savings deposit rate and bank lending rate.
In overall, the estimate outcome showed F-statistic of 18.45014 with a probability of 0.000005 signifying that the combined effect of the exogenous variables on the endogenous variable is statistically significant.
3.4. Discussion of Results
The association between savings deposit rate and stock market capitalization is found to be negative and statistically significant for the period under review. This result is in line with the classical economist opinion that savings habit will be enhance if the savings deposit rate increases; with higher savings deposit rate, investors would like to sacrifice their current consumptions. Meaning that if financial institutions increase savings deposit rate, in order to make more income in the future, individuals and others can save. To a great extent, investors would like to shift from other investment avenue; including buying of stock to invest in financial institutions by saving their fund. This clearly showed that, there is an inverse relationship between saving deposit rate and stock market capitalization.
The findings of this investigation concur with the study outcome of Farooq et al. (2016); Etale and Tabowei (2019) that there is an inverse association between interest rate and stock market capitalization. But this is contrary to the findings of Khrawish et al. (2016); Priscilla and Ezeanyeji (2019) that there is positive association between interest rate and stock market capitalization. The relationship between bank lending rate and stock market capitalization is also negative but is not statistically significant. Our study estimate outcome here agrees with the study outcome of Akpansung and Babalola (2011) that lending rate impedes economic growth in Nigeria.
This research investigated the effect of savings deposit rate on stock market capitalization in Nigeria. The following findings were inferred from the study:
There is a significant negative association between savings deposit rate and stock market capitalization in Nigeria.
There is insignificant negative link between bank lending rate and stock market capitalization in Nigeria.
The intention of this study is to investigate the effect of savings deposit rate on stock market capitalization in Nigeria. The study employed monthly data from January 2016 to December 2019. The data were collected from the publications of the National Bureau of Statistics (NBS) and Central Bank of Nigeria (CBN). The variables on which data were collected were market capitalization (MCAP), savings deposit rate (SDR) and bank lending rate (BLR) as a control variable. The data was analyzed with the aid of descriptive statistics, Johansen cointegration test, ADF unit root test and regression technique. The investigation discovered a significant negative association between savings deposit rate and stock market capitalization. The research also discovered insignificant negative link between bank lending rate and stock market capitalization in Nigeria. The overall equation judging from the R2, Durbin-Watson statistics and F-statistics is significant. Based on this revelation, it is concluded that, there is a negative relationship between savings deposit rate and stock market capitalization in Nigeria.
It is thus recommended that:
At anytime the country intend to raise the level of stock market capitalization, government should formulate and implement policies to reduce savings deposit rate in Nigeria.
Government should also implement policies to reduce bank lending rate to boast economic growth and as well raise the level of stock market capitalization in Nigeria.
The intention of this study is to investigate the effect of savings deposit rate on stock market capitalization in Nigeria. The research employed monthly data from January 2016 to December 2019. The data were collected from the publications of the NBS and CBN. The variables on which data were collected were market capitalization (MCAP), savings deposit rate (SDR) and bank lending rate (BLR) as a control variable. The data was analyzed with the aid of descriptive statistics, Johansen cointegration test, ADF unit root test and regression technique. Further investigations could increase the scope or use other exogenous variables and could widen the stock market capitalization to capture the entire stock market returns, or still, utilize other econometric methods. This will aid comparison and further increase confidence on and strength of the outcomes of this investigation. Also, further research should be carried out to find out the impact of macroeconomic forces on stock market performance.
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
Acknowledgement: Both authors contributed equally to the conception and design of the study. |
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