Problem 1. Policymakers are interested in how the number of crimes in a large ci
ID: 2947574 • Letter: P
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Problem 1. Policymakers are interested in how the number of crimes in a large city depends the unemployment rate and the number of TV advertisements which discourage criminal acts obtained: PRF SRF: Using the data for the period from January 2009 to July 2017, the following OLS estimates a OLS SRF estimates: 151.0+8.899 X-20.01 A 40.51) (4.589) (8.031) R2 0.845, S-0.472,-103 where Yi the number of crimes in month the unemployment rate (in percentage points) in month r 4-the number of TV advertisements which discouraged criminal acts in month a. (I point) Interpret the coefficient of determination (R). b. (1 point) Interpret the OLS point estimate of Po. c. ( 1 point) Interpret the OLS point estimate of ?. d. (1 point) Interpret the OLS point estimate of ßa. e. (2 points) Find the 95% confidence interval estimate ofPe. Interpret your results. f (2 points) Test to see if the unemployment rate (X) explains the behavior of crime (0. In answering, write out the null and alternative hypotheses and the decision rule. Show calculations and state your conclusion. 8- (2 points) Test at the 5% level of significance the null hypothesis that the independent variables jointly do not explain the behavior of the dependent variable. In answering, write out the null and alternative hypotheses and the decision rule. Show your calculations state your conclusion. h. (2 points) Calculate the 95% confidence interval estimate of ?. Interpret your result. i. IZrews) gt is claimed thar the Stodod entr otr rymsim ? ,s .40. ouk zeits in SrenhionCh). n oddihon Specify the nul Page 1 of S and astenave hypothsais j CIpoint) xplain wshy we use the OLS eshimuhon meted to examine the in the RF, why not use unknawn Popularon panamemo Ao.P, , other estimahon methods ?Explanation / Answer
a. Coefficient of determination (R2) :
R2 is the percentage of variation in response variable (number of crimes in month) that is expained by the model. Here R2 is 0.845 suggest that 84.5% variation in response variable (number of crimes in month) that is expained by the model. Overall R2 suggest that fit is very good.
b.
If the unempoyment rate in month i.e. Xt and number of advertisement which discourage criminal acts in month i.e. At are zero (i.e. Xt=0 and At=0 ) then there will be 151 crimes in the months.
c.
If At is constant then each one unit of number of advertisement which discourage criminal acts in month causes to decline the number of crimes in month by an average 20.01.
d.
If Xt is constant then each one unit of unemployment rate in month causes to increase the number of crimes in month by an average 8.899.
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