1. Task Force on Establishment of European set of Labour Market Areas
Preliminary Analysis and Results
Unit for the Coordination of Territorial Statistics
Task Force Meeting on Labour Market Areas
October 2018

2. Overview 1 | Final LMA Geography and comparison with other geographies
3 | Regional Urban-Rural Typology Matrixes
2 | Statistics and Analysis on Regional Urban-Rural Typology
4 | Sensitive Analysis
1 | Final LMA Geography and comparison with other geographies
5 | Main findings

3. Goals
Study the urban-rural linkages considering the Regional Urban-Rural Typology
Set a framework of study areas based on the preliminary analysis and types of territories
Investigate the use of different parameters to define LMA depending on the types of territories through sensitive and comparability analysis
Evaluate a set of metropolitan and non-metropolitan parameters

4. Functional Urban Areas (FUA)
1| Final LMA Geography and comparison with other geographies
Portuguese Cities, 2011
NUTS 3 (2013)
Functional Urban Areas (FUA)

5. 2 | Statistics and Analysis on Regional Urban-Rural Typology
Comparative Statistical Indicators between Regional Urban-Rural Typologies (LAU 1)
Typology
PTRUR
PTINT
PTURB PT
Nr. of territorial units (t.u.)
191 52 35
278
Surface (km2)
Min 14 25 8
Max
1 721
764
465
Average
381
216
144
320
Median
279
182
128
229 SD
311
153
111
284
CV (%) 82 71 77 89
Resident Population (inhab.)
1 834
2 917
17 569
17 677
40 190
36 143
10 537
26 582
93 858
15 700
20 186
37 760
58 222
114 94 84
161
Employed Resident Population (Workers)
607
829
7 781
60 993
78 779
6 526
15 998
54 142
14 293
3 708
10 566
38 432
5 433
8 344
16 391
45 210
24 308
102
170
Employment (Jobs)
635
853
6 873
74 539
82 923
6 423
15 759
55 060
3 276
9 639
30 251
4 834
8 977
17 426
86 078
35 690
140
156
250
Employed resident population working in the territorial unit
563
729
3 225
52 361
65 209
5 124
12 193
30 288
9 615
2 700
7 259
22 335
3 876
7 019
13 555
32 541
16 333
137
107
Typology
PTRUR
PTINT
PTURB PT
Nr. of territorial units (t.u.)
191 52 35
278
SC Demand Side Indicator
Min 41 61
Max 94 89 84
Average 80 79 64 78
Median 82 69 SD 9 6 14 10
CV (%) 11 8 21 13
SC Supply Side Indicator 38 57 34 95 88 83 74 55 75 53 77 12 15 24 18
Rural Areas
- 68,7% of LAU 1
81,7% of total surface
In average, 77,6% of the rural employed population lives and works in the same territorial unit (LAU 1)
High levels of self-containment indicators (more employed population works and lives in the same LAU 1)
Urban Areas
12,6% of LAU1
5,7% of total surface
In average, 55,2% of the urban employed population lives and works in the same territorial unit
More mobility between LAU 1 comparing to rural areas

6. 2 | Statistics and Analysis on Regional Urban-Rural Typology
Regional Urban-Rural Typology and Final LMA Geography
LMA
LMA Name
Typology
LAU1
Workers Density (per km2)
Jobs Density (per km2)
Emp_live_work Density (per km2)
SC demand side indicator
SC supply side indicator 10
AVEIRO
Intermediate
8 448
8 648
6 002
72,5
67,6
Rural 1
3 602
250
200
80,2
69,3 19
SANTA MARIA DA FEIRA 3
6 526
1 971
1 457
78,9
69,4
Urban 6
14 466
8 051
5 705
68,0
67,9 24
BEJA 13
528
2 952
2 468
83,7
81,2 36
BRAGA 8
11 243
11 306
9 068
79,8 41
GUIMARÃES 7
15 549
12 283
9 797
81,1
76,9 2
21 703
2 869
1 910
64,9
64,0 49
BRAGANÇA
661
3 063
2 718
88,2
90,5 62
CASTELO BRANCO
1 005
3 974
3 468
81,5
85,4 73
COIMBRA
5 511
9 696
7 158
76,0
62,1 92
ÉVORA
868
3 416
2 819
83,3
78,0
101
PORTALEGRE 17
740
3 019
2 518
82,3
80,0
106
FARO
3 516
6 366
4 936
80,1
74,9
112
PORTIMÃO
3 732
5 347
4 199
80,4
79,0
124
GUARDA
880
2 500
2 114
85,1
137
ALCOBAÇA
6 033
5 065
4 015
77,6
71,4
140
LEIRIA
5 283
8 709
6 792
76,1
74,1
153
LISBOA
5 149
5 024
3 651
68,4
60,4 18
39 524
78 418
40 931
63,1
48,7
182
PORTO
63 155
33 446
18 614
62,7
56,9
187
PAREDES 5
12 217
6 515
5 069
78,3
72,7
21 949
1 930
1 444
74,8
197
TOMAR 14
1 260
3 500
2 848
78,7
78,4
212
SANTARÉM
2 686
6 351
4 653
72,9
63,6
226
SINES
728
2 595
2 030
80,8
82,8
239
VIANA DO CASTELO
3 842
5 487
4 473
80,5
254
VILA REAL
1 212
134
109
81,6
1 424
3 718
3 212
86,0
87,4
259
LAMEGO
2 765
463
396
86,1
75,3 11
2 142
2 117
1 733
82,2
277
VISEU
2 602
7 959
6 469
79,1

7. 2 | Statistics and Analysis on Regional Urban-Rural Typology
Regional Urban-Rural Typology and Final LMA Geography
Demand Side Self-Containment (LAU1) and Final LMA
Supply Side Self-Containment (LAU1) and Final LMA
Regional Typology and Final LMA

8. 2 | Statistics and Analysis on Regional Urban-Rural Typology
Regional Urban-Rural Typology and Final LMA Geography
56% of the LMA have LAU 1 in rural regions
Only 1 out of the 25 LMA has LAU 1 which intersect exclusively with urban region (Porto), because this LMA is smaller than Porto Metropolitan Area
12% of the LMA have LAU 1 in urban and intermediate regions (no rural regions)
Only the LMA of Lisboa has LAU 1 in urban and rural regions (no intermediate regions)
The LMA which intersect exclusively with rural regions, especially the ones located in the inland regions of Mainland Portugal have the lowest levels of workers density (employed population working in rural areas)
The LMA which intersect with rural regions have higher levels of self-containment: more employed population lives and works in LAU 1 of the same typology
The lowest levels of self-containment are in the LMA which intersect with urban regions (high mobility between urban LAU 1)

9. 2 | Statistics and Analysis on Regional Urban-Rural Typology
Proportion of Employed Population working per Economic Sector, 2011
The LMA which intersect with rural regions are situated in the north inner territory and NUTS 2 Alentejo have higher representation of the primary sector (between 9% and 16,2%)
The employment in the secondary sector was more important in LMA which intersect with urban and intermediate regions (Santa Maria da Feira, Guimarães and Paredes), surrounding the LMA of Porto (almost 50%)
The tertiary sector is more significant in the LMA which intersect with urban regions (Lisboa and Porto) and with the intermediate regions (Faro and Portimão), situated in NUTS 2 Algarve
LMA
LMA Name
Typology
Primary sector
Secondary sector
Tertiary sector 10
AVEIRO
Intermediate
2,9
37,5
59,6
Rural
8,3
27,6
64,1 19
SANTA MARIA DA FEIRA
2,6
42,9
54,4
Urban
1,3
47,7
51,0 24
BEJA
12,3
18,8
68,9 36
BRAGA
2,5
39,4
58,1 41
GUIMARÃES
1,4
51,7
46,9
1,2
48,5
50,3 49
BRAGANÇA
12,5
18,7
68,7 62
CASTELO BRANCO
4,2
27,2
68,6 73
COIMBRA
2,4
22,9
74,7 92
ÉVORA
9,1
20,1
70,8
101
PORTALEGRE
20,2
106
FARO
3,8
16,4
79,7
112
PORTIMÃO
2,7
15,7
81,6
124
GUARDA
7,3
22,7
70,0
137
ALCOBAÇA
7,4
27,4
65,2
140
LEIRIA
1,9
60,6
153
LISBOA
4,6
25,9
69,5
0,7
16,6
82,7
182
PORTO
23,8
74,9
187
PAREDES
1,6
47,4
1,1
45,7
53,1
197
TOMAR
5,2
27,3
67,5
212
SANTARÉM
6,1
24,8
69,1
226
SINES
11,7
63,5
239
VIANA DO CASTELO
3,9
34,8
61,3
254
VILA REAL
9,0
29,9
61,1
11,0
19,8
69,2
259
LAMEGO
9,7
38,6
51,6
16,2
21,5
62,3
277
VISEU
4,5
30,6
64,9

10. 3 | Regional Urban-Rural Typology Matrixes
Commuting Matrixes according to Regional Urban-rural Typology by LAU 1
Flows of employed population according to Regional Urban-Rural Typology by LAU 1, 2011
LAU 1 Matrix
% Internal Flows
% In Flows
% Out Flows
% Total Flows
% Employed Population
Urban
38,4
31,4
30,2
100
Intermediate
62,3
18,2
19,4
Rural
65,5
16,6
17,9
Concerning internal flows (flows between the same LAU 1), 65,5% of the rural employed population and 38,4% of the urban employed population lives and works in the same LAU 1
External flows (in and out flows) are more significant in urban LAU 1 (31,4% and 30,2% respectively) compared to intermediate and rural LAU 1 – more mobility in urban LAU 1

11. 3 | Regional Urban-Rural Typology Matrixes
Regional Urban-Rural Typology in commuting matrix
Proportion of employed population in commuting matrix according to Regional Urban-Rural Typology, 2011
From/To
Urban
Intermediate
Rural
Total
46,2
0,9
0,6
47,7
1,2
19,4
0,4
20,9
1,1
0,3
29,9
31,4
48,5
20,6
30,9
100
Almost 49% of employed population works in urban LAU 1, of which 46,2% lives and works in urban LAU 1
Almost 31% of employed population lives in rural LAU 1, of which 29,9% lives and works in rural LAU 1
- Concerning the flows between different typologies, the flows between intermediate LAU 1 and urban LAU 1 represent the highest proportion of employed population: 1,2%

12. Study Areas and Regional
4 | Sensitive Analysis
Study Areas based on Regional Urban-Rural Typology
NUTS3 and Regional
Urban-Rural Typology
Study Areas and Regional
Urban-Rural Typology
Study Areas:
Lisboa Metropolitan Territory
Porto Metropolitan Territory
Rural Territory
Algarve
Alto Minho
The study area of Alto Minho was chosen because of its non spatial contiguity with other rural territories
Sensitive analysis were conducted in two scenarios/study areas:
Alto Minho separated with other rural regions
Alto Minho with other rural regions

13. 4 | Sensitive Analysis
Study Areas based on Regional Urban-Rural Typology (Rural regions vs alto minho)
Rural Regions
Alto Minho
Rural Regions

14. 4 | Sensitive Analysis
Study Areas based on Regional Urban-Rural Typology
Based on previous results it was concluded that despite setting high or low values on the parameters, the number of LMA in Alto Minho it is the same for both scenarios.
So it were defined 4 study areas:
Final Study Areas
Lisboa Metropolitan Territory
Lisboa Metropolitan Area + 2 Rural Regions (Oeste and Lezíria do Tejo)
Porto Metropolitan Territory
Hypothesis 1: Porto Metropolitan Area
Hypothesis 2: : Porto Metropolitan Area + 4 Intermediate Regions (Cávado, Ave, Tâmega e Sousa and Região de Aveiro)
Rural Territories
14 Rural Regions
Algarve
1 Intermediate Region
Concerning the two scenarios for Porto Metropolitan Territory, tests were conducted for both territories for comparability reasons at metropolitan level

15. Study Areas characteristics Self-containment by LAU 1
4 | Sensitive Analysis
Study Areas Characteristics
Study Areas characteristics
Study Area
Nº LAU 1
% Employed Population
Self-containment by LAU 1
Demand Side
Supply Side
Lisboa Metropolitan Territory 41
36,0
56,0
56,3
Porto Metropolitan Territory
(Hypothesis 1) 17
17,8
59,8
60,4
(Hypothesis 2) 53
34,2
68,0
67,7
Rural Territories
168
25,3
80,5
80,4
Algarve 16
4,5
78,0
78,2

16. 4| Sensitive Analysis Parameterization Scenarios
Three parameterization scenarios:
1 - Scenario based on the LMA final geography parameters:
2 - Scenario based on parameters adjusted to metropolitan territories: depicting internal organization of metropolitan territories
- high levels of functional integration
- lower size and self-containment values
3 – Scenario based on parameters adjusted to non-metropolitan territories: defining functional urban regions
- high levels of self-containment at LAU 1
- over evaluate size and self-containment values
Several tests were conducted but only one result was selected for each scenario
minSZ
minSC
tarSZ
tarSC
35 000
0.80
0.85

17. 4| Sensitive Analysis Lisboa Metropolitan Territory Scenario 1

18. 4| Sensitive Analysis Porto Metropolitan Territory (Hypothesis 1)
Scenario 1
Scenario 2
Scenario 3

19. 4| Sensitive Analysis Porto Metropolitan Territory (Hypothesis 2)
Scenario 1
Scenario 2
Scenario 3

20. 4| Sensitive Analysis Rural Territories Scenario 1 Scenario 2

21. 4| Sensitive Analysis
Algarve
Scenario 2
Scenario 1
Scenario 3

22. 5 | Main findings
Scenario 3 results, based on parameters adjusted to non-metropolitan territories – functional urban regions approach – are similar to the results of Scenario 1 – LMA final geography (Eurostat Grant).
Scenario 2, based on parameters adjusted to metropolitan territories – depicting internal organization of metropolitan territories – applied to non-metropolitan territories ensure high levels of functional integration in rural regions, meaning, in the Portuguese context, a high number of LMA with one single LAU 1: 48 LMA – 51,6%...
- Following our analysis and tests:
Should a specific set of parameters be defined according to the type of territory U/R OR
should a hierarchical system of LMA be defined according to size and functional integration?
The Algarve study area (intermediate region) is a good example on how this hierarchical system may work

23. Task Force on Establishment of European set of Labour Market Areas
Preliminary Analysis and Results
Unit for the Coordination of Territorial Statistics
Task Force Meeting on Labour Market Areas
October 2018