It has always been very evident that the Inflation( “A general increase in prices and fall in the purchasing value of money”. ) rate plays a great role when it comes to companies employing people or students. It is usually stated that the rate of inflation and unemployment are dependent on each other and the relationship is said to be such as that the Unemployment level depends on the level of Inflation; We will be finding out if this is true or false through our analysis. Also the rate of School enrollment of every year has been taken in order to see how the unemployment rates affect the future of children and their educations.
Objective
The aim and objective of this MNGT 213 coursework project is “ To see the impact of the changing inflation rate on the Unemployment level of United states of America and how it affects the education of future generations, by comparing the School enrolments per year”.
Data Description
The authentic data which I have collected for the coursework is ;Inflation, in terms of GDP deflator which has been calculated in Percentage ( The measurement scale for Inflation is Percentage ).
“Gross primary or secondary school enrolment ratio – The number of children enrolled in a level (primary or secondary), regardless of age, divided by the population of the age group that officially corresponds to the same level“.
School Enrolment rate ( Primary data ) which has been calculated in NET percentage.
“The unemployment rate is a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force. During periods of recession, an economy usually experiences a relatively high unemployment rate”. which has been calculated as of January of every year and is again measured in percentage.
*All the data has been collected Annually, and the unemployment rate is as of January every year. All the data is in Percentages and the data collected is for years 1991-2015
In the research being attempted for the coursework; Inflation is an Independent variable, whereas the Rate of unemployment depends on the Inflation and School enrolment rate is also a dependant variable and it depends on the unemployment rate; which in this case turns to be the Independent variable
Case 1 : Inflation Independent | Unemployment Dependent
Case 2 : Unemployment Independent | School enrolment Dependent
Descriptive Analysis:
Inflation Unemployment School Enrolment ( Primary Net )
Mean 2.015643 6.136000 94.066827
Median 1.994057 5.700000 94.494920
Mode .7594a 5.7000 91.3925a
Std. Deviation .6510273 1.5726517 1.6761766
Variance .424 2.473 2.810
Range 2.5693 5.8000 5.5459
Minimum .7594 4.0000 91.3925
Maximum 3.3287 9.8000 96.9384
Sum 50.3911 153.4000 2351.6707
Percentiles 25 1.515803 4.850000 92.436947
50 1.994057 5.700000 94.494920
75 2.329331 7.300000 95.464865
Below are the graphs showing how Inflation, Unemployment and School enrolment has changed over the years;
Graph 1
The inflation of United states has been varying and changing rapidly over the years, high is 3.3287 in the year 1991 and the lowest is 0.7594 in the year 2009.
Graph 2
The level of unemployment has not had very large changes over the time but has changed every year and we can see a rapid growth after the year 2007. The Highest is 9.8 in the year 2010 and the lowest is 4 in the year 2000.
Graph 3
School enrolments have been constant for a few years then has changed a little and then have had a constant phase. The lowest has been in 2013 and the highest has been in 1991.
Analysis
Regression Analysis
Correlations
Inflation Unemployment School Enrolment ( Primary Net )
Inflation Pearson Correlation 1 -.293 .229
Sig. (2-tailed) .156 .270
N 25 25 25
Unemployment Pearson Correlation -.293 1 -.537**
Sig. (2-tailed) .156 .006
N 25 25 25
School Enrolment ( Primary Net ) Pearson Correlation .229 -.537** 1
Sig. (2-tailed) .270 .006
N 25 25 25
Refer to Appendix 2
Graph 4 : Correlation between Inflation and Unemployment
There is a week correlation between Unemployment and Inflation as “ A correlation is weaker the farther apart the points are located to one another on the line “.
This means that the level of unemployment is affected by the rate of inflation but there is not a huge impact of Inflation on unemployment and this is concluded by the above correlation scatter plot ( Graph 4 ).
Refer to Appendix 2
Regression Model : Y=F(x)
Y = Dependent variable which in this case is Unemployment
X = Independent variable which in this case is Inflation
This relation can also be represented by regression model as in :β0+β1x+ where β0 and β1 are the parameters of the percentage of population where β0 is the intercept and β1 is the slope and ε represents the error
The regression equation Is given by : y = β 0+ β1x
Refer to Appendix 2
Generated by SPSS the equation will be : 7.562 – 0.707x.
It is concluded by this that as the rate of inflation rises by 1 unit, the level of unemployment is decreased by 0.707 units, Hypothesis testing has to be done in order to know whether or not this equation is true for further testing or not.
Hypothesis Testing
P Value Approach
Ho: β1 = 0 (Inflation is not useful or good to predict the Unemployment rate of United States )
Ha: β1 ≠ 0 (Inflation is useful or good to predict the Unemployment rate of United States )
Significance Level: α = 0.05
P = The value of approach
Reject Null hypothesis if p value < 0.05
Accept Null hypothesis if p value > 0.05
P- Value = 0.156
Hence 0.156 > 0.05
So Ha :Inflation is useful or good to predict the Unemployment rate of United States
Critical Value Approach
t* = -1.468
Degrees of freedom = n-1 = (25-1) = 24
α/2 = 0.025
T ( using Table ) = 2.064
2.064 > -1.4 68 , we will accept the Null Hypothesis
We have used both the P value approach and the critical value approach and have enough proof to say that we will accept the null hypothesis Ha: β1 ≠ 0 (Inflation is useful or good to predict the Unemployment rate of United States )
R(Square ) = 0.86 or 86%, which indicated that about 86% of unemployment can be affected by Inflation.
Graph 5 : Correlation between Unemployment and School enrolment
There has also been a weak Correlation “A correlation is weaker the farther apart the points are located to one another on the line”. Between School enrolment and unemployment rate and the school enrolment level has been affected but there is not a huge impact of unemployment. ( Graph 5 )
Refer to Appendix 3
Regression Model : Y=F(x)
Y = Dependent variable which in this case is School Enrolment
X = Independent variable which in this case is Unemployment
This relation can also be represented by regression model as in : β0+β1x+ where β0 and β1 are the parameters of the percentage of population where β0 is the intercept and β1 is the slope and ε represents the error
The regression equation Is given by : y = β 0+ β 1 x
Refer to Appendix 3
Generated by SPSS the equation will be : 97.577 – 0.572x.
It is concluded by this that as the rate of Unemployment rises by 1 unit, the level of School Enrolment is decreased by 0.572 units, Hypothesis testing has to be done in order to know whether or not this equation is true for further testing or not.
Hypothesis Testing
P Value Approach
Ho: β1 = 0 ( Unemployment rate of United states is not good enough to predict the School Enrolment rate in the future )
Ha: β1 ≠ 0 (Unemployment rate of United states is good enough to predict the School Enrolment rate in the future )
Significance Level: α = 0.05
P = The value of approach
Reject Null hypothesis if p value < 0.05
Accept Null hypothesis if p value > 0.05
P- Value = 0.006
0.006 < 0.05
So H0 = Null Hypothesis Rejected
Hence, Unemployment rate of United states is good enough to predict the School Enrolment rate in the future
Critical Value Approach
t* = -3.051
Degrees of freedom = n-1 = (25-1) = 24
α/2 = 0.025
T ( Using Table ) = 2.064
2.064 > -3.051 , we will accept the Null Hypothesis
We have used both the P value approach and the critical value approach but the results of them have been different and it would not be fine to say that we have enough evident to judge if Unemployment rate of United states is good enough to predict the School Enrolment rate in the future or not.
R(Square) = 0.288 or 28% which states that only 28% correlation is there in unemployment and school enrolment rate.
Conclusion :
After doing the analysis to find out of the level of unemployment is depended on the rate of inflation of United states and If the no. of school enrolments are depended on the level of unemployment or not.
It would be fine to say that the level of unemployment is somehow not highly but a little affected by the rate of inflation, there might be other factors which impact the level of unemployment.
The no of school enrolments per year might not be depended on the level of unemployment as our critical value approach did not match the p value approach hence it shows that there might be a lot of other factors which affect the school enrolment numbers instead of just unemployment level, or unemployment level might not play a role at all in affecting the school enrolments.