Career instability in a context of technological change
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The document analyzes career instability in the context of technological change, highlighting the expected automation of over 5 million jobs worldwide. It seeks to empirically test assumptions about career patterns and job transitions, particularly focusing on workers in routine occupations versus non-routine roles. Findings suggest that routine occupational workers experience more career instability and longer unemployment spells, with notable differences in the impacts observed in Germany and Great Britain.
Career instability in a context of technological change
- 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 March 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 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 Data 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
- 9. Career instability in a context of technological change Hypothesis 1 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
- 10. Career instability in a context of technological change Hypothesis 1 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
- 11. Career instability in a context of technological change Hypothesis 1 Sample career 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 - Germany 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 - Great Britain 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 Hypothesis 1 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
- 13. Career instability in a context of technological change Hypothesis 1 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
- 14. Career instability in a context of technological change Hypothesis 1 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
- 15. Career instability in a context of technological change Hypothesis 1 Method Specification timeNE,t = f (RTIt−1, controls) where timeNE,i → lenght of non-employment spell i. 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
- 16. Career instability in a context of technological change Hypothesis 1 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
- 17. Career instability in a context of technological change Hypothesis 1 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 (a) 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 (b) Great Britain 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 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
- 19. 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
- 20. 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