Table 4

Results of robust regression (RREG) and dynamic GMM models

(1)(2)(3)(4)
FINVFINVENVSENVS
RREGDynamic GMMRREGDynamic GMM
HR−0.0449 (0.0738)0.170 (0.0954)−0.0219 (0.0764)−0.0380 (0.114)
AT_RES−0.281*** (0.0659)−0.114 (0.0656)0.195** (0.0682)0.175* (0.0751)
FIN_S0.498*** (0.0670)0.0347 (0.0358)0.159* (0.0694)0.0213 (0.0420)
U_I_TECH0.256*** (0.0688)0.0308 (0.0809)−0.152* (0.0713)−0.0245 (0.0877)
INNOV0.124 (0.0659)0.0384 (0.0414)−0.115 (0.0682)−0.0102 (0.0501)
LINK0.0647 (0.0465)0.116** (0.0375)−0.0711 (0.0482)−0.0930* (0.0439)
INTEL_A0.194** (0.0719)0.0269 (0.108)0.191* (0.0745)0.134 (0.132)
EMPL_I0.0552 (0.116)0.130 (0.0946)0.302* (0.120)0.0106 (0.107)
L.FINV 0.111 (0.137)  
L.ENVS   0.256 (0.133)
_cons−2.532 (5.627)33.23 (17.86)49.53*** (5.828)89.60*** (25.69)
N216162216162
R20.588 0.361 

Note(s): Standard errors in parentheses; *p < 0.05, **p < 0.01, ***p < 0.001

Source(s): Authors’ research in Stata 18

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