1 Introduction
2 Theory and earlier work
2.1 Theory
2.2 Empirical evidence for the Netherlands
3 Data
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Employment growth. Data on employment are taken from Statistics Netherlands and the employment figures relate to employee jobs expressed in full-time equivalents or labour years. Part-time work is proportionally being counted as fulltime work. Self-employed workers and unpaid family workers are excluded from the data. The employment levels have been measured at the first of January each year. The employment growth rates are measured over periods of 3 years, and are expressed in per cent points.
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Start-up rate. Following the labour market approach we define the start-up rate as the number of new-firm start-ups divided by employment in full-time equivalents (as described above). The data on the number of start-ups are taken from the Dutch Chambers of Commerce. The number of start-ups is defined to include all independent new-firm registrations. It includes both new firms with employees and new firms without employees. Mergers, new subsidiary companies, new branches and relocations to other regions are not counted as a start-up.
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Wage growth measures three-yearly changes in regional wage rates and is expressed in per cent points. The wage rate is computed as total wages in a sector/region divided by the employment of employees in full-time equivalents. Data on wages are also taken from Statistics Netherlands (CBS). Because sectoral classifications used by CBS changed in 1993, corrections had to be made in order to arrive at wage rates according to a uniform sectoral classification.
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Data on population density were also taken from Statistics Netherlands.
1990–1993 | 1993–1996 | 1996–1999 | 1999–2002 | |
---|---|---|---|---|
Employment growth | ||||
Mean | 3.08 | 3.25 | 9.27 | 3.63 |
Standard deviation | 7.52 | 10.11 | 10.32 | 8.11 |
Start-up rate | ||||
Mean | 12.41 | 12.84 | 12.84 | 11.71 |
Standard deviation | 8.78 | 7.94 | 7.58 | 6.96 |
Number of observations | 200 | 200 | 200 | 200 |
Manufacturing | Construction | Trade | Transport and communication | Services | |
---|---|---|---|---|---|
Employment growth | |||||
Mean | −3.62 | 2.58 | 6.33 | 3.75 | 11.50 |
Standard deviation | 6.75 | 10.22 | 5.55 | 11.06 | 7.13 |
Start-up rate | |||||
Mean | 3.30 | 17.19 | 19.29 | 8.56 | 16.01 |
Standard deviation | 1.68 | 6.49 | 6.93 | 4.79 | 4.85 |
Number of observations | 160 | 160 | 160 | 160 | 160 |
North | East | West | South | |
---|---|---|---|---|
Employment growth | ||||
Mean | 4.66 | 5.46 | 2.80 | 4.85 |
Standard deviation | 11.21 | 9.22 | 9.10 | 9.43 |
Start-up rate | ||||
Mean | 13.75 | 12.79 | 12.97 | 11.60 |
Standard deviation | 8.31 | 8.80 | 7.57 | 7.44 |
Number of observations | 180 | 160 | 320 | 140 |
4 Model and research design
4.1 Research design for analysis of the lag structure of the economic impact of new firms
4.1.1 Sector adjustment in data
4.1.2 Almon lags
S
t
|
S
t - 1
|
S
t - 2
|
S
t - 3
|
S
t - 4
|
S
t - 5
|
S
t - 6
|
S
t - 7
|
S
t - 8
| |
---|---|---|---|---|---|---|---|---|---|
S
t
| 1 | ||||||||
S
t - 1
| 0.89 | 1 | |||||||
S
t - 2
| 0.81 | 0.90 | 1 | ||||||
S
t - 3
| 0.77 | 0.82 | 0.90 | 1 | |||||
S
t - 4
| 0.70 | 0.73 | 0.79 | 0.90 | 1 | ||||
S
t - 5
| 0.65 | 0.65 | 0.69 | 0.78 | 0.90 | 1 | |||
S
t - 6
| 0.59 | 0.59 | 0.59 | 0.67 | 0.78 | 0.89 | 1 | ||
S
t - 7
| 0.54 | 0.57 | 0.56 | 0.58 | 0.68 | 0.78 | 0.89 | 1 | |
S
t - 8
| 0.49 | 0.54 | 0.55 | 0.52 | 0.58 | 0.69 | 0.77 | 0.88 | 1 |
4.1.3 Control variables
4.1.4 Estimation method
4.2 Research design for analyses of sectors and degree of urbanization
4.2.1 Control variables
4.2.2 Degree of urbanization
5 Results
5.1 Time structure of the impact of new firms on regional employment growth
Unrestricted regression | Estimated Almon polynomial of order n:
\(\beta _i = \gamma _0 + \gamma _1 i + \cdots + \gamma _n i^n \) (i = lag length in years) | Restricted start-up coefficients (lags in left column) | ||||
---|---|---|---|---|---|---|
Second-order | Third-order | Fourth-order | Third-order | |||
Start-up rate current year t
| 0.33 (1.5) |
γ
0
| −0.14 (1.0) | 0.12 (0.8) | 0.21 (1.0) | 0.124 |
Start-up rate year t - 1 | −0.54* (2.4) |
γ
1
| 0.13* (2.3) | −0.29#
(1.7) | −0.55 (1.3) | −0.068 |
Start-up rate year t - 2 | 0.18 (0.8) |
γ
2
| −0.016* (2.5) | 0.11* (2.2) | 0.26 (1.1) | −0.101 |
Start-up rate year t - 3 | 0.047 (0.2) |
γ
3
| −0.010* (2.5) | −0.039 (0.9) | −0.037 | |
Start-up rate year t - 4 | −0.062 (0.3) |
γ
4
| 0.0018 (0.7) | 0.065 | ||
Start-up rate year t - 5 | 0.17 (0.9) | 0.143 | ||||
Start-up rate year t - 6 | 0.11 (0.7) | 0.137 | ||||
Start-up rate year t - 7 | 0.024 (0.1) | −0.015 | ||||
Start-up rate year t - 8 | −0.36* (2.3) | −0.371 | ||||
Wage growth t - 3 | 0.24** (6.1) | 0.20** (5.7) | 0.24** (6.5) | 0.24** (6.4) | ||
Spatial autocorrelation (residuals in adjacent regions) | 0.45** (2.7) | 0.63** (4.1) | 0.56** (3.8) | 0.54** (3.4) | ||
R² | 0.702 | 0.679 | 0.691 | 0.693 | ||
Loglikelihood | −552.3 | −560.7 | −556.2 | −555.8 | ||
Number of observations | 233 | 233 | 233 | 233 |
5.1.1 Interpreting the ‘immediate effect’
Estimated third-order Almon polynomial \(\beta _i = \gamma _0 + \gamma _1 \left( {i - 2} \right) + \gamma _2 \left( {i - 2} \right)^2 + \gamma _3 \left( {i - 2} \right)^3 \) (i = lag length in years) | |
---|---|
γ
0
| −0.239 (0.9) |
γ
1
| 0.517#
(1.8) |
γ
2
| −0.160#
(1.9) |
γ
3
| 0.013* (2.0) |
Wage growth | 0.253** (5.4) |
Spatial autocorrelation | 0.831** (3.9) |
R² | 0.773 |
Number of observations | 155 |
5.2 Does the impact of new firms on regional development differ by sector?
Manufacturing | Construction | Trade | Transport and communication | Services | |
---|---|---|---|---|---|
Constant | −8.70** (7.06) | −2.99 (1.54) | 0.94 (0.54) | 0.16 (0.06) | 5.28** (2.82) |
Start-up rate | 1.28** (5.32) | 0.39** (3.24) | 0.14* (2.35) | 0.39* (2.18) | 0.34** (4.14) |
Population density | −0.003** (4.47) | −0.003 (1.88) | −0.001** (3.19) | 0.002 (1.05) | −0.0009 (1.71) |
Wage growth | 0.13** (2.87) | 0.12 (1.93) | 0.21** (3.90) | −0.071 (0.90) | 0.18** (3.36) |
Lagged growth | −0.071 (1.25) | −0.079 (0.90) | 0.003 (0.05) | −0.031 (0.38) | −0.13* (2.12) |
Spatial autocorrelation | 0.89** (8.84) | 0.20 (0.94) | 0.70** (4.40) | 0.40** (2.80) | 0.90** (11.02) |
Adjusted R
2
| 0.512 | 0.117 | 0.320 | 0.055 | 0.548 |
JB test [p-value] | [0.409] | [0.794] | [0.365] | [0.957] | [0.972] |
Number of observations | 157 | 158 | 155 | 154 | 157 |
5.3 Does the impact of new firms on regional development differ by degree of urbanization?
Model I | Model II | |
---|---|---|
Constant | −6.0** (7.0) | −10.3** (8.9) |
Start-up rate | 0.30** (4.6) | 0.49** (5.9) |
Degree of urbanization | −5.3** (2.8) | |
Start-up rate, interaction term degree of urbanization
| 0.19 (1.5) | |
Degree of rurality | 5.3** (2.8) | |
Start-up rate, interaction term degree of rurality
| −0.26* (2.0) | |
Wage growth | 0.14** (5.4) | 0.14** (5.4) |
Lagged growth | −0.047 (1.3) | -0.042 (1.2) |
Spatial autocorrelation | 0.69** (11.5) | 0.69** (11.5) |
Adjusted R
2
| 0.506 | 0.504 |
JB test [p-value] | [0.052] | [0.049] |
Number of observations | 777 | 777 |
Estimated third-order Almon polynomial \(\beta _i = \gamma _0 + \gamma _1 i + \gamma _2 i^2 + \gamma _3 i^3 \) (i = lag length in years) | ||
---|---|---|
Urban regions: ‘Randstad’ | Rural regions | |
γ
0
| 0.72** (2.7) | −0.057 (0.3) |
γ
1
| −0.54* (2.1) | -0.20 (0.9) |
γ
2
| 0.17* (2.4) | 0.086 (1.2) |
γ
3
| −0.014** (2.7) | −0.0083 (1.5) |
Wage growth | 0.30** (6.5) | 0.21** (3.8) |
Spatial autocorrelation | 0.83** (4.1) | 0.45* (2.2) |
R² | 0.779 | 0.682 |
Number of observations | 84 | 149 |