The World Bank is the primary host of global information/data on the world’s economic performance. In a study titled “Why Digital Payments are Key to Entrepreneurs’ Success”, Klapper (2017) provides a systemic explanation of electronic cash and its effect on the financial system. According to the author, the adoption of electronic cash allows individuals to receive payments, pay suppliers, and remit taxes among other functions. The study makes a relational benefit discussion with supportive information and data on electronic cash.
Electronic cash can increase money transfer efficiency and higher profitability. The benefit cuts across small scale business and large global institutions such as the World Bank. The system allows entrepreneurs to manage their inventories and profit margins. Electronic cash is the largest invention of e-commerce with a huge clientele. In addition, electronic payments like e-filling and e-payment have lowered the cost of doing business (Klapper, 2017). The system has also impacted corporate responsibilities such as tax compliance through calculations and tax payments. The formalization of electronic cash is also evident in banks. Financial institutions have the opportunity to reach out to potential entrepreneurs by viewing their e-statements on interconnected platforms. Thus, electronic cash has increased the efficiency and profitability of businesses.
Electronic cash is also associated with the promotion of economic affirmative action. The World Bank and other institutions use electronic payment systems to empower women entrepreneurs. Cultural norms and family responsibilities bar women’s from accessing financial services (Klapper, 2017). In fact, women had to travel long distances to access financial services. Today, digital payment gives women access to markets and financial transactions without the need to travel to banks as suggested by the World Bank. These systems also give women the opportunity to manage and transact without scarifying their social responsibilities. The study also refers to World Bank records that show women as the largest customers of online shops.
The World Bank information also argues for “Win-all-situation” for the society that uses digital money. The system has brought many people into the formal financial structure. The World Bank data indicates that over 2 billion people are structurally unbanked, especially the self-employed ones (The World Bank Database, 2017). The electronic money system allows these individuals to conduct financial transactions without banks. They further give merchants and other informal business operators an incentive to conduct regular business operations. The situation provides financial transparency and reduces illicit activities. The system has enhanced a saving culture among the pensionable business owners and employers. Moreover, traders and consumers have the facility to track their transactions and set limits according to their income. In addition, electronic money has opened more opportunities for credits and sponsorship. The efficiency of credit information and test of worthiness allows businesses to access soft loans quicker. Thus, the ease of credit access through electronic money has increased business and consumer purchasing power across the globe, especially in developing countries.
The information on digital money has a precise view of its importance and effect in the money market. The World Bank data in the article show a numerical representation of its value in the market. Electronic cash promotes business operations and expands accessibility to funds and loans to unbanked small business owners. The article also provides alternative use of electronic cash to promote affirmative business inclusion. In addition, the article has several supportive data and information that proves their claim. Therefore, the World Bank has credential information on electronic cash.
Leonard (2011) introduces his lecture by stressing that sampling must be random. The tutor’s understanding of sampling is built on the randomness of the sample as a surety of its authenticity. He further distinguishes between experience and observation as factors to be considered in sampling. In his view, experience gives a surveyor an interactive understanding of the samples while observation only takes keynote of interesting segments. Both help in the treatments and measurement of the data collected. Thus, he reiterates that experience involves modification of technique while observation does not.
Leonard defines a random sample as the technique that gives all sample elements an equal chance of being selected. In this case, the author refers to a street survey with unknown people as a common type of random sample. In addition, he discusses various types of random sample to make it clearer to the students (Leonard, 2011). The random sample technique is classified into the simple, stratified, cluster, and systematic categories depending on the selection procedure. The tutor stresses the difference between the random sample techniques as explained by the convenience of their purpose. Therefore, a convenient sample is one with no premeditated response.
Leonard (2011) defines the simple random sample as one that gives all elements equal opportunity of being selected. On the other hand, the tutor refers to systematic sampling as a sequential data collection technique. Moreover, it has a precise procedure that spells unique data collection process. The systematic technique also gives grouped element an opportunity within a designed order. That strategy is different from the sampling technique in which all elements have an equal opportunity but not guaranteed placements.
The tutor also discusses a stratified random sample, which divides a large population into groups (Leonard, 2011). The technique ensures that members from every group have an equal chance in the sample. Unlike a cluster random sample that selects groups instead of sample elements, the stratified random sample picks elements from the stratified groups.
The Tutor makes reliable remarks in his discussion on the development of a random sample. From the beginning, the tutor defines a sample and uses relevant classroom examples to exemplify his discussion. He also discusses the various types of random samples to clarify their indifference. The tutor distinguishes the simple, stratified, and systemic categories of random sampling using various examples. However, his distinction between the types of random samples is based on procedures involved. He concludes his discussion with retaliation of every point discussed from the beginning to create the literal flow of the discussion. Thus, he gives his students the best opportunity to understand the random types of sampling.
Klapper, L., (2017). Why Digital Payments are Key to Entrepreneurs’ Success. World Bank Data. Retrieved from http://blogs.worldbank.org/jobs/why-digital-payments-are-key-entrepreneurs-success
Leonard, P. (2011). Statistics Lecture 1.5: Sampling Technique. How to Develop a Random Sample. [Video File]. Retrieved from https://www.youtube.com/watch?v=MfkJu7J1LE4
The World Bank, (2017). The Global Findex Database 2017. The World Bank. Retrieved from https://globalfindex.worldbank.org/
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