Table 1.

Regressions results for specialization economies

 OLSIV
 (1)(2)(3)(4)(5)(6)(7)(8)(9)
Aging0.15***0.15***0.14***0.14***0.31***0.42***0.31***0.41***
(0.03)(0.03)(0.04)(0.04)(0.04)(0.05)(0.04)(0.05)
SE0.01*0.000.000.040.000.000.18**0.19**
(0.00)(0.00)(0.00)(0.04)(0.00)(0.00)(0.09)(0.09)
Aging × SE−0.01−0.06**−0.06**
(0.01)(0.03)(0.03)
Observations39,62539,44539,44539,44539,44539,17639,17639,17639,176
No. of clusters133133133133133128128128128
Controls
Year fixed effects (FE)
Industry FE
First-stage F-stat39.1441.6418.2626.88
Hansen J-stat0.040.080.060.15
 OLSIV
 (1)(2)(3)(4)(5)(6)(7)(8)(9)
Aging0.15***0.15***0.14***0.14***0.31***0.42***0.31***0.41***
(0.03)(0.03)(0.04)(0.04)(0.04)(0.05)(0.04)(0.05)
SE0.01*0.000.000.040.000.000.18**0.19**
(0.00)(0.00)(0.00)(0.04)(0.00)(0.00)(0.09)(0.09)
Aging × SE−0.01−0.06**−0.06**
(0.01)(0.03)(0.03)
Observations39,62539,44539,44539,44539,44539,17639,17639,17639,176
No. of clusters133133133133133128128128128
Controls
Year fixed effects (FE)
Industry FE
First-stage F-stat39.1441.6418.2626.88
Hansen J-stat0.040.080.060.15

Notes: From columns (1) to (9), firms’ data are aggregate at the three-digit industry (s) and the NUTS-2 level (r). The dependent variable is |${\eta _{rst}}$| that is the time-varying regional industrial FE estimated from the production function. From columns (1) to (5), OLS including industry FE and yearly FE are employed. From columns (6) to (9), we adopt an instrumental variable technique. Excluded instruments are regional |$log\left( {LiveBirth} \right)$| in 1960, 1965, and 1970 computed as described in Section 3.1. Column (9) also uses the interaction between indexes of specialization and the three |${\rm{log}}\left( {LiveBirth} \right)$| instruments as additional instruments and includes the interaction between the index of specialization and aging as endogenous regressor as well. Columns (4), (5), (7), and (9) include as control variables: old dependency ratio, young dependency ratio, average size of firms, an index of local competition, and population density. From columns (6) to (9) the number of regions reduces to 128 because we remove all regions from overseas departments due to the instrumental variable. All specifications include year and industry FE.

***

P < 0.01,

**

P < 0.05, and

*

P < 0.1.

Table 1.

Regressions results for specialization economies

 OLSIV
 (1)(2)(3)(4)(5)(6)(7)(8)(9)
Aging0.15***0.15***0.14***0.14***0.31***0.42***0.31***0.41***
(0.03)(0.03)(0.04)(0.04)(0.04)(0.05)(0.04)(0.05)
SE0.01*0.000.000.040.000.000.18**0.19**
(0.00)(0.00)(0.00)(0.04)(0.00)(0.00)(0.09)(0.09)
Aging × SE−0.01−0.06**−0.06**
(0.01)(0.03)(0.03)
Observations39,62539,44539,44539,44539,44539,17639,17639,17639,176
No. of clusters133133133133133128128128128
Controls
Year fixed effects (FE)
Industry FE
First-stage F-stat39.1441.6418.2626.88
Hansen J-stat0.040.080.060.15
 OLSIV
 (1)(2)(3)(4)(5)(6)(7)(8)(9)
Aging0.15***0.15***0.14***0.14***0.31***0.42***0.31***0.41***
(0.03)(0.03)(0.04)(0.04)(0.04)(0.05)(0.04)(0.05)
SE0.01*0.000.000.040.000.000.18**0.19**
(0.00)(0.00)(0.00)(0.04)(0.00)(0.00)(0.09)(0.09)
Aging × SE−0.01−0.06**−0.06**
(0.01)(0.03)(0.03)
Observations39,62539,44539,44539,44539,44539,17639,17639,17639,176
No. of clusters133133133133133128128128128
Controls
Year fixed effects (FE)
Industry FE
First-stage F-stat39.1441.6418.2626.88
Hansen J-stat0.040.080.060.15

Notes: From columns (1) to (9), firms’ data are aggregate at the three-digit industry (s) and the NUTS-2 level (r). The dependent variable is |${\eta _{rst}}$| that is the time-varying regional industrial FE estimated from the production function. From columns (1) to (5), OLS including industry FE and yearly FE are employed. From columns (6) to (9), we adopt an instrumental variable technique. Excluded instruments are regional |$log\left( {LiveBirth} \right)$| in 1960, 1965, and 1970 computed as described in Section 3.1. Column (9) also uses the interaction between indexes of specialization and the three |${\rm{log}}\left( {LiveBirth} \right)$| instruments as additional instruments and includes the interaction between the index of specialization and aging as endogenous regressor as well. Columns (4), (5), (7), and (9) include as control variables: old dependency ratio, young dependency ratio, average size of firms, an index of local competition, and population density. From columns (6) to (9) the number of regions reduces to 128 because we remove all regions from overseas departments due to the instrumental variable. All specifications include year and industry FE.

***

P < 0.01,

**

P < 0.05, and

*

P < 0.1.

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