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a1.pngb1.png

src="/qa/attachment/10756086/" alt="abcd.png" />

Model 2 is for question a, model 3 is for question b

a1.png

Model 2: OLS, using observations 1-3278 (n = 3273)
Missing or incomplete observations dropped: 5
Dependent variable: PerCapitaInc
coefficient
std. error
t-ratio
p-value
const
25737.9
116.798
220.4
0.0000
Mean dependent var
25737.92
S.D. dependent var
6682. 042
Sum squared resid
1. 46e+11
S. E. of regression
6682. 042
R-squared
0. 000000
Adjusted R-squared
0. 000000
Log-likelihood
-33469.58
Akaike criterion
66941.16
Schwarz criterion
66947 . 26
Hannan-Quinn
66943.35

abcd.png

(a) [1 point] Run a regression of per capita income (PerCapitaInc) on percent employment in the FIRE sector
(PctEmpFIRE). What is the estimated slope? Explain what this number means in words in terms of per
capita income and also indicate if the relationship is statistically significant at the 10%, 5%, and 1% levels.
(b) [1 point] Run a regression of per capita income on percentage FIRE share, but now also include
additional regressors: unemployment rate in 2010 (UnempRate2010) and percentage non-Hispanic white in
2010 (WhiteNon HispanicPct2010). Now, what is the estimated effect of percentage FIRE share on per capita
income and also indicate if the relationship is statistically significant at the 10%, 5%, and 1% levels?
(c) [2 points] Provide economic/econometric intuition as to why the effect of FIRE share on per capita income
changed between parts (a) and (b). Note that I am asking you to think about the context (and hence the
"story" behind these data).
(d) [2 point] Construct a 95% confidence interval for the slope coefficient on PetEmpFIRE in (b). Write out
your calculations. Clearly indicate how this confidence interval relates to whether PetEmpFIRE is
statistically significant or not in this context.

b1.png

Model 3: OLS, using observations 1-3278 (n = 3271)
Missing or incomplete observations dropped: 7
Dependent variable: PerCapitaInc
coefficient std. error t-ratio
p-value
const
29979.7
556.990
53.82
0.0000
UnempRate2010
-845 . 858
30.7409
-27.52
4.32e-150
WhiteNonHispanic~
50.6536
4. 69292
10.79
1. 04e-026
Mean dependent var
25730.05
5.D. dependent var
6673.982
Sum squared resid
1. 04e+11
S. E. of regression
5628.207
R-squared
0. 289271
Adjusted R-squared
0. 288836
F(2, 3268)
665.0465
P-value(F)
4.8e-243
Log-likelihood
-32886.72
Akaike criterion
65779.44
Schwarz criterion
65797.72
Hannan-Quinn
65785.98

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