Industrial districts, innovation and I-district effect: territory or industrial specialization?



(0.003)

(0.757)

(0.206)

(0.000)

Business services

-0.0408

0.0293

(0.925)

(0.943)

Traditional services

-0.6194

-0.1850

-0.1125

(0.395)

(0.196)

(0.379)

Consumer services

-0.1502

-0.0791

(0.460)

(0.676)

Social services

-0.5463 ***

-0.4776***

(0.000)

(0.000)

Construction

-0.5007 ***

-0.4301***

(0.000)

(0.000)

Agriculture and fishing

-1.2804 ***

-1.2131***

(0.000)

(0.000)

Extractives

-0.2947 *

-0.2241

(0.067)

(0.128)

Fixed effects by LPS

0.4954 ***

0.1192

0.3486 ***

-0.0513

-0.2313 **

-0.2218

-0.4588***

(0.000)

(0.274)

(0.007)________

(0.878)

(0.017)________

(0.118)

(0.000)

(1) Fixed effects corresponds to regressions 1.4 to 1.6 using business R&D from firm microdata

Notes: (a) Dependent variable = Patents per employee in the 2001-2006 period; (b) All variables are natural logarithms; (c) P-values are in parentheses and asterisks
represent statistical significance at 1% (***), 5% (**) and 10% (*); (d) Within group effect model estimates; (e) Fixed effects provided under the restriction that ∑
α
i = 0, so that the dummy coefficients mean deviations from the averaged group effect (intercept); (f) Heckman adjusted coefficients; (g) Robust Huber-White
estimators when slight problems of heteroskedasticiy, collinearity or outliers are detected; (h) In the combined interaction estimation, Other manufacturing LPS
specialized in Metal products has been aggregated to Machinery because it caused problems in the restrictions for obtaining the fixed effects.

20



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