Economic Growth in the United States

Posted: August 27th, 2021

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Economic Growth in the United States

Introduction

This study examines the United States’ economic growth from 2006 to 2019, which is 14 years. The objectives of the research are to explain or analyze the factors influencing economic growth for the country. The U.S. economy is a developed, mixed type of economy. According to the most recent statistics, it is the largest economy globally, followed closely with China in terms of nominal gross domestic product (“U.S. Unemployment Rate 1991-2020.”). The key factors that fuel the country’s economy include highly developed infrastructures and productivity. Besides, the American population enjoys the highest employee and household income amongst the Organization for Economic Cooperation and Development (OECD) Smith (44). Hence, this study utilizes various factors to assess the performance of the U.S. economy over the period. The key factors considered in the analysis include population growth, race, life expectancy, inflation rate, unemployment rate, the mean age of the population, and refugee population as the explanatory factors, while gross domestic product as an independent factor to assess the U.S. economic growth.

Dataset

The dataset is collected from online open sources, including the www.microtrends.com and the IMF reports. The independent variable utilized in the study is the gross domestic product (GDP). The GDP, in this case, is utilized for measuring economic growth. It describes the aggregate value of all goods and services produced in the country within a given period. In this case, a year. The explanatory variables include both economic and social factors. The economic factors are inflation and life unemployment rates. Social factors include life expectancy, refugee population, and population, as identified in the introduction. Thus, these variables will be analyzed to get an insight into the U.S. economic growth over the period.

Literature Review

A study by Popa (12) examined the impact of social factors on the economy’s growth, taking empirical evidence from Romania and European Union Countries. The study summarized both the economic and social environment for the two economies. The researchers conducted tests for the econometric and clustering models for the European Union countries. It was established that social factors such as expected schooling years and life expectancy are positively correlated with economic growth. However, population and unemployment rates negatively influence economic growth. Equally, while assessing inequality and economic growth, Galbraith & Kum (2) establishes that inequality tends to decrease with an increase in per capita income. However, this assertion is unsustainable following the findings made on data after 1981, where they establish that increase in interest rates and economic factors such as depression affect positive economic growth. The studies cite several challenges that affected the overall research. These include the scarcity of data to analyze inequality and controversies in the measurements. Thus, these challenges may influence the overall results of such studies.

Methods

Quantitative methods were used in the analysis of the study. Data was collected from online open sources. It was then analyzed using R Programming software and excel.

Results (means)

1. Simple Graphs

Figure 1: GDP growth versus population growth

Figure 1 shows the growth in the population against growth in GDP. Between 2006 and 2009, there is a decrease in GDP as the population increases. However, from 2010, the GDP grows sharply despite the increase in population.

Table 1: Correlation Analysis

	US GDP Growth	US POPULATION GROWTH	INFLATION RATE	MEAN AGE PER HOUSEHOLD	ALL RACES	REFUGEE POPULATION	LIFE EXPECTANCY	UNEMPLOYMENT RATE
US GDP Growth	1
U.S. Population Growth	0.35773	1
Inflation Rate	0.24683	-0.340	1
Mean Age Per Household	0.33215	0.1338	0.1607	1
All Races	-0.28538	-0.923	0.36545	-0.23137	1
Refugee Population	0.31827	0.633	0.1415	0.469103	-0.66	1
Life Expectancy	0.27144	0.894	-0.4448	-0.03194	-0.78	0.245	1
Unemployment Rate	-0.42817	-0.365	-0.251	-0.21206	0.38	-0.754	-0.01083	1

Table 1 is a correlation analysis of the variables selected in the study. As revealed in the table, economic growth is negatively correlated with races and unemployment rate but positively related to the refugee population, mean age per household, inflation rate, and population growth. Positive correlation shows that an increase in such variable (explanatory) results in an increase in economic growth, and the opposite is actual for negatively correlated variables.

Table 2: Simple Regressions

	Coefficients	Standard Error	t Stat	P-value
Intercept	-22.21	12.75	-1.74	0.11
US Population Growth	7.31	0.00	1.84	0.09
Inflation Rate	0.53	0.35	1.53	0.15

Adjusted R Squared = 0.53 or 53%

From Table 2, simple regression gives the following model;

The model shows that when all factors are held constant, the U.S. economic growth will deteriorate at -22.21 units. However, the economy grows at 7.31 units for a unit increase in population and 0.53 units for a unit increase in the inflation rate. These statistics are explained by only 53% of all the factors in the model. Factors outside the model explain the remaining 47%.

Table 3: Complicated Regressions

	Coefficients	Standard Error	t Stat	P-value
Intercept	223.70	531.13	0.42	0.69
US Population Growth	0.00	0.00	0.88	0.41
Inflation Rate	0.63	0.52	1.22	0.27
Mean Age Per Household	0.79	0.51	1.54	0.18
All Races	0.00	0.00	0.19	0.86
Refugee Population	0.00	0.00	-1.17	0.29
Life Expectancy	-4.40	8.12	-0.54	0.61
Unemployment Rate	-0.40	0.34	-1.17	0.29

R Squared = 0.746 or 74.6%

The complicated regression reveals the following model;

Detailed regression results are fairly accurate, with about 74.6% of the explanatory factors influencing economic growth. The model also shows that population growth, refugee population, and type of race have no significant influence on population growth. However, it reveals that the U.S. economy will grow at 223.7 units when all factors are held constant. A unit increase in inflation positively influences population growth by 0.63 units, while a unit increase in the mean age per household increases economic growth by 0.79 units. Conversely, an increase in life expectancy and the unemployment rate have a negative influence on economic growth.

Conclusion

Correlation analysis reveals thateconomic growth is negatively correlated with race and unemployment rate but positively related to the refugee population, mean age per household, inflation rate, and population growth. The results of simple analysis and complicated analysis are different. While simple regression shows that the population positively impacts economic growth, further analysis in the complicated regression reveals that it has no influence. These results agree with Popa’s (2012) studies that the unemployment rate and population have a negative influence on economic growth. However, regarding inflation, the study needs further research to confirm the claims posted in this study. The reason is that inflation as an economic factor is known to influence economic growth negatively. Thus, this was one of the exciting findings in this study.

Works Cited

‌ “U.S. Unemployment Rate, 1991-2020.” Www.Macrotrends.net, www.macrotrends.net/countries/USA/united-states/unemployment-rate.

Galbraith, James K., and Hyunsub Kum. “Inequality and Economic Growth: Data Comparisons and Econometric Tests.” Papers.Ssrn.com, 5 Apr. 2002, papers.ssrn.com/sol3/papers.cfm?abstract_id=315699. Accessed 12 Dec. 2020.

Popa, Ana-Maria. “The Impact of Social Factors on Economic Growth: Empirical Evidence for Romania and European Union Countries.” Romanian Journal of Fiscal Policy (RJFP), vol. 3, no. 2, 2012, pp. 1–16, www.econstor.eu/handle/10419/107942.

Smith, Gary. Standard Deviations : Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics. New York, Ny, Overlook Duckworth, 2015.

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