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+ A Markov system analysis application on labour market dynamics: The case of Greece This project has received funding from the European Unions Horizon 2020 research and innovation programme Maria Symeonaki under grant agreement No

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A Markov system analysis application on labour market dynamics: The case of Greece

Maria Symeonaki Glykeria Stamatopoulou IWPLMS, 22-24 June, Athens, Greece

Panteion University of Social and Political Sciences

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 649395

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+ The structure of the presentation

n Motivation – Objectives n Data n Methodology n Results – Conclusions n Future work

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IWPLMS, 22-24 June, Athens, Greece

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+ Motivation – Objectives

n To examine:

n the flow data and transition rates between

labour market states on a micro-level, i.e. the labour market outcomes of the individuals

n Using:

n quantitative analysis and Markov system

theory for Greece*

*Source: Hellenic Statistical Authority

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IWPLMS, 22-24 June, Athens, Greece

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+ Data

n The EU LFS is a large household sample survey

providing results on labour participation of people aged 15 and over as well as on persons outside the labour force

n All definitions apply to persons aged 15 years and

  • ver living in private households

n Persons carrying out obligatory military or

community service are not included in the target group of the survey, as is also the case for persons in institutions/collective households

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EU LFS

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IWPLMS, 22-24 June, Athens, Greece

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+ Data

EU LFS

n Information about the labour market transitions in

Greece from 2006 to 2013.

n To study and compare the distribution of transition

probabilities from employment, unemployment and inactiveness and vice versa

n The current labour status (MAINSTAT) and the

situation one year before the survey (WSTAT1Y) are the variables that will be used in the present analysis

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IWPLMS, 22-24 June, Athens, Greece

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Unemployment rates (total population) 15-74 by country (%), 2013

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Country Year: 2013 Country Year: 2013

Belgium 8.4 Luxembourg 5.9 Bulgaria 13.0 Hungary 10.2 Czech Republic 7.0 Malta 6.4 Denmark 7.0 Netherlands 7.3 Germany 5.2 Austria 4.9 Estonia 8.6 Poland 10.3 Ireland 13.1 Portugal 16.4 Greece 27.5 Romania 7.1 Spain 26.1 Slovenia 10.1 France 10.3 Slovakia 14.2 Croatia 17.3 Finland 8.2 Italy 12.2 Sweden 8.0 Cyprus 15.9 United Kingdom 7.6 Latvia 11.9 Iceland 5.4 Lithuania 11.8 Norway 3.5

Source: Eurostat, Labour Force Survey (lfsa_urgan), http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_urgan&lang=en

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+

Youth unemployment rates, 15-24 by country (%), 2013

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Country Year: 2013 Country Year: 2013

Belgium 23.7 Luxembourg 16.9 Bulgaria 28.4 Hungary 26.6 Czech Republic 18.9 Malta 13.0 Denmark 13.0 Netherlands 13.2 Germany 7.8 Austria 9.2 Estonia 18.7 Poland 27.3 Ireland 26.8 Portugal 38.1 Greece 58.3 Romania 23.7 Spain 55.5 Slovenia 21.6 France 24.8 Slovakia 33.7 Croatia 50.0 Finland 19.9 Italy 40.0 Sweden 23.6 Cyprus 38.9 United Kingdom 20.7 Latvia 23.2 Iceland 10.7 Lithuania 21.9 Norway 9.1

Source: Eurostat, Labour Force Survey (lfsa_urgan), http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_urgan&lang=en

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+ Unemployment rates (2013)

8 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Belgium Bulgaria Czech Republic Denmark Germany Estonia Ireland Greece Spain France Croatia Italy Cyprus Latvia Lithuania Luxembourg Hungary Malta Netherlands Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden United Kingdom Iceland Norway Total UR Youth UR

IWPLMS, 22-24 June, Athens, Greece

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IWPLMS, 22-24 June, Athens, Greece

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IWPLMS, 22-24 June, Athens, Greece

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Basic parameters of a non homogeneous Markov system

1 2 3 p t

13( )

p t

33( )

p t

22( )

p t

12( )

p t

11( )

p t

21( )

p t

31( )

p t

32( )

p t

23( )

p t

k 1 1 ,

( )

+

p t

  • 1( )

p t

k 2 1 ,

( )

+

p t

  • 3( )

p t

  • 2( )

p t

k 3 1 ,

( )

+

IWPLMS, 22-24 June, Athens, Greece

P(t)

{ }t=0

∞

po(t)

{ }t=0

∞

pk+1(t)

{ }t=0

∞

{ }

Q( ) t

t = ∞

T t ( )

[ ]

N( ) ( ), ( ), , ( ) t N t N t N t

k

=

1 2

…

ΔT t T t T t ( ) ( ) ( ) = − −1

N N Q p ( ) ( ) ( ) ( ) ( ) t t t T t t

  • +

= + 1 Δ

Transition diagram of a Markov system with three states

k = 3

S = 1,2,...,k

{ }

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+ States in LFS

1.

Carries out a job or profession, including unpaid work for a family business or holding, including an apprenticeship or paid traineeship, etc

2.

Unemployed

3.

Pupil, student, further training, unpaid work experience

4.

In retirement or early retirement or has given up business

5.

Permanently disabled

6.

In compulsory military service

7.

Fulfilling domestic tasks

8.

Other inactive person

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IWPLMS, 22-24 June, Athens, Greece

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+ States in NHMS and possible transitions

1: Employment (1) 1 → 1 1 → 2 1 → 3 2: Unemployment (2) 2 → 1 2 → 2 2 → 3 3: Inactivity (5, 6,7,8) 3 → 1 3 → 2 3 → 3

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IWPLMS, 22-24 June, Athens, Greece

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+ Basic parameters 2006 - 2013

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Q(t) = q11(t) q12(t) q13(t) q21(t) q22(t) q23(t) q31(t) q32(t) q33(t) ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥ ⎥ P(t) = p11(t) p12(t) p13(t) p21(t) p22(t) p23(t) p31(t) p32(t) p33(t) ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥ ⎥

po(t) = po1(t), po2(t), po3(t) ⎡ ⎣ ⎤ ⎦

pk+1(t) = I − P(t)

( )⋅ ′

1 = pk+1,1(t), pk+2,2(t), pk+1,3(t) ⎡ ⎣ ⎤ ⎦

qij(t) = pij(t) + pi,k+1(t)poj(t)

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+ Mobility indices

M(PS) = 1 n −1 ⎛ ⎝ ⎜ ⎞ ⎠ ⎟ (n − tr(Q))

n Bartholomew’s index of

mobility

n Shorrocks’ index of mobility n Immobility index n Prais – Bibby mobility index

IM = tr(Q) n ⎛ ⎝ ⎜ ⎞ ⎠ ⎟

M B = 1 k qij i − j

j=1 k

∑

i=1 k

∑

MT =1− tr Q

( )

k

IWPLMS, 22-24 June, Athens, Greece

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+ Results 2006, 2007

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Greece 2006 Greece 2007

po(2007) = 0.367 0.357 0.276 ⎡ ⎣ ⎤ ⎦ Q(2007) = 0.957 0.027 0.016 0.234 0.726 0.040 0.024 0.020 0.956 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

N = 257,228

IWPLMS, 22-24 June, Athens, Greece

N = 262,884

po(2006) = 0.395 0.372 0.233 ⎡ ⎣ ⎤ ⎦ Q(2006) = 0.955 0.029 0.016 0.237 0.722 0.041 0.026 0.023 0.951 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

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+ Results 2008, 2009

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Greece 2008 Greece 2009

po(2008) = 0.343 0.352 0.305 ⎡ ⎣ ⎤ ⎦ Q(2008) = 0.957 0.026 0.017 0.248 0.709 0.043 0.023 0.021 0.956 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

N = 255,701

N = 258,428

po(2009) = 0.309 0.418 0.273 ⎡ ⎣ ⎤ ⎦ Q(2009) = 0.944 0.040 0.016 0.208 0.748 0.044 0.024 0.029 0.947 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

IWPLMS, 22-24 June, Athens, Greece

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+ Results 2010, 2011

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Greece 2010 Greece 2011

N = 262,172

po(2010) = 0.257 0.431 0.312 ⎡ ⎣ ⎤ ⎦ Q(2010) = 0.934 0.050 0.016 0.171 0.787 0.042 0.022 0.034 0.944 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

N = 236,551

Q(2011) = 0.917 0.067 0.016 0.117 0.848 0.035 0.015 0.034 0.951 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥ po(2011) = 0.195 0.537 0.268 ⎡ ⎣ ⎤ ⎦

IWPLMS, 22-24 June, Athens, Greece

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+ Results 2012, 2013

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Greece 2012 Greece 2013

N = 212,307

po(2012) = 0.154 0.555 0.291 ⎡ ⎣ ⎤ ⎦

Q(2012) = 0.903 0.078 0.019 0.092 0.876 0.032 0.012 0.045 0.943 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

N = 215,244

po(2013) = 0.172 0.552 0.276 ⎡ ⎣ ⎤ ⎦

Q(2013) = 0.904 0.076 0.020 0.100 0.872 0.028 0.013 0.041 0.946 ⎡ ⎣ ⎢ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ ⎥

IWPLMS, 22-24 June, Athens, Greece

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+ Mobility and Immobility Indices

Greece M(PS) IM M(B) M(T) 2006 0.186 0.876 0.138 0.124 2007 0.180 0.879 0.133 0.120 2008 0.189 0.874 0.139 0.126 2009 0.181 0.879 0.134 0.120 2010 0.168 0.888 0.124 0.111 2011 0.142 0.905 0.105 0.095 2012 0.139 0.907 0.103 0.093 2013 0.098 0.907 0.104 0.092

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IWPLMS, 22-24 June, Athens, Greece

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+ Mobility indices 2006 - 2013

0.05 0.1 0.15 0.2 2006 2007 2008 2009 2010 2011 2012 2013 M(PS) M(B) M(T)

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IWPLMS, 22-24 June, Athens, Greece

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+ Immobility index 2006 - 2013

0.84 0.86 0.88 0.9 0.92 2006 2007 2008 2009 2010 2011 2012 2013 IM

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IWPLMS, 22-24 June, Athens, Greece

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+ Conclusions

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Transition probabilities EèE 2006 0.955 2007 0.957 2008 0.957 2009 0.944 2010 0.934 2011 0.917 2012 0.903 2013 0.904

IWPLMS, 22-24 June, Athens, Greece

Input probabilities UèU 0.722 0.726 0.709 0.748 0.787 0.848 0.876 0.872 EèU 0.029 0.027 0.026 0.040 0.050 0.067 0.078 0.076 èE 2006 0.395 2007 0.367 2008 0.343 2009 0.309 2010 0.257 2011 0.195 2012 0.154 2013 0.172 èU 0.372 0.357 0.352 0.418 0.431 0.537 0.555 0.552 èIA 0.233 0.276 0.305 0.273 0.312 0.268 0.291 0.276

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+ Future work

n First, we will study the asymptotic

behaviour of the system

n The same methodology will be

applied for all European countries (starting with the Southern European countries)

n We will also study gender and age

differences

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IWPLMS, 22-24 June, Athens, Greece