The document analyzes the relationship between career instability and technological change using individual-level data from Germany and Britain. It finds that workers in routine occupations experienced more career instability, as measured by more unstable career paths and longer unemployment spells when leaving routine jobs. However, the results differ between countries, with British workers in routine jobs having more unstable careers overall, while German workers experienced longer unemployment spells. The findings provide some empirical validation of models of routine-biased technological change at the individual level but also indicate the relationship is complex and country-specific.

1. Career instability in a context of technological change
Career instability in a context of technological
change
Lucas Augusto van der Velde
University of Warsaw
Faculty of Economic Sciences
Warsaw International Economic Meeting
July 2017
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

2. Career instability in a context of technological change
Introduction
Motivation
Context
Over 5 million jobs expected to be automated worldwide
New topic in economics
Most evidence is on aggregate data (net employment changes)
Models’ assumptions are largely untested
Our contribution
Test models assumptions.
Provide first empirical analysis relating career patterns and
technological change using individual level data.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

3. Career instability in a context of technological change
Theoretical considerations
Routine biased technological change
Premise:
Analyze tasks → units of activity that produce output
Task classification:
Manual Cognitive / interpersonal
Non-Routine Cleaning, repairing Managing, creating
Routine Assembling, packing Bookkeeping, spell checking
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

4. Career instability in a context of technological change
Theoretical considerations
Routine biased technological change
Effects of technological progress
(Autor et al. 2003, 2006, Acemoglu and Autor 2011)
Routine tasks
→ Substitution effects dominate.
→ ↓ demand, ↓ price.
Non-routine cognitive tasks
→ Complementarity
→ ↑ demand, ↑ price.
Non-routine Manual tasks → neither complements nor substitutes
→ ↑ demand, ↑↓ price.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

5. Career instability in a context of technological change
Theoretical considerations
How do workers switch tasks
Main models → Not considered
(e.g. Autor et al. 2003, 2006, Acemoglu and Autor 2011, Goos et al. 2014, Jung
and Mercenier 2014)
Jaimovich and Siu (2012)
→ switching market with lower efficiency
→ Lower efficiency reflects learning skills
→ Non-routine is an absorving state
Carrillo-Tudela and Visschers (2013)
→ Switch leads human capital loses
→ > Pr(unemp) → > Pr(switch)
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

6. Career instability in a context of technological change
Theoretical considerations
Hypotheses
H1 Workers in routine occupations experienced more career
instability.
H2 Workers leaving routine occupations experienced longer
unemployment spells.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

7. Career instability in a context of technological change
Method & data
Data
1. German Socioeconomic Panel (GSOEP)
1984 - today (West Germany)
> 1500 individuals with balanced data (1991-2000)
2. British Household Panel Survey (BHPS)
1991 - 2008 → Discontinued
> 2500 individual with balanced data (1991-2000)
3. Occupation Network (O*NET)
Grouped data from US
Applied to EU before (e.g. Goos et al. 2014)
Routine task intensity = routine tasks − non-routine tasks
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

8. Career instability in a context of technological change
Method & data
Hypothesis 1: Measuring career instability
Imagine two workers with careers:
W1 E - U - E - E
W2 U - E - E - E
How to make them equal?
1. Substitution → W2: E - U - E - E
2. Insert and Delete (INDEL) → W2: E - U - E - E - ¡E
Minimum number of steps ⇒ Optimal matching
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

9. Career instability in a context of technological change
Method & data
Optimal matching
Definitions Proposals
Career elements
Quintiles of RTI + NE
Labor market status (FT PT SE NE)
Substitution costs
One
Differences in RTI + one to/from NE
Indel costs Half of substitution costs
Reference sequence Continuous employment in same element
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

10. Career instability in a context of technological change
Method & data
Method
Specification
yt,t+1 = β0 + β1RTIt + controls + t
where
yt,t+1 is a measure of instability.
β1 is coefficient of interest → Hypothesis: β1 > 0.
Other controls: year of birth, gender, educational attainment, city.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

11. Career instability in a context of technological change
Results
Sample careers: Germany
0
100
200
300
Individuals
1081 1105 1129 1153 1177 1201
Months since 01/1900
RTI Quintiles 1 2 3 4 5 NE
Group 1: Most Non Routine
0
100
200
300
400
Individuals
1081 1105 1129 1153 1177 1201
Months since 01/1900
RTI Quintiles 1 2 3 4 5 NE
Group 5: Most Routine
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

12. Career instability in a context of technological change
Results
Sample careers: Great Britain
0
100
200
300
400
Individuals
1081 1105 1129 1153 1177 1201
Months since 01/1900
RTI Quintiles 1 2 3 4 5 NE
Group 1: Most non-routine
0
100
200
300
400
Individuals
1081 1105 1129 1153 1177 1201
Months since 01/1900
RTI Quintiles 1 2 3 4 5 NE
Group 5: Most routine
Common careers
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

13. Career instability in a context of technological change
Results
Measures of instability
Group 1 2 3 4 5 6 (NE)
Germany
OM1 - unit cost 0.20 0.32 0.39 0.35 0.33 0.64 ***
OM2 - RTI costs 0.13 0.16 0.20 0.18 0.22 0.64 ***
Great Britain
OM1 - unit cost 0.28 0.36 0.46 0.42 0.39 0.54 ***
OM2 - RTI costs 0.22 0.19 0.36 0.25 0.29 0.54 ***
Alternative measures
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

14. Career instability in a context of technological change
Results
Results
Specification: yt,t+1 = β0 + β1RTIt + controls + t
Germany Great Britain
Costs Unit RTI Unit RTI
RTI 0.01 0.01 0.03*** 0.02**
(0.02) -0.01 (0.01) (0.01)
R2
0.04 0.06 0.03 0.03
N 1593 1593 1985 1985
Results
Follow our expectations
Resilient to robustness checks
Statistically significant..., but economically relevant?
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

15. Career instability in a context of technological change
Robustness checks
Non-linearities
Quintil Germany Great Britain
OM-Unit OM-RTI OM-Unit OM-RTI
1 Baselevel
2 0.10* 0.01 0.07** -0.03
(0.05) (0.03) (0.03) (0.02)
3 0.13*** 0.03 0.16*** 0.13***
(0.04) (0.03) (0.04) (0.02)
4 0.10** 0.02 0.12*** 0.02
(0.05) (0.03) (0.03) (0.02)
5 0.07 0.05 0.09** 0.06**
(0.05) (0.03) (0.04) (0.03)
R2
0.05 0.06 0.05 0.08
N 1593 1593 1985 1985
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

16. Career instability in a context of technological change
Robustness checks
Hypotheses
H1 Workers in routine occupations experienced more career instability.
H2 Workers leaving routine occupations experienced longer
unemployment spells. H2
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

17. Career instability in a context of technological change
Conclusions
Conclusions
Weak link between career patterns and RTI
Link is country specific
1. Longer unemployment spells in Germany.
2. More unstable careers in Great Britain.
How to reconcile empirical results and theory
1. Embedded technological progress.
2. Link human capital loss to differences in task content.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

18. Career instability in a context of technological change
Conclusions
Thank you for your attention
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

19. Career instability in a context of technological change
Bibliography
Bibliography I
Acemoglu, D. and Autor, D.: 2011, Skills, tasks and technologies: Implications for
employment and earnings, Handbook of Labor Economics 4, 1043–1171.
Autor, D., Katz, L. F. and Kearney, M. S.: 2006, The polarization of the US labor
market, American Economic Review 96(2), 189–194.
Autor, D., Levy, F. and Murnane, R. J.: 2003, The skill content of recent
technological change: An empirical exploration, Quarterly Journal of Economics
118(4), 1279–1333.
Carrillo-Tudela, C. and Visschers, L.: 2013, Unemployment and endogenous
reallocation over the business cycle, Discussion Papers 7124, Institute for Study of
Labor (IZA).
Goos, M., Manning, A. and Salomons, A.: 2014, Explaining job polarization:
Routine-biased technological change and offshoring, American Economic Review
104(8), 2509–2526.
Jaimovich, N. and Siu, H. E.: 2012, The trend is the cycle: Job polarization and
jobless recoveries, Working paper 18 334, National Bureau of Economic Research.
Jung, J. and Mercenier, J.: 2014, Routinization-biased technical change and
globalization: Understanding labor market polarization, Economic Inquiry
52(4), 1446–1465.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

20. Career instability in a context of technological change
Bibliography
Common career patterns
Germany
Group 1 Group 5
Sequence Frequency Sequence Frequency
1 46.44 5 35.01
161 8.81 56 12.47
16 5.76 545 5.28
14 2.71 565 4.08
141 2.37 53 3.12
Great Britain
Group 1 Group 5
Sequence Frequency Sequence Frequency
1 28.47 5 19.86
16 5.32 56 6.31
161 4.4 565 4.21
121 3.94 54 3.04
1616 2.08 545 2.34
Back
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

21. Career instability in a context of technological change
Bibliography
Alternative measures of instability
Group 1 2 3 4 5 6 (NE)
Germany
# Elements 1.76 2.05 2.22 2.20 2.01 2.51 ***
# Jobs 3.06 3.20 3.37 3.64 3.41 3.76 ***
Great Britain
# Elements 2.31 2.42 2.50 2.61 2.51 2.94 ***
# Jobs 4.85 4.67 4.87 4.96 4.80 5.05 ***
Back
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

22. Career instability in a context of technological change
Bibliography
Method
Specification
timeNE,t = f (RTIt−1, controls)
where
timeNE,i → lenght of non-employment spell i starting in t.
f (·) → log-logistic hazard rate.
RTIt−1 → RTI last occupation → H0: βRTI > 0.
other controls: year of birth, educational level, gender and spell
number.
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

23. Career instability in a context of technological change
Bibliography
Results
Specification: timeNE,t = f (RTIt−1, controls)
Germany Great Britain
NE U I NE U I
RTIt−1 0.09*** 0.10*** 0.06 0.05 -0.06 0.18***
(0.03) (0.03) (0.04) (0.04) (0.04) (0.05)
LL -5875 -4610 -766.1 -4179 -1507 -2198
AIC 11775 9246 1552 8390 3047 4425
Results
Follow our expectations
Resilient to robustness checks
Statistically significant..., but economically relevant?
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change

24. Career instability in a context of technological change
Bibliography
Results: predicted survival curves
Specification: timeNE,t = f (RTIt−1, controls)
0
.2
.4
.6
.8
1
Survival
0 10 20 30 40 50
Months in non−employment
RTI Quintile: 1 2 5
Predicted survival curves
Germany
.2
.4
.6
.8
1
Survival
0 10 20 30 40 50
Months in non−employment
RTI Quintile: 1 2 3 4 5
Predicted survival curves
Great Britain
Lucas van der Velde University of Warsaw Faculty of Economic Sciences
Career instability in a context of technological change