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Data Analysis

Assume that you are an economic consultant hired by an international organization/government to provide your expert advice on conditions pertaining to international trade in Italy and Sweden. Your analysis will consist of two separate reports (one for Assignment 1 and the other for Assignment 2). As an expert, your job is two-fold:

  1. You are required to analyse any relevant issue using your technical skills. This involves utilizing your knowledge in international trade models as well as inspecting and interpreting data.
  1. You need to communicate your results in an effective way.

The purpose of this exercise is to assess your aptitudes in each domain. You will evaluate the trading conditions in these countries (Italy and Sweden) based on the scenarios detailed in each question in this Assignment. Your analysis will form the basis for a short report to the international organization/government body---summarising your analysis and the associated rationale.

  1. Data Source

For your data analysis, you first need to obtain data from the World Bank (see the link below) and follow the steps described below. Notice that World Bank regularly updates its database; therefore it is crucial to obtain all data as soon as possible. The data range is from 2003 to 2015.

You need to obtain the country-level data for Italy and Sweden on:

  1. Imports of goods and services (in current US$)
  2. Exports of goods and services (in current US$)
  • GDP (in current US$)
  1. GDP per capita (in current US$)
  2. GINI  Index  (World  Bank  estimate)  from  the  World  Bank's  World

Development Indicators:

(http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators).

Your tasks involve two dimensions. Firstly, you need to analyse the data (see Steps 1, 2 and 3 in the next section). Secondly, you need to perform a technical analysis by considering a hypothetical trading environment based on Ricardian model (see Step 4 in the next section).

Accordingly, you are required to:

Provide information about how integrated these two countries (Italy and Sweden) are with the rest of the world. To do so, you need to look at their trade flows relative to their GDP and calculate openness.

Provide a visual representation of your findings by plotting a graph that shows the change in openness for these countries over the time period between 2003 and 2015.

Establish whether being integrated with the rest of the world helped these two countries by looking at the correlation between their openness and GDP per capita.

Conjecture what would have happened if these countries were not open to trade with the rest of the world by evaluating a hypothetical scenario based on a simple Ricardian model.

Data Analysis

Step 1. Using trade flows in your data, calculate openness as a percentage for Italy and Sweden and present them for each year for both countries as a table. You need to explain your method, namely, how you calculated openness using trade flows (write down the formula). In addition, you need to state what other alternative ways you could have adopted to calculate openness other than using trade flows.

Step 2. Using the calculations you did for openness in Step 1, plot openness (as a percentage) against time (2003-2015) for both countries (Italy and Sweden) in a single graph. Put openness (as a percentage) on the vertical axis and time on the horizontal axis. Explain and compare briefly how openness changes for these countries over time. Make sure you limit your explanation to 200 words.

Step 3. Explain in up to 200 words the relationship between openness and economic development by calculating the correlation coefficient between GDP per capita (proxy for economic development) and openness for each of the two countries

Technical Analysis

Step 4. In order to conjecture the circumstances in these two countries under autarky (when there is no trade), consider the following hypothetical scenario based on Ricardian model. Assume throughout that those two countries (Italy and Sweden) are the only two countries in the world, at least for purposes of trade. There are two goods: shoes and calculators. Consumers in both countries always spend half of their income on shoes and half of their income on calculators. The only factor of production is labour. Each Italian worker can produce 1 shoe or 2 calculators per unit of time. Each Swedish worker can produce 4 shoes or 2 calculators per unit of time. There are 80 workers in Italy and 60 workers in Sweden. You need to provide conditions in each country by stating:

  1. Which country has an absolute advantage in shoes? In calculators?

  2. Which country has a comparative advantage in shoes? In calculators?

  3. Draw the production possibility frontier for each country and indicate slope (put shoes on the vertical axis and calculators on the horizontal axis).

  4. Find the autarky relative price of calculators in both countries (i.e., the price of calculators divided by the price of shoes).

  5. What is the optimal consumption and production for each country under autarky?

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 (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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