Econometrics Analysis Report: Personal Income and Economic Variables

This report presents an econometrics analysis using regression analysis to examine the relationship between personal income, GDP, personal interest income, and personal dividend income. The analysis validates the model's accuracy, showing a strong correlation between independent and dependent variables. The results indicate that GDP has the most significant impact on personal income, with a 0.78-point change for every single-point change in GDP. Personal interest and dividend income have less impact. The report discusses the implications of these findings, particularly for businesses in the USA, emphasizing the importance of considering GDP changes when making decisions about employee compensation. It highlights the need to balance cost management with maintaining employee morale. The study references relevant literature on financialization and innovation in the service economy.

ECONOMETRICS ANALYSIS

TABLE OF CONTENTS
Method of testing and data validation.............................................................................................1
Analysis of results............................................................................................................................1
Discussion........................................................................................................................................5
REFERENCE..................................................................................................................................6

Method of testing and data validation
Regression analysis method is used to identify relationship between personal income,
GDP, personal interest income and personal dividend income. Prepared model is able to make
accurate prediction as it is verified from output charts where actual and predicted values are in
line to each other. Thus, assumptions of linear regression model is fulfilled and it can be said that
model is perfectly prediciting relationship between dependent and independent variables.
Analysis of results
H0: There is no significent impact on personal interest income, personal dividend income and
GDP on personal income.
H1: There is significent impact on personal interest income, personal dividend income and GDP
on personal income.
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.9998
38
R Square
0.9996
77
Adjusted R
Square
0.9996
65
Standard Error
282.02
57
Observations 89
ANOVA
df SS MS F
Signific
ance F
Regression 3
2.09E+1
0
6.97E
+09
8758
1.26
3.4E-
148
Residual 85 6760770
7953
8.47
Total 88
2.09E+1
0
Coeffi
cients
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept - 52.1661 - 0.191 - 35.049 - 35.0494
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68.670
8 2
1.316
39 583 172.391 42 172.391 2
Gross domestic
product
0.7860
87
0.01922
5
40.88
839
1.11
E-57
0.74786
2
0.8243
12
0.74786
2
0.82431
2
Personal
interest income
0.0004
39
0.00051
4
0.854
039
0.395
484
-
0.00058
0.0014
6
-
0.00058 0.00146
Personal
dividend income
0.0031
08
0.00048
2
6.445
04
6.67
E-09
0.00214
9
0.0040
67
0.00214
9
0.00406
7
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0
20000
40000
60000
80000
0
40000
Gross domestic product Line
Fit Plot
Personal income
Predicted Personal
income
Gross domestic product
Personal income
0 1000000 2000000
0
20000
40000
60000
Personal interest income
Line Fit Plot
Personal income
Predicted Personal
income
Personal interest income
Personal income
0
500000
1000000
1500000
0
40000
Personal dividend income
Line Fit Plot
Personal income
Predicted Personal
income
Personal dividend income
Personal income
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0 20 40 60 80 100 120
0
20000
40000
60000
Normal Probability Plot
Sample Percentile
Personal income
0 10000 20000 30000 40000 50000 60000
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
f(x) = 17.5999782197246 x − 55385.656754659
R² = 0.923735648697426
f(x) = 31.6480122096426 x − 3138.40506663715
R² = 0.972697026224717
f(x) = 1.18446153815082 x + 313.772211720627R² = 0.999446041069591
Chart Title
Gross domestic product Linear ( Gross domestic product)
Linear ( Gross domestic product) Personal interest income
Linear ( Personal interest income) Personal dividend income
Linear ( Personal dividend income)
Interpretation of results
Regression analysis table reflect that value of R square is 0.99 which means that with
change in independent variables 99% change comes in the dependent variable. This means that
with change in GDP, personal interest income, personal dividend income 99% change comes in
the personal income. Degree of relationship is high in case of these variables as multiple R value
is 0.99 which is indicating that these variables are closely related to each other and degree of
relationship is very high. Value of level of significence is 3.4>0.05 and this means that there is
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not significent mean difference between independent variables and dependent variable. Means
that due to change in independent variable variation comes in personal income in positive
direction but in DV huge degree of percentage change is not observed relative to independent
variable. Facts further reveal that in case GDP change by single point personal income get
changed by 0.78 points. On other hand, if personal interest income get changed very minor
impact will be observed in personal income as score is 0.000439. Personal dividend income also
does not have much impact on personal income as score is only 0.003. Hence, overall it can be
said that GDP relative to other two independent variables have higher impact on dependent
variable.
Discussion
Employee cost is the one of the expenditure that cover major part of overall cost that is
incurred in the business. Change in economic condition have significent impact on firms and it
become very important for them to identify that with change in economic condition what sort of
variation comes in employee cost. Hence, regression analysis is conducted which reflect that in
past time period when GDP increase employee cost increase or vice verse. Means that it can be
assumed that even GDP declined increment in employee cost happened gradually by very small
percentage (Onaran, Stockhammer and Grafl, 2011). Thus, corporate that are operating business
in USA can in line to change in GDP can offer salary or wages to employees. Employees are the
one of the important stakeholder of the company as they are the entity that play vital role in
growth of the company. Thus, company solely can not immediately reduce offered salary and
wage rate with decline in GDP as such kind of practices may demotivate current workforce and
general public. Hence, two variables personal interest and dividend income are also taken in to
account for analysis purpose. Low beta values are clearly pointing out that interest income and
diviend income even increased they does not contribut much to personal income. This is because
interest rate is low and in case of equity majority of shareholders hold few number of shares in
the market. Due to this reason income from additional soures have less impact on personal
income on per capia basis (Metcalfe and Miles, 2012). So, it can be said that firms can curtail
salary and wages growth rate with decline in GDP but same must not be at higher rate because
same practice will lead to fall in morale level of workforce which ultimately results in decline in
production and quality. All these things eventually put negative impact on company and growth
rate. Hence, salary and wage growth rate related decision may be taken with due care.
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REFERENCE
Books and journal
Onaran, Ö., Stockhammer, E. and Grafl, L., 2011. Financialisation, income distribution and
aggregate demand in the USA. Cambridge Journal of Economics. 35(4). pp.637-661.
Metcalfe, J.S. and Miles, I. eds., 2012. Innovation systems in the service economy: measurement
and case study analysis. Springer Science & Business Media.
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