H1: Tertiarisation increases income inequality.
H2: The effect of Tertiarisation depends on time varying variables.
n= 2504 communities, 4 waves (1995,2001,2005,2008)
Y= Gini of taxable income
X= employees by sector on community-level (log-scale)
Hybrid-Model with separation of between and within effects.
| Y=Gini | |
|---|---|
| Constant | .2232 (.0083)*** |
| between effect of full-time jobs (log) in primary sector (1995) | -.0136 (.0012)*** |
| between effect of full-time jobs (log) in secondary sector (1995) | -.0169 (.0012)*** |
| between effect of full-time jobs (log) in tertiary sector (1995) | .0050 (.0016)** |
| within effect of full-time jobs (log) in primary sector (1995) | .0000 (.0016) |
| within effect of full-time jobs (log) in secondary sector (1995) | .0013 (.0010) |
| within effect of full-time jobs (log) in tertiary sector (1995) | -.0033 (.0017)* |
| linear time trend | .0002 (.0002) |
| Interaction: between effect primary X linear time trend | -.0002 (.0000)*** |
| Interaction: between effect secondary X linear time trend | .0000 (.0000) |
| Interaction: between effect tertiary X linear time trend | .0002 (.0001)*** |
| Interaction: within effect primary X linear time trend | .0003 (.0002) |
| Interaction: within effect secondary X linear time trend | .0002 (.0001) |
| Interaction: within effect tertiary X linear time trend | .0004 (.0002)* |
| Log taxable inhabitants | .0328 (.0022)*** |
| R2 | 0.1425 |
| Adj. R2 | 0.1423 |
| Num. obs. | 10017 |
| ***p < 0.001, **p < 0.01, *p < 0.05 | |