A dynamic approach to the tendency of industries to cluster

between the employment in producer services and accessibility to manufacturing also for
non-urban regions. This holds only, though, for the non-knowledge intensive industries
within the two sectors. Moreover, the estimate for the interaction variable in the producer
service equation is substantially smaller than in Table 4.3. Thus, regional size-effects are
present also for non-knowledge intensive industries, but the effects are smaller.

Table 4.4. 3SLS estimations of Equations 13a and 13b, non knowledge-intensive manufacturing and
producer services.

*)denotes significance at the 0.05 level.

**)denotes significance at the 0.1 level.

***) t-values are presented within brackets. For the Hausman specification test, the figure within
brackets is the critical value at the 0.05 level.

Point elasticity calculations are useful in order to be more precise about the relative
impact values of the variables. The point elasticity of manufacturing with respect to
(w.r.t) accessibility to producer services is calculated according to Equation (15).

∂M pa^a
ε =--*^

M,^p   ∂P^a  M

In the above equation, εM _pa expresses the point elasticity of manufacturing w.r.t
accessibility to producer services. ∂M∣∂P^a is the parameter estimate of accessibility to
producer services. p^a is the mean value for the accessibility producer services and M is
the mean value for manufacturing employment. The point elasticity for producer service
employment w.r.t accessibility to manufacturing employment is calculated in an
equivalent fashion. Due to the presence of the dummy for urban regions together with an
interaction variable in the estimated equations, one elasticity value will be calculated for
urban regions and one for non-urban regions.

Table 4.5, presents the point elasticities based on the parameter estimates in Table
4.2-4.4. Evidently, the elasticity values differ heavily both between urban and non-urban

17

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