Experience, Innovation and Productivity - Empirical Evidence from Italy's Slowdown



Table 6. Second stage results for system (9’), OLS and 2SLS.

Dependent

OLS

2SLS

OLS

2SLS

K

2 ln —

2 L

Lit

Coeff

Robust

St.E.

Coeff

Robust

St.E.

Coeff

Robust

St.E.

Coeff

Robust

St.E.

Innovative firms

Non Innovative firms

α1 (K/L ratio)

0.256***

0.0265

0.199***

0.0302

«2

0.087***

0.0212

0.085***

0.0239

β1 (constant)

20.164***

3.204

20.46***

3.146

β2

-6.68

7.755

-6.67

7.698

Yi (age)

-0.307***

0.0465

-0.313***

0.0453

Y2

0.061

0.1375

0.061

0.1366

μ1 (temporary
workers)

-0.114***

0.023

-0.123***

0.0234

μ2

-0.273**

0.120

-0.272**

0.1194

-σεiω

2.597*

1.526

3.659**

1.528

σε2ω

-1.557

3.152

-1.545

3.1343

R2

0.215

0.099

R2

0.208

0.099

Sargan test

3.429
[0.064]

.413
[0.520]

N

5859

5859

N

1914

1914

Note. All regressions include size, sector, area and group dummies. The first stage refers to column 1 and 2 of
Table 5. The 2SLS method instruments the growth rate of the capital stock per worker with the lagged K/L in
levels and the lagged investment intensity.

As a robustness check we replicate the estimates of equation (4) for the sub-sample of managers
who are supposed to take decisions within the board. We select those firms whose board contains
competence-specific managers, who are supposed to influence the decision to introduce innovations
in the firm, eventually. The sign and size of the main coefficients are confirmed. We omit reporting
them here for brevity.

We finally implement the Maximum Likelihood Endogenous Switching model which allows us to
obtain consistent and efficient estimates.

22



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