Forecasting
of long-term unemployment
at the individual level
Tomáš Soukup
RILSA
Czech Republic
[email protected]
Content
• Introduction
• Theoretical approach
(Job Search Theory)
• Data
• Results
• Future developement
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2
Introduction
• Macro versus micro approach
• Use of forecasting at the individual level
– defining vulnerable groups at the LM
– forecasting the length of unemployment
•
•
•
•
segmentation of claimants
areas of services at labour offices (zones)
precautions in social policy
Predicting the effects of ALMP
• Foreign experience
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Theoretical approach 1
• Job Search Theory
H = f (V, c U)
H–
final result of the job search process, matching demand and
supply in the labour market
V–
U–
c –
number of Vacancies
number of Unemployed
job search efficiency on the part of the claimant
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Theoretical approach 2
The success of the job search is principally
affected by:
•
•
•
The situation in the labour market
The availability of vacancies and employer
discrimination (Queuing Theory, Concept of
Human Capital, Discrimination, Segmentation
Theories)
Job seeker motivation (Nominal Flexibility, Basic
incentives for work, Concept of Feeling Efficacy)
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Data and method
•
•
•
•
Need for continuous data
Panel survey 2000 - 2001, 2 waves
N=759
Binary logistic regression
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Output variable
• “Found a job in 6 months”
• 1 found a job
• 0 didn’t find a job.
• The probability of finding a job within the next
6 months was predicted.
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Main input variables
• Subjective assessment of
own chances
• Total duration of past
unemployment
• Plans concerning exit
from the labour market
• Number of claimants per
one vacancy (in region
and education)
• Nominal flexibility
• Woman with children up
to 7 years
• Willingness to change
area of work
• Promise of a new job
• School leaver
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Results 1
Nagelkeke
R-square
Correctly
predicted cases
-
54%
General model
0.367
73%
Model with variables in the
PES database
0.192
65%
Model with variables in the
PES database
+ 5 interview questions
0.331
72%
Model
Model with constant only
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Results 2
Prediction versus reality
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
010
%
11
%
-2
0%
21
%
-3
0%
31
%
-4
0%
41
%
-5
0%
51
%
-6
0%
61
%
-7
0%
71
%
-8
0%
81
%
-9
0%
90
%
-1
00
%
Really have found a job
100%
Predicted probability of finding a job
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Results 3
Predicted probability
of finding a job
Job
YES
Job
NO
Total
N
0-30%
13%
87%
100%
266
31%-70%
52%
48%
100%
303
71%-100%
83%
17%
100%
189
Total
46%
54%
100%
758
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Future development
• Analysis of register data
• Prediction of the effects of ALMP
• Scheme for practical use at labour offices
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Thank you very much for your attention
Tomas Soukup
RILSA, CZ
[email protected]
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