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?