Excel Assignment
Introduction
This particular research will involve the study of the gross domestic product of a different number of countries all over the world—the total local products of these countries from the year of 1820 to the year 1998. The data on the excel sheet about the GDP of the various states have got four subsets of different countries (Kuc-Czamecka, 2017). The subsets of the countries across the world include the Latin American countries, Asian countries, European countries, Asian countries, and the African countries. Some necessary analysis of the data using the excel sheet formulas will be done to study the economy of the world from the year of 1870 to the year 1998.
Data Analysis
The purpose of the data on the excel sheet is to enhance the examination of the world economy using different forms of data analysis. There will be the calculation of the convergence regressions in association with the Salai-martin plots about the economy of the given years. The study will be done on all the captured counties as a whole and also on the various subsets within the collected data. These four subsets include the African countries, Asian countries, Latin American countries, and the European countries. There will be various plots of the data to come up with the proper and relevant schemes to carry out the analysis of the economy worldwide (Shofield, 2015). To produce the projects that have got similar appearance to those of figure 1 and figure 2, it is necessary to calculate the natural logarithm of some variables on the excel sheet.
There are two main types of converges of the data, that is the β unites, and the δ converges. When the weak economies seem to overgrow than the vibrant economies, then the process is said to be absolute β convergence (Tachella, 2018). The δ converges to the groups of the prosperity that tend to unite in a manner of dispersion where the actual capital on the GDP decreases with time. The analysis of the data is done using the Gross domestic product per country in various countries across the world.
Figure 1.1. The distribution of the GDP for the entire world
Fig 1.2: The distribution Gross domestic product from the year 1820 to the year of 1998 of the second subset of the data.
Figure 1.3: The distribution of the Gross domestic product from the year 1820 to the year 1998
Figure 1.4: The relationship between the Gross domestic product if the entire world and the second subset of the data.
Figure 1.5: The relationship between the Gross domestic product of the whole countries and the first two subsets from the year 1820 to the year 1998
Results and Conclusion
As per the distribution of the data from the first set to the third set, the economy of the trend increases persistently from the year 1820 to the year 1998. The analysis was done using the δ convergence, where the natural logarithms are used to plot the relevant graph of the data. The standard deviation of the data that ranges from the approximate minimum of the three and a maximum of 4.3 (Teeling, 2020). These respective values indicate the sigma convergence that is obtained by the use of the natural logarithms.The data is said to follow the distribution o0f the Gross domestic product since the dispersion of the GDP values decreases with time on the graph plot. Therefore, as per the dissemination of the data, there is enough evidence by use of the visual impression on the plot of the data to say that the data follows the δ convergence distribution.
References
Kuc-Czarnecka, M. (2017). Is the regional divergence a price for the international convergence? The case of the Visegrad group. Journal of Competitiveness, 9(4), 50-65.
Schofield, D., Shrestha, R. N., Cunich, M. M., Passey, M. E., Veerman, L., Tanton, R., & Kelly, S. J. (2017). The costs of diabetes among Australians aged 45–64 years from 2015 to 2030: projections of lost productive life years (PLYs), lost personal income, lost taxation revenue, extra welfare payments and lost gross domestic product from Health&WealthMOD2030. BMJ Open, 7(1).
Tacchella, A., Mazzilli, D., &Pietronero, L. (2018). Dynamical systems approach to gross domestic product forecasting. Nature Physics, 14(8), 861-865.
Teeling, S. P., Dewing, J., &Baldie, D. (2020). A discussion of the synergy and divergence between Lean Six Sigma and person-centered improvement sciences. International Journal of Research in Nursing.