Factors Affecting the GDP Growth of the United States

Dependent Variable: GDP Growth Rate

Regressor: Interest Rate, Inflation Rate, Employment Rate

The project is analyzing the relationship between the regressors and the dependent variable

Introduction

            The United States of America (USA) is the largest economy in the world, in terms of Nominal GDP. The economy was growing with a modest pace at the start of the 21st century, but the recent economic crisis affected adversely on their economic well-being. This research question that has been answered throughout this research paper is as follows

What are the factors affecting the GDP Growth of the United States?

 The research question is important because it is integrating the GDP growth of the United States with other factors connected with it. Moreover, the research question also analyzes the most promising factor that impacts on the GDP position of the country. The research paper has covered with different headings which have been used to answer the research question in a professional manner. In order to answer the research question in a perfect and valuable manner, the researcher utilized a sophisticated statistical tool such as Descriptive Statistics, Correlation and Regression Analysis.

            There are five other sections other than “Introduction” that have been covered throughout this research. The next section is the Literature review. This section will be dealing with the studies covered in the same aspect. It will give a thorough idea about other studies that have been covered by other authors previously. The next couple of sections of the report will be dealing with the description of the model and description of the data. The sections will enlist the model that will be mould accordingly to this research and its regressors. Description of the data includes information about the important data that has been selected for the same assessment, along with the method that uses to corroborate the data. The next section will be the section of the result, which is connected with the previous one. This section will be dealing with the analysis of the results. All the econometric tools that have been mentioned earlier will be applied in this section, and their output will be mentioned in the section accordingly. Finally, the entire research will be summarized accordingly in the conclusion section to extract a meaningful result.

 

 

Literature Review

            This is the second section of the report, in which the literature has been mentioned based on the regressors selected. The literature review has been divided into two main sections. The first section is the theoretical perspective, while the second section is about the empirical pieces of evidence. The description of each of the dependent and independent variables have been covered in the theoretical perspective. However, past researches conducted in the same domain have been covered in the empirical evidence section.

Theoretical Perspective

GDP Growth

            According to Van den Berg, Gross Domestic Product (GDP) is the total amount of goods that have been generated by a country in a specific financial year (45). GDP informs about the actual economic worth of a country in a professional manner. Higher GDP is an indemnity that the economic worth of the country is on a higher note, and it will certainly help them to become competitive in the market. GDP Growth, on the other hand, is the analytical wing in which the GDP growth has been analyzed on the basis of the year basis. GDP is a combination of four things which are consumption, savings, investment and net exports. Each of these elements is essential to cover up the things professionally and attain effective results at the end of the day.

Interest Rate

            Interest rate is the first regressor that has been included in the same research. The theoretical ground presented by Park, Donghyun, and Kwanho Shin identified interest rate as an important element (2795). It is the rate at which loan can be borrowed by the individuals or businesses from the financial institution. For impulsive borrowings, it is essential to set the interest rate on a lower node, because it will lower the cost of borrowings. The interest rate has been set in the Monetary Policy, and it is initiated by the Central Bank of a Country. The interest rate has been set in accordance with the current economic outlook of the country.

Inflation Rate

            The inflation rate is the 2nd regressor that has been included in the same research. As per the definition presented by Kaushal, Leena Ajit, and Neha Pathak, inflation rate identifies the price association of different products found in a basket in a country. Interest rate and inflation rate are a connection with each other, or moves parallel to each other (21). It means that when the interest rate increases, the inflation rate also increase and vice versa. The decision of Inflation rate is essential to undertake by an economy, and this particular decision has been taken in the Fiscal Policy, in which tax targets and other important factors also define properly.

Employment Rate

            It is the third regressor that found in this research. It is defined as the rate of the employment prevailing in the country. The high employment rate is effective from the viewpoint of an economy. The higher the employment rate, the higher would be the happiness index in a country. Therefore, the employment factor should have been managed properly so that effective results could have been found.

Empirical Evidence

            Işik, Cem, Evangelia Kasımatı, and Serdar Ongan is one of the authors who researched the topic of economics (666). The research was about integrating different macroeconomic variables with the GDP Growth of the country. The region in which the study conducted was Australia. The research method that has been considered for the completion of the same research was Quantitative in which pure quantification basis have been selected. However, the data collection method was Secondary, in which data was collected via online periodicals. Australian Statistics website has been selected as the base to select the desired data. A total of 20 years of data has been selected, on which multiple regression tool has been applied. Based on the same assessment, the researcher found an insignificant negative connection among GDP Growth and Interest Rate, which means that the higher the interest rate, the lower would be the GDP growth in the country. A similar connection is found among the Tax to GDP ratio and GDP Growth rate of the country. It means that Tax to GDP ratio needs to be decreased or managed properly.

 Apart from this study, there was another study that has been selected for the same connection. The research has been conducted in the region of Turkey. The variables have been divided into a dependent and independent variable. The dependent variable that has been connected in the same connection was the GDP Growth of Turkey, while independent variables that have been covered in the same research were unemployment rate and Foreign Direct Investment (FDI) growth. Pearson Correlation Statistical tool has been applied to the same scenario. A negative correlation is found between GDP Growth of Turkey and the unemployment rate. It means that the unemployment rate and GDP Growth rate has negativity, which means that high unemployment rate tends to decrease the GDP growth of the country and vice versa. Apart from the unemployment rate, there is another variable that has been selected for the same connection, such as FDI Growth. FDI is effective and powerful for any economy, and its connection found highly positive and direct with the economic growth of the country. It means that the higher the FDI Growth in Turkey, the higher would be their GDP Growth.

Description of the Model

            A statistical model is essential to identify for research. Valuable model is effective to list down the variables which are likely to cover in this research (Omri, Anis, et al, 243). The model that has been covered in a similar connection is as follows;

Y (GDP Growth) = A + β1 (Interest Rate) + β2 (Inflation Rate) + β3 (Employment Rate)

            The Model is divided into two parts which are independent part and dependent part. The independent part is about the GDP Growth, while the dependent part includes the interest rate, inflation rate and the employment rate. The impact of the independent variables is likely to analyze with the GDP Growth rate.

Description of the Data

            This is the most important section of the report. Firstly, it is required to write about research methods. It is divided into two main types such as quantitative and qualitative method. The research method that has been covered in the same connection is Quantitative. The main rationale behind the selection of this method is clear, as the title of the research includes quantification on the basis of GDP Growth, Interest Rate and other variables. The second important thing is the data collection method. It is defined as the method that uses for the collection of the desired data. It is also divided into two main elements such as primary and secondary method. The data collection method that has been considered here is Secondary in which Official Data of the United States has been selected. The main rationale in using secondary data collection method is based on authenticity and reliability. The data collected via the secondary medium is authentic and effective. The sampling factor is another important thing that covers the analysis. A total sample of 25 years has been selected for the same analysis. It means that the economic data of the U.S. has been selected for the last 25 years. The sample for the data has been selected from 1993 to 2018. Cross-Sectional Data has been considered for the same assessment, in which different elements is connected with the GDP. This particular dataset covers all the period before and after the economic crisis that provides a complete determination about the economic well-being of the company.

Results

            This is the most important and influential part of the research. This part has been divided into three different sections. The first section is about the descriptive analysis, followed by correlation and regression analysis. Complete Data-set from the years 1993 to 2018 has been mentioned in the Appendix-1 of the report. The descriptive statistics result and analysis is as follows;

GDP Growth
Interest Rate
Inflation Rate
Employment Rate

Mean
       2.83
       2.38
       2.43
          61.55

Standard Error
       0.47
       0.39
       0.20
            0.43

Median
       3.80
       2.00
       2.30
          62.25

Mode
       4.80
       0.25
       2.50
          63.00

Standard Deviation
       2.39
       1.99
       1.02
            2.22

Sample Variance
       5.71
       3.95
       1.04
            4.91

Kurtosis
       2.59
     (1.06)
       2.75
           (1.54)

Skewness
     (1.38)
       0.47
       1.01
           (0.27)

Minimum
     (4.80)
       0.25
       0.25
          58.00

Maximum
       5.40
       6.50
       5.50
          64.50

Sum
     73.70
     62.00
     63.20
     1,600.40

Count
     26.00
     26.00
     26.00
          26.00

 From the above-mentioned descriptive output, it is found that the output has been divided into four different elements which are GDP Growth Rate, Interest Rate, Inflation Rate and Employment Rate. The first column is showing the descriptive output of GDP Growth Rate. The mean value of the GDP Growth rate is 2.83%, showing that the average GDP Growth rate in the last 25 years remained in a position of 2.83%. The standard error that found in the same connection is 0.47% with a standard deviation of 2.39%. The difference between the maximum and minimum values is on a higher node, showing that the GDP Growth rate of the country moved rigorously in these selective 25 years of period. The second column is showing the descriptive output of Interest Rate. The mean value of the Interest rate in the U.S. is 2.38%, in the last 25 years. The standard error that found in the same connection is 0.39% with a standard deviation of 1.99%. The difference between the maximum and minimum values is on a higher node, showing that the interest rate of the country moved rigorously in these selective 25 years of period.

 A couple of other columns that have been defined in the same analysis are inflation rate and employment rate. The mean inflation and employment rate in the U.S. in the selective period of 25 years are 2.43% and 61.55%. It is showing that the inflation rate prevailed in the U.S. with an average rate of 2.43% which is quite reasonable. On the contrary, the employment rate on average remained in a position of 61.55%. Apart from the descriptive statistics, there is another tool that can be used for the same purpose such as Correlation. It needs to analyze the relationship between two different variables.

 GDP Growth
 Interest Rate
 Inflation Rate
 Employment Rate

 GDP Growth
     1.000

 Interest Rate
     0.420
     1.000

 Inflation Rate
   (0.486)
   (0.081)
     1.000

 Employment Rate
     0.367
     0.845
   (0.116)
          1.000

            The correlation table is showing the relationship between the GDP Growth Rate of the United States with other macroeconomic variables. The connection between the interest rate and GDP Growth found positive and highly significant. It means that the higher the prevailing interest rate factor in the U.S. the higher would be its GDP Growth. The correlation factor is showing a value of “0.420”, which is high and positive. The second connection has been found between GDP Growth Rate and Inflation Rate of the country. The relationship between these variables is negative. The correlation factor is showing a value of -0.486, which is in the negative node. It means that the high inflation rate in the country will decrease the GDP Growth rate in particular and vice versa. Inflation rate needs to be managed professionally to get the desired outcome, especially in the long run. The last connection that has been covered in the same connection was between the employment rate and GDP Growth Rate of the United States. The correlation factor is showing a value of “0.367”, which is again in the positive node, and showing a significant and direct connection with the independent variable such as GDP Growth Rate. Based on the same connection, it is found that the higher the employment rate in the country, the higher would be its economic or GDP growth. Therefore, the policymakers need to increase the employment rate in the country to become economically competitive and better.

            The last econometric tool which is likely to apply in this scenario is Multiple Linear Regression. This tool is used to get an idea about the values that will be put in the model mentioned earlier. The Regression output is as follows;

SUMMARY OUTPUT

 Regression Statistics

 Multiple R
         0.618

 R Square
         0.382

 Adjusted R Square
         0.298

 Standard Error
         2.001

 Observations
       26.000

 ANOVA

 df
 SS
 MS
 F
 Significance F

 Regression
         3.000
       54.519
       18.173
         4.537
          0.013

 Residual
       22.000
       88.129
         4.006

 Total
       25.000
     142.649

 Coefficients
 Standard Error
 t Stat
 P-value
 Lower 95%
 Upper 95%
 Lower 95.0%
 Upper 95.0%

 Intercept
         6.390
       20.252
         0.316
         0.755
      (35.610)
        48.390
      (35.610)
               48.390

 Interest Rate
         0.492
         0.377
         1.306
         0.205
        (0.290)
          1.275
        (0.290)
                 1.275

 Inflation Rate
        (1.068)
         0.395
        (2.705)
         0.013
        (1.887)
        (0.249)
        (1.887)
               (0.249)

 Employment Rate
        (0.035)
         0.339
        (0.102)
         0.920
        (0.739)
          0.669
        (0.739)
                 0.669

 From the aforementioned regression output, it is found that the Multiple-R value is 0.618, showing that there is a significant connection between the dependent and independent variables. While, the adjusted R-Square is 0.298, which is showing that the application model is effective and tend to yield a meaningful result for the researcher. The Significance-F Value is 0.013, which is showing that there is a significant connection found between the variables. The model mentioned above will be used now to assess the intensity of the connection

Y (GDP Growth) = A + β1 (Interest Rate) + β2 (Inflation Rate) + β3 (Employment Rate)

Y (GDP Growth) = 6.390 + 0.492 + (-1.068) + (-0.035)

= 6.390% + 0.492% – 1.068 – 0.035

= 6.882% – 1.068 – 0.035

Y (GDP Growth) = 5.779%

            Based on the model specification, it is found that change in values of interest rate, inflation rate and employment rate impacted positively on the GDP Growth Rate of the U.S. The proportion of the change that has been analyzed here is 5.779% or 5.8% in selected period of 25 years.

 

 

Conclusion

            This assignment is about analyzing the connection between GDP Growth and other macroeconomic variables of the U.S. These macroeconomic variables are Interest Rate, Inflation Rate and Employment Rate. The research question has been answered that the factors which impact on the GDP Growth rate are of three folds such as interest rate, inflation rate and employment rate. The connection between these variables found significant, which means that change in any of the variables changes the GDP Growth rate in the U.S. The result revealed positive connection between interest/employment rates with GDP Growth, which is the same as found in the previous researches. Based on the results of this research, it can be said that the inflation rate of the U.S. needed to be managed properly, along with the prevailing interest rate because both of these factors impacts differently on the GDP Growth based scenario of the country.

Work Cited

Işik, Cem, Evangelia Kasımatı, and Serdar Ongan. “Analyzing the causalities between economic growth, financial development, international trade, tourism expenditure and/on the CO2 emissions in Greece.” Energy Sources, Part B: Economics, Planning, and Policy 12.7 (2017): 665-673.

Kaushal, Leena Ajit, and Neha Pathak. “The causal relationship among economic growth, financial development and trade openness in the Indian economy.” International Journal of Economic Perspectives 9.2 (2015): 5-22.

Omri, Anis, et al. “Financial development, environmental quality, trade and economic growth: What causes what in MENA countries.” Energy Economics 48 (2015): 242-252.

Park, Donghyun, and Kwanho Shin. “Economic growth, financial development, and income inequality.” Emerging Markets Finance and Trade 53.12 (2017): 2794-2825.

Van den Berg, Hendrik. Economic growth and development. World Scientific Publishing Company, 2016.

Appendix-1: Data

Year
GDP Growth
Interest Rate
Inflation Rate
Employment Rate

1993
4.2
5
2.2
63

1994
4.3
4.5
2.5
62

1995
4.8
4.5
2.3
63

1996
3.8
5
3
63.5

1997
4.2
5.5
1.5
64.2

1998
5.4
4
1.7
64.3

1999
4.9
3.5
2.3
64.3

2000
5
6.5
2.5
64.5

2001
0.25
2.5
3
64

2002
1.5
2
3.2
62.5

2003
2.5
2
1.25
62

2004
5.4
1.25
2.5
62.2

2005
4.8
2
2.6
62.3

2006
1.5
2.5
4.2
62.3

2007
2.5
4.5
1.8
63

2008
0.2
2
2
63.5

2009
-4.8
0.25
5.5
58

2010
3.8
0.25
2
58.5

2011
0.45
0.25
4
59

2012
3.8
0.25
1.8
58.5

2013
4.8
0.25
1.7
58.8

2014
0.25
0.25
2
58.9

2015
5.1
0.25
2.1
59

2016
0.25
0.25
0.25
59.5

2017
2.5
0.75
2.5
59.6

2018
2.3
2
2.8
60