See the following dataset and the output from Stata OLS and Mata code provided in Stata Blog by David Drukker https://blog.stata.com/2016/01/12/pr...nd-using-mata/.
Code:
clear
input double(y x1 x2 x3 x4 x5 x6)
-.053244516 .74 -1.56 .95 -.18 -1.46 -.109749
.06378974 .74 -1.56 .95 -.18 -1.46 -.109749
.021148825 .74 -1.56 .95 -.18 -1.46 -.109749
-.055137638 .74 -1.56 .95 -.18 -1.46 -.109749
-.04604394 .74 -1.56 .95 -.18 -1.46 -.109749
.005379249 .74 -1.56 .95 -.18 -1.46 -.109749
-.003599284 .74 -1.56 .95 -.18 -1.46 -.109749
-.041651525 .74 -1.56 .95 -.18 -1.46 -.109749
-.029081209 .74 -1.56 .95 -.18 -1.46 -.109749
.11075136 .74 -1.56 .95 -.18 -1.46 -.109749
-.004830927 .74 -1.56 .95 -.18 -1.46 -.109749
-.036290001 .74 -1.56 .95 -.18 -1.46 -.109749
.052939385 .74 -1.56 .95 -.18 -1.46 -.109749
.010752792 .74 -1.56 .95 -.18 -1.46 -.109749
-.017558312 .74 -1.56 .95 -.18 -1.46 -.109749
-.092018902 .74 -1.56 .95 -.18 -1.46 -.109749
-.007434979 .74 -1.56 .95 -.18 -1.46 -.109749
-.005221944 .74 -1.56 .95 -.18 -1.46 -.109749
-.005797118 .74 -1.56 .95 -.18 -1.46 -.109749
.013793322 .74 -1.56 .95 -.18 -1.46 -.109749
.063281447 .74 -1.56 .95 -.18 -1.46 -.109749
.00873368 .74 -1.56 .95 -.18 -1.46 -.109749
-.026145279 .74 -1.56 .95 -.18 -1.46 -.109749
-.001409444 .74 -1.56 .95 -.18 -1.46 -.109749
.017094433 .74 -1.56 .95 -.18 -1.46 -.109749
-.021337137 .74 -1.56 .95 -.18 -1.46 -.109749
-.081678033 .74 -1.56 .95 -.18 -1.46 -.109749
0 .74 -1.56 .95 -.18 -1.46 -.109749
-.023657016 .74 -1.56 .95 -.18 -1.46 -.109749
-.025943395 .74 -1.56 .95 -.18 -1.46 -.109749
-.021053409 .74 -1.56 .95 -.18 -1.46 -.109749
-.018648559 .74 -1.56 .95 -.18 -1.46 -.109749
.033170536 .74 -1.56 .95 -.18 -1.46 -.109749
-.058127742 .74 -1.56 .95 -.18 -1.46 -.109749
.010582109 .74 -1.56 .95 -.18 -1.46 -.109749
.020438667 .74 -1.56 .95 -.18 -1.46 -.109749
.006299234 .74 -1.56 .95 -.18 -1.46 -.109749
-.007017573 .74 -1.56 .95 -.18 -1.46 -.109749
.027920596 .74 -1.56 .95 -.18 -1.46 -.109749
.038655818 .74 -1.56 .95 -.18 -1.46 -.109749
-.034916267 .74 -1.56 .95 -.18 -1.46 -.109749
.037139546 .74 -1.56 .95 -.18 -1.46 -.109749
.064247444 .74 -1.56 .95 -.18 -1.46 -.109749
.009569451 .74 -1.56 .95 -.18 -1.46 -.109749
.032088313 .74 -1.56 .95 -.18 -1.46 -.109749
.00925543 .74 -1.56 .95 -.18 -1.46 -.109749
0 .74 -1.56 .95 -.18 -1.46 -.109749
.014764607 .74 -1.56 .95 -.18 -1.46 -.109749
-.050643735 .74 -1.56 .95 -.18 -1.46 -.109749
-.050325084 .74 -1.56 .95 -.18 -1.46 -.109749
-.021739986 .74 -1.56 .95 -.18 -1.46 -.109749
-.04284016 .74 -1.56 .95 -.18 -1.46 -.109749
-.033662669 .74 -1.56 .95 -.18 -1.46 -.109749
end
Code:
reg y x1-x6
Source | SS df MS Number of obs = 53
-------------+---------------------------------- F(0, 52) = 0.00
Model | 0 0 . Prob > F = .
Residual | .077875744 52 .00149761 R-squared = 0.0000
-------------+---------------------------------- Adj R-squared = 0.0000
Total | .077875744 52 .00149761 Root MSE = .0387
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | 0 (omitted)
x2 | 0 (omitted)
x3 | 0 (omitted)
x4 | 0 (omitted)
x5 | 0 (omitted)
x6 | 0 (omitted)
_cons | -.0046275 .0053157 -0.87 0.388 -.0152943 .0060392
------------------------------------------------------------------------------
Code:
. myregress11 y x1-x6
------------------------------------------------------------------------------
| Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | 0 (omitted)
x2 | .0029664 .0034075 0.87 0.388 -.0038713 .009804
x3 | 0 (omitted)
x4 | 0 (omitted)
x5 | 0 (omitted)
x6 | 0 (omitted)
_cons | 0 (omitted)
------------------------------------------------------------------------------
0 Response to Stata and Mata give different results for OLS
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