Quantitative Research Methodology Project Interpretation Marin Adrian Cosmin LMA

7/25/2019 Quantitative Research Methodology Project Interpretation Marin Adrian Cosmin LMA

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Quantitative

research

methodology

projectMarin Adrian Cosmin,

Applied Modern Languages,

948


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Quantitative research

analysis for economic indicators

Introduction

In conducting my analysis, I chose a set of 4 variables for 30 respondents, in my case

for 30 countries from all around the globe. The purpose of my research is to see how exactly

one economic phenomenon is influencing another. The 3 of the 4 indicators are economic

related, meaning that they measure the economic situation of a country, the 4th one being

the population growth of those countries, in order to see how the increase in population

may influence the economic activity, but I will discuss in the following section more aboutthe correlation between the indicators. All the data was provided by the World Bank Group,

data files which are available on the World bank website,www.worldbank.org.

1. Describing the indicators

The first indicator that I analysed is the GDP growth as a percentage. The metadata

for this indicator is as follows: Annual percentage growth rate of GDP at market prices

based on constant local currency. Aggregates are based on constant 2005 U.S. dollars. GDP is

the sum of gross value added by all resident producers in the economy plus any product

taxes and minus any subsidies not included in the value of the products. It is calculated

without making deductions for depreciation of fabricated assets or for depletion and

degradation of natural resources. Basically, this is the main method of analysing the

economic growth of a country and it is closely watched by everyone, from the governmental

entities such Central Banks, to all the financial analysts that are interested in a particular

country. Due to the fact, that it tracks all the goods and services produced in a country, it

might be also measure of the productivity in the national borders. The GDP has 3 methods

based on which it is calculated: consumption method, income method and value added

method, so you have to be careful how you interpret the data. As the metadata of the

indicator that I analysed told us, this GDP growth was calculated through the value added

method.

As I said earlier the GDP growth is driven by the population of the country, so I looked

into the actual growth of that population. A higher population number means that there are

more people who can produce at a some point goods and services that can increase the

economic growth of that country. So, the metadata of the indicator that I used is the

following one: Annual population growth rate for year t is the exponential rate of growth of

midyear population from year t-1 to t, expressed as a percentage . Population is based on

the de facto definition of population, which counts all residents regardless of legal status or

citizenship--except for refugees not permanently settled in the country of asylum, who are

generally considered part of the population of the country of origin.As we can see, in thepopulation measurement there are counted all the people within the borders of a country,
http://www.worldbank.org/http://www.worldbank.org/http://www.worldbank.org/http://www.worldbank.org/


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as they have maintain a standard of living and engage in economic activities.The World Bank

Group gathered the data from: (1) United Nations Population Division. World Population

Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Report

(various years), (3) Census reports and other statistical.

After analysing the population of the country, I have looked into the householdconsumption as a percentage of the GDP to see exactly how much is the private sector

spends on goods and services. The metadata of this indicator as stated by the World Bank is

as follows: Household final consumption expenditure (formerly private consumption) is the

market value of all goods and services, including durable products (such as cars, washing

machines, and home computers), purchased by households. It excludes purchases of

dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments

and fees to governments to obtain permits and licenses. Here, household consumption

expenditure includes the expenditures of nonprofit institutions serving households, even

when reported separately by the country. This item also includes any statistical discrepancy

in the use of resources relative to the supply of resources. As you can see, the privatesector consumption is one of the best ways to see how prosperous a country is. It can give

you an insight also on the standards of living for a specific country, which is pretty much

related to the economic growth.

The last indicator which I used to conduct my research is the inflation. It is generally

known that a countrys most desired level of inflation is 2%, as it is considered the right level

at which an economy grows properly. The metadata of this indicator as stated by the World

Bank is as follows: Inflation as measured by the consumer price index(CPI) reflects the

annual percentage change in the cost to the average consumer of acquiring a basket of

goods and services that may be fixed or changed at specified intervals, such as yearly. TheLaspeyres formula is generally used. Low inflation encourages consumers to buy goods and

services, which leads to economic growth. Delaying will mean that they would have to pay

more for the same product. Low inflation also makes it more appealing to borrow money so

that the entrepreneurs could engage in different projects, since interest rates are usually

also low during periods of low inflation. High inflation can cause the populations confidence

in their own currency and economy to decline, and it can be less appealing for foreign

investors to invest in the country concerned. High inflation therefore often has a harmful

effect on economic growth. For this indicator data, the World Bank Group used data from

International Monetary Fund, International Financial Statistics and data files.

2.

Describing the data

So far, we have analysed only the indicator, what they measure, how are they related

to each other. Lets move now to analysing the data that I have gathered. In the beginnning I

would like to mention that all this data represents the data for 2012 in this countries, as I

could find the data for all the countries. Data of more recent period had not been completed

for every country.

In the first instance, I have sorted the data from the lowest to the highest in terms of


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GDP growth as a percentage. By this indicator, the country with the lowest growth, or better

said with a decrease, is Italy, -2.81%, so the economy of this country was actually sinking in

2012. Closely after Italy, it was Spain with a -2.62%. So, there are actually two countries with

a decrease in the GDP with more than 2.50%, which is a very bad sign, the economy was

practically in a recession. On the other side, the country with the biggest increase in the GDP

is China, +7.75%, which was prospering compared to the other countries, now China has aGDP growth around 6.9% and it is expected to decrease. After China, we had United Arab

Emirates and Philippines with a growth of 6.89%, respectively 6.68%. As a little conclusion,

the European countries had a very bad economic situation, while the Asian countries were a

lot above the others.

Here, in the Figure 1., we can see exactly where is each country situated in terms of

its GDP growth. There are 5 countries which had a decrease in their GDP for the year 2012.

This could represent a very big problem for the people living there as their economy is

sinking, affecting in the end every economic sector.

After analysing the graphic for the GDP growth, I have sorted in the same manner the

data from the lowest to the highest the level of private consumption for the chosen

countries. As you can see in the figure 2, most of the countries have the household

consumption as a percentae of the GDP between 50%-60%.

Luxembourg is the country with the lowest percentage in the household consumption, after

which China is situated almost at the same level as Singapore. These countries have an

economy in which the private consumption is not thatwell developed. It might be a bad signat a certain point when you find out that the consumption sector is driven mostly by the

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Italy

Spain

Finland

Luxembourg

Sweden

Belgium

France

Ukraine

Germany

Romania

Austria

Argentina

Switzerland

UnitedKingdom

Poland

Japan

Brazil

Canada

Turkey

New

Zealand

SouthAfrica

UnitedStates

Norway

RussianFederation

Singapore

Australia

India

Philippines

UnitedArabEmirates

China

Figure 1. GDP growth (annual %)

GDP

growth(annual %)


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public sector, represented by the Government, thing that might affect the people confidence

in the political class. On the other side we have Philippines, Turkey and the United States,

countries that have around 70% from consumption made by the private sector. This could be

interpreted as a good information, but it might be also problematic as the economy is not

producing too much, just consuming.

I have analysized further the population growth of those countries. In the figure 3 we

have the ranking of this data.

There are some countries which actually encountered in 2012 a decrease in their

population. The number of such countries is five. Germany leads this chart with a negative

growth, almost -1.5%. The reasons for population decrease might be very various. The

population might be aging and dying or they might just leave the country, but given the factthat we are discussing here about the biggest economy in the Europe, I think that the first

reason is more appropriate. At a certain point, there would be a very low percentage of

people in the working class that have to sustain the economy.

We have 3 countries which have a population growth of almost 2.5% and those are

United Arab Emirates, Singapore and Luxemboug. In this countries, there are more and more

people. Analysing from the point of view of the economy, this means that the standards of

living are very good in those countries and the economic activities are working properly,

reason why people are more confident that their children could be in a good place to grow.

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20

30

40

50

60

70

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Luxembourg

China

Singapore

Norway

UnitedArab

Sweden

Russian

Belgium

Austria

Australia

Switzerland

Finland

Canada

France

Germany

New

Zealand

Spain

India

Japan

SouthAfrica

Brazil

Poland

Italy

Romania

United

Argentina

Ukraine

UnitedStates

Turkey

Philippines

Figure 2. Household consumption (% of GDP)

Household

consumption

expenditure(% of

GDP)


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In the Figure 4. I have analysed the inflation from the countries as measure by theConsumer Price Index. The country with the lowest inflation is Switzerland, country with a

negative inflation of -0.66%, the same country which has for a few years a negative

benchmark interest rate, which is thought to stimulate the economic activities. Along with

Switzerland, Japan faced a negative inflation of -0.03% in that year, too. Right now, Japan

followed the same monetary policy as Switzerland, fact which makes us take into

consideration more seriously the inlation level. On the ther side, we have Argentina with an

inflation level around 10%, followed by India and Turkey around 9%. This high level of

inflation, again, is not regarded as a good sign, meaning that the population can purchase

fewer and fewer goods and services, which in the long run have a very bad influence on the

overall economy.

3.Grouping the data

The nest step in conducting my research was to group the data into classes. I took

each indicator and I grouped the data by different ranges, showing them in histograms.

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Germany

Romania

Ukraine

Japan

Poland

Spain

RussianFederation

Italy

France

Austria

Finland

China

New

Zealand

UnitedKingdom

Belgium

Sweden

UnitedStates

Brazil

Argentina

Switzerland

Canada

Turkey

India

Norway

SouthAfrica

Philippines

Australia

Luxembourg

Singapore

UnitedArabEmirates

Figure 3. Population growth (annual %)

Population

growth

(annual %)

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1

3

5

7

9

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Switzerland

Japan

Ukraine

UnitedArabEmirates

Norway

New

Zealand

Sweden

Canada

Australia

France

Germany

UnitedStates

Spain

Austria

China

Luxembourg

Finland

Un

itedKingdom

Belgium

Italy

Philippines

Romania

Poland

Singapore

RussianFederation

Brazil

SouthAfrica

Turkey

India

Argentina

Figure 4. Inflation, consumer prices (annual %)

Inflation,

consumer

prices


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(-3%)-(-1%) (-1%)-1% 1%-3% 3%-5% 5%-7% 7%-9%

Figure 5. GDP growth(annual %)

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32%-42% 42%-52% 52%-62% 62%-72% 72%-82%

Figure 6. Household consumption

The Figure 5. Here we have the histogram for the indicator related to the GDP

growth(annual %).

As you can see, I grouped the data into 6 intervals, with a interval width of 2%. From

this histogram we can see very well that 20 out of 30 countries have a GDP growth ranged

between -1% to 3%. In these two intervals, we have 9, respectively 11 countries. From this

histogram we can conclude that there is a positively skewed distribution.

The next histogram is regarded the household consumption, Figure 6.

Based on this indicator, I have grouped the data into 5 intervals with a width of 10%.

15 out of 30 countries, meaning 50%, have a private consumption as a percentage of the

GDP between 52% and 62%. So, those countries find themselves in the middle compared tothe others.


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In the Figure 7. I have drawn a histogram for the population grwoth as a percentage.

Based on the data that I have gathered in the first place, I have grouped it into 7

intervals with a width of 0.5%, as the results of my research provided to be included

between -2% and 2.5%. The interval where is situated a large number of countries is 0%-

0.5%, meaning 7 countries. Closely after this interval, as we can see from this figure, there

are two intervals with the same number of countries, still having a positively skewed

distribution.

In the next histogram, Figure 8, I have grouped the data that I found for the inflation.

Again, there is a positively skewed histogram, with a big percentage of countries with

a inflation between 2.4% and 3.9%. So, most of the countries are situated in the right side of

the histogram.

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(-2%)-(-1,5%) (-0,5%)-0% 0%-0,5% 0,5%-1% 1%-1,5% 1,5%-2% 2%-2,5%

Figure 7. Population growth %

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4.

Descriptive statistics

In the next section, I have summarized the data using descriptive statistics for each

indicator. I would like firstly to explain each component of this descriptive statistics:

the mean is the average of the data, which is the sum of all the observations

divided by the number of observations.

The median is the midpoint of the data set. This midpoint value is the point at

which half the observations are above the value and half the observations are

below the value. The median is determined by ranking the observations and

finding the observation that are at the number [N + 1] / 2 in the ranked order. If

the number of observations are even, then the median is the average value of the

observations that are ranked at numbers N / 2 and [N / 2] + 1.

The mode is the value that occurs most frequently in a set of observations.

Minitab also displays how many data points equal the mode.

The range is the difference between the largest and smallest data values in the

sample. The range represents the interval that contains all the data values. The standard deviation is the most common measure of dispersion, or how

spread out the data are about the mean. The symbol (sigma ) is often used to

represent the standard deviation of a population, while s is used to represent the

standard deviation of a sample. Variation that is random or natural to a process is

often referred to as noise.

The variance measures how spread out the data are about their mean. The

variance is equal to the standard deviation squared.

Skewness is the extent to which the data are not symmetrical.

Kurtosis is used to initially understand general characteristics about the

distribution of your data. The sum is the total of all the data values.

In this figure 9. We have all the statistics for the GDP growth.

The mean of the this indicator is 1.76, meaning that this is the average growth in the

GDP for this 30 particular countries for which I have analysed the data. We can conclude also

that half of the countries have a GDP growth below 1.65% and half of them have a GDP

growth above this number of 1.65%. Giving the fact that there is no identical data in the data

GDP growth (annual %) Figure 9.

Mean 1.768514452

Standard Error 0.458519756

Median 1.657701542

Mode #N/A

Standard Deviation 2.511416134

Sample Variance 6.307210998

Kurtosis 0.619754611

Skewness 0.610550319

Range 10.56823619

Minimum -2.817938597

Maximum 7.750297593

Sum 53.05543357

Count 30


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set, meaning no country has the same values as another one, we have no mode. Moving

forward, we can conclude also that the standard deviation 2.51% meaning that the GDP

growth deviates on average by 2.51% from the mean. In this case we have a positive

kurtosis meaning that the value indicates that the distribution has heavier tails and a sharper

peak than the normal distribution. As for skewness, a positive skewed or right skewed data is

so named because the "tail" of the distribution points to the right, and because its skewnessvalue will be greater than 0 (or positive). GDO growth is often skewed in this manner: many

countries grow relatively little, while increasingly few countries grow faster. The range of the

data is around 10.56, which might be a big difference in the GDP growth of two countries.

The maximum and the minimum of the data set are 2.81%, rescpectively 7.75%. The total

sum of the growths for these countries resulted in a number of 53% for a total number of 30

countries.

The next data set on which I have analysed the descriptive statistics is the household

consumption, as you can see in the Figure 10.

Figure 10. Household consumption expenditure(% of GDP)

Mean 56.01328083


Median 57.04551133

Mode #N/A



Kurtosis -0.031505885

Skewness -0.590229432

Range 41.38900656

Minimum 32.82569233

Maximum 74.21469888

Sum 1680.398425

Count 30

As for the private consumption, from the data set it has resulted a mean of 56%,

meaning that this is the average percentage for the 30 countries of their private

consumption related to their GDP. From the median, we understand that half of the

countries have registered a private consumption as a percentage of the GDP below 57%,whlie half of the countries registered more than this number. Again, as there are no identic

data, there is no mode that can be shown. The standard deviation for this particular

indicator is around 10, meaning that the values can fluctuate more or less 10% from the

mean. A distribution with a negative kurtosis value indicates that the distribution has lighter

tails and a flatter peak than the normal distribution. Left skewed or negative skewed data is

so named because the "tail" of the distribution points to the left, and because it produces a

negative skewness value. As we have seen in the histogram also, there were more countries

on the left side of the histogram. The range for this indicator is 41.38%, which is the

difference between the minimum value, 32.82%, and the maximum, 74.21%.


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Figure 11. Inflation, consumer prices (annual %)

Mean 3.099765888


Median 2.644560242

Mode #N/AStandard Deviation 2.622311712



Skewness 1.321443899

Range 10.69720359

Minimum -0.66694456

Maximum 10.03025902

Sum 92.99297663

Count 30

In the Figure 11, the mean for the inflation indicator is 3.09%, meaning that on average thosecountries have a level of inflation around 3%. Based on the median, half of the countries have an

inflation level below 2.64%, and the other half have more than this level. We do not have a mode for

this indicator, as well, so there is no value to be the same for two countries. In terms of the standard

deviation, on average, the inflation level can fluctuate more or less then the medin by 2.62%. The

same as for the first indicator, GDP growth, we have encountered for the inflation level a positive

Kurtosis and Skewness, so there are more countries in the first intervals by their grouping. The range

is around 10.7%, which is the difference between the maximum level registered by the 30 countries,

10% and the minimum -0.66%.

Finally, in the figure 12, we have the desciptive analysis for the last indicator, population

growth.Figure 12. Population growth (annual %)

Mean 0.78218298


Median 0.732897464

Mode #N/A




Skewness -0.230300358

Range 4.154488678Minimum -1.691348956

Maximum 2.463139721

Sum 23.46548939

Count 30

For this last indicator, we have a mean of 0.78, meaning that on average this is the

percentage that these countries have in terms of their annual population growth. Regardin the

median, it is shown that half of the countries have a population growth below 0.73%, while the other

have has more than this number. For this indicator, we have no mode. The standard deviation shows

us that the growth for this countries deviates from the median with around 0.90%. What is a little

strange is the fact that we encountered a positive Kurtosis and a negative Skewness, meaning that


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the value indicates that the distribution has heavier tails and a sharper peak than the normal

distribution as for kurtosis and it is left skewed.

5.Scatter Diagram

For creating this scatter plot diagram, I have chosen two out of the 4 indicators, and those

are the GDP growth and the Population growth. We can analyse this graphic by 3 major

characteristics: direction, form and strenght.

In terms of the direction, we can see very well that there is a positive direction. The data

goes from lower values and it increases on the both axis. The higher the GDP growth, the higher the

population growth we have. As for the form of the scatter diagram, there is a tendancy of a linear

association of these values, forming a trend line, but if we take into consideration the strenght, we

conclude that there is a moderate" positive correlation.We have to mention also, that there a few outliers which influence the diagram, giving it this

moderate correlation. Excluding the outliers, we would have a strong correlation between the two

variables.

6.Covariance and Coefficient of Correlation

Covariance indicates how two variables are related. A positive covariance meansthe variables are positively related, meaning that when a variable increases, the other

acts the same, while a negative covariance means the variables are inversely related,

which is in opposite reaction.

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-2 -2 -1 -1 0 1 1 2 2 3 3

Populationgrowth(annual%)

GDP growth (annual %)

Scatter plot diagram


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For the 4 indicators that I have analysed, they had both positive and negative

covariance. The covariance between GDP growth and the household consumption was

-3.49, so when the first indicator increases, the other one decreases. Between the GDP

and the inflation, we had a covariance of 0.72, meaning that when the first one

increases, the second one increases as well, and for the GDP and population growth, the

covariance was 0.88, positive relatedThe household consumption and inflation have a covariance of 7.20, and for between

household and population growth is -3.06, having a negative relation for the two

indicators. Between the inflation and population growth there is postive related

correlation, of 0.39.

Correlationis another way to determine how two variables are related. In additionto telling you whether variables are positively or inversely related, correlation also tells

you the degree to which the variables tend to move together.

Correlation standardizes the measure of interdependence between two variablesand, consequently, tells you how closely the two variables move. The correlation

measurement, called a correlation coefficient, will always take on a value between 1 and

1:

In our case, the coefficient of correlation between GDP growth and household

consumption is -0.1406, meaning that they do not move together. On the other hand,

between GDP and inflation level, I have encountered a positive correlation 0.1144, meaning

that when it is increasing, the other one follows. The same we can say about GDP and

population growth, with a coefficient of correlation of 0.4049.

The household consumption and the inflation have a correlation of 0.2779, while

with the population growth it has a negative one, of -0.3462. And finally, the correlation

between inflation level and population growth is -0.3462, so they are negative correlated.

The closer the correlation coefficient is from the two extremes, -1 and 1, the stronger

the positive or negative correlation between two indicators. So, the strongest one is in the

case of GDP growth and population growth.

7.Spearman correlation-nonparametric measurement

All correlation analyses express the strength of linkage or co-occurrence between to

variables in a single value between -1 and +1. This value is called the correlation

coefficient. A positive correlation coefficient indicates a positive relationship between

the two variables (the larger A, the larger B) while a negative correlation coefficients

expresses a negative relationship (the larger A, the smaller B). A correlation coefficient

of 0 indicates that no relationship between the variables exists at all. However

correlations are limited to linear relationships between variables. Even if the correlation

coefficient is zero a non-linear relationship might exist.

For this correlation, I have chosen the same indicators as in the scatter diagram, the

GDP growth and the population growth. Based on this method of analysis, the Spearmancoefficient of correlation was -0.00333704, which is pretty much closely to 0. As I said


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earlier, this could mean that the two variables are not correlated and it tends to go into

the negative correlation, meaning that when a variable increases, the other might

decrease.

Conclusions

As a conclusion, there are various methods in which you can interpret and analyze a

set of data, each method serving a different purpose. The various the methods of

analysing, the better understanding you get from the relation between more variables.

In terms of my research, I think that there will always be a correlation between every

indicator or every action which is related to the human action. Everyone is acting in his

own manner, but since we are all people, we might think the same way at a certainpoint. We all want the best we can get from our life and we can see this from a set of

indicators as I have analysed. Even if, we might thing that a small action has not an

influence on another one, well, in the end it seems that it has.

Project realised by:

Adrian Cosmin Marin

Applied Modern Languages

International Business and Economics

Group:948

Quantitative Research Methodology Project Interpretation Marin Adrian Cosmin LMA

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