The robots are coming!? Can the threat of automation drive public support for basic income?

BIKN9th November 2018

Joe Chrisp & Dr. Luke MartinelliIPR, University of Bath

DRAFT – PLEASE DO NOT QUOTE OR CITE WITHOUT PERMISSION FROM THE AUTHORS. 저자의 허락 없이 발표문의 자료/결과를 인용할 수 없습니다.

Why automation and basic income?

•Moving beyond these teleological accounts: what are the precise mechanisms by which automation might lead to basic income?oElite-driven reform (fear of populist pitchforks)oPolitical economy approach: potential political constituencies of basic income?

Why automation and basic income?

Welfare preferences

•Redistribution and insurance oIncome and risk

•Labour market insiders and outsiders (Rueda, 2005)

oStatus vs. risk (Rovny & Rovny 2017)

•Risk from automation: routine-task intensity (Thewissen & Rueda 2016)

•Automation short-hand for “ever increasing computing power, Big Data, the penetration of the Internet, Artificial Intelligence (AI), the Internet-of-Things, and online platforms” (OECD 2016)

•Contended risks:oRoutine jobs (vis-à-vis cognitive/manual jobs) under threat (Goos & Manning 2007; Autor and Dorn, 2013)

Role of automation in labour market change

Source: Thewissen & Rueda (2016)

•Contended outcomes:1. Technological unemployment (Frey & Osborne

2013; Arntz et al. 2016)

2. Job/wage polarisation (Goos & Manning 2007; Oesch 2013)

3. Proliferation of non-standard employment (Standing, 2011; Degryse 2016)

•Same general phenomenon? Precarious employment status? Weakening bargaining power of labour?

Role of automation in labour market change

The promise of basic income vis-à-vis conventional social security systems:Removing burden on (unemployed) recipients of labour market conditionality – stigma, bureaucratic effort; sanctionsExtending provision for the alleviation of in-work povertyGuaranteeing entitlement to those in non-standard employment – without need for a contribution record or real-time reporting

Why basic income?No jobs -> basic income

• Insurance mechanism/POUM hypothesis (Benabou et al.)

•High-skilled outsiders (Häusermann et al. 2015; Martinelli & Pearce 2018)

•Conditionality and authoritarianism (Achterberg et al. 2017)

The role of education

H1: Routine-task intensive workers will support basic income more than non-routine workers

H2: Individuals with a precarious employment status will support basic income more those in permanent jobs

H3: Effect of status > effect of risk

H4: Interaction between education and risk & status

Hypotheses

European Social Survey (ESS) Wave 821 EU/EEA member states (exclude Israel and Russia)

Excluded non-working age adults

Bivariate analysis at European- and country-level

Population and post-stratification weights

Multivariate probit regression models

Country dummies and clustered standard errors

Robustness checks

Data & dependent variable

Independent variables

Risk: routine-task intensity (Thewissen & Rueda 2016)

Status: working poor (permanent), unemployed, temporary, solo-self-employedSocio-demographic controls: age, gender, education, post-industrial occupational class (Oesch 2006; Kitschelt & Rehm 2006)

Other controls:Subjective povertyPolitical preferences: redistribution, welfare chauvinism

Results

    (1) (2) (3) (4)VARIABLES           Routine task intensity 0.026*** 0.033** 0.034*** 0.028**

(0.005) (0.015) (0.013) (0.011)Highest education (ISCED) level -0.021** -0.014 -0.014

(0.011) (0.010) (0.011)Gender -0.074* -0.083* -0.106***

(0.043) (0.042) (0.040)Age -0.006*** -0.006*** -0.006***

(0.001) (0.001) (0.001)Post-industrial class Mixed service functionaries 0.015 -0.008 -0.015(Ref: Capital accumulators) (0.062) (0.063) (0.065)

Blue collar 0.107 0.077 0.038(0.075) (0.080) (0.077)

Socio-cultural professionals 0.256*** 0.231*** 0.182**(0.076) (0.078) (0.075)

Low service functionaries 0.160** 0.132 0.091(0.078) (0.082) (0.082)

Subjective poverty 0.174*** 0.148***(0.037) (0.033)

Redistribution -0.172***(0.025)

Welfare chauvinism -0.092***(0.022)

Constant -0.033*** 0.318*** 0.562*** 1.272***(0.000) (0.084) (0.081) (0.116)

Observations 21,591 21,528 19,806 19,214Country dummies YES YES YES YESPseudo R-squared 0.0127 0.0197 0.0221 0.0383No. of countries   21 21 20 20Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

    (1) (2) (3) (4)VARIABLESEmployment status Working poor (Permanent) 0.155** 0.133** 0.110* 0.097(Ref: Permanent/Employers) (0.064) (0.066) (0.065) (0.060)

Unemployed 0.319*** 0.267** 0.201* 0.199*(0.102) (0.114) (0.112) (0.115)

Temporary contract 0.125*** 0.066*** 0.038 0.024(0.021) (0.025) (0.030) (0.034)

Solo self-employed 0.061 0.118 0.103 0.115(0.082) (0.095) (0.098) (0.099)

Inactive 0.179*** 0.104** 0.093* 0.084*(0.036) (0.049) (0.053) (0.047)

Highest education (ISCED) level -0.015* -0.009 -0.011(0.008) (0.008) (0.009)

Gender -0.041 -0.052 -0.079**(0.033) (0.032) (0.032)

Age -0.006*** -0.006*** -0.006***(0.001) (0.001) (0.001)

Post-industrial class Mixed service functionaries 0.021 0.007 -0.009(Ref: Capital accumulators) (0.049) (0.050) (0.053)

Blue collar 0.116* 0.093 0.047(0.060) (0.066) (0.065)

Socio-cultural professionals 0.204*** 0.198*** 0.157***(0.057) (0.059) (0.056)

Low service functionaries 0.132** 0.115* 0.073(0.062) (0.067) (0.064)

Never worked 0.162* 0.142* 0.104(0.086) (0.083) (0.087)

Subjective poverty 0.151*** 0.121***(0.032) (0.025)

Redistribution -0.179***(0.025)

Welfare chauvinism -0.094***(0.014)

Constant -0.087*** 0.170** 0.431*** 1.184***(0.018) (0.071) (0.075) (0.087)

Observations 27,409 26,807 24,715 23,923Country dummies YES YES YES YESPseudo R-squared 0.0168 0.0223 0.0236 0.0403No. of countries   21 21 20 20Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

Routine – educationinteraction

Probability of support for basic income by routine jobs and education level

Probability of support for basic income by routine jobs and higher education

Probability of support for basic income by RTI and education level

Precarious – educationinteraction

Probability of support for basic income by precarious status and education level

Probability of support for basic income by precarious status and higher education

Probability of support for basic income by being at risk and education level

High-skilled outsiders

Non-tertiary Tertiary Total

Not precarious

55.02% 23.95% 78.96%

Precarious status

16.02%(22.6% of non-tertiary)

5.02% (17.3% of tertiary)

21.04%

Total71.04% 28.96% 100.00%

Non-tertiary Tertiary Total

Not at risk 31.76% 15.62% 47.38%

At risk 39.28%(55.3% of non-tertiary)

13.35%(46.1% of tertiary)

52.62%

Total 71.04% 28.96% 100.00%

•Routine-task intensity weakly associated with support for basic income

•Precarious status has a stronger effect, but not all statuses

•A policy for high-skilled outsiders?

Headline results

•Risk vs. status – does it matter?•Not homogenous effect across statuses•Future constituencies: not the usual suspects? Routine workers and high-skilled outsiders

•Country-level institutions likely to mediate impact of automation

•Varieties of basic income (De Wispelaere & Martinelli)

Conclusion and caveats

Appendix

A basic income scheme includes all of the following: - The government pays everyone a monthly income to cover essential living costs. - It replaces many other social benefits. - The purpose is to guarantee everyone a minimum standard of living. - Everyone receives the same amount regardless of whether or not they are working. - People also keep the money they earn from work or other sources. - This scheme is paid for by taxes

Survey question