2. 1
IMPACT OF 9/11 ATTACKS ON ELECTRONIC STORE SALES
Prepared for
Dr. Norma F. Angel
BUS-325-01 Advanced Computer Applications
Prepared by
Karl Fink, Lyric Swain, Russell Schaffer
Ferrum College Undergraduates
December 12, 2015
3. 2
TABLE OF CONTENTS
TITLE PAGE .................................................................................................................................. 0
INTRODUCTION .......................................................................................................................... 3
LITERATURE REVIEW ............................................................................................................... 3
METHODOLOGY.......................................................................................................................... 4
RESULTS ....................................................................................................................................... 5
CONCLUSIONS............................................................................................................................. 7
RECOMMENDATIONS................................................................................................................ 7
APPENDIX..................................................................................................................................... 7
LIST OF FIGURES
MEANS REPORT………………………………………………………………………………...5
ONE WAY ANOVA REPORT…………………………………………………………………...6
CURVE FIT CHART……………………………………………………………………………..7
4. 3
INTRODUCTION
The purpose of this study was to analyze the effects that the terrorist attack on September 11,
2001 on nonessential consumer goods. The effects on consumer goods were determined by
analyzing the sales of electronic stores. Our hypothesis was that the 9/11 attacks would have had
a strong negative impact on the sales of electronic stores as electronics may have been viewed
more superfluous than before by Americans due to the tragedy. The report attempts to answer the
following questions:
What were the overall sales of electronic sales in each of the years of 2000, 2001, and
2002?
Was there a significant impact in the overall sales of electronics after the 9/11 attacks?
How may the results of this data effect economic decisions following future disasters?
LITERATURE REVIEW
Bush, George W. Text of George Bush’s Address. 11 September 2001. Speech. 8 December 2015
This article is the direct text of President George W. Bush’s speech following the 9/11
attacks. The purpose of the speech was to give the American people ease of mind
following such a traumatic event. One of the greatest worries at that time was possible
political and economic unrest. President Bush ensured the American public that the
government had, and was implementing emergency plans in response to the attack. The
president then went on to tell the American people that the terrorist attack would not have
an effect on American resolve offering inspiring rhetoric to appease the American public.
Finally the president issued a statement saying that all federal agencies would be open the
following day and that economy would remain strong due the unity and resilience of the
American people.
Roberts, Bryan W. “The Macroeconomic Impacts of the 9/11 Attack: Evidence from Real-Time
Forecasting.” Working Paper (2009): 1-16. Journal.
An issue from a scholarly journal that discusses the macroeconomic impact of the 9/11
attacks. The journal uses economic forecasts compared to actual economic changes to
determine the difference between what was suspected to happen in the economy versus
how the economy was actually affected The overall point of the survey was to analyze
the effects of the attack on 9/11 to show the difficulty in predicting the actual impact of a
disaster. The private sector, for example, very often reacts to mitigate the effects of the
disaster. Computer models and forecasts also have a harder time accounting for the
behavioral changes that may occur after a disaster. . The journal concluded that the 9/11
an economic impact in the very short run, but not so much the following year.
Roff, Peter. “The ‘Common Man’ Response 9/11 Shows American Exceptionalism”. U.S. News.
September 15, 2011. Web Article.
5. 4
The United States government’s response in the capital to the terrorist attacks of 9/11 was
to clear the streets of civilians and fill it instead with police and military with automatic
weapons. What was a time of urgency for the US government was, instead, a time of
compassion, cohesion, and overall exceptionalism. This is odd considering the outcry that
typically follows disasters such as terrorist attacks. This behavior doesn’t just refer to the
heroics of the first responders and the civilians who overpowered the terrorists on Flight
93, but the rest of the American public not directly involved with the attack.
Volunteering, such as blood donations, either increased or were unaffected overall by the
attacks.
Doward, Jamie. “Ashes to Ashes, Boom to Dust”. The Guardian. 07 September 2002. 07
September 2002.
In this article, the author, Jamie Doward , talks about the economy a year later from the
tragic incident of “09/11”. Early in the article he states that “09/11” acted as a wake-up
call. In result to the unfortunate event, companies halted on trading, consumers stopped
shopping temporarily and the capital markets dried up, and businesses could not continue
papering over the cracks. Jeremy Batstone, head of research at Natwest Stockbrokers,
said that it was a reality check for US investors. Months after “09/11” many companies
announced redundancy programs while admitting they would fail to meet their jobs
causing corporate America to close down for a while. The Bush administration was able
to use the tragic events to railroad through Congress a $1.35 trillion tax cut. The Federal
Reserve coupled with aggressive interest rate cuts. The relaxation of fiscal policy
provided a strong but yet, immediate stimulus to the economy. Oil prices were now at
$29 a barrel. A hike in the oil price would have dire implications for US business.
England, Michael. “The Economic Surprises after 9/11”. 10 September 2002. 11 December 2015
After the crisis of the twin towers, there was a large resilience of the U.S. consumer, the
economy has grown rapidly. There was no dent in the spending. Here was an increase in
the net volume of spending in 2001’s second half. Third quarter consumption growth was
depressed, hitting only 1.5%, compared to our estimate of 3.5%. But within the 4th
quarter there was a 6% buying jump. The spending growth in those three months
approximately the same 2% above the 3.5% to 4% trend that started a few months earlier
there was no net loss in the last three weeks of September.
METHODOLOGY
The file was downloaded from the class website and imported to into the IBM SPSS Statistics
Data Editor. The original database included sales figures from 1992-2014. We then assigned the
data type to each variable. For “YEAR” we assigned a nominal value. This section allowed us to
view the results of each year by month. Allowing for ease when viewing by season. For each
year we then relabeled each variable beginning with an “E” and then the numbered year. To
allow us to view the data by season, we created a variable titled “Seasons” and gave them values
of 1-4: each of the four seasons in a calendar year. We then ran the following reports: Means
report, One-Way Anova with Post Hoc LSD Tests, T-Tests for 2000-2001 and 2001-2002,
Correlations between 2000-2001 and 2001-2002, and a linear Curve Fit test.
6. 5
RESULTS
FIGURE 1. MEANS REPORT
Seasons 2000 2001 2002
Winter Mean 6849.00 6781.00 6964.33
Median 6912.00 6669.00 6970.00
Minimum 6670 6605 6935
Maximum 6965 7069 6988
N 3 3 3
Std. Deviation 157.267 251.460 26.951
Spring Mean 6940.00 6510.33 7029.33
Median 6926.00 6491.00 7034.00
Minimum 6898 6473 7012
Maximum 6996 6567 7042
N 3 3 3
Std. Deviation 50.478 49.893 15.535
Summer Mean 6753.33 6609.67 6969.33
Median 6751.00 6631.00 6969.00
Minimum 6717 6565 6889
Maximum 6792 6633 7050
N 3 3 3
Std. Deviation 37.554 38.695 80.501
Fall Mean 6783.67 6708.67 6951.00
Median 6764.00 6669.00 6946.00
Minimum 6693 6506 6915
Maximum 6894 6951 6992
N 3 3 3
Std. Deviation 101.933 225.136 38.743
The Means report displays the mean, median, number of cases, and standard deviation of each
season for each year. The mean for 2001 for each season dropped in comparison to the
proceeding and successive years suggests in a slight dip sales. This dip in electronic sales is
suggested by Jamie Doward’s article “Ashes to Ashes, Boom to Dusts” where he talks about how
certain aspects of the consumer market dried up or underperformed following the events of 9/11.
7. 6
FIGURE 2. ONE-WAY ANOVA REPORT with POST HOC Test
Sum of Squares df Mean Square F Sig.
2000 Between Groups 61429.667 3 20476.556 2.096 .179
Within Groups 78163.333 8 9770.417
Total 139593.000 11
2001 Between Groups 125138.917 3 41712.972 1.415 .308
Within Groups 235810.000 8 29476.250
Total 360948.917 11
2002 Between Groups 10875.000 3 3625.000 1.620 .260
Within Groups 17898.000 8 2237.250
Total 28773.000 11
To follow up our hypothesis upon viewing the means in the Means report, we ran a One-Way
Anova with a Post Hoc Test (see appendix) to see if this dip in sales was statistically significant.
According to the Anova report, there needed to be a significance of .05 in order to be statistically
significant. According to the data, there is no significant difference between sales of each year.
This may be due to the resilience of the American consumer that President Bush was calling for
in his address to the nation, to continue the status-quo in a post 9/11 economy. The data is further
reinforced by the T-Tests and Correlation reports (see appendix).
FIGURE 3. CURVE FIT CHART
In Bryan W. Roberts article about the
macroeconomic effects of 9/11 he talked about the
unpredictability of the effects that a natural disaster
has on any economic environment. According to the
Curve Fit chart, T-Tests, Correlation reports, and
One-Way Anova, this definitely seems to be the
case. One would assume that a national tragedy
would have some sort of effect, positive or negative,
following such an event. However, the true
“economic surprise” mentioned by Michael England
is that there was no real effect on the economy. This
revelation is important in that such knowledge as to
the ineffectiveness of natural and man-made
disasters in affecting the actual performance of the economy could help prevent future economic
disasters. Faith in the longevity of an economy can be preserved if investors and consumers are
fully aware of the minimal effect disasters and terrorist attacks have on the overall performance
of the economy.
8. 7
CONCLUSIONS
In conclusion, this report has determined that the tragic events of September 11, 2001 had little
to no effect on the overall performance in the American economy. The data showed that although
there may have been a slight dip in sales in electronics, the American consumer was resilient in
continuing their pre-9/11 buying habits. This was most likely due to the relatively calm state of
the American public and faith in the government’s capacity to keep the nation safe following a
major terrorist attack.
RECOMMENDATIONS
Based on the findings and conclusions this report makes the following recommendations:
1. Raise awareness as to the true effect of tragedies on the American economy.
2. Losing faith in the economy does little to help the performance of the economy.
3. Continuing to purchase, even superfluous items such as electronics, will actually help
suppress the effects of tragic events.
4. Consumer faith in economic stability should not rely on computer simulations and
forecasts presented by media outlets, but rather past economic performance.
5. Tragic events should be used to not only rally an economy, but rally and unite different
demographics.
6. A government’s apparent fearful response to a crisis does not necessarily reflect a
nation’s consumer’s response to a crisis.
7. Seasonal characteristics, such as holidays and major sporting events, can do a great deal
in suppressing the effects of a crisis many months following the event.
APPENDIX
Electronic Store Sales From 2000-2001
YEAR 2000 2001 2002
JANUARY 6912 6669 6935
FEBRUARY 6965 6605 6988
MARCH 6926 6567 7034
APRIL 6996 6491 7012
MAY 6898 6473 7042
JUNE 6751 6565 7050
JULY 6717 6631 6969
AUGUST 6792 6633 6889
SEPTEMBER 6894 6506 6946
OCTOBER 6764 6669 6992
NOVEMBER 6693 6951 6915
DECEMBER 6670 7069 6970
9. 8
Post HOC Tests
Dependent Variable (I) Seasons (J) Seasons
Mean Dif f erence
(I-J) Std. Error Sig.
95% Conf idence Interv al
Lower Bound Upper Bound
2000 Winter Spring -91.000 80.707 .292 -277.11 95.11
Summer 95.667 80.707 .270 -90.44 281.78
Fall 65.333 80.707 .442 -120.78 251.44
Spring Winter 91.000 80.707 .292 -95.11 277.11
Summer 186.667*
80.707 .049 .56 372.78
Fall 156.333 80.707 .089 -29.78 342.44
Summer Winter -95.667 80.707 .270 -281.78 90.44
Spring -186.667*
80.707 .049 -372.78 -.56
Fall -30.333 80.707 .717 -216.44 155.78
Fall Winter -65.333 80.707 .442 -251.44 120.78
Spring -156.333 80.707 .089 -342.44 29.78
Summer 30.333 80.707 .717 -155.78 216.44
2001 Winter Spring 270.667 140.181 .090 -52.59 593.93
Summer 171.333 140.181 .256 -151.93 494.59
Fall 72.333 140.181 .620 -250.93 395.59
Spring Winter -270.667 140.181 .090 -593.93 52.59
Summer -99.333 140.181 .499 -422.59 223.93
Fall -198.333 140.181 .195 -521.59 124.93
Summer Winter -171.333 140.181 .256 -494.59 151.93
Spring 99.333 140.181 .499 -223.93 422.59
Fall -99.000 140.181 .500 -422.26 224.26
Fall Winter -72.333 140.181 .620 -395.59 250.93
Spring 198.333 140.181 .195 -124.93 521.59
Summer 99.000 140.181 .500 -224.26 422.26
2002 Winter Spring -65.000 38.620 .131 -154.06 24.06
Summer -5.000 38.620 .900 -94.06 84.06
Fall 13.333 38.620 .739 -75.72 102.39
Spring Winter 65.000 38.620 .131 -24.06 154.06
Summer 60.000 38.620 .159 -29.06 149.06
Fall 78.333 38.620 .077 -10.72 167.39
Summer Winter 5.000 38.620 .900 -84.06 94.06
Spring -60.000 38.620 .159 -149.06 29.06
10. 9
Fall 18.333 38.620 .648 -70.72 107.39
Fall Winter -13.333 38.620 .739 -102.39 75.72
Spring -78.333 38.620 .077 -167.39 10.72
Summer -18.333 38.620 .648 -107.39 70.72
*. The mean difference is significantatthe 0.05 level.
T-Tests
Seasons N Mean Std. Deviation Std. Error Mean
2000 Fall 3 6783.67 101.933 58.851
Winter 3 6849.00 157.267 90.798
2001 Fall 3 6708.67 225.136 129.982
Winter 3 6781.00 251.460 145.180
Seasons N Mean Std. Deviation Std. Error Mean
2001 Fall 3 6708.67 225.136 129.982
Winter 3 6781.00 251.460 145.180
2002 Fall 3 6951.00 38.743 22.368
Winter 3 6964.33 26.951 15.560
Correlations
2001 2002
2001 Pearson
Correlation
1 -.437
Sig. (1-tailed) .078
N 12 12
2002 Pearson
Correlation
-.437 1
Sig. (1-tailed) .078
N 12 12
2000 2001
2000 Pearson
Correlation
1 -.714**
Sig. (1-tailed) .005
N 12 12
2001 Pearson
Correlation
-.714** 1
Sig. (1-tailed) .005
N 12 12
**. Correlation is significant atthe 0.01 level
(1-tailed).
11. 10
Independent Samples Test
Levene's Test for
Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
2000 Equal variances
assumed
1.113 .351 -.604 4 .579 -65.333 108.202 -365.752 235.085
Equal variances not
assumed
-.604 3.428 .584 -65.333 108.202 -386.578 255.911
2001 Equal variances
assumed
.143 .725 -.371 4 .729 -72.333 194.866 -613.368 468.702
Equal variances not
assumed
-.371 3.952 .730 -72.333 194.866 -615.966 471.299
Levene's Test for
Equality of Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
2001 Equal variances
assumed
.143 .725 -.371 4 .729 -72.333 194.866 -613.368 468.702
Equal variances
not assumed
-.371 3.952 .730 -72.333 194.866 -615.966 471.299
2002 Equal variances
assumed
.340 .591 -.489 4 .650 -13.333 27.248 -88.985 62.319
Equal variances
not assumed
-.489 3.568 .653 -13.333 27.248 -92.735 66.068
