The influence of basic spatial structures and the volume ... · The influence of basic spatial structures and the volume of commuting on the applicability of EURO method Kezán András

The influence of basic spatial structures and the

volume of commuting on the applicability of EURO

method

Kezán András

[email protected]

Labour Market Areas: current development and future use,

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Project

Goal

To set up a non-overlapping, contiguous system of Labour

Market Areas for the whole country.

Organization

Molnár Ernő Phd – University of Debrecen

Pénzes János Phd – University of Debrecen

Pálóczi Gábor – University of Debrecen

Fábián Zsófia Phd – HCSO

Gerse József – HCSO

Jankó Balázs – HCSO

Szilágyi Dániel - HCSO


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COMMUTING DATA


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Input data (census)

Employed

(3 942 723)

Temporarily staying

abroad

(56 694)

Living in Hungary

(3 886 029)

Not living and working

in the same LAU2 unit

(1 340 831)

Living and working in

the same LAU2 unit

(2 545 198)

Working in various

LAU2 units

(153 410)

Working in other

LAU2 unit

(1 160 293)

Commuting abroad

(27 128)

Practically in

Hungary that

figure does

not only refer

to daily

commuters!


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Further corrections in commuting matrix

Daily and midterm commuting flows had to be

distinguished. On the basis of the Hungarian commuting

habits, the commuting flows were cut, where the

commuting time exceeded the 90 minutes limit, or the

commuting distance exceeded the 100 km limit. (It meant

only about the 4% of the commuting flows.)


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SPECIALTIES OF THE

SPATIAL STRUCTURE


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Commuting intensity

%

– 50,0

50,1 – 74,9

75,0 – 99,9

100,0 – 124,9

125,0 – 149,9

150,0 –

Intensity=(Inflows+Outflows)/Local employees

Low

intensity

(rural area)


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Source: PÉNZES J., MOLNÁR E., PÁLÓCZI G.: Helyi munkaerő-piaci vonzáskörzetek az ezredforduló utáni Magyarországon, 2014

Specialties of the spatial structure


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• The intensity of work-related commute has very significant

differences in different parts of Hungary,

• Lot of areas with low commute intensity in Hungary, with high SC

values in LMAs.

• Towns with agricultural characteristics on the Great Plain have

fairly enclosed labour markets, thus significanty higher SC

values may occur in LMAs in this area.

• The settlement network in different parts of the country has

significant differences, which lead to very different relations amongst

settlements

• Commute to centers (nodal type of commute) is the most typical in

Hungary, which also affects results of the method.

SENSITIVITY ANALYSIS

Labour Market Areas: current

development and future use,

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• Several methods can be applied during testing sets of

parameters, but whatever option is chosen, it is worth to

implement a systematic, automatized method.

Systematic, big samples help to understand effects of

parameters, and not appropriate sets of parameters can

be quickly abandoned.

• In our research we had followed the recommendations of

the LMA Task Force. Only one parameter had changed

in each successive run.

Sensitivity analysis


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EVALUATION PROCESS


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Possible ways of optimization

Heuristic parameter

tests

Study the impact of the changes in

parameters (sensitivity analysis)

Selective tests

Validation based on centers

Selection of relevant parameter sets


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Validation based on

indicators & statistics

Validation based on

border stability

Seeking parameter sets with the most frequently occured centers

Multivariate statistical models

Global indicators &

statistics

Genetic algorythm

Occurance of centres


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Global indicators


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32

34

36

38

40

42

44

46

60 70 80 90 100 110 120 130 140

avera

ge I

IRC

L

Number of LMAs

0.804

0.806

0.808

0.810

0.812

0.814

0.816

0.818

0.820

0.822

0.824

60 70 80 90 100 110 120 130 140

Q_m

odula

rity

Number of LMAs

Having studied and tested several

indicators on national level, we

concluded that solely none of them

is capable of guaranteeing

optimization process. The only

indicator suitable for evaluating the

delineation was Q modularity

(Newman–Girvan 2004).


From theoretical point of view multivariate models could be used to

validate the results of sensitivity analysis:

• Factor analysis and principal component analysis are considered

suitable not just for analysing statistical data, but also for groupping

areas with a focus on labour market (e.g. Kosfeld-Werner 2012).

• Cluster analysis is also suitable for groupping areas (e.g. Smart

1974; Kristensen 1998), but can be used for statistically analysing

LMAs with multivariate modells. In our research hierarchical cluster

analysis was selected from possible methods.

• In the discriminant analysis the dependent variable was the

frequency of occurence of LMAs. The results of 1000 parameters

were distributed into 10 categories.


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Similarly to the indicators on country level (e.g. Q

modularity), multivariate modells favor to create relatively

few LMAs, with bigger sizes, therefore those units have

better indicators. It’s also clear that these analytical

methods can’t reflect on possible errors in spatial relations

(e.g. LMAs where relations are not represented well).

Considering these specialties, multivariate modells

should be ignored while choosing the optimal sets of

parameters, even though this approach could (have)

provide(d) proper base to evaluate statistics and to

classificate variables


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Commuting links (outflows) on the basis

of basic census data


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Stability of borders on the basis of 1000

parameter sets


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Experimental optimization and evaluation

process based on border stability

Creation of border

stability map

Selection of the most

permanent LMA’s

Examination of the

characteristics the remaining (more or less)

unstable LMAs

Selection of those LMAs

that are corresponding

to the definition of

LMAs

Find those outcomes (parameter

sets) in which these

selected LMA’s were appeared


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• Having studied and tested several indicators on national

level, we concluded that solely none of them is capable

of guaranteeing optimization process. The only indicator

suitable for evaluating the delineation was Q modularity

(Newman–Girvan 2004).

• The quest to find optimal parameters was inevitably

accompanied by researchers’ subjectivity, as neither our

own research, nor literature offered alternative solutions

to manufacture objective results..

• It was very useful to study strongest commute links of

units while searching optimal delineation.

• Studying stability of boundaries was also very useful to

evaluate results.

Evaluation of the outcomes


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RELATIVISATION AND

SYMMETRIZATION OF

COMMUTING DATA

SMART MEASURE VS. CURDS MEASURE


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Formula

• SMART measure (1974):

𝑇𝑖𝑗2

𝑇𝑖𝑘𝑘 ∗ 𝑇𝑘𝑗𝑘+

𝑇𝑗𝑖2

𝑇𝑗𝑘∗ 𝑇𝑘𝑖𝑘𝑘

• CURDS measure:

𝑇𝑖𝑗

𝑇𝑖𝑘𝑘

+ 𝑇𝑖𝑗

𝑇𝑘𝑗𝑘

+ 𝑇𝑗𝑖

𝑇𝑗𝑘𝑘

+ 𝑇𝑗𝑖

𝑇𝑘𝑖𝑘


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The 10 000 strongest commuting links

calculated by the Smart measure


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The 10 000 strongest commuting links

calculated by the CURDS measure


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Stability of borders on the bases of 240

different parameter sets (Smart measure)


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Stability of borders on the bases of 240

different parameter sets (CURDS

measure)


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Example for an erroneous outcome

Dominant commuting links of the LAU2 units were grouped

into „Egyek” LMA (MINSZ=1000 MINSC=0,667 TSZ=10000

TSC=0,75)


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EXCLAVES


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Screening of exclaves

As EURO method doesn’t cover contiguity relations, LMAs created by

the algorythm are often not contiguous. In advance, the following

methods were considered feasible to eliminate exclaves:

• „Network contiguity”, where contiguity is based on administrative

boundaries of settlements or on the inhabited area (on road

network) – the latter option is better.

• In cases where settlements in the surrounding area belong to the

same LMA centre, the exclave is joint to that centre.

• In cases where an exclave is located amongst two or more LMAs,

aspects of microregions could be considered (due to public

administration, educational, health care etc. reasons).


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Problem of the spatial contiguity through

the example of Békéscsaba LMA


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LABOUR MARKET AREAS IN

HUNGARY


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Labour Market Areas in Hungary


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Differences between the border of LMAs

and NUTS3 regions


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Dominant commuting links and self-

containment of LMAs, 2011


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Size & self-containment


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RECOMMENDATIONS &

SUMMARY


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Recommendations

Several problems left even after these conclusions, which

have to be resolved prior applying the method in all

countries in the European Union:

• Common principles should be set for testing and

selecting parameters to apply the method in every

country (filter parameter-sets for testing).

• Common evaluating criteria should be set to select the

optimal set of parameters.

• Current general selection and evaluation principles

should be finetuned, as the definition of adjacency,

spatial contiguity is not clear, which was apparent in the

case of Hungary.


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• Objective indicators about the whole delineation should

be selected to support validation process, and to define

how these could be used for evaluation, optimalization.

Methods to find optimal solutions could be tested like

genetic algorithm.

• In association with the latter proposal, clarified methods

would be welcomed for common and expected

evaluation.

• Further tests and finetuning are needed for the EURO

method and for its components, especially for the Smart

measure, as the measure often creates LMAs which are

not in accordance with real commute relations and

results wrong delineations.

Recommendations


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Summary

In general, the EURO method and similar, not pre-

determined spatial delineation methods are deemed

suitable to delineate local labour market areas. However,

the general use of the Smart measure in a common

method is not recommended as its' results are not in line

with real phenomena in areas with special spatial and

commute characteristics. On the bases of these results it is

more than questionable to integrate this measure into

methodological directives. We recommend to study the

current method further, and to refine it prior the

recommendation of its use by the European Commission.


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THANK YOU FOR YOUR KIND ATTENTION!

Kezán András

[email protected]


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Documents

The influence of basic spatial structures and the volume ... · The influence of basic spatial structures and the volume of commuting on the applicability of EURO method Kezán András