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Table 4 Logit model estimations on innovative nascent entrepreneurs

From: Why are some entrepreneurs more innovative than others?

  Innovative nascent entrepreneurs (sinno)
Model 1 Model 2
Odds P > |z| Odds P > |z|
Individual covariates
Female 1.14** 0.02 1.15** 0.02
HH income (middle 33%) 0.97 0.71 0.97 0.65
HH income (upper 33%) 1.02 0.78 1.06 0.43
Tertiary education 1.37** 0.00 1.21** 0.00
Employment (not working) 1.30** 0.00 1.20** 0.04
Employment (retired, students) 1.38** 0.03 1.36** 0.04
Age 0.99 0.30 1.00 0.86
Age*Age 1.00 0.42 1.00 0.94
Knowent (yes) 1.04 0.55 1.02 0.70
Fearfail (yes) 0.91 0.17 0.94 0.34
Suskill (yes) 1.23** 0.01 1.21** 0.02
Opport (yes) 1.20** 0.00 1.17** 0.01
Discent (yes) 1.04 0.65 0.96 0.64
Country covariates
GDP per capita, % of USA 1.90** 0.00
Tertiary education, % of pop 0.98 0.39
Controls
Country dummies Yes  
Year (2003) 0.84** 0.01 0.97 0.69
Year (2004) 0.81** 0.00 1.07 0.42
Model diagnostics
N 6,605 6,576
LL −3,918 −3,768
Prob > χ2 0.00 0.00
  1. Note: The reference category of the dependent variable in both estimations is purely imitative behavior (=0). Reference categories of the explanatory variables are HH income (lower 33%), tertiary education (no), employment (full or part-time job), Year (2002), and “no” as an answer to the binary variables
  2. * Denotes significance at 95% confidence
  3. ** Denotes significance at 99% confidence