Correlation between Openness and the GINI Index for each nation:
Paraguay |
||||||
Indicator Name |
Exports of goods and services (current US$) |
Imports of goods and services (current US$) |
GDP per capita (current US$) |
GDP (current US$) |
GINI index (World Bank estimate) |
openness = (X+M)/GDP |
2001 |
3459319570 |
2727373823 |
1417.261 |
7.66E+09 |
54.6 |
0.807388793 |
2002 |
3402825624 |
2298406126 |
1148.23 |
6.33E+09 |
57.3 |
0.901358887 |
2003 |
3625989129 |
2623501714 |
1174.779 |
6.59E+09 |
54.9 |
0.948602359 |
2004 |
4371893087 |
3307792347 |
1408.528 |
8.03E+09 |
52.3 |
0.955912704 |
2005 |
5083809323 |
4018039423 |
1507.146 |
8.73E+09 |
51.4 |
1.042038865 |
2006 |
6252319090 |
5221045741 |
1809.711 |
1.06E+10 |
53 |
1.077700041 |
2007 |
7818347667 |
6461917817 |
2312.193 |
1.38E+10 |
53 |
1.035183617 |
2008 |
9993980610 |
9166237324 |
3059.992 |
1.85E+10 |
50.7 |
1.035456255 |
2009 |
8210295841 |
7130137358 |
2599.596 |
1.59E+10 |
49.1 |
0.962996073 |
2010 |
11036468064 |
10313046052 |
3225.592 |
2E+10 |
51 |
1.065848792 |
2011 |
13186264509 |
12621883682 |
3988.012 |
2.51E+10 |
52.3 |
1.028226124 |
2012 |
12278348692 |
11979621541 |
3855.538 |
2.46E+10 |
47.6 |
0.986284003 |
2013 |
14356651476 |
12983600420 |
4479.906 |
2.9E+10 |
47.9 |
0.943876964 |
2014 |
13954911448 |
13242370791 |
4712.823 |
3.09E+10 |
50.7 |
0.880707726 |
Poland |
||||||
Year |
Imports of goods and services (current US$) |
Exports of goods and services (current US$) |
GDP per capita (current US$) |
GDP (current US$) |
GINI index (World Bank estimate) |
Openess= (X+M)/GDP |
2001 |
58766945944 |
5.19E+10 |
4981.199 |
1.91E+11 |
32.8 |
0.580751947 |
2002 |
63908088235 |
5.71E+10 |
5196.933 |
1.99E+11 |
34.1 |
0.609244563 |
2003 |
78406788377 |
7.26E+10 |
5693.524 |
2.18E+11 |
34.9 |
0.694373057 |
2004 |
94256069554 |
8.74E+10 |
6681.179 |
2.55E+11 |
35.4 |
0.71213167 |
2005 |
1.09184E+11 |
1.06E+11 |
8021.252 |
3.06E+11 |
34.5 |
0.702749609 |
2006 |
1.3768E+11 |
1.31E+11 |
9040.77 |
3.45E+11 |
33.7 |
0.777913937 |
2007 |
1.80703E+11 |
1.66E+11 |
11260.32 |
4.29E+11 |
33.5 |
0.806620046 |
2008 |
2.28993E+11 |
2.02E+11 |
14001.45 |
5.34E+11 |
33.7 |
0.807544541 |
2009 |
1.67514E+11 |
1.64E+11 |
11542.02 |
4.4E+11 |
33.6 |
0.752259133 |
2010 |
2.01543E+11 |
1.92E+11 |
12597.86 |
4.79E+11 |
33.2 |
0.821083264 |
2011 |
2.35386E+11 |
2.25E+11 |
13890.7 |
5.29E+11 |
32.8 |
0.870827228 |
2012 |
2.24547E+11 |
2.22E+11 |
13143.52 |
5E+11 |
32.4 |
0.893274621 |
2013 |
2.32599E+11 |
2.43E+11 |
13780.19 |
5.24E+11 |
32.5 |
0.906918664 |
2014 |
2.51529E+11 |
2.59E+11 |
14339.67 |
5.45E+11 |
32.1 |
0.937329374 |
Using Excel, the correlation between the GINI Index and openness for each nation is calculated. For Paraguay the correlation coefficient is -0.25798 and for Poland it is -0.60988.
Correlation |
|
Paraguay |
-0.25798 |
Poland |
-0.60988 |
Gini Index is a statistical measure for income inequality. It is used to estimate inequality in income distribution and also in wealth distribution in the economy. The GINI index ranges from 0 to 1 where the value 0 indicates perfect income equality and 1 represents perfect income inequality among the population (Staff, 2018).
The Openness Index is calculated as the ratio of total trade, i.e. (exports plus imports), to the country’s GDP (“Trade openness”, 2018).
Openness= (Exports + Imports) / (Gross Domestic Product) =(X + M) / (GDP)
The interpretation of the Openness Index is: the higher the index the larger the influence of trade The higher the trade openness, the higher will be the trade’s influence on domestic activities.
Paraguay has a negative relationship (-0.257) between trade openness and the GINI Index which means that as the inequality rises, i.e. the GINI Index rises, the trade openness will fall down. Since the negative relationship is not very strong, the damage will not be severe.
Poland also has a negative relationship (-0.6098) between trade openness and the GINI Index which means that as the inequality rises, i.e. the GINI Index rises, the trade openness will fall down. Since the negative relationship is strong (greater than 0.5) the damage will be slightly severe.
The negative impact will be more on Poland than on Paraguay.
According to the Stolper Samuelson Theorem, if the relative price of a labour intensive good rises in an economy, then the producers of labour intensive good will be better off than the producers of capital intensive good (“Stolper-Samuelson Theorem (SST) | Theorems | Economics”, 2018).
The Stolper-Samuelson Theorem is valid when certain conditions are fulfilled by the market. It establishes a relationship between factor price ratio and commodity price ratio. If the price of labour intensive good will rise, then an increase in the production of that good will increase the demand for labourers which will put upward pressure on the wage rate. Due to increase in the price of labour intensive good, the production of capital intensive good will fall and this will not only reduce the demand for capital but also reduce the rental rate (Salvatore, 2016).
In the above diagram as the price of apparel rises, which is labour intensive, the real wage rate rises and the rental rate falls, hence proving the theorem. E is the initial equilibrium and E’ is the new equilibrium after the price rise in the apparel.
Using the correlation coefficient of both the country to explain the relevance of Stolepr-Samuelson Theorem:
Paraguay has a negative correlation coefficient of -0.25798 and Poland has a negative correlation coefficient of -0.60988. It represents a weak relationship between economic growth and trade for both the countries. Stolper-Samuelson theory is a fundamental theorem of the Hecksher-Ohlin model to establish the returns on capital and labour. If both the countries are labour abundant, then the relative prices of the labour will rise as compared to capital. My data is not very consistent with the Stolper-Samuelson theorem because in case of Paraguay a very strong relationship cannot be established and in case of Poland the relationship is comparatively stronger.
Each home country worker can produce 2 units of Corn or 3 units of Radios per unit of time, while each foreign worker can produce 2 units of Corn or 4 units of Radios per unit of time. There are 30 workers in Home and 60 workers in Foreign.
Price of Radios (PR) * Quantity of Radios (QR) = 2/3M
Price of Corn (PC) * Quantity of Corn (Qs) = 1/3M
Where M = Income
QR / QC = 2 PC / PR
Calculating the opportunity cost of producing radio per unit of Cloth at Home
Labour = 30
For producing corn, unit labour required is aLC = ½
For producing radio, unit labour required is aLR = 1/3
aLR / aLC = 2/3 labour is required for producing radio with respect to cloth.
Calculating the opportunity cost of producing radio per unit of Cloth at Foreign
Labour* = 60
For producing corn, unit labour required is a*LC = ½
For producing radio, unit labour required is a*LR = 1/4
a*LR / a*LC = 1/2 labour is required for producing radio with respect to cloth.
Relative Quantity: (QR + QR*) / (QC + QC*) = (30/(1/3)) / (60/ (1/2)) = ¾
The equilibrium is established at the point where Quantity Demanded is equal to Quantity Supplied (“International Trade: Theory and Policy v1.0 | FlatWorld”, 2018).
When QR / QC = ¾,
Then PR / PC = 2/ (3/4) = 8/3
We can see that 8 / 3 > (aLR / aLC = 2/3)’
In the diagram, the relative demand curve passes through the right part of the relative supply curve.
At equilibrium:
PR / PC = aLR / aLC = 2/3
QR / QC = 2 PC / PR = 2 (3/2) = 3
Relative Demand and Supply Curve
Under free trade
a*LR = 1/4
a*LC = ½
L* = 60
Foreign will produce Corn: 60 / (1/2) = 120 units.
aLC = ½
aLR = 1/3
L= 30
Home will produce both corn and radio since QR / QC = 3 = (QR + QR*) / (QC + QC*)
3 = QR / (QC + 120)
3 QC + 360 = QR
Home can produce any combination of corn and radio that satisfies the above equation (“Terms of Trade”, 2018)..
free trade in each country.
Both the countries gain from trade (“17.1 The Gains from Trade | Principles of Economics”, 2018). According to comparative advantage, the countries produce the commodity in which they have a lower opportunity cost. Home and Foreign countries produce according to their opportunity cost and hence both gain from trade.
Foreign is producing radios, and radio is a capital intensive good, so the labourers working in the radio production will be better off, than the workers engaged in corn production. Labourers involved in producing corn will not support free trade as much as radio producers.
In Home, both the goods are produced so the labourers will be neutral about free trade. Since labourers involved in both the industries are gaining from trade (Krugman, Obstfeld, Melitz, Yamagata & Morioka, n.d.).
References
17.1 The Gains from Trade | Principles of Economics. (2018). Retrieved from https://open.lib.umn.edu/principleseconomics/chapter/17-1-the-gains-from-trade/
International Trade: Theory and Policy v1.0 | FlatWorld. (2018). Retrieved from https://catalog.flatworldknowledge.com/bookhub/28?e=fwk-61960-ch07_s02
Krugman, P., Obstfeld, M., Melitz, M., Yamagata, H., & Morioka, S. Kuruguman kokusai keizaigaku. Maruzenshuppan.
Salvatore, D. (2016). International economics. Hoboken, NJ: John Wiley & Sons, Inc.
Staff, I. (2018). Gini Index. Retrieved from https://www.investopedia.com/terms/g/gini-index.asp
Stolper-Samuelson Theorem (SST) | Theorems | Economics. (2018). Retrieved from https://www.economicsdiscussion.net/theorems/stolper-samuelson-theorem-sst-theorems-economics/26931
Terms of Trade. (2018). Retrieved from https://www.investopedia.com/exam-guide/cfa-level-1/global-economic-analysis/terms-trade.asp
Trade openness. (2018). Retrieved from https://www.economicsonline.co.uk/Global_economics/Trade_openness
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