ECO 311- ECONOMETRICS II
CLASS EXERCISES
EXAMPLE 1: CPS78_85. DTA
Using OLS estimation, we run the following regression with the STATA output.
. reg lwage educ y85educ exper expersq union female y85fem
Source
SS
df
MS
Model
Residual
135.837797
183.253371
7
1076
19.4053995
.170309824
Total
319.091167
1083
.29463635
lwage
Coef.
educ
y85educ
exper
expersq
union
female
y85fem
_cons
.0707913
.0270352
.029649
-.000401
.19999
-.3193655
.0919317
.511833
Std. Err.
.0052464
.0025154
.0035665
.0000775
.0302095
.0365133
.050795
.0751173
Number of obs
F( 7, 1076)
Prob > F
R-squared
Adj R-squared
Root MSE
t
P>|t|
13.49
10.75
8.31
-5.17
6.62
-8.75
1.81
6.81
0.000
0.000
0.000
0.000
0.000
0.000
0.071
0.000
=
=
=
=
=
=
1084
113.94
0.0000
0.4257
0.4220
.41269
[95% Conf. Interval]
.060497
.0220995
.0226509
-.0005531
.1407139
-.3910109
-.0077367
.3644399
.0810856
.0319709
.0366471
-.0002489
.2592661
-.2477202
.1916002
.6592261
EXAMPLE 2: KIELMC. DTA
. reg
rprice nearinc if year==1981
Source
SS
df
MS
Model
Residual
2.7059e+10
1.3661e+11
1
140
2.7059e+10
975815048
Total
1.6367e+11
141
1.1608e+09
rprice
Coef.
nearinc
_cons
-30688.27
101307.5
Std. Err.
5827.709
3093.027
t
-5.27
32.75
Number of obs
F( 1,
140)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
=
=
=
=
=
=
142
27.73
0.0000
0.1653
0.1594
31238
[95% Conf. Interval]
-42209.97
95192.43
-19166.58
107422.6
In this example, we look at the effect of a Garbage Incinerator’s Location on Housing
Prices with Two Years of Data- with data only for 1981 (after the incinerator is built).
We observe that the average home values near the incinerator site were $30,688 less
than those far from the incinerator. Does this alone imply that the incinerator caused
a fall in the housing values? Same model for 1978 is as follows:
. reg
rprice nearinc if year==1978
Source
SS
df
MS
Model
Residual
1.3636e+10
1.5332e+11
1
177
1.3636e+10
866239953
Total
1.6696e+11
178
937979126
rprice
Coef.
nearinc
_cons
-18824.37
82517.23
Std. Err.
t
4744.594
2653.79
-3.97
31.09
Number of obs
F( 1,
177)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
=
=
=
=
=
=
179
15.74
0.0001
0.0817
0.0765
29432
[95% Conf. Interval]
-28187.62
77280.09
-9461.117
87754.37
Even before the incinerator was built, the housing values near the incinerator
site was $18, 824 less!! This is consistent with the view that the incinerator
was built in an area with lower housing values.
Can we really tell whether building a new incinerator depresses housing
values? To see how the coefficient on nearinc changed between 1978 and 1981,
we estimate:
. reg
rprice nearinc y81 y81nrinc
Source
SS
df
MS
Model
Residual
6.1055e+10
2.8994e+11
3
317
2.0352e+10
914632739
Total
3.5099e+11
320
1.0969e+09
rprice
Coef.
nearinc
y81
y81nrinc
_cons
-18824.37
18790.29
-11863.9
82517.23
Std. Err.
4875.322
4050.065
7456.646
2726.91
t
-3.86
4.64
-1.59
30.26
Number of obs
F( 3,
317)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.113
0.000
=
=
=
=
=
=
321
22.25
0.0000
0.1739
0.1661
30243
[95% Conf. Interval]
-28416.45
10821.88
-26534.67
77152.1
-9232.293
26758.69
2806.867
87882.36
TWO-PERIOD PANEL DATA ANALYSIS
We now use data CRIME2. DTA which contains data on crime and
unemployment rates for 46 cities for 1982 and 1987.
EXAMPLE 3: CRIME2. DTA