Volume 3, Number 2 (2016) pp 67-74 doi 10.20448/802.3.2.67.74 | Research Articles
This study adopted the regression analysis to analyze the data with a view to determining the impact of cashless policy on small scale businesses. The regression analysis is carried out using the E-views statistical package version 7.1. The data employed in this study are national aggregates obtained from secondary sources. The data covers the period of 1980-2014. The major sources of the data include the Central Bank of Nigeria statistical Bulletins. Findings among others show that the coefficient of money supply (MOS) had a significant positive relationship (0.0018) at 1% probability level with the contribution of SMEs to total GDP. The result implies that as money supply in the system increases, the contribution of SMEs to total GDP also increases. Finally, the variable of interest, cashless policy (CP) is a positive insignificant relationship with contribution of SMEs to total GDP (Proxy for Performance of SMEs). This significant relationship could be attributed to the infant nature/stage of the policy implementation. Hence, in the long-run, the policy will have more positive impact on SMEs in the country.
Keywords: Implication, Policy, Cashless policy, Economy, Nigeria.
DOI: 10.20448/802.3.2.67.74
Citation | Augustine L. Joel; Igbara Neeka; Njoku Kelvin; Nwadike, George (2016). Repositioning Cashless Policy in the Nigeria Economy: Policy Options For Small Scale Business Development. International Journal of Economics, Business and Management Studies, 3(2): 67-74.
Copyright: This work is licensed under a Creative Commons Attribution 3.0 License
Funding : The authors declare that they have no competing interests.
Competing Interests: The author declares that there are no conflict of interests regarding the publication of this paper.
History : Received: 31 May 2016/ Revised: 20 June 2016/ Accepted: 28 June 2016/ Published: 4 July 2016
Publisher: Online Science Publishing
The cashless policy in Nigeria started in 2012; few years behind some other African countries. Wizzit in South Africa and M-PESA in Kenya as at 2012 was reported by Akintaro (2012) and corroborated by Omotunde et al (2013) to have over three hundred and nine million customers respectively. The new policy on cash based transaction by the Central Bank of Nigeria which was started in Lagos on March 30, 2012, aimed majorly at reducing the amount of physical cash in circulation as well as encouraging electronic transactions (CBN, 2011). The objectives of this policy include:
In achieving the above objectives, the policy aims at solving the negative consequences that arise as a result of much use of physical cash in the economy, such as high cost of cash, high risk of using cash, high subsidy, informal economy, inefficiency and corruption (www.cenbank.org).
Nevertheless, this policy in Nigeria has been received with mixed feelings which is as a result of internet fraud, technology/technical problems, illiteracy, ignorance, fear of unemployment, and electricity challenges (Reinvent, 2011; Akhalumeh and Ohiokha, 2012; Echekoba and Ezu, 2012; Odior and Banuso, 2012; Omotunde et al, 2013; Ajayi, 2014). Yet there are reports (CBN, 2011 and Echekoba and Ezu, 2012) on the challenges encountered in over the counter transactions which include long queues in the bank, attitudes of teller officers, distance of bank locations, which may be the reason for a high percentage of cash withdrawal through the ATM as reported by CBN (2011). This point to the fact that some Nigerians are enjoying the benefits of the cashless policy while still entertaining doubts about its efficacy, which explains illiteracy and ignorance as reasons for the mixed feelings in accepting the cashless policy.
The place of financial inclusion in the development of any economy cannot be overlooked. This is evidently the reason why its discourse has been highly promoted among the academia and policy makers alike (Jonker, 2005; Gangopadhayay, 2009; Ebiringa, 2010; Mas, 2012; EFInA, 2013). Financial exclusion which could be seen as the absence of financial inclusion has been defined by Musa (2015) as the inability to access appropriate services. Nigeria has been reported to rank low in indicators of financial inclusion with the poor and rural populace (higher percentage of the population) being the most affected (Demirguc-Kunct & Klapper, 2013; CBN, 2013). Therefore, it has been argued by Musa (2015) that for the cashless policy to achieve the desired result, its relationship with financial inclusion must be seriously considered and the factors that promote financial exclusion tackled. The implication is that those who are financially excluded invariably have no business with the cashless policy, for how can the market woman without a bank account transact her business without physical cash? How can the small scale entrepreneurs who have no access to the internet transact online? How can the farmers in the rural areas where there are no banks, ATMs or internet facilities purchase their seeds without physical cash? However, Omotunde et al (2013) argued that cashless economy is not necessarily an economy where there is no cash at all, but a setting where transactions are made through electronic channels. This agrees with Woodford (2003) definition of cashless economy as one where there is the assumption of no transaction frictions that can be reduced through the use of money balances even when they earn rate of return. So Marco and Bandiera (2004) argue that monetary policy becomes more effective at the increase use of cashless banking instruments. The above assertions explain the highpoint of the Nigerian cashless policy which is the limiting of bankers daily withdrawal or deposits. It was previously pegged at N150, 000 per individual customer and N1 million for corporate clients, and later changed to N500, 000 for individuals and N3 million for corporate bodies as a response to the public agitations. Yet the policy does not prohibit transactions above the stipulated amounts but has fixed handling charges for every over the counter transaction done above the stipulated amount. Therefore, to avoid such charges, customers will have to resort to cashless transaction channels such as Mobile banking; Telephone banking; Implants; Electronic card; Internet banking; ATMs and POS terminals (Carow and Staten, 2000; Amujiri and Onodugo, 2015).
The Small and Medium Scale Enterprises (SMEs) have been given many different definitions (Carpenter, 2003; Udechukwu, 2003; Olorunshola, 2003; Safiriyu and Njogo, 2012). Yet, in all these views, it is generally believed that SMEs is the driver of economic growth in especially developing economies like Nigeria. The SMEs contribute immensely in local capital formation which promotes productivity, in addition to its role in improving the living standard of the citizens (Ebeiyamba, 2014; Igbara et al, 2015). According to Adebiyi (2013) the SMEs play a very significant role in employment generation, export earnings, gross domestic products, and competitive market pressure, as well as in downsizing, privatization and restructuring of large enterprises. Nevertheless, factors such as poor management, inadequate information, poor policy implementation, lack of continuity, poor capital outlay, lack of raw materials, unstable policy environment, poor accounting system, lack of market knowledge, poor marketing strategy, lack of technical know-how, and higher interest rates have been identified to often lead to the failure of SMEs (Ekpenyong and Nyong, 1992; Udechukwu, 2003). Therefore, considering the importance of the SMEs to the Nigerian economy, it is important to consider the impact of any policy on them. Therefore, this discourse is taking a closer look at the impact of the cashless policy on the SMEs as it has to do with their contribution to the nation’s GDP. Ebeiyamba (2014) argues that the electronic money which is the bane of cashless economy is linked to bank accounts and that many SME operators have no access to such and also often don’t know how to operate the technologies associated with them. This assertion by Ebeiyamba (2014) conforms to that of Ogu (2011) who posited that the high level of illiteracy in Nigeria have made electronic transaction not easy in many instances and will therefore hinder the full implementation of the cashless policy. Moreover, Omose (2011) have pointed out increase in the overhead cost of running business as the impact of the cashless policy on businesses which may have more impact on SMEs due to their little capital. Apart from the 0.5% the banks charge as commission on turnover, the cashless policy has introduced an additional charge if one uses the POS for sales. Every transaction done through the POS terminals attracts a charge of 1.25% on the amount of the transaction. This charge does not consider the losses incurred by the business and this may lead to business failure. Ebeiyamba (2014) furthered that the role of the SMEs in providing employment may be hampered by the cashless policy since there will not be much need for sales personnel and cashiers who will be replaced with POS and ATMs, thereby leading to higher unemployment rate. Moreover, these channels are often made ineffective by faulty infrastructure which can lead to breach in communication. If this happens during transaction, it may lead to multiple payments, thereby threatening security of funds. Therefore, following the arguments for and against the cashless policy as seen so far, to achieve economic growth for Nigeria through the contribution of the SMEs to GDP, the impact of the policy especially on the SMEs should be given great attention.
This study adopted the regression analysis to analyze the data with a view to determining the impact of cashless policy on small scale businesses. The regression analysis is carried out using the E-views statistical package version 7.1. The data employed in this study are national aggregates obtained from secondary sources. The data covers the period of 1980-2014. The major sources of the data include the Central Bank of Nigeria statistical Bulletins.
In analyzing the impact of cashless policy on the performance of businesses in Nigeria, the model is thus formulated.
To avoid obtaining spurious regression results that would make the estimate biased and inconsistent, it is important that the time series properties of the data set employed in the estimation of equation (2) be ascertained. It might seem reasonable to test for the presence of a unit root in the series. Precisely, stationarity denotes the non-existence of unit roots. The study employed both the Augmented Dickey Fuller (ADF) test due to Dickey and Fuller (1979) and Philip Peron (PP) test due to Philips and Peron (1988) to test for the unit root of the variables. Furthermore, the maximum-likelihood test procedure established by Johansen and Juselius (1990) was employed to test for the presence or otherwise of co-integration.
Table 1 presents the result of the Augmented Dickey Fuller (ADF) test and the Phillip Perron test for the variables used in the analysis. The use of the unit root test helps to check the stationarity of the data used in various analyses in the study. Non-Stationary variable might lead to spurious results. If this occurs, the coefficient generated from the regression might suggest statistically significant relationships among variables in the model, when in fact it is just evidence of contemporaneous correlation (Daniel and Sunday, 2002). The test results for the variables in levels and in first differences are shown in Table 4.3. In levels, all the specified time series were not stationary at 5% probability levels, implying the non-rejection of the null hypothesis of non-stationarity. But they all became stationary in their first differences, both in the Augmented Dickey fuller and the Philip Peron test statistics. We cannot therefore, specify the impact of cashless policy model on the performance of small and medium scale enterprises in Nigeria in the level of the specified variables without the risk of obtaining spurious results unless the variables concerned are co-integrated. The result of the Augmented Dickey Fuller and the Philip Peron test necessitated the test for the co-integration test as proposed by Johansen and Julius (1990). The test results are presented below.
The results of the co-integration condition (that is the existence of a long term linear relation) using methodology proposed by Johansen and Julius (1990) are presented in Table 2 presents the summary of the Trace and Maximum Eigen Value Co-integration rank tests. Economically speaking, two variables will be co-integrated if they have a long-term, or equilibrium relationship between them. Looking at the results of presented in both tables, the hypothesis of no co-integration is accepted. The result shows that there is no co-integrating equation in both Trace tests and Maximum Eigen value. Hence, there is no existence of a long-run equilibrium relationship between contribution of SMEs to total GDP (Proxy of performance of SMEs) and money supply, commercial Bank Loans to Small Scale Enterprises and Cashless Policy in Nigeria.
Table 3 presents the estimated results for equation in section 3. The estimated coefficients (variables) represent the contribution of SMEs to total GDP (Proxy for Performance of SMEs) with respect to immediate past contribution of SMEs to total GDP, Commercial Bank Loans to Small Scale Enterprises, Money Supply and cashless policy.
The E-view computed R2 (R-Squared) value of 0.9316 obtained simply implies that the specified explanatory time series explained about 93.2% of the total variations in the contribution of SMEs to total GDP (proxy for performance of SMEs). The F-statistic of 95.3528 is significant at 1% probability level, indicating that the R2 is significant and thus implying that the model (equation) has goodness of fit. The computed Durbin-Watson value of 1.68, however, indicates that there exists a minor serial correlation.
From Table 3, the immediate past contribution of SMEs to total GDP (Proxy for Past Performance of SMEs) has a significant effect on the current contribution of SMEs to total GDP. The coefficient of the immediate past contribution of SMEs to GDP (Proxy for past performance of SMEs) (0.4487) had a significant positive relationship (at 5% probability level) with the current contribution of SMEs to total GDP (Proxy for Performance of SMEs). The result implies that as the past performance of SMEs CSGC (-1) also increases, the contribution of SMEs to total GDP (proxy for performance of SMEs) also increases. The result could be explained by the fact that, in the short run, accumulation of revenue by SMEs will add significantly to the current performance of SMEs, thereby promoting its contribution to the total GDP in Nigeria.
A percentage increase in money supply in the economy improves the contribution of SMEs to total GDP by approximately 0.0018 percent. The impact is very The coefficient of money supply (MOS) had a significant positive relationship (0.0018) at 1% probability level with the contribution of SMEs to total GDP. The result implies that as money supply in the system increases, the contribution of SMEs to total GDP also increases. minute and this could be traceable to excessive idle funds which are not fully deployed into productive ventures. By implication, irrespective of the fact that enough money is in circulation, financial institutions do not make this money available to SMEs which could be the reason why the variable Commercial Bank Loans to Small Scale Enterprises (LSME) is not significant.
Finally, the variable of interest, cashless policy (CP) is a positive insignificant relationship with contribution of SMEs to total GDP (Proxy for Performance of SMEs). This significant relationship could be attributed to the infant nature/stage of the policy implementation. It is believed that in the long-run, the policy will have more positive impact on SMEs in the country.
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