Data Analysis

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

1. Taking into consideration the information presented, for shoes the absolute advantage is with Sweden considering the fact that four shoes may be manufactured in a unit time in Sweden as against one shoe in Italy. In case of calculators, absolute advantage is possessed by neither of the two countries since in a unit time, each country manufactures 2 calculators per unit time. (Barro, 2017).
2. The comparative advantage is dependent on the underlying opportunity cost associated with the production of a given item (Mankiw, 2016). With regards to shoes, Italy has an opportunity cost of 2 calculators. On the other hand, Sweden has an opportunity cost of (2/4) or 0.5 calculators. As a result, Sweden has the comparative advantage in shoes. With regards to calculators, Italy has a lower opportunity cost of (1/2) shoes or 0.5 shoes in comparison to (4/2) or 2 shoes for Sweden. Hence, comparative advantage for calculators is with Italy.
3. The PPF for Italy and Sweden are indicated in Exhibit 3. The respective slope of PPF for Italy and Sweden are -0.5 and  -2 respectively.
4. Calculator relative price under autarky in Italy = (80/160) = 0.5
   Calculator relative price under autarky in Sweden = (240/120) = 2
5. Based on the given data, under autarky, it is suggested that Sweden should make a total of 240 shoes owing to competitive advantage. The consumption should be 100 shoes while the remaining 140 ought to be exported to Italy. With regards to Italy, the comparative advantage lies in manufacturing of calculator and hence 160 calculators should be produced. Out of these 160 calculators, 100 should be consumed while 60 ought to be exported to Sweden.

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 (4^thed.). London: Cengage Learning, pp. 67-68

Dombusch, R., Fischer, S. and Startz, R. (2015).Macroeconomics (10^thed.). 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 (3^rd ed.). London: Worth Publishers, pp. 102-103

Mankiw, G. (2016). Principles of Macroeconomics (6^th ed.). London: Cengage Learning, pp. 114-116