CEET1 Determinants of job separation and occupational mobility Chandra Shah MONASH UNIVERSITY - ACER...
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CEET 1 Determinants of job separation and occupational mobility Chandra Shah MONASH UNIVERSITY - ACER CENTRE FOR THE ECONOMICS OF EDUCATION AND TRAINING 13 th Annual National CEET Conference Thursday, 30 October 2009
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Transcript of CEET1 Determinants of job separation and occupational mobility Chandra Shah MONASH UNIVERSITY - ACER...
CEET 1
Determinants of job separation and occupational mobility
Chandra Shah
MONASH UNIVERSITY - ACERCENTRE FOR THE ECONOMICS OF EDUCATION AND
TRAINING
13th Annual National CEET ConferenceThursday, 30 October 2009
CEET 2
Motivation
1. Job turnover is an important aspect of a dynamic labour market. In an open economy it facilitates an optimal allocation of labour
2. The consequences of turnover can be large for the individual, for the firm and the wider economy
CEET 3
Individual
1. Job change has the potential to increase earnings and earnings growth, particularly for young people
2. Joblessness after job separation has the potential to reduce earnings and skills development and increases the risk of unemployment ‘recidivism’ (including risk to households)
CEET 4
Enterprise
1. Turnover allows for optimal allocation of labour and assists with bringing new ideas and new ways of doing business into the firm
2. Firms with high turnover generally invest less in training and have less worker-to-worker transfer of firm-specific skills and knowledge
CEET 5
Economy
1. Turnover can help reduce the imbalance in the demand and supply of skilled labour
2. High rates of turnover has the potential to reduce social cohesion and community capacity building
CEET 6
Theoretical models on turnover
1. Human capital
2. Job matching
3. Job search
CEET 7
Research questions
1. What are the significant demographic, human capital and labour market factors affecting the job separation process of individuals?
2. Conditional on job separation, what are the factors affecting a person’s job-to-job (differentiated by occupation) and job-to-joblessness (unemployment and exit from the labour force) transitions?
CEET 8
Main results
The significant factors affecting turnover behaviour are:1. gender2. age3. marital status4. qualifications5. hours of work6. reason for job separation7. tenure in previous job8. industry and occupation
CEET 9
Turnover by sex, persons who worked sometime in year to February 2002, Australia (%)
Stayers MoversNew
entrants All
Males 73 21 6 100
Females 70 22 8 100
All 72 21 7 100
CEET 10
Turnover by age, persons who worked sometime in year to February 2002, Australia (%)
Stayers MoversNew
entrants All
15-19 43 32 25 100
20-24 57 33 10 100
25-34 68 26 6 100
35-44 77 18 5 100
45-54 82 14 4 100
55-69 84 14 3 100
All 72 21 7 100
Turnover by occupation, persons who worked sometime in year to February 2002, Australia (%)
Occupation Stayers MoversNew
entrants All
Managers 84 15 1 100
Professionals 78 18 4 100
Associate professionals 77 19 5 100
Trades 77 18 5 100
Adv clerical & service 79 18 3 100
Inter. clerical sales & service 67 25 8 100
Inter. prod & transport 70 23 7 100
Elem. clerical sales & service 59 27 14 100
Labourers 59 29 12 100
All 72 21 7 100
CEET 11
Percentage job losers, movers in year to February 2002, Australia
Occupation of last job Males Females Persons
Managers 32 15 27
Professionals 35 31 33
Associate professionals 28 22 25
Trades 49 31 47
Adv clerical & service 39 30 31
Inter. clerical sales & service 35 33 33
Inter. prod & transport 48 43 47
Elem. clerical sales & service 37 32 34
Labourers 55 57 56
All 42 33 38
CEET 12
Labour market destinations, movers in year to February 2002, Australia
Job-to-jobJob-to-
joblessness
Occupation of last job Same Horiz Down Up UnempOut of
LF All
Managers 49 3 24 0 10 14 100
Professionals 53 6 7 3 11 20 100
Associate professionals 45 5 16 7 10 18 100
Trades 44 4 14 4 17 17 100
Adv clerical & service 38 1 13 9 7 32 100
Inter. clerical sales & service 31 9 10 12 14 23 100
Inter. prod & transport 28 15 11 12 18 16 100
Elem. clerical sales & service 23 3 4 22 20 28 100
Labourers 16 9 0 22 27 26 100
All 35 7 9 11 16 22 100CEET 13
CEET 14
Results from job separation
Immigrant status
Probability of job separation is 20% (13 %) higher for a male
from MESC (non-MESC) who arrived after 1997 than for an
Australian-born
Probability of job separation is 22% (14 %) higher for a female
from MESC (non-MESC) who arrived after 1997 than for an
Australian-born
CEET 15
Results from job separation
Qualifications
No significant difference in the probability of job separation
between males with qualifications and without qualifications
Probability of job separation significantly higher for females
with qualifications compared to those without (3-6 percent)
CEET 16
Results from job separation
Marital status
Only significant for women but the size of the effect is relatively
small
Hours of work
Probability of job separation 11% higher for males working part-
time than full-time
Probability of job separation 4% higher for females working
part-time than full-time
Occupation
Significant effect for both males and females
Probability of job separation is generally lower from higher
skilled occupations
Predicted probability of job separation for ‘typical’ workers
0.0
0.1
0.2
0.3
0.4
0.5
15 20 25 30 35 40 45 50 55 60 65
Pro
ba
bili
ty
Age
Male-FT Male-PT Female-FT Female-PT
CEET 18
Results from occupational mobility
Immigrant status
MESC immigrants’ occupational mobility is generally the same
as that of Australian-born
Non-MESC males are more likely to become unemployed
Non-MESC females are more likely to leave the labour force but
only those who arrived prior to 1997 are more likely to become
unemployed
CEET 19
Results from occupational mobility
Marital status
Married men are more likely to stay in same occupation and they
are less likely to become unemployed than unmarried men
Married women are less likely to become unemployed but they
are more likely to leave the labour force than unmarried women
CEET 20
Results from occupational mobility
Metro/non-metro
Both men and women in metro areas are more likely to stay in
the same occupation than those in non-metro areas
Males in non-metro areas more likely to change to another
occupation in the same major group
Hours of work
All part-time workers are less likely to make job-to-job transition
than full-time workers (males 18% and females 14% )
Male part-time workers are less likely to become unemployed
but more likely to leave the labour force
Female part-time workers more likely to leave the labour force
CEET 21
Results from occupational mobility
Qualifications
In general, persons holding higher level qualifications are more
likely to make job-to-job transitions than those who have no
qualifications
While men with qualifications are less likely to become
unemployed, women with qualifications are less likely to leave
the labour force
Certificate I/II have no significant effect on occupational
mobility, except persons with qualifications at this level are about
7% less likely to leave the labour force than those who have no
qualifications
CEET 22
Results from occupational mobility
Tenure
For men, short tenure in the previous job is generally associated
with a higher probability of unemployment but a lower
probability of leaving the labour force
For women, short tenure is associated with a higher probability
of staying in the same occupation and a lower probability of
leaving the labour force
CEET 23
Results from occupational mobility
Reason for job separation
Job losers are less likely to find employment in the same
occupation than job leavers
They are also more likely to be unemployed and leave the labour
force
CEET 24
Results from occupational mobility
Reason for job separation
Job losers are less likely to find employment in the same
occupation than job leavers
They are also more likely to be unemployed and leave the labour
force
Predicted probabilities of occupational mobility
No change Horizontal Down Up Unemp Out of LF
Male 0.38 0.07 0.11 0.12 0.17 0.14
Job leaver, FT 0.56 0.06 0.10 0.12 0.09 0.08
Job loser, FT 0.25 0.06 0.12 0.07 0.34 0.17
Job leaver, PT 0.31 0.09 0.10 0.25 0.08 0.17
Job loser, PT 0.12 0.08 0.10 0.13 0.26 0.31
Female 0.34 0.08 0.10 0.10 0.14 0.25
Job leaver, FT 0.49 0.09 0.10 0.09 0.09 0.16
Job loser, FT 0.23 0.07 0.10 0.09 0.26 0.26
Job leaver, PT 0.32 0.08 0.09 0.12 0.08 0.32
Job loser, PT 0.13 0.05 0.08 0.10 0.20 0.44
CEET 25
Predicted probabilities of transition to same occupation for ‘typical’ male workers
CEET 26
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
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49
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61
62
63
64
65
66
67
68
69
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of transition to same occupation for four typical female workers
CEET 27
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
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39
40
41
42
43
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45
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49
50
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53
54
55
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57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.10
0.20
0.30
0.40
0.50
0.60
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of transition unemployment for ‘typical’ male workers
CEET 28
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of exit from labour force for ‘typical’ male workers
CEET 29
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
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49
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51
52
53
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57
58
59
60
61
62
63
64
65
66
67
68
69
0.000.100.200.300.400.500.600.700.800.901.00
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of exit from labour force for ‘typical’ female workers
CEET 30
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.000.100.200.300.400.500.600.700.800.901.00
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
CEET 31
Concluding comments
• Qualifications are significant in explaining job separation for
women but not men• Qualifications are associated with a lower probability of
unemployment for men and lower probability of exit from the
labour force for women• Qualifications have the potential to reduce joblessness
‘recidivism’, ‘scarring’ and skills atrophy• Immigrants have different patterns of job turnover depending on
whether they came from a MESC or not but also their time since
arrival
Predicted probabilities of horizontal change for ‘typical’ male workers
CEET 32
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
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40
41
42
43
44
45
46
47
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49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.02
0.04
0.06
0.08
0.10
0.12
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of horizontal change for ‘typical’ female workers
CEET 33
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
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49
50
51
52
53
54
55
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57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.02
0.04
0.06
0.08
0.10
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of downward change for ‘typical’ male workers
CEET 34
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
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38
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49
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53
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55
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63
64
65
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67
68
69
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of downward change for ‘typical’ female workers
CEET 35
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
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39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.02
0.04
0.06
0.08
0.10
0.12
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of upward change for ‘typical’ male workers
CEET 36
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.05
0.10
0.15
0.20
0.25
0.30
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
Predicted probabilities of upward change for ‘typical’ female workers
CEET 37
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
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39
40
41
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43
44
45
46
47
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49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
FT Job leaver PT Job leaver FT Job loser PT Job loser
Age
Pro
bab
ilit
y
