Openness Analysis For Sweden And Italy
Step 1
Openness for Italy and Sweden from 2003 to 2015 has been reflected in Exhibit 1. The formula for computation of the same is reflected below (Barro, 2017)
Instead of computing openness as indicated above, the incidence of trade barriers (both tariff and non-tariffs) could also have been considered. Considering the percentage of imports on which there is some kind of trade barrier, the two countries can be compared and a degree of their respective openness can be estimated. Higher trade barriers would imply a lower openness of the economy (Dombusch, Fischer and Startz, 2015).
Step 2
The respective plot for openness of the two nations has been represented in Exhibit 2. This graph highlights that Sweden has a higher openness in comparison to Italy for the considered time period. This implies lower barriers to trade in Sweden as compared to Italy. From 2003 till 2008, openness in Sweden witnessed a linear upward trend as openness increased by 20% to reach 94%. This trend was disturbed by the global financial crisis during 2008-2009 when trade witnessed a sharp downfall leading to fall in openness (Krugman, 2015). Even though, Sweden has witnessed minor improvement in openness from the lows witnessed during the global financial crisis but it has not been able to regain the pre-crisis glory as openness has not crossed 90%.
Openness in Italy improved from 46% to 55% during 2003-2008 backed by the buoyant global economic growth. This amounts to an increase of 9% which fades in comparison of Sweden that witnessed a 20% improvement during the same period. During the global financial crisis, the openness for Italy fell to 46% (Mankiw, 2016) However, post crisis improvement in openness for Italy has been superior than Sweden considering that Italy has crossed the peak level of 55% observed in pre-crisis era.
Step 3
The correlation coefficient has been calculated using CORREL() Excel function. This coefficient has been derived as 0.77 for Italy based on the available data for the time period 2003-2015. The positive value of correlation coefficient highlights the existence of a positive relationship between openness and GDP per capita. This is indicative of the fact that there is an association between improvement in openness and improvement in GDP per capital. Further, the strength of this linear association is strong considering that value of the correlation coefficient is close to the theoretical maximum of 1 (Hair et. al., 2015).
In context of Sweden, the correlation coefficient between openness and GDP per capita has been derived as 0.52. The value has come out as positive which implies a positive relation between the two variables. Unlike Italy, the magnitude in case of Sweden is comparatively less but still the relationship is moderately strong. Hence, it is evident that there is positive linear association between openness and economic development for both the nations. However, the precise of this relationship varies for the two countries with Italy showing a stronger trend (Flick, 2015).
Step 4
Exhibit 1
Openness for Italy and Sweden
Exhibit 2
Graph for indicating openness for Italy and Sweden
Exhibit 3
PPF for Italy and Sweden is shown below.
References
Barro, R. (2017). Macroeconomics: A Modern Approach (4thed.). London: Cengage Learning, pp. 67-68
Dombusch, R., Fischer, S. and Startz, R. (2015).Macroeconomics (10thed.). New York: McGraw Hill Publications, pp. 78-79
Flick, U. (2015) Introducing research methodology: A beginner’s guide to doing a research project. 4th ed. New York: Sage Publications, pp. 134-135
Hair, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., and Page, M. J. (2015) Essentials of business research methods. 2nd ed. New York: Routledge, pp. 81-82
Krugman, P. (2015).Macroeconomics (3rd ed.). London: Worth Publishers, pp. 102-103
Mankiw, G. (2016). Principles of Macroeconomics (6th ed.). London: Cengage Learning, pp. 114-116
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