ECONOMIC ANALYSIS

Economic Analysis

[Name of the Institute]

Introduction

The global economic paradigm has been divided into three prominent groups, in which almost all of the countries lie in any one of them. For the analysis, in our research, the data set has been divided into three prominent categories, where the countries are divided into developed, under developing and least developed (Bills et.al, 2011, pp. 129). The criteria set for determining the development is mainly on the basis of the economic health of that very country. The most common criteria for gauging the economic condition of any of the country are on the basis of the GDP that they have (Carson et.al, 2009, pp. 381). As it can be seen in the data set that we have, the GDP is the primary variable, for every country. However, GDP alone is not the criteria to gauge the economic development of the country, and that is the reason for which we will be seeing many countries in the data set, with a high GDP but yet not placed under the developed category.

How GDP differs between groups

The first and the foremost task of our data analysis is to get the results for the differentiated GDP figures, which exist between the countries belonging to three different categories, which are, developed, under developing and least developed. In order to conduct the analysis there are few assumptions that we have to make and then test them through an appropriate test. The most appropriate test for the comparison can be “difference of means.” This test is used to find out, whether; on an average the testing variable has the same or the different values among the groups. Similar values define that there are no differences, on an average between the GDPs of the countries, while different values define that average GDPs of the countries, belonging to the different groups are differentiated from each other.

Table 1:

Test of Homogeneity of Variances

Gross Domestic Product per capita

Levene Statistic

df1

df2

Sig.

34.813

2

88

0.00

Table 2:

ANOVA

Gross Domestic Product per capita

 

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

4543000000.00

2.00

2272000000.00

33.12

0.00

Within Groups

6037000000.00

88.00

68600000.00

 

 

Total

10580000000.00

90.00

 

 

 

Table 3:

Multiple Comparisons

Dependent Variable: Gross Domestic Product per capita

 

(I) development level

(J) development level

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

 

 

 

 

 

 

 

Lower Bound

 

LSD

Developed

Developing

13491.04

2004.56

0.00

9507.40

 

 

 

Least Developed

16708.36

2308.94

0.00

12119.82

 

 

Developing

Developed

-13491.04

2004.56

0.00

-17474.69

 

 

 

Least Developed

3217.32

2218.91

0.15

-1192.30

 

 

Least Developed

Developed

-16708.36

2308.94

0.00

-21296.90

 

 

 

Developing

-3217.32

2218.91

0.15

-7626.94

 

Tamhane

Developed

Developing

13491.04

2438.48

0.00

7420.21

 

 

 

Least Developed

16708.36

2275.81

0.00

10973.03

 

 

Developing

Developed

-13491.04

2438.48

0.00

-19561.88

 

 

 

Least Developed

3217.32

1034.21

0.01

658.60

 

 

Least Developed

Developed

-16708.36

2275.81

0.00

-22443.69

 

 

 

Developing

-3217.32

1034.21

0.01

-5776.04

 

. The mean difference is significant at the 0.05 level.

For the first table above, we can see that the results of the Levene test, telling us the equality or difference of the variation, which exist between the group. By looking at the results, we could say that our assumption or null hypothesis of equality of variance among the group has been rejected. Therefore we would say that the variation in the GDP with in the groups is not same among the group. Further elaborating this, we could say that with in each of the categories, lies a difference in the GDP countries (Castro et.al, 2008, pp.180), which is different from the variation in other categories. But more importantly, we have to analyze the results, which elaborate the mean or the average GDP of the categories and the reason of their ...