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- Subject Name : Entrepreneurship
Quantitative Research Analysis Report
Introduction to Global Entrepreneurship Monitor Analysis
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.
Aim/Objective
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:
- Univariate analysis of the GEM indicators.
- Multivariate analysis of GEM indicators.
- Independence test of the indicators.
Methodology of Global Entrepreneurship Monitor Analysis
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:
- Total [early stage] Entrepreneurial Activity (TEA): 18-64 years of the population (%) of a new business who are either a nascent entrepreneur or an owner-manager.
- Fear of Failure Rate: Population (%) of 18-64 years who are afraid of setting up a new business due to failure’s fear.
- Perceived Opportunities: Population (%) of 18-64 years who have a positive attitude to start a new business in their residential area.
Under univariate analysis (Glen, S. 2014.),
- Descriptive Summary.
- Graphical representation (Boxplot).
- Correlation and covariance.
Under multivariate analysis,
- Regression of TEA on fear’s failure rate and perceived opportunities.
Under the Independence test,
- Hoteling T-squared test (Glen, S. 2016.)
Descriptive Statistics
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.
Graphical Representation
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.
Correlation and Covariance
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.
Multivariate Regression
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.
Independence Test
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.
Descriptive Statistics
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.
Graphical Representation
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.
Correlation and Covariance
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.
Multivariate Regression
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.
Independence Test
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.
Conclusion on Global Entrepreneurship Monitor Analysis
From the comparison of the cross-sectional analysis of 2018-19 and 2019-20 reports, the conclusions will be:
- In the year 2018-19, there is a negative relation between TEA and fear's failure rate, that in 2019-20, have a positive relationship. Fear's failure rate is more related to TEA in 2018-19 as compared to that in 2019-20.
- Under regression, the individual t-tests and joint F-test are significant in 2018-19 and insignificant in 2019-20. Conclude that in 2019-20, the impact of fear’s failure rate and opportunities on TEA became insignificant.
- The independence test (Hoteling T2) is significant in 2018-19 and 2019-20, concluding there is a relationship between the variables.
References for Global Entrepreneurship Monitor Analysis
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].
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