Economic growth (or production growth) is what every economy aims for along with a sustainable environment. One of the factors is entrepreneurship which brings investments, and new capital, more related to the business goals and helps to achieve the economy’s growth along with the achievement of the SDGs (Kelley, D. and Bosma, N. 2018.).
Like the other factors, entrepreneurship also requires supervision to make it work efficiently and towards the right goal. A non-profit organization has been formed in 1999, named “The Global Entrepreneurship Monitor (GEM)” to monitor the entrepreneurs’ activities across countries by studying the indicators, in terms of quality, rank, and percentage and the aspect of attitudes, and countries’ perceptions, motivations, their activities in entrepreneurship, and impact of all the other aspects on the economy and the growth of the economy (jobs, scope and so on).
This report will cover the aim of the study, then the methodology, which will discuss what variables and what analyses will be performed and how it will be done. After that, a section will analyze the data and concluded the results which will be discussed in the conclusion section.
The aim of the study is to analysis any 3 common factors of GEM reports of 2018-19 and 2019-20 reports with the following objectives:
To achieve the objectives of this study, the data (in %) will be collected from the reports of the different countries and a cross-sectional analysis will be performed using excel and STATA software for year individually.
The GEM indicators that will be studied are:
Under univariate analysis (Glen, S. 2014.),
Under multivariate analysis,
Under the Independence test,
The above descriptive summary tells that the average TEA is 12.62%, that is, 12.62% of the population is an owner-manager or a nascent of a new business. 36.23% of the people are afraid to start a business due to failure. 45.59% of people are being optimistic about starting a business in their residential areas.
The boxplot representation shows that the variables’ groups are different from each other as each variable’s mean and median is quite far from each other and outside the others’ interquartile range. The perceived opportunities’ data has a larger dispersion relatively. It can also be noticed that TEA and the rate of failure's fear are having outliers as well.
From the above tables, it can be noticed that TEA and the rate of failure's fear are having a negative relationship and having a positive relationship with perceived opportunities and both are having a weak correlation with TEA. The independent variables, failure rate, and opportunities are having a negative relationship.
Regressing TEA on failure’s fear rate and opportunities perceived concludes that the independent variables are explaining 30% of the TEA’s variations. Individual t-tests of the coefficients rejected the null hypothesis is rejected and concluded the coefficients are not 0, having a significant impact on TEA. F-test for joint significance rejected the null hypothesis, concluded that at least one coefficient is not 0.
The hypothesis:
H0: No association between the variables.
H1: Association between the variables.
Under the assumption of the true null hypothesis, using the p-value test has rejected the null hypothesis, concluded all the variables are not the same, and hence, there is an association between the variables at a 5% significance level.
The above descriptive summary tells that the average TEA is 12.82%, that is, 12.82% of the population is an owner-manager or a nascent of a new business. 41.75% of the people are afraid to start a business due to fear of failure. 53.65% of people are being optimistic about starting a business in their residential areas.
The boxplot representation shows that the variables' groups are different from each other as each variable's mean and median is quite far from each other and outside the others' interquartile range. The perceived opportunities'' data have larger dispersion relatively. It can also be noticed that TEA and rate of failure's fear are having outliers as well, where TEA is having outlier at the upper end and the latter one is having at a lower end.
From the above tables, it can be noticed that TEA is having a positive relationship with the rate of failure’s fear and perceived opportunities and both are having a very weak correlation with TEA. The independent variables, failure rate, and opportunities are also having a positive relationship with each other and have a relatively strong correlation as compared to that with TEA.
Regressing TEA on failure’s fear rate and opportunities perceived concludes that the independent variables are explaining 0.2% of the TEA’s variations. Individual t-tests of the coefficients did not reject the null hypothesis, concluded the coefficients are 0, and having an insignificant impact on TEA. F-test for joint significance, do not reject the null hypothesis, concluded that coefficients are 0.
The hypothesis:
H0: No association between the variables.
H1: Association between the variables.
Under the assumption of the true null hypothesis, using the p-value test has rejected the null hypothesis, concluded all the variables are not the same, and hence, there is an association between the variables at a 5% significance level.
From the comparison of the cross-sectional analysis of 2018-19 and 2019-20 reports, the conclusions will be:
Bosma, N., Hill, S., Ionescu-Somers, A., Kelley, D., Levie, J., and Tarnawa, A. 2020. Global Entrepreneurship Monitor: 2019/2020 Global report. [Online]. Available at: https://www.gemconsortium.org/report/gem-2019-2020-global-report [Accessed on September 20, 2020].
Glen, S. 2014. Univariate Analysis: Definition, Examples. [Online]. Available at Statistics How to: https://www.statisticshowto.com/univariate/ [Accessed on September 22, 2020].
Kelley, D., and Bosma, N. 2018. Global Entrepreneurship Monitor: 2018/2019 Global report. [Online]. Available at: https://www.gemconsortium.org/file/open?fileId=50213 [Accessed on September 20, 2020].
Glen, S. 2016. Hoteling’s T-squared: Simple Definition. [Online]. Available at Statistics How to: https://www.statisticshowto.com/hotellings-t-squared/ [Accessed on September 22, 2020].
Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Entrepreneurship Assignment Help
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