Reference no: EM133114876
Question - Forecasting GDP based on Education, Unemployment, and Compensation
|
Period
|
Gross Domestic Product
|
Education Spend
($ million)
|
Unemployment Rate
(% of Labor Force)
|
Employee Compensation
($ million)
|
|
GDP
|
ED
|
UE
|
EC
|
|
2000
|
256,376
|
14,185
|
7.00
|
128,564
|
|
2001
|
264,335
|
15,004
|
6.60
|
135,710
|
|
2002
|
273,256
|
15,821
|
7.50
|
141,985
|
|
2003
|
281,200
|
16,566
|
8.20
|
144,669
|
|
2004
|
296,820
|
16,709
|
8.40
|
148,851
|
|
2005
|
310,038
|
17,646
|
8.50
|
153,985
|
|
2006
|
325,152
|
18,295
|
8.30
|
161,393
|
|
2007
|
343,619
|
18,962
|
7.50
|
170,106
|
|
2008
|
351,743
|
20,133
|
7.00
|
179,628
|
|
2009
|
346,473
|
21,071
|
7.90
|
180,906
|
|
2010
|
363,140
|
21,936
|
8.30
|
184,711
|
|
2011
|
375,968
|
23,356
|
7.20
|
193,171
|
|
2012
|
386,175
|
24,158
|
7.60
|
199,806
|
|
2013
|
392,880
|
25,045
|
8.40
|
203,606
|
|
2014
|
403,003
|
25,436
|
8.50
|
206,201
|
|
2015
|
416,701
|
26,282
|
8.50
|
208,128
|
|
2016
|
430,085
|
26,675
|
7.80
|
211,813
|
|
2017
|
444,991
|
27,853
|
7.10
|
219,187
|
|
2018
|
460,419
|
28,618
|
6.00
|
226,300
|
Required -
1. Run correlation on the independent variables (ED, UE, EC). Show output.
2. Which two independent variables are highly correlated?
3. Run regression on GDP against ED, UE, and EC. Show output.
4. Interpret the R Square value with emphasis on the role of the independent variables.
5. Build the regression model for GDP forecasting.
6. Which independent variables may not belong in the model? Why?
7. Re-run regression, this time excluding the suspect independent variables.
8. Is the P-value significant (≤5%)? What's the interpretation regarding the independent variable(s) in the model?