Quantitative Data Analysis Report

This report evaluates the impact of unemployment over the GDP of the economy using quantitative data analysis. It covers business research problem, literature review, dataset identified, quantitative analysis, visualisation of data and findings.

Quantitative Data Analysis
Report

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
Business research problem..........................................................................................................3
Literature review.........................................................................................................................3
Dataset identified........................................................................................................................5
Quantitative analysis...................................................................................................................5
Visualisation of data....................................................................................................................7
Findings.......................................................................................................................................8
CONCLUSION................................................................................................................................8
REFERENCES..............................................................................................................................10

INTRODUCTION
Quantitative data analysis is concerned with evaluating the numerical figures on that fact
based decision can be formulated. In the current era, having quantitative data analysis is required
to be taken into consideration so hat significant ability to evaluate the prevailing performance
can become possible. The current study is based on evaluating the impact of unemployment over
the GDP of the economy. It will give emphasis on evaluating business research problem and
literature by covering the relevant theory. The study will pay attention on having quantitative
analysis of data set along with the visualization. This will include findings so that appropriate
knowledge can be provided.
MAIN BODY
Business research problem
Unemployment is one of the major issue that is related with individuals who are actively
finding the employment opportunities but unable to get. GDP indicator of economy growth by
reflecting its performance. Unemployment leads to low personal consumption, investment, etc.
activities that can impact on GDP of country. From the evaluation it can be specified that the
GDP and unemployment usually go together. It can be articulated that there are few sectors who
are considered to be labour intensive which involves having unemployment rate is higher if the
GDP comes from the greater labour intensive industry. This can be properly understanding with
help of the below conducted quantitative data analysis.
Literature review
In the views of Cosculluela-Martinez (2020) GDP is one of the significant factor that is
taken into consideration for standard measure of value added via production of the goods and
services for the specified period. It is taken into process for evaluating the performance of
business in the significant manner via focusing on private consumption, gross private and
government investment along with spending. It refers to the monetary market value of all the
finished goods and services that are manufactured in the particular duration. It plays important
role in reflecting the overall performance of country. There are different factors that influences
the GDP of country which includes personal composition, investment, net exports and
government expenditure. In against to this, Strauss, Isaacs and Rosenberg (2021) that GDP is
reflection of country's performance which is determined by taking distinct factors into

consideration. The elements include natural resources, capital goods and technology and human
resource. Human resource is considered to be crucial factors that influences GDP performance of
economy. On the basis of this, it can be interpreted that unavailability of required level of skilled,
unskilled, etc. form of employees impact the GDP.
In the views of Brancaccio, Garbellini and Giammetti (2018) Unemployment refers to
situation in which individuals are actively seeking jobs but unable to get the opportunity. There
is distinct type of the elements that decides the level of unemployment prevailing in country
which comprises availability of the job information, skills & education possessing, degree of
labour mobility, flexibility of labour market, etc. These all leads to creation of the unemployment
situation in the country that impact its functioning. The main reason behind having impact of
unemployment over GDP is due to lower availability of productivity that can hamper outcomes
generated by companies that ultimately affect the performance of economy. In against to this, _
specified that GDP of organization get determined by number of factors which affect the
functioning of country. This includes the government course of actions taken for other activities
conducting in industries, underground economy, environment quality, resource depletion,
standard of life, economic inequality. On the basis of this, it can be articulated that these are few
of the factors that impact over the GDP of economy.
According to Bartolucci and et.al., (2018) there are different theories of unemployment
which helps in gaining the significant information about it impacts. The one of the crucial theory
of unemployment involve Keynesians theory that depicts that wage rigidity is the cause of
involuntary. It is basically concerned with having free enterprise capitalist economy that is
unable to offer full employment due to presence of rigidity in its wage structure. The significant
emphasis has been provided on underemployment equilibrium hypothesis than full equilibrium.
This theory the unemployment is found due to the rigidity in the wage structure that hamper the
standard living of people in the country. On the other side Zhang and et.al., it can be specified
that frictional unemployment is highly useful in accomplishing the understanding that results of
voluntary employment transitions within an economy. This can be taken into process to
understand that workers choose to leave job in order to choose the new one. In addition to this,
the workers who are entering into the job for the first time are considered to be frictional
unemployment.

In the views of Aum, Lee and Shin, (2021) GDP is one of the significant indicator of the
economy performance which can be properly understood by taking theory into consideration.
New growth theory is one of the major model that is related with having human desires and
unlimited wants that indicate that ever-increasing productivity and economic growth can be
obtained. The people pursuits of profits will perceptually incline. It is emphasized on importance
of entrepreneurship., knowledge, innovation, technology, rejecting the popular views regarding
economic growth. It can be specified that knowledge is treated as an asset for the growth. This is
helpful in gaining the significant information that there are exogenous growth neoclassical
economies that progress that is determined by external and uncomfortable forces. On the other
side, Kreishan (2021) indicated that Neoclassical economics is another model that is highly
useful in gaining the significant information in board pattern that focuses on supply and demand
as driving forces behind the production, pricing and consumption of goods and services.
Potential GDP and full employment are found to be significant factor that is related with
personal satisfaction. The main reason behind the particular statement that consumer perceptions
of the value of a product its price and demand. On the basis of this, it can be specified that there
is no significant relationship is found behind unemployment over GDP of the economy as
employment is should be the primary objective of the economy.
Dataset identified
For the research to be successful it is very important that proper data is being selected
related to the research problem. The reason behind this fact is that when the company will be
using appropriate data then this will result in proper research being conducted and objective of
the study will be attained. Hence, for the collection of the data relating to unemployment and
GDP is being collected from the secondary source. This is being gathered from the Office of
National Statistics that is ONS and the data has been gathered for the time frame of 10 years that
is 2012 to 2021 (ONS, 2022). In case the data will not be appropriate then the research objectives
will not be attained and this can negatively affect the result and objectives will not be attained.
Quantitative analysis
Descriptive statistics
Unemployment GDP
Mean 5.34 0.5

Standard Error 0.46337 0.1802
Median 4.7 0.475
Mode 4.5 0.4
Standard
Deviation 1.4653 0.56984
Sample Variance 2.14711 0.32472
Kurtosis -0.2441 3.58581
Skewness 1.03038 -0.1486
Range 4.2 2.35
Minimum 3.8 -0.7
Maximum 8 1.65
Sum 53.4 5
Count 10 10
With the analysis of the descriptive statistics it is clear that the average unemployment
rate for the period of past 10 years is 5.34 whereas average GDP is 0.5. Moreover, with the
analysis of the standard deviation it is clear that the dispersion from the mean value in case of
unemployment is 1.4653 and in case of GDP is 0.56984. hence, with this it is clear that the
dispersion in unemployment is more and GDP is less (Rodríguez-Caballero and Vera-Valdés,
2020). Along with this, the minimum unemployment rate in past 10 years was 3.8 and maximum
witnessed was 8. On the other hand, in case of GDP the minimum was -0.7 and the highest went
to 1.65.
Regression analysis
H0- There is not any impact is being created by unemployment over GDP of economy.
H1- There is impact being created by changes in unemployment over the GDP of the company.
Regression
Statistics
Multiple R 0.1028
R Square 0.01057
Adjusted R
Square -0.1131
Standard Error 0.60121
Observations 10
ANOVA
df SS MS F
Significance
F

Regression 1 0.03088 0.03088 0.08544 0.7775
Residual 8 2.89162 0.36145
Total 9 2.9225
Coefficients
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 0.28653 0.75467 0.37967 0.71407
-
1.4537 2.0268
-
1.4537 2.0268
Unemployment 0.03998 0.13677 0.2923 0.7775
-
0.2754 0.35536
-
0.2754 0.35536
By evaluating the regression model it is clear that the R value is 10 % which simply
means that there is very low correlation within both the variables. Furthermore, the R square is
1.05 % and this simply states that the change within the independent variable will be causing
only 1.05 % change in the dependent variable. Moreover, with help of the significance value it is
clear that there is not any relation being present in unemployment and GDP. This is simply
because of the reason that the significance value is 0.77 which is more than the standard that is
0.05. Hence, this implies that the null hypothesis is being accepted and alternate is being
rejected. In support of this Nguyen (2018) states that when the unemployment is high the more
people are not having job and they do not have money to spend. Hence, as a result of this the
GDP of the economy is negatively affected because people will not be spending the money and
GDP will not be improving.
Visualisation of data
Year Unemployment GDP
2012 8.0 0.4
2013 7.6 0.6
2014 6.2 0.8
2015 5.4 0.6
2016 4.9 0.5
2017 4.4 0.4
2018 4.1 0.4
2019 3.8 0.3
2020 4.5 -0.7
2021 4.5 1.7

With the help of the above visualisation it is clear when the unemployment was constant
then he GDP was also constant. Along with this when unemployment increased after 2019 then
at that time GDP declined (Su and et.al., 2021). Further when the unemployment become stable
the GDP started to increase. This simply states that when unemployment increase then this
results in the decrease in GDP of the economy.
Findings
By evaluating the above finding it is clear that there is not any relation being present in
both the variables because they are not much related to one another. Also it was found that the R
value that is the level of relation within both the variable is very low that is only 1.05%. hence,
this outlines that fact that any change in unemployment will cause a very minute change in the
GDP of the economy. In support of this Cuestas and Ordóñez (2018) states that any change in
unemployment will be negatively affecting the GDP. The reason behind this fact is that when the
unemployment will increase then more people will be without jobs. Hence, when the people will
not be having job then as a result of this they will not be spending money within the economy.
This no flow of money within the economy will be resulting in no purchase and sale and as a
result of this the production will be affected. Hence ultimately this will be affecting the GDP of
the economy and this will be affected in negative manner.
CONCLUSION
The above report stated that using the quantitative analysis is very important in order to
evaluate the working and study in better and effective manner. This is pertaining to the fact that

when the quantitative analysis is being used then this will be resulting in better and accurate
output and as a result of this hypothesis is being proved. The above report stated that selecting
the proper source of data is important and for the present case ONS that is Office for National
Statistics is being used. Further the descriptive statistics and regression outlined that there is not
any relation being present in unemployment and GDP and because of this unemployment creates
negative impact over the GDP of the economy.

REFERENCES
Books and Journals
Aum, S., Lee, S.Y.T. and Shin, Y., 2021. Inequality of fear and self-quarantine: Is there a trade-
off between GDP and public health? Journal of Public Economics. 194. p.104354.
Bartolucci, F. and et.al., 2018. GDP dynamics and unemployment changes in developed and
developing countries. Applied Economics. 50(31). pp.3338-3356.
Brancaccio, E., Garbellini, N. and Giammetti, R., 2018. Structural labour market reforms, GDP
growth and the functional distribution of income. Structural Change and Economic
Dynamics. 44. pp.34-45.
Cosculluela-Martinez, C., 2020. Sustainable knowledge investment increases employment and
GDP in the Spanish agricultural sector more than other investments. Sustainability. 12(8).
p.3127.
Cuestas, J. C. and Ordóñez, J., 2018. Oil prices and unemployment in the UK before and after
the crisis: A Bayesian VAR approach. A note. Physica A: Statistical Mechanics and its
Applications. 510, pp.200-207.
Kreishan, F.M., 2021. Economic growth and unemployment: An empirical analysis. Journal of
Social Sciences. 7(2). pp.228-231.
Nguyen, A. T., 2018. The relationship among economic growth, trade, unemployment, and
inflation in South Asia: A vector autoregressive model approach. Asian Journal of
Economics and Empirical Research. 5(2). pp.165-172.
Rodríguez-Caballero, C. V. and Vera-Valdés, J. E., 2020. Long-lasting economic effects of
pandemics: Evidence on growth and unemployment. Econometrics. 8(3). p.37.
Strauss, I., Isaacs, G. and Rosenberg, J., 2021. The effect of shocks to GDP on employment in
SADC member states during COVID‐19 using a Bayesian hierarchical model. African
Development Review. 33. pp. S221-S237.
Su, C. W. and et.al., 2021. COVID-19 pandemic and unemployment dynamics in European
economies. Economic Research-Ekonomska Istraživanja, pp.1-13.
Zhang, S. and et.al., 2021.How Can Structural Change Contribute to Concurrent Sustainability
Policy Targets on GDP, Emissions, Energy, and Employment in China? Available at
SSRN 4011136.
Online
ONS. 2022. [Online]. Available through: < https://www.ons.gov.uk/>