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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