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st: AW: Stata gives no result for Std. Err, t, P>|t| or Conf. Interval. (Master Thesis - help needed)
From |
"Martin Weiss" <[email protected]> |
To |
<[email protected]> |
Subject |
st: AW: Stata gives no result for Std. Err, t, P>|t| or Conf. Interval. (Master Thesis - help needed) |
Date |
Thu, 6 Aug 2009 12:06:31 +0200 |
<>
As Eric rightly said http://www.stata.com/statalist/archive/2009-08/msg00110.html : You seem to have a perfect fit. Note the list policy on reposts, though...
Try the code below to see that this could well be the source of all your troubles...
*************
clear*
set obs 10000
//generate perfect fit
gen x= rnormal()
//so no error
// in the data
//generating process...
gen y=3+2*x
//regress cannot give ses
reg y x
//graphic representation
twoway (scatter y x) /*
*/ (lfit y x)
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected] [mailto:[email protected]] Im Auftrag von Bianca Claassen
Gesendet: Donnerstag, 6. August 2009 12:03
An: [email protected]
Betreff: st: Stata gives no result for Std. Err, t, P>|t| or Conf. Interval. (Master Thesis - help needed)
Hello,
I would like to ask for some help with my master thesis since I do not
have a lot of Stata experience.
I would really appreciate your help!
I am trying to run regressions with my data but somehow it does give
me the coefficient but no result for Std. Err, t, P>|t| or Conf.
Interval.
The regression is:
(O_giz-O_niz )=α+ β_n (X_gz-X_nz )+∑_(z=1)^Z〖γ_z c_z 〗+ε_n
reg delta_sic delta_age delta_quality delta_rba id_*, robust
Where the depended variable (delta_sic) is the difference between the
square footage a certain industry occupies in green building g, as a
percentage of the total occupied space in the building, compared to
the fraction of the total occupied space it rents in control building
n in cluster z. A vector of the differences in hedonic characteristics
of the green sample versus the control sample, (X_gz-X_nz), accounts
for differences in building size, quality and age. c_z is a dummy
variable with a value of one if a building is located within a
specific building cluster z and zero otherwise. Clusters were formed
for each one of the green building and includes all conventional
office buildings within a quarter mile radius of it. Finally, α, β_n
and γ_z are estimated coefficients and ε_n the error term.
This means that:
delta_sic = is a value between 0 and 1
delta age, delta_quality and delta_rba are the characteristics and
take values between -100 and 100 which are multiplied by dummy
variables (that are there to identify the cluster the buildings belong
to)
id_* = the cluster identification variable (every green id has a
related dummy variable so that the control variables can be linked to
it)
What am I doing wrong that my regression does not yield any Std. Err,
t, P>|t| or Conf. Interval?
I would really appreciate help because I am trying to write my master
thesis and do not have much experience with Stata.
Thank you in advance.
Bianca
----------------------------------------------------------
reg delta_sic6 delta_age delta_quality delta_rba id_*, robust
Linear regression Number of obs = 798
F( 0, 0) = .
Prob > F = .
R-squared = 1.0000
Root MSE = 0
------------------------------------------------------------------------------
| Robust
delta_sic6 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
delta_age | -.0000587 . . . . .
delta_qual~y | -.0186775 . . . . .
delta_rba | .0142273 . . . . .
id_109 | -.0749682 . . . . .
id_110 | -.0081043 . . . . .
id_111 | -.0358519 . . . . .
id_112 | .300693 . . . . .
id_113 | -.0222221 . . . . .
id_114 | -.0213012 . . . . .
id_116 | .079335 . . . . .
id_117 | .0213555 . . . . .
id_118 | (dropped)
id_119 | -.0012657 . . . . .
id_120 | -.0064438 . . . . .
id_121 | -.000078 . . . . .
id_122 | (dropped)
id_123 | (dropped)
id_124 | -.043714 . . . . .
id_125 | .0054831 . . . . .
id_126 | .0061213 . . . . .
id_127 | -.0099928 . . . . .
id_128 | (dropped)
id_130 | .0058896 . . . . .
id_131 | .0341311 . . . . .
id_132 | (dropped)
id_133 | -.1664293 . . . . .
id_134 | -.1653741 . . . . .
id_135 | -.1742016 . . . . .
id_136 | .0058644 . . . . .
id_137 | -.0024823 . . . . .
id_138 | -.0077241 . . . . .
id_139 | -.0080733 . . . . .
id_140 | .0030768 . . . . .
id_141 | .0066013 . . . . .
Etc.
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