Question
Some experts have suggested that the US economy thrives when the nation is involved in global conflict. The dataset below contains defense spending and the
Some experts have suggested that the US economy thrives when the nation is involved in global conflict. The dataset below contains defense spending and the U.S. GDP for 28 quarters. Build a simple regression model to estimate the impact of the past quarter's (q-1) defense spending on the quarterly U.S. GDP.
a) Make a scatterplot where the residuals are the Y-values (vertical axis) and the lagged (q-1) quarterly defense spending are the X-values (horizontal axis). Based on your scatterplot would you conclude that the residuals and the lagged (q-1) quarterly defense spending are independent? Why or why not?
b) Make a histogram of the residuals where you compare the distribution of the residuals with the normal distribution. Based on your chart would you conclude the residuals are approximately normally distributed? Why or why not?
c) At the .01 level of significance, is the past quarter defense spending a driver of GDP? Justify your conclusion using the regression outputs.
d) What percent of variation in quarterly GDP can be explained by variation in the past quarterly defense spending? Justify your conclusion using the regression outputs.
e) What is the 95% margin of error for forecasts of GDP using the regression model?
f)How much does the predicted quarterly GDP change with a $1 billion increase in defense spending in the past quarter? Provide a 95% confidence interval for your estimate?
Quarter | Defense spending q-1 ($B) | GDP (B$) |
6/30/2000 | 360.90 | 9,823.00 |
9/30/2000 | 375.20 | 9,862.00 |
12/31/2000 | 371.30 | 9,954.00 |
3/31/2001 | 373.80 | 10,022.00 |
6/30/2001 | 383.50 | 10,129.00 |
9/30/2001 | 388.30 | 10,135.00 |
12/31/2001 | 393.00 | 10,226.00 |
3/31/2002 | 405.60 | 10,338.00 |
6/30/2002 | 418.50 | 10,446.00 |
9/30/2002 | 431.70 | 10,547.00 |
12/31/2002 | 436.50 | 10,618.00 |
3/31/2003 | 461.00 | 10,706.00 |
6/30/2003 | 467.40 | 10,832.00 |
9/30/2003 | 506.90 | 11,086.00 |
12/31/2003 | 501.50 | 11,220.00 |
3/31/2004 | 513.10 | 11,431.00 |
6/30/2004 | 537.70 | 11,649.00 |
9/30/2004 | 548.10 | 11,799.00 |
12/31/2004 | 564.10 | 11,970.00 |
3/31/2005 | 555.10 | 12,173.00 |
6/30/2005 | 576.80 | 12,346.00 |
9/30/2005 | 584.30 | 12,573.00 |
12/31/2005 | 605.00 | 12,731.00 |
3/31/2006 | 590.90 | 13,008.00 |
6/30/2006 | 613.50 | 13,197.00 |
9/30/2006 | 616.50 | 13,323.00 |
12/31/2006 | 618.10 | 13,458.00 |
3/31/2007 | 635.80 | 13,620.00 |
6/30/2007 | 633.5 |
Step by Step Solution
There are 3 Steps involved in it
Step: 1
To answer these questions we will first perform a simple linear regression analysis using the provided dataset Lets start by importing the data and then proceed with the analysis Lets start by importi...Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started