To estimate the unexpected money supply, we have found quarterly observation from first quarter of 1960 to the forth quarter of 2002, and we run the following regression:

_MS = b₀ + b _{1 FE} + b_{2 UN} +e_t

where: MS = changes in the money supply in a given quarter ( the variable that Barro wished to predic FE = the change in federal expenditure in the given quarter. UN = the unemployment rate in a given quarter

money.wf1

		with a DW = 0.79, we can conclude that the estimated slope of UN is unbiased
		with a DW = 0.79, we can conclude that the estimated slope of FE is not reliable (inefficient).
		with a DW = 0.79, we can conclude that the estimated t values are overestimated.
		all of the options are correct.

Dependent Variable: MS Method: Least Squares Date: 03/29/20 Time: 17:35 Sample (adjusted): 1960Q2 2002Q3 Included observations: 170 after adjustments Variable Coefficient Std. Error - Statistic Prob. FE UN -7.961183 0.135468 2.131818 2.700643 -2.947884 0.051446 2.633218 0.4494914.742734 0.0037 0.0093 0.0000 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.175312 Mean dependent var 0.165435 S.D. dependent var 8.570778 Akaike info criterion 12267.53 Schwarz criterion -604.9271 Hannan-Quinn criter. 17.75039 Durbin-Watson stat 0.000000 6.274706 9.381888 7.152084 7.207421 7.174539 0.792736 Dependent Variable: MS Method: Least Squares Date: 03/29/20 Time: 17:35 Sample (adjusted): 1960Q2 2002Q3 Included observations: 170 after adjustments Variable Coefficient Std. Error - Statistic Prob. FE UN -7.961183 0.135468 2.131818 2.700643 -2.947884 0.051446 2.633218 0.4494914.742734 0.0037 0.0093 0.0000 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.175312 Mean dependent var 0.165435 S.D. dependent var 8.570778 Akaike info criterion 12267.53 Schwarz criterion -604.9271 Hannan-Quinn criter. 17.75039 Durbin-Watson stat 0.000000 6.274706 9.381888 7.152084 7.207421 7.174539 0.792736