Question

In his study on the labor hours spent by the FDIC (Federal deposit insurance Corporation) on 91 bank examinations, R.J. Miller estimated the following function.
lnY=2.41+0.3674lnX1+0.2217lnx2+0.0803lnx3-0.1755D1+0.2799D2+0.5634D3-0.2572D4
     (0.55)     (0.0477)       (0.0628)      (0.0287)      (0.2905)    (0.1044)     (0.1657)     (0.0787)
R2=0.766
Where Y= FDIC examiner labor hours
            X1= Total assets of bank, x2 total number of offices in bank, x3 ratio of classified loans to total loan for bank . D1=1 if management rating was good D2=1 if management rating was fair D3=1 if management rating was satisfactory D4=1 if examination was conducted jointly with the state.
a) Interpret the results
b) Interpret the dummy variables
c) Which of the parameters from the estimated regression are statistically significant at 5% significance level?  

Question 3

Using the data in SLEEP75.RAW, we obtain the estimated equation

Sleep =3,840.83 -.163totwrk - 11.71educ - 8.70 age -.128 age2 + 87.75 male            

              (235.11)    (.018)              (5.86)        (11.21)          (.134)       (34.33)                     

N=706, R2=.123,

The variable sleep is total minutes per week spent sleeping at night, totwrk is total weekly minutes spent working, educ and age are measured in years, and male is a gender dummy.

1. All other factors being equal, is there evidence that men sleep more than women? How strong is

The evidence?

2. Is there a statistically significant tradeoff between working and sleeping? What is the estimated

Tradeoff?

3. What other regression do you need to run to test the null hypothesis that, holding other factors

Fixed, age has no effect on sleeping?

Question 4

From the data for 46 states in the United States for 1992, Baltagi obtained the following regression results:

                                              LogC= 4.3- 1.34 log P +0.17 log Y

                                                    Se=(0.91) (0.32)       (0.20)                                    R²=0.27

Where C= cigarette consumption, Packs per year

              P= real price per pack

              Y= real disposable income per capita

1. What is the elasticity of demand for cigarettes with respect to price? Is it statistically significant?
2. What is the income elasticity of demand for cigarettes? Is it statistically significant?
3. What is the overall significance of the regression? Which test do you use?

Answer 1