Updating MS (Mobilité spatiale - Spatial Mobility) Regions and Labour market areas in

1 Today

106 MS Regions 16 Labour market areas

Colour : Labour market areas : MS Regions

Basic units : LAU 2

2 MS Regions

Work done in the 80’s Method : based on commuters statistics But : limits were adapted to administrative boundaries (land use planning regions and mountain regions)

3 First results applying the LMA method – R algorithm

4 New LMA Regions in Switzerland

• As our country is a small one, and considering that we base our study on the previous version of Labour market areas established in the 80’s with the scope of maintaining more or less the same number of LMAs, we have chosen the following values for the various parameters : minSC : 0.57; tarSC : 0.75; minSZ : 3000; tarSZ : 5000 • Various tests have been done (see the results of some of them on the next slides)

5 Basic units : LAU 2 Basic units : LAU 2 Calcul des régions MS : tests avec différents seuils

Seuils :

minSZ : 3000 tarSZ : 5000 minSC: 0.57 tarSC 0.75

Nombre de régions : 78

Basic units : LAU 2 Problems and solutions (so far)

9 Size of LMA Regions Number of commuters

800000

700000

600000

500000

400000

300000

200000

100000

0

10 Size of LMA Regions

• Stakeholders and experts consider that these big urban areas should be subdivided (for statistical purposes)

Solution tested : subdivision of the 5 biggest urban areas (Zurich, Geneva, , and ) with the same method, but with lower thresholds

11 Nombre de régions MS CH : 78 Legend

LMA Region Lausanne

Present MS Regions Lausanne LMA Region subdivided Example : Lausanne

Thresholds for Switzerland :

minSZ : 3000 tarSZ : 5000 minSC: 0.57 tarSC 0.75

Thresholds for big urban areas :

minSZ : 1000 tarSZ : 5000 minSC : 0.4 tarSC : 0.75 Legend

LMA Region Zurich

Present MS Regions Zurich LMA Region subdivided Example :

Thresholds for Switzerland :

minSZ : 3000 tarSZ : 5000 minSC: 0.57 tarSC 0.75

Thresholds for big urban areas :

minSZ : 1000 tarSZ : 5000 minSC : 0.4 tarSC : 0.75 Results

• Not very convincing • LMAs in urban regions seem not to be as consistent as for rural regions, probably because of the thresholds chosen • Decision : try to apply other methods / algorithms to these types of regions : ClustGeo, Skater, PAM Ward, kmeans, all with and without spatial constraints • Results : seem to be better (work in progress)

15 Other problems

• Cantons (NUTS-3) boundaries (a certain number of LMAs are cross-border) • Language boundaries (same problem) Some stakeholders consider important LMAs boundaries to fit to these administrative or cultural bounderies : discussions in progress

• Cross-border LMAs (with France, , Germany and Austria)

16 Rural / Urban typology / DEGURBA

• At that time, we didn’t consider these questions as we try to solve the other problems mentioned…

17