Table AI DDF regression for only good... | Emerald Publishing

Table AI

DDF regression for only good output

Variables	Coef.	SE	Variables	Coef.	SE	Variables	Coef.	SE
Intercept	–0.5052***	0.023	y₁t	0.0013*	0.0007	x₂t	0.0015**	0.0007
y₁	–0.3847***	0.009	$y_{2}^{2}$	–0.0345***	0.0018	$x_{3}^{2}$	0.0756***	0.0039
y₂	–0.0898***	0.007	y₂y₃	–0.0077***	0.0023	x₃t	0.0011	0.0010
y₃	–0.0319***	0.009	y₂x₂	0.0070***	0.0023	t²	–0.0005	0.0003
x₂	–0.0195**	0.009	y₂x₃	–0.0007	0.0025	GDP	0.0028**	0.0011
x₃	0.4578***	0.012	y₂t	–0.0024***	0.0005	HHI	0.0000	0.0000
t	0.0022	0.003	$y_{3}^{2}$	–0.0184***	0.0039	Equity	0.0066***	0.0003
$y_{1}^{2}$	–0.0784***	0.003	y₃x₂	–0.0091***	0.0029	Liquid	–0.6375***	0.0182
y₁y₂	0.0417***	0.002	y₃x₃	0.0027	0.0034	Unlisted	0.5228***	0.0201
y₁y₃	0.0305***	0.003	y₃t	0.0023***	0.0008	Listed	0.5070***	0.0201
y₁x₂	0.0021	0.003	$x_{2}^{2}$	0.0127***	0.0038	Delisted	0.4959***	0.0223
y₁x₃	0.0032	0.003	x₂x₃	–0.0055*	0.0028	σ²	0.0153***	0.0004
						γ	0.0000***	0.0000

Variables	Coef.	SE	Variables	Coef.	SE	Variables	Coef.	SE
Intercept	–0.5052***	0.023	y₁t	0.0013*	0.0007	x₂t	0.0015**	0.0007
y₁	–0.3847***	0.009	$y_{2}^{2}$	–0.0345***	0.0018	$x_{3}^{2}$	0.0756***	0.0039
y₂	–0.0898***	0.007	y₂y₃	–0.0077***	0.0023	x₃t	0.0011	0.0010
y₃	–0.0319***	0.009	y₂x₂	0.0070***	0.0023	t²	–0.0005	0.0003
x₂	–0.0195**	0.009	y₂x₃	–0.0007	0.0025	GDP	0.0028**	0.0011
x₃	0.4578***	0.012	y₂t	–0.0024***	0.0005	HHI	0.0000	0.0000
t	0.0022	0.003	$y_{3}^{2}$	–0.0184***	0.0039	Equity	0.0066***	0.0003
$y_{1}^{2}$	–0.0784***	0.003	y₃x₂	–0.0091***	0.0029	Liquid	–0.6375***	0.0182
y₁y₂	0.0417***	0.002	y₃x₃	0.0027	0.0034	Unlisted	0.5228***	0.0201
y₁y₃	0.0305***	0.003	y₃t	0.0023***	0.0008	Listed	0.5070***	0.0201
y₁x₂	0.0021	0.003	$x_{2}^{2}$	0.0127***	0.0038	Delisted	0.4959***	0.0223
y₁x₃	0.0032	0.003	x₂x₃	–0.0055*	0.0028	σ²	0.0153***	0.0004
						γ	0.0000***	0.0000

Notes: Number of observations =2,805; log-likelihood function =1,880; LR (χ²) test statistic on one-sided error =1,374.2. *,**,***Denote significance at the 10, 5 and 1 percent levels, respectively