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Education, Training and Networking for Entrepreneurship in ...

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Table 8.9<br />

Logistic regression of adults’ vocation, owner-manager contrasted non-entrepreneur<br />

Adults (only non-entrepreneurs <strong>and</strong> owner-managers) <strong>in</strong> Denmark 2003-08<br />

Coefficient Odds ratio Probability-value<br />

Medium higher education - 0,3 0,7 0,0001 two-tailed<br />

Short higher education - 0,1 0,9 0,20 two-tailed<br />

Vocational education - 0,3 0,8 0,0003 two-tailed<br />

Neither higher nor voc. ed. - 0,2 0,8 0,02 two-tailed<br />

Competency 1,8 6,0 0,0001 one-tailed<br />

<strong>Network<strong>in</strong>g</strong> with starter 0,8 2,3 0,0001 one-tailed<br />

Gender (female 0, male 1) 0,5 1,7 0,0001 one-tailed<br />

Age (logarithmic) 0,8 2,1 0,0001 one-tailed<br />

Constant - 6,6<br />

<strong>Tra<strong>in</strong><strong>in</strong>g</strong> * - 0,2 0,9 0,23 one-tailed<br />

N = 17529 adults<br />

* Estimated by 2008 data<br />

<strong>for</strong> any figure <strong>in</strong> the monograph, but is <strong>in</strong>cluded<br />

here to show robustness of results.<br />

The robustness of estimated effects can also<br />

be exam<strong>in</strong>ed by focus<strong>in</strong>g on vocation <strong>in</strong> a contrast<br />

between non-entrepreneurs <strong>and</strong> starters,<br />

as here <strong>in</strong> Table 8.8. The results are similar. Table<br />

8.8 is not used <strong>for</strong> any figure <strong>in</strong> the monograph,<br />

but is <strong>in</strong>cluded here to show robustness<br />

of results.<br />

Effects are also estimated <strong>for</strong> vocation as a contrast<br />

between non-entrepreneurs <strong>and</strong> ownermanagers,<br />

as here <strong>in</strong> Table 8.9. The coefficients<br />

are fairly similar to those <strong>in</strong> the regresssions us-<br />

<strong>in</strong>g staters or prospective starters (the estimated<br />

coefficient <strong>for</strong> tra<strong>in</strong><strong>in</strong>g is here negative, but<br />

quite <strong>in</strong>significant). Table 8.9 is not used <strong>for</strong> any<br />

figure <strong>in</strong> the monograph, but is <strong>in</strong>cluded here to<br />

show robustness of results.<br />

Notes to Chapter 9<br />

Figure 9.2 <strong>in</strong> Chapter 9 is based on Tables 9.11,<br />

9.12 <strong>and</strong> 9.13. The unit of analysis is an entrepreneur.<br />

The sample is the entrepreneurs identified<br />

<strong>in</strong> our surveys of adults <strong>in</strong> Denmark. The sample<br />

of entrepreneurs is fairly representative of<br />

the population of entrepreneurs <strong>in</strong> Denmark,<br />

because the sampled adults are a fairly representative<br />

sample of the population of adults <strong>in</strong><br />

Table 9.11<br />

Logistic regression of entrepreneurs’ tra<strong>in</strong><strong>in</strong>g<br />

Entrepreneurs <strong>in</strong> Denmark 2008<br />

Coefficient Odds ratio Probability-value<br />

Medium higher education 0,5 1,7 0,17 two-tailed<br />

Short higher education 0,5 1,7 0,24 two-tailed<br />

Vocational education 0,5 1,7 0,19 two-tailed<br />

Neither vocational nor hi ed 0,4 1,5 0,33 two-tailed<br />

Gender (female 0, male 1) 0,2 1,2 0,24 one-tailed<br />

Age (logarithmic) - 0,9 0,4 0,01 one-tailed<br />

Constant 2,1<br />

N = 305 entrepreneurs<br />

90

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