Description
Develop a regression model for a topic of your choosing in an attempt to explain a phenomenon of interest. In doing so, you will be required to locate data on the Internet and do the appropriate analysis. You will also have to explain your topic of interest, the variables chosen, and why the variables were chosen, in addition to presenting and explaining your results. Your paper should include the following:
Introduction - describe the phenomena you are attempting to model and its importance (2 – 3 paragraphs)
Literature Review (find at least two references) - who has done similar work and what were their findings? (2 - 3 paragraphs)
Data - summary statistics of the data (2 - 3 paragraphs)
Methods and Results - what analysis did you perform and what were the expectations for the model? Were your results similar to those in the references you used? (3 - 6 paragraphs)
Conclusions (2 - 3 paragraphs) Your paper must follow current APA standards. Be sure to include tables and to label them properly (review the APA manual and the readings).
Throughout the course there have been many topics related to analyzing data that you should consider including in your write-up such as a graph of the data. In the Appendix, you may want to include graphs used to evaluate normal distribution. A discussion of the results of such analysis should be included in the results section of the paper.
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Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
The Impact of Entrepreneurship to the Growth of U.S Economy
Course
Name
Date
Instructor
1
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
2
The Impact of Entrepreneurship to the Growth of U.S Economy
Introduction
The concept of entrepreneurship is one complex concept, as social scientists are yet to
agree on the definition and the determinants of entrepreneurial behavior for innovation and
business competitiveness and its impact on the economic growth of different economies. In
essence, entrepreneurship may be viewed as the process of wealth creation, identifying and
implementing innovative business ideas to establish a viable business. It is imperative to know
that entrepreneurs are the individuals who create this wealth by being innovative, thoroughly
creative and competitively operating the businesses that they have come up with. Since
‘information is power’, entrepreneurs are keen on acquiring the necessary information about the
market and this puts them on a springboard from where they have the capacity of operating on a
competitive edge.
Entrepreneurship has indeed been seen as a crucial aspect to economic growth in many
countries across the globe and for many years, it has been considered as a vital component of
economic growth and ultimately economic development. This paper analyzes the impact of
entrepreneurship to the economic growth of the United States. Economic growth encompasses
the increase in per capita income, higher purchasing power, an increase in the overall production
or output, an increase in average living standards, a continual rate of innovation and capital
accumulation as well as a greater share of employment. The paper considered the Gross domestic
product (GDP) per capita, the number of new jobs created and the measure of innovative
intensity as the variables for the study. In this case, the dependent variable is the GDP per capita,
which measures the economic output of the US taking into consideration the population of the
country. The independent variables are the number of new jobs creation and the measure of
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
3
innovative intensity. New jobs creation through entrepreneurial ventures contributes to the
overall level of employment in the country, which determines the level of the country’s GDP per
capita. The measure of innovative intensity considers the rate of entrepreneurial start-ups, which
contributed to the positive growth of the country’s economy.
Literature Review
Different researchers have extensively explored the impact of entrepreneurship in
different economic regions to establish the extent to which it contributes to the growth of
economies around the world. Most of these studies are seen to make the assertion that
entrepreneurship is a key factor in stimulating economic growth, even though there is not much
of the discussion on the possibility of an inverse relationship between entrepreneurship and
economic growth. They have mainly focused on the investigation of this relationship on a
national scope, although a few focused on the local perspective.
In their study to investigate the relationship that exists among the following factors: a
culture of entrepreneurship, the disposition of start-up activity and regional development, Fritsch
& Wyrwich (2017) postulate that a region with pronounced entrepreneurial culture will
consequently experience high start-up activity, which will eventually lead to an augmented state
of economic growth. They exploit regional variation in entrepreneurial culture to ascertain the
causal impact that start-up activity has on the growth of employment. The empirical analysis was
for West Germany from 1976 to 2010. They established that regions that comprised of high selfemployment levels tend to have perpetually high levels of new start-ups across a longer period of
time. Therefore, they assert that a culture of entrepreneurship will stimulate new business
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
4
formation and consequently lead to a region’s economic growth. According to the outcome of
their empirical analysis, new entrepreneurial start-up firms, through a culture of
entrepreneurship, are essential in enhancing the level of economic growth as they provide
employment opportunities mostly in themselves as well as creating employment in the existing
firms (Fritsch & Wyrwich, 2017).
In another related study, Capello & Lenzi (2016) present a study that proposes a reassessment of the relationship between entrepreneurship and economic growth of a region with
an aim of underscoring the respective conditions under which entrepreneurial factor plays a
crucial role on the growth of a regional. They postulate that the innovative environment that
incubates the formation of new firms, and the behavioral disposition of entrepreneurship
constitute the conditions that authors the relationship between entrepreneurship and the growth
of a region. The authors assert that the innovative context is indeed, a crucial aspect as it
influences the entrepreneurship function of market discovery and execution of the discovery
through appropriate action. The authors found out that the potential of entrepreneurial perception
of opportunities has positive impact on innovation aspects. In this case, where innovation is
fueled by the local knowledge and relevant discoveries, entrepreneurs are stimulated to convert
this set of knowledge into innovation and thus, make a significant impact to the growth of the
region’s economy (Capello & Lenzi, 2016).
Data and Summary Statistics
The study used secondary data obtained from the World Bank national accounts data and
the United States Bureau of Labor Statistics. The table 1.0 below show a 10-year period data for
the US GDP per capita, the number of patents issued, the number of new jobs created by
entrepreneurial start-ups and the innovation intensity, from 2007 to 2017. Innovation Intensity:
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
5
the variable innovation intensity in the study was measured by dividing the number of issued
patents issued in the respective years by the value of the GDP per capita for each of the years.
Therefore, the results were presented as in the table below. Innovation intensity is measured
using the model:
Innovation Intensity (I) = No. of Patents/ GDP
Year
GDP Per Capita (‘000)
Number of
Patents issued
2007
48061.54
2008
Innovation
Intensity
184,376
New Jobs
created by
Start-ups
3307309
48401.43
182,556
3033421
62.672
2009
47001.56
190,122
2802403
59.623
2010
48375.41
233,127
2515246
51.994
2011
49793.71
244,430
2570850
51.630
2012
51450.96
270,258
2793113
54.287
2013
52782.09
290,083
2804566
53.134
2014
54696.73
329,612
2885614
52.757
2015
56443.82
322,449
3018287
53.474
2016
57588.54
334,107
3135574
54.448
2017
59531.66
347,642
3419007
57.432
68.814
Table 1.0, Source: World Bank data and US Bureau of Labor Statistics
According to the data, the trend for the GDP per capita rose progressively across the 10year period, with a slight drop in 2009 due to the ramifications of the Great Depression. There was
also a progressive increase in the number of patents issued during the period, although there were
slight fluctuations representing a slight decrease. It is evident from the table that number new jobs
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
6
created was initially high then followed by a slight drop in the same, but the trend began to rise
again. Nevertheless, there was still a significant number of new jobs created through
entrepreneurial start-ups. The number of patents issued and the number of new jobs created within
the period signifies that the level of entrepreneurship activities significantly rose as well. Figure
1.1 below represents the trends for the three variables over the 10 years.
Trend of New Jobs creation, Innovation intensity and the US's GDP per
Capita
70
60
50
40
GDP per Capita
(millions)
30
New Jobs created by
start-ups ('00,000)
20
Innovation Intensity
10
0
2007
2008
2009
2010
2011
2012
2013
Year
Figure 1.1
Regression model
The regression model used for the study is;
Y = a + β1N + β2 I+ ε
Where:
Y= Dependent variable (Economic Growth)
a = constant term
β= variable co-efficient (1, 2)
2014
2015
2016
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
7
N= New jobs creation (new jobs created through entrepreneurial business start-ups/ as a
measure of employment growth)
I = Innovation intensity (measures the rate of new business creations and new start-ups)
ε - Error term
Methods and Results
The data collected was analyzed multiple regression analysis. The software tool applied
for the analysis of the data was Microsoft Excel application for statistical analysis and
presentation. A multiple regression analysis was conducted in testing the relationship between
the independent variables (new jobs creation and innovation intensity) and the dependent
variable (income growth). The data analysis results were presented using graphs and tables for
establishing how the independent variable factors affect the income growth of the United States.
Multiple Regression Analysis
Standard
Variable
Coefficients
Error
t-Statistics
P-value
Constant term
49.25
0.7201
68.3230
2.3443
New jobs Creation
1.7793
0.0274
64.8771
3.5442
Innovation Intensity
-0.8739
0.0144
-60.6039
6.1068
Table 1.1
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
8
Multiple regression analysis was conducted as to determine the relationship between the
country’s GDP per capita growth and the two variables; new jobs creation and innovation
intensity. According to the Excel generated table above, the model equation used in the study;
Y = a + β1N + β2 I+ ε becomes:
Y= 49.25+ 1.7793N - 0.8739 I.
According to the regression analysis, it was established that taking all factors into account (New
jobs creation and Innovation intensity) constant at zero, the country’s GDP per capita would be
49.25. The findings presented further show that taking innovation intensity to be constant at
zero, a unit increase in the new jobs creation will lead to a 1.7793 increase in the country’s GDP
per capita. Further, the analysis show that taking the variable new jobs creation to be constant at
zero, a unit increase in innovation intensity will lead to a 0.8739 decrease in the country’s GDP
per capita. This outcome may be different due to various factors critical in the innovation
context.
This infers that new jobs creation contributes significantly to the GDP per capita for the
country, followed by innovation intensity. The results show that at 95% level of confidence, the
two independent variables were statistically significant in showing that there exists a positive
relationship between them and the dependent variable. The regression results above indicate that
there is indeed a positive relationship between new jobs creation with the U. S’s GDP per capita.
The findings of the study are similar to those of the references used.
Conclusion
The paper analyzes the impact of entrepreneurship to the economic growth of the United
States. The empirical literature reviewed for the study showed that entrepreneurship is a key
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
9
factor in the economic growth of a country. The study employed the quantitative type of
approach employed in the research and an exploratory design was used to explore the impact of
entrepreneurship on the economic growth. From the research findings, it is evident that there
exists a positive relationship between entrepreneurship and economic growth. The findings show
that new jobs creation, through entrepreneurship is a factor that contributes strongly to the
growth of the economy. New jobs creation is a variable that is seen to increase the levels of
employment in any given economy. Innovation intensity, which was employed to measures the
rate of entrepreneurial business start-ups, is also a key factor that leads to the growth of an
economy.
Therefore, there is a positive relationship entrepreneurship between entrepreneurship and
economic growth. New jobs creation, which is a process of entrepreneurship, increases the rate
of employment. The reduced unemployment rates imply higher levels of per capita income,
which consequently raises the level of GDP per capita. The overall effect therefore, is the growth
in the income level of the country. Innovation intensity, which is also a process of
entrepreneurship, leads to start-up of businesses and new firms, which play a key role in
increasing the economic output and income level of the country. Therefore, entrepreneurship is a
factor that leads to a significant growth in the economy.
Running head: The Impact of Entrepreneurship to the Growth of U.S Economy
10
References
Capello, R., & Lenzi, C. (2016). Innovation modes and entrepreneurial behavioral characteristics
in regional growth. Small Business Economics, 47(4), 875-893.
Fritsch, M., & Wyrwich, M. (2017). The effect of entrepreneurship on economic development—
an empirical analysis using regional entrepreneurship culture. Journal of Economic
Geography, 17(1), 157-189.
U.S. Bureau of Labor Statistics. (2018). Employment, Hours, and Earnings from the Current
Employment Statistics survey (National) Home Page. Retrieved from
https://www.bls.gov/ces/#tables
World Bank Group. (2018). GDP per capita (current US$) | Data. Retrieved from
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=US
Data Source
Last Updated Date
World Development Indicators
6/28/2018
Country Name
Aruba
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Arab World
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Indicator Name
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
Indicator Code
1960
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 59.7773265
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 1807.34978
NY.GDP.PCAP.CD 935.460427
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 70.3490786
NY.GDP.PCAP.CD 1273.69166
NY.GDP.PCAP.CD
93.022509
NY.GDP.PCAP.CD 68.4247486
NY.GDP.PCAP.CD 88.6912106
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 1550.32431
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 304.917107
NY.GDP.PCAP.CD 1902.40212
NY.GDP.PCAP.CD 152.461846
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 57.9776819
NY.GDP.PCAP.CD 74.5959443
NY.GDP.PCAP.CD 2294.56881
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 1787.36035
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 532.616267
NY.GDP.PCAP.CD 89.5205415
NY.GDP.PCAP.CD 153.471594
NY.GDP.PCAP.CD 119.534187
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD 127.004746
1961
1962
1963
59.8781528 58.4928738
78.782758
1874.30477 1851.42482
1031.815 1087.83424
1963.63908
1167.00053
71.4872777
1350.19767
95.5721547
71.5581801
97.1427302
73.7817649
1438.52323
94.464535
76.5206114
99.5767137
78.9002836
1535.02373
99.8591139
78.3720719
101.260491
1651.47548 1752.97029
1867.11299
316.403606 327.126867
1961.53817 2020.38597
162.695705 174.493386
336.941466
2020.26525
184.275535
61.2422483 64.7070068
80.520802 79.9677958
2231.29382 2255.23004
67.3758706
81.5879157
2354.83912
1971.31632 2131.39165
2294.18285
584.237786
75.8058379
167.355531
124.421692
671.399705
70.9094117
167.995943
129.515519
687.268374
74.3136434
190.407375
131.083487
142.537516 152.451213
153.541996
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
NY.GDP.PCAP.CD
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274.789958
297.673299
1370.21285
429.442874
164.644319
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685.614712
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563.58676 633.640315
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111.34248 109.459474 109.479045
117.820383
241.558035
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253.997553
146.29459
170.037838
160.631571 163.917196
167.291564
142.77955 142.838043 141.446979
146.33993
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
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133.050046
40.6055353
126.23295 126.618265
41.2012137 47.4502225
135.982691
52.3443123
2242.01582
2222.36637 2311.79885
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3281.35124
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2312.94999 2343.29221 2448.62863
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2622.22027
1594.17067
82.5472458
474.125822
93.9886874
583.444528
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GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
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255.61837 280.153338 308.597874
254.427071 267.147774 156.682154
328.508382
168.016967
114.636032
119.316939 124.688814
128.999043
44.6786893
717.514843
46.2552297 48.2333304
777.215027 854.744805
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510.987189
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140.749664 145.035842
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115.582084
119.25829 124.133267
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115.610759
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130.153587
323.658636
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349.73039
1983.10654
100.454669
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144.768151
288.058159
187.537374
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109.129606 114.582174
79.7226582 72.0977406
116.777461
76.1126566
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GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
GDP per capita (current US$)
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GDP per capita (current US$)
GDP per capita (current US$)
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100.767596
107.497932 113.782502
118.143245
81.3798161
115.610759
631.329859
85.0141566 88.8641316
119.282377 124.159649
675.974402 703.753422
98.2477912
130.153587
759.868843
509.424112
285.012709 309.446903
350.663223
62.3151223
63.0151613 62.0168215
68.9352512
171.279504
489.350147
3007.12345
153.847522 154.260418
601.701131 656.712218
3066.56287 3243.84308
164.375256
584.290747
3374.51517
161.417161 170.435141 174.565283
1072.432
1070.4867 1140.08288
162.869285
1185.48358
744.615385
749.271137 1054.28571
1040.20101
446.474871
458.626489 482.650669
510.672494
433.941194
234.166194
280.994586
444.896268 461.798232
221.728401 213.894229
283.315869 279.440989
498.601747
214.852954
280.566213
1964
82.2084439
1965
1966
101.290471 137.899362
1967
1968
1969
1970
161.322 129.506654
129.798541 157.187422
222.688851
3238.55685
238.909677 256.420887
2127.5669 2277.06668 2339.86194
1269.41258 1374.53214 1486.96861
2575.62008
2719.4298 2986.21889
3299.0373
1569.66718 1677.67353 1825.38613 2058.76908
86.6031946
1701.84628
104.339768
80.4727667
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51.6573647
1835.59477
110.132794
81.7251155
105.78917
55.1316867
2086.63601
111.951602
84.3631649
121.662093
1994.54492
2144.83097 2322.94385
351.161126
2199.72701
203.601149
377.594305 406.097967
2282.21655 2630.85047
223.2783...