Effect of mobile money transfer scheme on the economic growth of cameroon

This study evaluated the “Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon”. Mobile Money Transfer Scheme was the independent variable, meanwhile Economic Growth was the dependent variable and the proxies used were Gross Domestic Product (GDP) and Inflation Rate.

International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 12, December 2019, pp 484-511, Article ID: IJMET_10_12_048 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=12 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication EFFECT OF MOBILE MONEY TRANSFER SCHEME ON THE ECONOMIC GROWTH OF CAMEROON Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke Department of Accountancy, University of Nigeria Nsukka, Enugu Campus, Nigeria ABSTRACT This study evaluated the “Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon” Mobile Money Transfer Scheme was the independent variable, meanwhile Economic Growth was the dependent variable and the proxies used were Gross Domestic Product (GDP) and Inflation Rate The population consisted of the two primary Mobile Money service providers in Cameroon i.e MTN Mobile Money and Orange Money Explanatory Research Design was employed in the Methodology Secondary data was used for the study, and the data were collected from the annual reports of Cameroon’s central bank (BEAC),IMF and Knoema for Mobile Money, GDP and Interest Rate respectively These data collected wereanalysed using simple Linear Regression at 5% probability level of significance with the aid of Statistical Package for the Social Sciences (SPSS), version 23.0 The findings revealed that there is a weak positive insignificant correlation between Mobile Money Transfer Scheme and Economic Growth in Cameroon i.e GDP (r = 162, alpha-significance is 520 at p > 0.05)and inflation rate (r = 385, alphasignificance is 115 at p > 0.05) The research concludes that the reason why this scheme does not currently have a material effect on Cameroon’s Economic Growth is probably due to the fact that the industry is relatively new in the country, gradually gaining grounds and so could potentially have a significant effect in the future It could also be due to the severe political instability plaguing Cameroon at the moment The study therefore recommends that the government should subsidise and also implement policies which will favour the further penetration of mobile money service even to the more remote parts of the country It equally recommends that the government should try to resolve the current, devastating political crisis so as to make the environment safer to conduct business Keywords: Mobile Money, Mobile Money Transfer Service, Mobile Money Agent, Economic Growth, Gross Domestic Product, Inflation, Life expectancy Cite this Article: Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke, Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon International Journal of Mechanical Engineering and Technology 10(12), 2020, pp 484-511 http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=12 http://www.iaeme.com/IJMET/index.asp 484 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon INTRODUCTION Access to financial services is a crucial boost to social and economic development of a country Until recently in Cameroon, such services focused on the formal banking sector, which traditionally does not open branches in low income and rural areas as their returns there would not be able to justify their substantial operating costs This meant that only wealthy and urban citizens could enjoy such privileges The rapid growth of the mobile network industry led to half the world‟s population having at least one mobile subscription by 2014 (GSMA Intelligence, 2015), with a total number of mobile subscriptions worldwide reaching more than billion by the close of 2015 (Sanou, 2015) These mobile devices offered a distribution technology for mobile financial services for the unbanked The initial goal of mobile money was to enable the unbanked persons to be able to carry out person-to-person (P2P) money transfer transactions, which were previously done through relatively unsecured physical means such as bus agencies as well as travelling relatives and friends This service, therefore, brought people from the cash-based, „unbanked‟ economy to the modern system of „bookentry money‟ Thus began the era of „banking the unbanked‟ (Klein & Mayer, 2011) Worldwide, mobile money service is available in 93 countries today The service is fast overtaking the banking sector with the number of registered accounts in the world increasing by 31% to 411 million in 2015 compared to the previous year Mobile money providers are processing an average of 33 million transactions per day Mobile money services offering International Money Transfer (IMT) saw the volume of cross-border remittances increase by 52% in 2015, compared to the previous year (GSMA, 2015) Indeed, the World Bank (2016) referred to mobile money as a “success story” that is also a “regulatory minefield” Africa has a vast potential for growth in the telecoms industry, especially as there is only 47% penetration so far One of the fastest growing areas in the telecom industry happens to be mobile money This service makes it possible for mobile phone users to send and receive money anywhere by facilitating transactions through their mobile phones This is essential especially in Africa which has poor infrastructure, and a vast majority of the people not have bank accounts (Paelo, 2014) So far, Kenya is the country where mobile money service is most successful as it has been there since 2007, especially with the advent of M-PESA provided by the Vodafone-owned Safaricom mobile network which has the largest market share in the country Though not yet fully embraced, it is also present in Nigeria thanks to MTN Mobile Money (working in partnership with GT Bank), Glo Xchange, Paga and so on In Cameroon, less than 20% of the population has a bank account whereas the penetration of mobile telephony is estimated at 80% (Cameroonweb, 2015) This could be because the cost of mobile phones is becoming more and more affordable over the years (currently as low as 5,000FCFA or $10) and subscribers not necessarily need an expensive Smartphone or internet connection on their phones to be able to use mobile money Some of these phones take even up to or SIM cards at once, meaning a customer could have multiple mobile money accounts using the same phone Three Mobile Network Operators (MNOs) - MTN, Orange and Nexttel are in Cameroon Two of these currently provide mobile money services MTN Mobile Money (also called MoMo) began in 2010 and Orange Money followed a year later in 2011 Nexttel Possa will be launched soon According to Media Intelligence (2016), as of June 2016, there were about 6.8 million mobile money subscribers in Cameroon, with 1.5 million active users Cameroon currently has a population of about 23 million, and the mobile money market is continuing to proliferate in the country For instance, Tabi (2018) posits that the Governor of the Bank of Central African States (BEAC) signed authorisation in 2018 permitting SociétéGénérale Cameroun (SGC) bank to partner with YUP Cameroun in launching its mobile money services within 12 months Worthy of note is the fact that SGC had initially http://www.iaeme.com/IJMET/index.asp 485 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke launched a mobile money service called Monifone, but this was suspended in 2014 due to competition and recurring conflicts with some telecommunication operators This time around, it has decided not to rely on any telecommunication operator, and instead chosen to partner with YUP Cameroun (Business in Cameroon, 2018).Tabi (2018) states that official statistics show that there are presently 34,114 mobile money service points in the CEMAC (Economic and Monetary Community of Central Africa) zone, with Cameroon accounting for 70% (23,880) of them Mobile money transfer has a lot of advantages It improves efficiency and effectiveness by increasing the speed, safety and frequency of payments and decreasing the cost, paper work, and processes of sending and receiving money even on off days and odd hours Besides, security is also a significant benefit here, as it eliminates the risk of theft Cash inflow to rural areas can be enhanced too Increased money flow from Urban to rural dwellers can greatly enhance economic growth Those who partner with telecom providers to offer financial services are called Mobile Money Agents (MMA) in this paper It examines the effect of the Mobile Money Transfer Scheme on the Economic Growth of Cameroon proxy by GDP and Inflation rate It has five parts made up of introduction, literature review, methodology, presentation and analysis of findings and conclusion and recommendations 1.2 Statement of the Problem The ability to carry out financial transactions through a mobile phone has attracted MNOs (especially in developing countries) to the financial services industry They were able to penetrate the market due to their comparatively quicker service and lower charges, compared to the formal banking sector In the case of Cameroon, MTN and Orange now offer Mobile Money Transfer (MMT) services called MTN Mobile Money and Orange Money respectively The third, Nexttel has plans to launch its own called Nexttel Possa According to Paelo (2014), Cameroon had more mobile money subscribers than bank account holders by the end of 2013 OCHA (2016) indicates that MTN Mobile Money formed a partnership with Afriland First Bank whereby MTN manages the technical platform as well as the marketing and distribution network, while Afriland issues the e-money and ensures compliance with the financial regulations It goes on to say the services include person-to-person (P2P), bill payment and purchasing of goods and services from authorised retailers but not substantiate on any of these aspects Bahri-Damon (2015) posits that Mobile Money services in Cameroon enable Cameroonians to send and receive money anywhere within and outside the country as well as pay their electricity bills, cable bills, insurance premiums, university tuition fees and taxes It equally creates a medium through which they can buy train tickets, flight tickets, airtime and fuel It even enables them to shopping in their authorised supermarkets Some companies pay salaries to their employees using this means Though these numerous activities are going on in the field of mobile money transfer in Cameroon, the economy of the country has been at a comatose and no study has attempted to determine the effect of the scheme on her economic growth Langaa (2012) only explored the social impact of mobile money and mobile electronic transfer services among rural farmers in the North West Region of Cameroon Therefore there exists a gap in literature in this field despite the need to find a solution to poor economic growth in Cameroon 1.3 Objectives of the Study and Accompanying Research Questions and Hypotheses The general objective of this study was to assess the effect of Money Mobile Transfer Scheme on the Economic Growth of Cameroon Its specific objectives were to: (i) establish the effect of Mobile Money Transfer Scheme on the GDP of Cameroon and (ii) ascertain the effect of http://www.iaeme.com/IJMET/index.asp 486 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon Mobile Money Transfer Scheme on the inflation rate of Cameroon These objectives gave rise the following research questions viz.(i) Does Mobile Money Transfer Scheme have a significant effect on the GDP of Cameroon? (ii) Does Mobile Money Transfer Scheme have a significant effect on the inflation rate of Cameroon? In tandem with the above therefore the following two hypotheses were formulated namely: (i) Mobile Money Transfer Scheme has a significant effect on the GDP of Cameroon and (ii) Mobile Money Transfer Scheme has a significant effect on the inflation rate of Cameroon This research is expected to be of great benefit to the government, researchers, mobile money service providers and the general public For instance, while the government would utilize the findings for effective policy formulation to make the scheme acceptable to all and sundry in the country, researchers will find in it usable data and reference point for further researches We acknowledge and appreciate the paucity of work done in this area about the Cameroonian economy due to the newness of the introduction of the scheme in the country (2010) relative to Kenya and other African countries Notwithstanding the above limitation, the study focused on MTN Mobile Money and Orange Money which occupy almost the entire market, it covered a period of 16 years (2002 – 2017), that is years before the advent of Mobile Money, and then years after LITERATURE REVIEW 2.1 Conceptual Framework 2.1.1 Mobile Money Transfer Mobile Money was relatively unknown over a decade ago starting only in 2001 But it is probably the phenomenal growth since 2007 of Kenya‟s M-Pesa system that has brought mobile money to international popularity Mobile money refers to financial transaction services potentially available to any mobile phone user, including the under banked and unbanked global poor who are not a profitable target for commercial banks According to Diniz, Albuquerque and Cernev (2011), Mobile Money is a digital repository of electronic money developed and implemented on a mobile device, allowing peer-to-peer transaction between users of the same service provider The services allow electronic money transactions over a mobile phone (Ernst & Young, 2009) while GSMA (2010) opines that Mobile Money is a service in which mobile phone is used to access financial services, giving rise to movement of value from a mobile wallet through a mobile phone Common mobile financial services offered through the mobile phone include bill payment, account transfers, domestic and international Person-to-Person transfers, proximity payments at the point of sale, and remote payments to purchase goods and services The Mobile Network Operators (MNOs) partner with banking institutions to be able to render these mobile money services Mobile Money is not Mobile Banking Mobile Money does not require an internet connection and works merely with codes On the other hand, Mobile Banking requires the subscriber to have a bank account, a Smartphone, download the app on the phone, and use internet connection to the electronic money transfer How it works according Aaron (2015) is that an individual/customer sets up an electronic money account with the mobile money service provider (after providing identity documents) and then deposits cash in exchange for electronic money This electronic money can be stored or withdrawn as cash, or transferred via a coded secure text message to others, without the customer having a formal bank account He further asserts that the scheme enables the use of mobile phones to pay bills, remit funds, deposit cash, and make withdrawals using e-money issued by banks as well as non-bank providers such as telecommunication companies This service currently exists in many developing countries today and is proliferating, especially in Africa It serves several people without access to banking services, known as the unbanked According to Buckley, Greenacre http://www.iaeme.com/IJMET/index.asp 487 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke and Malady, (2015), it provides financial inclusion which has the potential of helping the unbanked and low-income groups to save and borrow with a possible spiral effect of investment in education and asset generating activities 2.1.2 Economic Growth Economic growth is an increase in the production and consumption of goods and services This happens when there is an increase in the multiplied product of population and per capita consumption The global economy grows as an integrated whole made up of agricultural, extractive, manufacturing, and services sectors that require inputs and outputs Economic growth is often indicated by an increase in real Gross Domestic Product (GDP) or real Gross National Product (GNP) Economic growth has been a primary, perennial goal of many societies and most governments (Wilson et al., n.d) Haller (2012) posits that Economic Growth is, in a limited sense, an increase of the national income per capita, and it has to with the analysis, especially in quantitative terms, of this process It concentrates on the functional relations between the endogenous variables; in the broader sense, it involves the increase of the Gross Domestic Product(GDP), Gross National Product(GNP) and National Income (NI), resulting in national wealth, including the production capacity, expressed in both absolute and relative terms, per capita, as well as involving the structural modifications of economy According to Haller (2012), Economic Growth can be positive, zero or negative It is positive when the annual average rhythms of the macro-indicators (especially GDP) are higher than the normal rhythms of growth of the population and negative when it vice versa Then it is zero when the annual average rhythms of growth of the macro-economic indicators (especially GDP) are equal to those of the population growth Essentially, Economic growth is the sustained increase in the welfare of an economy together with the ongoing changes in that economy's industrial structure; public health, literacy, and demography; and distribution of income (Habane, 2012) The ultimate goal of Economic Growth is to increase the standard of living of the citizens by making them sustainably wealthier Researchers attribute economic growth to several factors – economic and non economic Economic factors range from natural resources, capital formation, technological progress, human resources, population growth, social overheads, and entrepreneurship to transformation of traditional agricultural society Each has varying degrees of impact on economic growth (Boldeanu & Constantinescu, 2015; Onyinye, Idenyi & Ifeyinwa, 2017; Muchdie et al., 2016; Arabi & Abdalla, 2013; Nwosu, Dike & Okwara, 2014; Biktemirova et al., 2015; Afghah, Raoofi and Hoshyar, 2014; Odetola & Etumnu, 2013; Sertoglu, Ugural and Bekun, 2017) On the other hand, non economic factors also affect economic growth and these are political, education, urbanization and religion (Younis, Lin, Sharahili and Selvarathinam, 2008; Kotaskova et al., 2018; Odit, Dookhan and Fauzel, 2010; Arouri, Youssef, Nguyen-Viet and Soucat, 2014; and Campante & Yangizawa-Drott, 2013) Long religious induced holidays and other religious bigotry affect economic growth negatively, for instance 2.1.3 Gross Domestic Product (GDP) GDP is the total market value of all final goods and services produced by all the people and companies in a country, within a given period It does not matter if they are citizens or foreign-owned companies, as long as they are located within the country's boundaries; the government counts their production as GDP (Amadeo, 2018) Fresh Forex (n.d) posits that GDP includes the market cost of all goods and services produced on the territory of the state by all branches of the economy purposed for consumption, accumulation or exporting for a year GDP is different from Gross National Product (GNP); as the latter is the total value of goods and services produced by citizens of a particular country, no matter which part of the http://www.iaeme.com/IJMET/index.asp 488 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon world they reside in Amadeo (2018) cites the World Bank for preferring to use Gross National Income in place of GNP, as it gives a better picture and the difference between both is insignificant However, GDP per capita is the best index for comparing GDP between countries as it is derived by dividing the GDP by the number of residents of a country Real GDP is usually lower than Nominal GDP, and most countries prefer to use it (Real GDP) since it takes out the effects of inflation, exchange rates, and differences in population Essentially, GDP is an important economic analysis tool because it is the best instrument to assess a country‟s economic health; it is a yardstick for several monetary policies 2.1.4 Inflation Rate Inflation rate according to Evans (2014) is a measure of a general increase of the price level in an economy, as represented typically by a general price index, such as the Consumer Price Index (CPI) The term indicates that many individual prices are rising simultaneously rather than one or two isolated prices The inflation rate has seven distinct thresholds viz: < 0% Deflation; 0% - 2.5% Price Stability; 2.5% - 5% Moderate Inflation; 5% - 8% Serious Inflation; 8% - 12% Self-Compounding Inflation; 12% - 20% Hyperinflation; and 20%+ Explosive Inflation A healthy rate of inflation is considered positive since it encourages consumption which can in turn stimulate the economy and create more jobs However inflation above the mild threshold is detrimental to economic growth and development 2.2 Theoretical Framework 2.2.1 The Technology Acceptance Model (TAM) TAM was postulated by Davis (1989) He believed that this model could be used as a tool to predict acceptance of technology This is because it demonstrates the relationship connecting believe, attitude and action purpose Holistically, TAM attempts to predict individuals‟ intentions toward using a technology based on its Perceived Usefulness (PU) and Perceived Ease of Use (POEU) Accordingly, PU is the degree to which a person believes that using a particular system would improve their job performance while PEOU is the degree to which a person believes that using a particular system would be free of physical as well as mental effort Very importantly, some researches having individual‟s acceptance of mobile services as their central research focus have used TAM to understand the adoption of different mobile services (Hong et al., 2006; Bouwman et al., 2012; Pederson, 2003; Wang et al., 2006) This suggests the possibility to predict users‟ acceptance and adoption of mobile services using TAM constructs However, Mathieson (1991) and Stern et al (2007) argue that despite the predictive ability of the constructs, they are not alone In other words, PU and PEOU in TAM are not sufficient enough to predict users‟ intentions 2.2.2 Agency Theory Jensen and Mecklin (1976) were among the propounders of the Agency Theory The theory focuses on the Principal – Agent - Delegation - of - Work paradigm using the contract The central idea here is that the Principal is too busy to a given job and so hires an agent to undertake the task for him The issues that arise from this is that while the Principal and the Agent work towards the same goal, they may not always have the same interest The literature on Agency Theory mostly focuses on methods and systems and their consequences that arise to try to match the interests of both the Principal and the Agent Mobile money transfer definitely benefits from a proper analysis and application of the Agency theory as it introduces middle men between the payer and receiver of money quite different from the bank itself http://www.iaeme.com/IJMET/index.asp 489 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke 2.2.3 Transaction Cost Theory Transaction Cost Theory was initially developed by Coase (1937) He aimed at explaining why certain activities, products, or services are carried out internally in firms, while others are bought and sold in the marketplace This implies that companies weigh the costs of exchanging resources with the environment, against the bureaucratic costs of performing activities in-house If the external transaction costs are higher than the company‟s internal bureaucratic costs, the company will be more profitable by performing activities in-house and vice versa Mobile money transfer definitely benefits from a proper analysis and application of the transaction cost theory as it is envisaged that cost of transaction would drastically be reduced through its adoption Recall that Transaction Cost Theory recognizes that it is unlikely to be economically optimal to obtain perfect knowledge and that even if this were possible, the extra cost of obtaining extra information should be weighed against its extra benefits (Baumol and Quandt, 1964) According to Williamson (1981), a transaction cost occurs “when a good or serviceis transferred across a technologically separable interface" From all the theories explained above, this study is anchored on the Theory of Technology Acceptance Model (TAM) This is because a potential user‟s acceptance or rejection of this new technology (mobile money) will depend on how easy and convenient they find it to use the service The more user-friendly the service, the more subscribers there will be and this will therefore go a long way to enhance economic activities 2.3 Empirical Review Nyasimi (2016) examined the effect of Mobile Money Transfers on Economic Growth in Kenya Her study employed Explanatory Research Design which concentrated on “why” questions by developing casual explanations The dependent variable was Economic Growth for the year 2007 to 2015 while the independent variables were Mobile Money Transfer Agents, Mobile Money Transfer Customer Enrolments, Mobile Money Transfer Transaction Frequency and Mobile Money Transfer Deposit Value These secondary data were collected from the Central Bank of Kenya (CBK) as well as the Kenya National Bureau of Statistics (KNBS) Reports After regressing the data, there was no co-integration between Economic Growth and Mobile Money Agents, Customers, Frequency of Transfer as well as the Value of Money Transferred Instead the VAR modelling impulse response showed that; Number of Agents, Customers and Frequency of Transactions have a long run real shock on Economic Growth while both interest rate and exchange rate impact it negatively She recommended the need to intensify the adaption of Mobile Money Transfer Services among those who have not adopted them while the Kenya government should consider the Mobile Money Transfer when drafting its policies Habane (2012) established the relationship between mobile money transfers and economic growth in Kenya using descriptive research design and correlation analysis The target population included six mobile phone service providers in Kenya which also provide mobile money transfer services The total amounts transferred through the mobile for the past five years was collected and then correlated with the economic growth proxy, Gross Domestic Product, measured by change in GDP Data were sourced from the Annual Financial Statements of the Central Bank of Kenya and the Mobile Phone Companies, and Kenya National Bureau of Statistics The study revealed that the amount of money transacted through Mobile Money Transfers increased steadily from KSh 0.06 billion in 2007 on its launch to KSh 118.08 billion by 2012 The growth was driven by the convenience offered by the service as the service does not require an individual to have a bank account in order to transact Customers also transacted business on Mobile Money Transfer platform from anywhere thus offering convenience But it also found that there was a positive though http://www.iaeme.com/IJMET/index.asp 490 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon insignificant correlation between Economic Growth and Mobile Money Transfer in Kenya The study recommended that the policymakers should take Mobile Money Transfer into account when drafting policies This was due to the indirect relationship of Mobile Money Transfer to Economic Growth through the provision of job opportunities, increased financial deepening and financial inclusion Ssonko (2010) explored the role of Mobile Money Services (MMS) in enhancing Financial Inclusion (FI) His study was inspired by the proliferation of mobile phones amongst low-income earners, the prepaid billing system sensitive to users‟ incomes, embrace of ICT by the government and the private sector that has enhanced e-commerce readiness of Uganda, as well as the launch of three Mobile Money Services in the country A Qualitative Analysis of the web content of the three MMS providers was undertaken and concentrated on issues related to services provided; transaction charges; number of registered customers; number and volume of transactions; stakeholders; user interfaces and security; institutional relationships; policy and regulation; as well as appropriateness of the current business model(s) The results indicated that while the MMS has enormous potential to enhance FI, it would require an open business model that involves all stakeholders to establish a truly national solution Moreover, the initial contribution of MMS to FI was in the enhancement of money transfer by lowering the transaction costs for small volumes He recommended that the regulatory authorities need to establish a legal framework that does not suppress innovation but ensures safety for customers‟ savings Mbogo (2010) investigated the success factors attributable to the use of mobile payments by micro-business operators through a sample of 409 micro business entrepreneurs in Nairobi, Kenya and applying the Theory of Technology Acceptance Model (TAM) which was extended to include other factors to assist her in predicting success and growth in microbusinesses The results revealed that the convenience of the money transfer technology as well as its accessibility, cost, support and security factors are related to behavioural intention to use and actual usage of the mobile payment services by the micro businesses to improve their success and growth Lee and Gardner (2010) analysed the impact of mobile phone penetration on economic growth by estimating a fixed-effect dynamic panel model on 56 South Asian and Sub-Saharan African countries from 1990 to 2008 Their results indicate that mobile phones are positively correlated with economic growth and that the marginal contribution is even more significant where the conventional fixed-line telecommunications infrastructure is poor Blauw and Franses (2011) also examined the impact of mobile telephone use on the economic development of individual households in Uganda They used unique cross-sectional data obtained through personal interviews with heads of households (N=196) in Uganda Economic development was measured at the household level by the Progress out of Poverty Index They found strong evidence that mobile phone use positively impacts economic development Kamau (2012) established the relationship between agency banking and financial performance of the banks in Kenya An agency bank is a company or organisation which acts in some capacity on behalf of another bank Through a review of secondary data, the study found that agency banking outlets had increased from 8,809 active agents in 2010 to 9,748 the following year, which is 2011 These specific agents facilitated a total volume of 8.7 million transactions which were valued at KSh 43.6 billion in 2011 Most of these transactions mainly consisted of cash withdrawals and cash deposits carried out at the various banking agency outlets In their own case, Batista and Vicente (2012) designed and conducted a field experiment to assess the impact of randomised mobile money dissemination in rural Mozambique For this purpose they benefited from the fact that mobile money was recently launched in the country, allowing for the identification of a real control group They found http://www.iaeme.com/IJMET/index.asp 491 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke clear adherence to the services from administrative and behavioural data in the treatment group Financial literacy and trust outcomes were positively affected by the treatment They showed behavioural evidence that the availability of mobile money increased the marginal willingness to remit Finally, they observed that mobile money substitutes traditional alternatives for both savings and remittances In a study in Uganda still, Kamukama and Tumwine (2012) found that Ugandan commercial banks were in a liquidity crisis, having fallen short of the Bank of Uganda‟s threshold ratio of 20% but mobile money services alone accounted for 36.7% of liquidity variance They recommended that commercial banks should partner or enter into a joint venture with mobile money operators so as to expand their physical reach into poor and rural areas Wanyonyi and Bwisa (2013) sought to determine if the use of Mobile Money Transfer Services in the Kitale municipality of Kenya, a rural town setting, had resulted in the success and growth of microenterprises Their study was based on a survey of 36 microenterprises, from three major sectors of the Kenyan economy; agriculture, service and processing sectors Microenterprises that were studied were those that had been in existence for more than five years and had experienced business without Mobile Money Transfer (MMT), before 2007 (when MMT was not yet in Kenya), and after that with it Their study used a questionnaire and Chi-Square analysis and found out that mobile money transfer for business-to-business (B2B) transactions when making purchases from suppliers, and customer-to-business (C2B) transfers when customers buy from the business as well as debt collection for credit sales contributed to improved performance of the micro-enterprises Similar finding was made by Kirui et al (2013) in the Agricultural sector in Kenya where the use of mobile phone –based money transfer significantly increased the level of annual household input use by $42, household agricultural commercialisation by 37% and annual household income by $224 They concluded that mobile phone-based money transfer services in rural areas help to resolve a market failure that farmers face; access to financial services Frederick (2014) examined the effect of Mobile Money usage on microenterprise profits in Zambia She employed an instrumental variable strategy using the type of mobile operator as the instrument to address the selection bias in adoption, as Mobile Money services are at the disposal of everyone In this urban context, she found initial evidence of positive net marginal benefits for microenterprises using mobile money, and she calculated bounds that range between 36% and 74% increase in profits Her study helped to fill the gaps in the emerging microenterprise and free money literature and offered guidance to public and private policymakers regarding this market segment According to Chale (2014), small and medium enterprises in Tanzania use Mobile Money services in different ways for business purposes, which include sales transactions, efficiency in the purchase of stock, receiving payment, payment of goods and services, savings as well as money transfer that influenced their business growth This also is closely aligned to the position of Makee et al (2014) who maintain that there is indeed a positive effect of the mobile phone transfer services innovations on enterprise performance among hair-dressing, carpentry and cloth making industries in Kitale town in Kenya as well as Aker et al (2014) to the effect that households receiving free transfers had higher diet diversity and children consumed more meals per day in Niger On adoptability of mobile money transfer services, Etim (2014) carpeted Nigeria for low use of mobile phones for money transfers But Tsilizani (2015) paints a different picture for Malawi where she says that mobile money transfer is well adopted and it has helped in poverty alleviation In like manner, in Ghana, Bampoe (2015) found that the adoption of mobile money transfer is affected by factors as perceived usefulness, perceived trust, social influence and competitive intensity and recommends that different parties of interest for http://www.iaeme.com/IJMET/index.asp 492 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon mobile money should recognise and address these factors to increase its use and encourage its general acceptance Other notable researchers in this field include Peruta (2015) who investigated the adoption patterns of Mobile Money in emerging developing countries such as Kenya, Tanzania, Uganda, Burundi and Rwanda, Saliu (2015) and Bank of Ghana (2017) in Ghana; Similu and Oloko (2015), Kirui and Onyuma (2015) and Soi (2018) in Kenya; Madila and Msamba (2016) in Tanzania; Islam et al (2016) in the East African countries of Kenya, Tanzania and Uganda; Mawejje and Lakuma (2017); Munyoro et al (2017) in Zimbabwe; These researchers extensively linked Mobile Money Transfer Scheme and Economic Growth though from different sectors of the varying economies and point to the success of Mobile money transfer scheme However, none of them, to the best knowledge of the researchers have assessed the effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon, and this constitutes the gap that this research has filled METHODOLOGY Explanatory Research Design was adopted It concentrates on “why” questions and answers involving the development of causal explanations (De Vaus, 2001) thus establishing cause and effect between variables (Mugenda and Mugenda 2003) It is for 16 year period from 2002 to 2017; years pre and years after the introduction the scheme in Cameroon The secondary data were collected from the Annual Reports of Cameroon‟s Central Bank i.e Bank of Central African States also called BEAC (2018) for mobile money data, IMF (2018) for the GDP of Cameroon, Global Economy (2018) for the unemployment rate of Cameroon, and Knoema (2018) for the inflation rate of Cameroon The population consisted of the two principal Mobile Money Operators in Cameroon, i.e MTN Mobile Money and Orange Money Regression Analysis was used while the applicable model for each of the hypotheses is specified below: H01: GDP = f(MMTS)……………………………………………………… (1) Where: GDP = Gross Domestic Product (dependent variable) MMTS = Mobile Money Transfer Scheme (MMTS) H02: IR = f(MMTS)…………………………………………………………… (2) Where: IR = Inflation Rate (dependent variable) MMTS = Mobile Money Transfer Scheme (MMTS) DATA PRESENTATION AND ANALYSIS Table 4.1: GDP of Cameroon from 2002 - 2017 Year 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 GDP, Current Price (bn US$) 11.6 14.6 17.4 18.0 19.4 22.4 26.5 26.1 26.2 29.4 29.1 http://www.iaeme.com/IJMET/index.asp GDP, Current PPP (bn US$) 35.6 38.0 41.7 43.9 46.8 50.4 53.2 54.8 57.3 60.9 64.9 493 Real GDP Growth (%) 4.2 4.6 6.8 2.0 3.5 4.9 3.5 2.2 3.4 4.1 4.5 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon GDP INFLATION RATE Figure 4.4: Showing the Trend in the GDP and Inflation Rate of Cameroon AFTER the Mobile Money Transfer Scheme Source: Researcher‟s Analysis, 2018 4.2 Test of Hypotheses 4.2.1 Test of Hypothesis One H0: Mobile Money Transfer Scheme does not have a significant effect on the GDP of Cameroon H1: Mobile Money Transfer Scheme has a significant effect on the GDP of Cameroon To test the hypothesis, the data on Tables 4.3 and 4.4were used The goal was to determine if the Mobile Money Transfer Scheme has a significant effect on the GDP of Cameroon Regression Test for Hypothesis One Table 4.5 Model Summaryb Model r r2 Adjusted r2 a 162 026 -.035 a Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME b Dependent Variable: GDP Std The error of the Estimate 1.25265 Source: SPSS Analysis, 2018 Table 4.6 Coefficientsa Model 1(Constant) MOBILE MONEY TRANSFER SCHEME a Dependent Variable: GDP Unstandardized Coefficients B Std Error 4.337 320 -8.522E-11 000 Standardised Coefficients Beta -.162 T 13.546 Sig .000 -.658 520 Source: Researcher‟s SPSS Analysis, 2018 http://www.iaeme.com/IJMET/index.asp 497 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke Result: The result of the regression model shows that there is no statistically significant relationship between mobile Money Transfer Scheme and the GDP of Cameroon (i.e p > 0.05, @ 0.05 significant level) It also indicates that the strength or magnitude of the relationship between the Mobile Money Transfer Scheme and the GDP of Cameroon is feeble even though it is positive (r = 162) Also, the coefficient of determination (r2) which shows the variance explained between Mobile Money Transfer Scheme and the GDP of Cameroon indicates 2.6% shared variance (i.e r2 expressed as a percentage) This implies that the Mobile Money Transfer Scheme explains only 2.6% of the variance in the GDP Furthermore, the coefficient of the variable vis-à-vis Mobile Money Transfer Scheme (that is 0.00000000008522 with a p-value of 520) is also not significant when related with the GDP of Cameroon for the period under study Thus, the effect of the Mobile Money Transfer Scheme on the GDP of Cameroon is not significant Decision Rule: If the p-value is less than 0.05, reject the null hypothesis and accept the alternate hypothesis Decision: The result of the regression model shows that there is no statistically significant relationship between Mobile Money Transfer Scheme and the GDP of Cameroon (r = 162, alpha-significance is 520 at p > 0.05) Therefore, we accept the null hypothesis which states that Mobile Money Transfer Scheme does not have a significant effect on the GDP of Cameroon 4.2.2 Test of Hypothesis Two H0: Mobile Money Transfer Scheme has no significant effect on the inflation rate of Cameroon H1: Mobile Money Transfer Scheme has a significant effect on the inflation rate of Cameroon To test the hypothesis, the data on Tables4.3 and 4.4were used The goal was to determine if the Mobile Money Transfer Scheme has a significant effect on the inflation rate of Cameroon Regression Test for Hypothesis Two Table 4.7 Model Summaryb Std The error of the Estimate 1.42650 Model R r Adjusted r 385a 148 095 a Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME b Dependent Variable: INFLATION RATE Source: Researcher‟s SPSS Analysis, 2018 Table 4.8 Coefficientsa Standardised Unstandardized Coefficients Coefficients B Std Error Beta 2.469 365 Model 1(Constant) Mobile Money Transfer -2.462E-10 Scheme a Dependent Variable: INFLATION RATE Source: Researcher‟s SPSS Analysis, 2018 http://www.iaeme.com/IJMET/index.asp 000 498 -.385 T 6.770 Sig .000 -1.668 115 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon Result: The result of the regression model shows that there is no statistically significant relationship between the Mobile Money Transfer Scheme and the inflation rate of Cameroon (i.e p > 0.05 at 0.05 significance level) It also indicates that the strength or magnitude of the relationship between mobile Money Transfer Scheme and the inflation rate in Cameroon is feeble even though it is positive (r = 385) Also, the coefficient of determination (r2) which shows the variance explained between Mobile Money Transfer Scheme and the inflation rate of Cameroonindicates 14.8% shared variance (i.e r2 expressed as a percentage) This implies that the Mobile Money Transfer Schemehelps to explain only 14.8% of the variance inthe inflation rate of Cameroon This is also an insignificant amount of variance explained Furthermore, the coefficient of the variable vis-à-vis Mobile Money Transfer Scheme (that is 0.0000000002462 with a p-value of 115) is also not significant when related with the inflation rate of Cameroon for the period under study This implies that the Mobile Money Transfer Scheme cannot be used solely to predict the inflation rate of Cameroon as other factors account for the remaining 85.2% of the variance unaccounted for Decision Rule: If the p-value is less than 0.05, reject the null hypothesis and accept the alternate hypothesis Decision: The result of the regression model shows that there is no statistically significant relationship between Mobile Money Transfer Scheme and the inflation rate of Cameroon (r = 385, alpha-significance is 115 at p > 0.05) Therefore, we accept the null hypothesis which states that Mobile Money Transfer Scheme has no significant effect on the inflation rate of Cameroon 4.3 Discussion of Results For hypothesis one, the result of the test of hypothesis indicated that Mobile Money Transfer Scheme has no significant effect on the GDP of Cameroon (r = 162, alpha-significance is 520 at p > 0.05).Also, the value of r-squared implied that Mobile Money Transfer Scheme only helps to explain only 2.6% of the variance in the GDP of Cameroon, and therefore insignificant This result or finding can be supported with the study of Nyasimi (2016) in Kenya who revealed that there was no significant influence of Mobile Money Transfer Scheme on Economic Growth She also revealed that mobile money transfer deposit value had a positive but insignificant relationship with economic growth in Kenya This further aligned with the result of Mawejje and Lakuma (2017) who found out that mobile money had only a moderate positive effect in the Ugandan economy, partly because the service was relatively new in the country and had not yet gained substantial ground in the economy In a similar vein, the study also agrees with the findings of Wilkison and Sundelelowotz (2007) who argued that there are direct and indirect links between the exponential growth of mobile telephony and the rate of economic growth in Africa A possible explanation for this finding could be seen in the work of Eriksson (2010) who stated that even though Mobile Money Transfer Scheme could have positive effects with economic growth, such benefits could be stifled by regulatory and initial investment barriers that could prevent the widespread adoption of mobile money In a practical sense, this could be said to be the situation in Cameroon where the government has not deemed it fit to subsidise the development of more local mobile money infrastructure or to adopt policies that would enable the formation of a decentralised network of trusted mobile money agents For hypothesis two, the result indicated that the Mobile Money Transfer Scheme has no significant effect on the inflation rate of Cameroon (r= 385, alpha-significance is 115 at p > 0.05) Besides, the value of the r-squared also implies that Mobile Money Transfer Scheme helps to explain only 14.8% of the variance in the inflation rate in Cameroon, therefore insignificant This finding can be corroborated with the study of Habane (2012) who revealed http://www.iaeme.com/IJMET/index.asp 499 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke that there was a weak positive insignificant correlation between economic growth (inflation rate) and mobile money transfer in Kenya as explained by the Pearson correlation coefficient of +0.027 which was very low with the significance two-tailed test figure being 0.966 which was greater than 0.05 A possible explanation could be adduced from the findings of Pat (2018) who stated that the major causes of inflation in Cameroon are increased money supply, increased input costs of raw materials and wages as well as staggering exchange rate which has made the Cameroon currency (FCFA) to become less valuable relative to foreign currency and has also made imports to be more expensive toCameroonian consumers while simultaneously making Cameroonian‟s exports cheaper to foreign consumers Generally, Mobile Money is an essential tool for poverty reduction since it bridges the gap that exists between banks and poor households Most banks not find it economically attractive to make banking infrastructure and financial services available in poor communities This is because high transaction costs relative to small transaction value sizes make it unprofitable for banks to service this population Similarly, poor people can be reluctant to access formal financial services as a result of the inconvenience and high cost involved in accessing these services relative to the more local and informal alternatives they have traditionally used Besides, some of them even mistrust these formal banking institutions.For these reasons, around 2.5 billion adults in the world today are excluded from the formal financial system and are subject to „financial exclusion.‟ This group of people are referred to as the „unbanked.‟ Providing the unbanked with access to financial services, known as „financial inclusion‟, is now recognised as an essential mechanism for alleviating poverty and enhancing a country‟s broader economic development Financial inclusion aims to provide the unbanked,low-income households and small business with a range of financial services which they can use to facilitate their consumption and protect themselves against „economic shocks‟, such as illness, accidents, theft, and unemployment An economic shock can be severely detrimental to the unbanked‟s already vulnerable financial position, making it more difficult for them to move out of poverty In many less developed countries, economic shocks can take a wide variety of forms beyond traditional financial or economic crisis; they can also be health-related emergencies, crop failures, livestock deaths, and farming-equipment expenses Financial inclusion also aims to help the unbanked and low-income groups to save and borrow which in turn can enable them to invest in education and asset generating activities, such as enterprises (Buckley, Greenacre and Malady, 2015) SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS 5.1 Summary of Findings There was no significant relationship between Mobile Money Transfer Scheme and GDP in Cameroon There was no significant relationship between Mobile Money Transfer Scheme and Inflation Rate of Cameroon 5.2 Conclusion The importance of the Mobile Money Transfer Scheme in third world countries, where bank accounts are unaffordable to most people, cannot be overemphasised However given the fact that this industry is a relatively new phenomenon in Cameroon, it has not yet attained the level whereby it can have a significant effect on the economic growth of Cameroon The result of the study attests to this fact One of the reasons that could account for this is due to the current,severe political crisis in Cameroon which is slowing down most businesses http://www.iaeme.com/IJMET/index.asp 500 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon 5.3 Recommendations The government of Cameroon needs to implement policies which will favour the further penetration of the Mobile Money operations right into the remote interior parts of the country They can so by giving incentives to MTN, Orange and Nexttel to install network poles in those areas so that the use of Mobile Money can reach the places The government of Cameroon needs to resolve the current political crisis in the North West Region and South West Region to facilitate the penetration of the Mobile Money services into the interior villages of those regions This will enable the service to be enjoyed by a greater audience and thus boost the economic growth of the nation Increase in the tele-density of Cameroon This could be done by subsidising the cost of mobile phones to make it even more affordable to a wider population of the country The government needs to more to ensure a more constant and stable supply of electricity This is because mobile phones are powered by electricity, and so blackouts will only help to reduce the frequency of mobile money transactions as the phone‟s battery will be running flat The government also needs to invest more in education so as to improve the literacy rate of the country This because the more literate the populace is, the greater exposure they will have and thus will be able make better use of technology such as mobile money The significant contribution to knowledge in this study is filling the existing gap observed in literature, which is absence of documented research on the effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon 5.4 Suggested Areas for Further Studies This study is by no means exhaustive The researcher has noted other possible areas for further studies such as: Mobile Money Transfer Scheme vis-viz Interest Rate in Cameroon REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] Afghah, S.M., 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Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon APPENDIX Regression Notes Output Created Comments Input 20-OCT-2018 19:14:59 Data Missing Value Handling Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used Syntax Resources C:\Users\DELL\Desktop\MICHAEL'S ANALYSIS\ANALYSIS FOR MICHAEL - SPSS.sav DataSet1 18 User-defined missing values are treated as missing Statistics are based on cases with no missing values for any variable used REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT GDP /METHOD=ENTER VOT /SCATTERPLOT=(*ZRESID ,*ZPRED) 00:00:02.54 00:00:11.22 1420 bytes Processor Time Elapsed Time Memory Required Additional Memory Required 240 bytes for Residual Plots [DataSet1] C:\Users\DELL\Desktop\MICHAEL'S ANALYSIS\ANALYSIS FOR MICHAEL SPSS.sav Variables Entered/Removeda Variables Removed Model Variables Entered MOBILE MONEY TRANSFER SCHEMEb a Dependent Variable: GDP b All requested variables entered Method Enter Model Summaryb Model r r2 Adjusted r2 Std Error of the Estimate a 162 026 -.035 1.25265 a Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME b Dependent Variable: GDP http://www.iaeme.com/IJMET/index.asp 507 editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke Model Regression Residual Total ANOVAa Sum of Squares df 678 25.106 16 25.784 17 Mean Square 678 1.569 F 432 Sig .520b a Dependent Variable: GDP b Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME Coefficientsa Unstandardized Coefficients B Std Error 4.337 320 -8.522E.000 11 Model (Constant) MOBILE MONEY TRANSFER SCHEME -.162 Coefficientsa Correlations Zero-order Partial Model (Constant) MOBILE MONEY TRANSFER SCHEME Standardised Coefficients Beta -.162 Part -.162 -.162 t 13.546 Sig .000 -.658 520 Collinearity Statistics Tolerance VIF 1.000 1.000 a Dependent Variable: GDP CollinearityDiagnosticsa Variance Proportions Model Dimension Eigen Value 1.387 613 Condition Index 1.000 1.504 (Constant) 31 69 MOBILE MONEY TRANSFER SCHEME 31 69 a Dependent Variable: GDP Predicted Value Residual Std Predicted Value Std Residual Residuals Statisticsa Minimum Maximum 3.6171 4.3370 -2.33699 2.46301 -3.196 408 -1.866 1.966 Mean 4.2556 00000 000 000 Std Deviation 19977 1.21525 1.000 970 N 18 18 18 18 a Dependent Variable: GDP http://www.iaeme.com/IJMET/index.asp 508 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon Charts REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT EMPLOYMENT /METHOD=ENTER VOT /SCATTERPLOT=(*ZRESID ,*ZPRED) Regression Notes Output Created Comments Input 20-OCT-2018 19:22:57 Data Active Dataset Filter Weight Split File N of Rows in Working Data File Missing Value Handling Definition of Missing Cases Used http://www.iaeme.com/IJMET/index.asp 509 C:\Users\DELL\Desktop\MICHAEL' S ANALYSIS\ANALYSIS FOR MICHAEL - SPSS.sav DataSet1 18 User-defined missing values are treated as missing Statistics are based on cases with no missing values for any variable used editor@iaeme.com Dr Robinson Onuora Ugwoke, Michael Keneath Foleng and Obioma Vivian Ugwoke Syntax REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT INFLATION /METHOD=ENTER VOT /SCATTERPLOT=(*ZRESID ,*ZPRED) 00:00:00.48 00:00:01.81 1420 bytes Resources Processor Time Elapsed Time Memory Required Additional Memory 240 bytes Required for Residual Plots Variables Entered/Removeda Model Variables Entered Variables Removed Method Enter MOBILE MONEY TRANSFER SCHEMEb a Dependent Variable: INFLATION RATE b All requested variables entered Model Summaryb Model r 385a r2 148 Adjusted r2 095 Std Error of the Estimate 1.42650 a Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME b Dependent Variable: INFLATION RATE ANOVAa Model Regression Residual Total Sum of Squares 5.662 32.558 38.220 Df 16 17 Mean Square 5.662 2.035 F 2.782 Sig .115b a Dependent Variable: INFLATION RATE b Predictors: (Constant), MOBILE MONEY TRANSFER SCHEME Coefficientsa Model (Constant) MOBILE MONEY TRANSFER SCHEME Unstandardized Coefficients B Std Error 2.469 365 -2.462E-10 http://www.iaeme.com/IJMET/index.asp 000 510 Standardised Coefficients Beta -.385 t 6.770 Sig .000 -1.668 115 editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon Coefficientsa Correlations Zero-order Partial Model (Constant) MOBILE MONEY TRANSFER SCHEME -.385 -.385 Collinearity Statistics Tolerance VIF Part -.385 1.000 1.000 a Dependent Variable: INFLATION RATE CollinearityDiagnosticsa Model Dimension Condition Index 1.000 1.504 Eigenvalue 1.387 613 Variance Proportions MOBILE MONEY (Constant) TRANSFER SCHEME 31 31 69 69 a Dependent Variable: INFLATION RATE Residuals Statisticsa Minimum Predicted Value Residual Std Predicted Value Std Residual Maximum Mean 2.4686 2.83144 408 Std Deviation 2.2333 00000 000 3891 -2.16856 -3.196 -1.520 N 57709 1.38391 1.000 18 18 18 1.985 000 970 18 a Dependent Variable: INFLATION RATE Charts http://www.iaeme.com/IJMET/index.asp 511 editor@iaeme.com ... editor@iaeme.com Effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon GDP INFLATION RATE Figure 4.4: Showing the Trend in the GDP and Inflation Rate of Cameroon AFTER the Mobile Money Transfer. .. Scheme on the Economic Growth of Cameroon Mobile Money Transfer Scheme on the inflation rate of Cameroon These objectives gave rise the following research questions viz.(i) Does Mobile Money Transfer. .. transfer scheme However, none of them, to the best knowledge of the researchers have assessed the effect of Mobile Money Transfer Scheme on the Economic Growth of Cameroon, and this constitutes the