1 Introduction
2 Theoretical framework
2.1 Impact over time
2.1.1 Regional differences in impact
2.2 Expectations
3 Data and methodology
3.1 Data
3.2 Dual causality
3.3 Model
Start-ups | Start-up rates with maximum 15 employees in the initial year. Except agriculture, labour market approach (dividing the number of start-ups by the potential labour market (age 15–65) per region) |
Population change | Population change per year, data from Statistic Netherlands. For further analysis, three categories are used: decline (less than \(-\)1 %); stable (\(-\)1\(>\)
\(<\)1 %); growth (\(>\)1 %), 2 year mean of 1996–2007 to avoid heavy fluctuations and to allow some response time for the dependent variable |
Urbanization | Population density—based on address density per square kilometre, from Statistics Netherlands at municipality level (log). Using the average number of addresses/km\(^{2}\) within a radius of 1 km from each individual address, address density uses the concentration of human activities such as living, working and utilizing amenities as indicators of urbanization—the lower the concentration of these activities, the lower the level of urbanization (Haartsen 2002) |
Controls | Commuting is measured in absolute numbers of incoming commuters in 1998, 2000, 2004 and 2005 due to data availability. Based on these years a trend line was determined and applied to the remaining years |
Age distribution is measured by annual numbers of inhabitants in two categories “Under_15” and “Over_65”. Data from Statistics Netherlands | |
Share of higher educated inhabitants relative to the active workforce (log), annual data of 1997–2007 due to data availability. Sixty-one small municipalities were excluded from the source dataset for privacy reasons. These municipalities are estimated based on the share of higher educated in the COROP region. Data from the EBB (Enquete Beroepsbevolking) executed by Statistics Netherlands | |
Share of immigrants, annually per inhabitant per municipality. Statistics Netherlands, municipality level | |
The annual share of low income households between 1997 and 2009 is used as a proxy for level of income per municipality. Low income households are in the 2nd, 3rd and 4th decile, the upper limit was 17.100 euro in 1997 and 23.700 in 2009 | |
Annual sector shares, measured in share of jobs per municipality, based on the LISA dataset. We used eight sectors based on a classification provided by Van Oort (2002): resource based activities, production (reference category), physical infrastructure, distribution, consumer-based activities, well-being, information activities, information infrastructure | |
Agency dummy | The 20 LISA regions were included as dummy variables |
3.3.1 Controls
Variables | Mean | SD | Min. | Max. | Observations |
---|---|---|---|---|---|
Start-up rate | 2.43 | 1.41 | 0 | 16.23 |
\(N = 5852\)/\(n = 418\)/\(T = 14\)
|
\(\hbox {EMP}_{\mathrm{total}}\)
| 1.92 | 4.85 |
\(-\)47.42 | 101.17 |
\(N = 5852\)/\(n = 418\)/\(T = 14\)
|
\(\hbox {EMP}_{\mathrm{new}}\)
| 1.46 | 0.84 | 0 | 6.75 |
\(N = 2090\)/\(n = 418\)/\(T = 5\)
|
\(\hbox {EMP}_{\mathrm{inc}}\)
| -0.06 | 3.24 |
\(-\)18.46 | 25.32 |
\(N=2090\)/\(n = 418\)/\(T = 5\)
|
Population change | 0.38 | 1.12 |
\(-\)11.51 | 13.73 |
\(N = 5852\)/\(n = 418\)/\(T = 14\)
|
4 Results
Total employment | Incumbents | New and young | |
---|---|---|---|
Start-up rate | |||
\(t = 0\)
| 0.88*** | 0.42*** | 0.46*** |
\(t = 1\)
| 0.06*** |
\(-\)0.10*** | 0.16*** |
\(t = 2\)
|
\(-\)0.34*** |
\(-\)0.33*** |
\(-\)0.02*** |
\(t = 3\)
|
\(-\)0.43*** |
\(-\)0.33*** |
\(-\)0.09*** |
\(t = 4\)
|
\(-\)0.30*** |
\(-\)0.20*** |
\(-\)0.10*** |
\(t = 5\)
|
\(-\)0.07*** |
\(-\)0.01 |
\(-\)0.06*** |
\(t = 6\)
| 0.16*** | 0.17*** |
\(-\)0.01*** |
\(t = 7\)
| 0.27*** | 0.25*** | 0.03*** |
\(t = 8\)
| 0.17*** | 0.15*** | 0.02*** |
\(t = 9\)
|
\(-\)0.26*** |
\(-\)0.21*** |
\(-\)0.05*** |
C
| 2.01 | 2.36* |
\(-\)0.34* |
Population change | 0.34** | 0.29** | 0.05** |
W_Population Change |
\(-\)1.81*** |
\(-\)1.71*** |
\(-\)0.10 |
Urbanization (log) |
\(-\)0.49*** |
\(-\)0.30** |
\(-\)0.19*** |
W_Urbanization |
\(-\)0.02 |
\(-\)0.04 | 0.02 |
Commute |
\(-\)0.00 |
\(-\)0.00 |
\(-\)0.00*** |
Higher educated (log) | 0.33 | 0.26 | 0.06 |
W_Higher Educated | 0.02 | 0.03 |
\(-\)0.01 |
Immigrants |
\(-\)0.01 |
\(-\)0.00 |
\(-\)0.01** |
Income (low) | 0.02 | 0.01 | 0.02*** |
W_Income | 0.02 |
\(-\)0.00 | 0.03** |
Youngsters | 0.02 | 2.36 |
\(-\)0.01 |
Elderly |
\(-\)0.09 | 0.29* | 0.01 |
Industry shares | Yes | Yes | Yes |
Agency dummies | Yes | Yes | Yes |
\(\alpha 1\)
|
\(-\)0.30*** |
\(-\)0.92*** |
\(-\)0.10*** |
\(\alpha 2\)
| 0.20*** |
\(-\)0.20*** | 0.02*** |
\(\alpha 3\)
| 0.05*** | 0.18*** | 0.02*** |
\(\alpha 4\)
|
\(-\)0.02*** | 0.03*** |
\(-\)0.00*** |
\(R^{2}\)
| 0.16 | 0.14 | 0.70 |
Log likelihood |
\(-\)5301.68 |
\(-\)5263.36 |
\(-\)1336.02 |
F-statistic | 9.44 | 8.00 | 114.56 |
Prob. (F-statistic) | 0.00 | 0.00 | 0.00 |
N
| 2090 | 2090 | 2090 |
Sum of lags | All | Decline | Stable | Growth | Rural | Interm. | Urban |
---|---|---|---|---|---|---|---|
New and Young | 0.34 | 0.32 | 0.40 | 0.36 | 0.57 | 0.42 | 0.46 |
Incumbents |
\(-\)0.19 |
\(-\)0.03 |
\(-\)0.71 |
\(-\)0.26 |
\(-\)0.54 | 0.12 |
\(-\)0.39 |
Tot emp. | 0.14 | 0.28 |
\(-\)0.31 | 0.10 | 0.03 | 0.54 | 0.07 |