JOBS, WAGES AND INEQUALITY: The role of non-standard employment Laval university seminar 14 November 2014 Wen-Hao Chen Social Analysis Division, Statistics Canada

The context - towards an inclusive growth? The decline of the wage-to-income share in OECD countries, /30

 Some regulatory reforms tended to increase flexibility, facilitating employer’s adjustments of the workforce via non- standard workers,  Demographic and societal developments also contributed to the supply of atypical workers,  Possible distributional implications, Research questions  Was employment growth primarily associated with low-paid, unstable jobs or with more productive and rewarding jobs?  To what extent are “atypical” jobs “stepping stones” to improved labour market prospects, or rather “traps”?  How do atypical work patterns affect household earnings and income inequality? The background and motivation 3/30

1. Development and characteristics of non-standard employment  Defining NSW work and documenting trends & characteristics  Are non-standard workers in low-paid or lower quality jobs? 2. Labour market prospects of non-standard workers  Are NSW jobs “Stepping stones” or “dead ends”? Employment transitions, wage penalties and upward earnings mobility 3. How does NSW affect household income inequalities and poverty?  How is NSW distributed at the household level?  Distributional position of NSW in household income distribution  In-work poverty risks 4. Conclusions Structure of the talk 4/30

 Country-specific conventions  Data issues  In its broadest terms, defined by what it is not (full- time dependent employment with an indefinite duration contract)  includes self-employment (own-account), all temporary and all part-time employees  Broad definition used by Eurofund, ILO, WB  Not a normative concept, and different from the notion of precarious employment “Non-standard” / “atypical” work: a fuzzy concept 5/30

Different forms of non-standard work: example Germany Source: EU-LFS Excluding … - Employers, - FT students, - Apprentices, - Older workers 6/30

The share of non-standard work is sizeable in OECD countries Share of non-standard employment by type as % of total employment, 2010 Note: Sample restricted to paid and self-employed (own account) workers aged years old, excluding employers and student workers. Source: EULFS, KLIPS (2008) for Korea, HILDA (2009) for Australia and LFS for Canada. 33 ﹪ 7/30

Part-time workers are a heterogeneous group Part-time employment, by type, 2010 or closest Note: Sample restricted to paid and self-employed (own account) workers aged years old, excluding employers, student workers and apprentices. Source: OECD (2014); EULFS; KLIPS for Korea, LFS for Japan, HILDA for Australia and LFS for Canada. 71% voluntary permanent temporary 8/30

NSW accounted for about half of employment growth between 1995 and 2010 Employment growth (%) by SW/NSW type, Note: Sample restricted to paid and self-employed (own account) workers aged years old, excluding employers and student workers. Source: EULFS, KLIPS (2008) for Korea, HILDA (2009) for Australia. 9/30

Non-standard work is the main source of employment growth, esp. for low-skill jobs * LFS 1995/ (C) Non-routine manual Task (low-skill) (A) Abstract task (high-skill)(B) Routine task (middle-skill) 10/30

Do atypical jobs pay less? Ratio of median hourly wages (standard workers = 1), 2010 Source: OECD (2014); EULFS; KLIPS for Korea, LFS for Japan, HILDA for Australia and LFS for Canada. 11/30

Do atypical jobs provide less job security? Ratio of reported probability of job loss within the next 6 months (standard workers = 1), 2010 Source: European Working Condition Survey (EWCS 2010). PT perm. 12/30

Are non-standard jobs “stepping stones” or “dead ends”? Longitudinal Data: European Survey of Income and Living Conditions (EU-SILC, ), Australia (HILDA), Korea (KLIPS), UK (BHPS), Germany (GSOEP) vvvv (reference = unemployed) 13/30

Are non-standard jobs “stepping stones” or “dead ends”? FT Temporary contracts are more likely than the unemployed to enter into a standard work one year later, by about p.p. Dynamic Probit Model: All regressions include regional dummies, year dummies, age groups, a dummy for the presence of children, a dummy for whether the individual suffers from a health problem, a dummy for whether the individual is married, dummies for low-skilled and high-skilled (corresponding to ISCED 0-2 and ISCED 5-6), equivalised household net income as well as initial conditions (L0, Xi). Source: EU-SILC; KLIPS for Korea, HILDA for Australia. Marginal effect (%-points) 14/30

Are non-standard jobs “stepping stones” or “dead ends”? Part-time workers on average face the same risk as the unemployed in terms of transition probability into standard work one year later Dynamic Probit Model: All regressions include regional dummies, year dummies, age groups, a dummy for the presence of children, a dummy for whether the individual suffers from a health problem, a dummy for whether the individual is married, dummies for low-skilled and high-skilled (corresponding to ISCED 0-2 and ISCED 5-6), equivalised household net income as well as initial conditions (L0, Xi). Source: EU-SILC; KLIPS for Korea, HILDA for Australia. Marginal effect (%-points) 15/30

 For part-timers, transition rates into standard jobs are higher for those with permanent job contracts – Weak stepping-stone effects for temporary PT workers. In Austria and Germany, these workers are associated with a negative probability of transition from PT to SW  In most countries, self-employed have a lower probability than the unemployed to move into standard work  Mixed evidence of stepping-stone effect of NSW by workers’ characteristics – In some countries, stepping-stone effects are only visible for prime-age and older workers, but not for young (female) workers with a temporary contract. Are those in NSW likely to move into standard jobs (2)? 16/30

 Temporary workers are at higher risk of unemployment and inactivity than those in SW in ¾ of countries  Part-timers are on average 4.5 p.p. more likely than SW to move out of the labour force  Self-employment is not associated with higher risks of unemployment but risk of inactivity are higher for women in half of the countries. Does NSW lead to higher risks of non- employment? 17/30

Is there a wage penalty for NSW, controlling for observed factors and unobserved fixed effects? Controlling observed differences, Temporary workers (both FT and PT) face a large wage penalty in hourly wages, compared with standard workers Note: All regressions include regional dummies, year dummies, age groups, a dummy for the presence of children, a dummy for whether the individual suffers from a health problem, a dummy for whether the individual is married, and dummies for medium-skilled and high-skilled (corresponding to ISCED 3-4 and ISCED 5-6). Source: EU-SILC, KLIPS, BHPS, HILDA, GSOEP. 18/30

The extent of wage penalty is reduced greatly once unobserved heterogeneity is controlled PT (permanent) workers are no longer associated with wage penalty, and in Australia there shows a wage premium for part-timers Note: All regressions include regional dummies, year dummies, age groups, a dummy for the presence of children, a dummy for whether the individual suffers from a health problem, a dummy for whether the individual is married, and dummies for medium-skilled and high-skilled (corresponding to ISCED 3-4 and ISCED 5-6). Source: KLIPS, BHPS, HILDA, GSOEP. 19/30

Stay in a temporary job in general is associated with certain degree of upward mobility, while greater earnings instability (i.e. high risks of both upward and downward mobility) is also observed in some countries Is there (upward) annual earnings mobility for persistent temporary contract workers? Average predicted probability of moving up/down quintiles of annual earnings Source: EU-SILC; KLIPS for Korea, HILDA for Australia. 20% 20/30

Will the growth in NSW lead to higher income inequality and poverty? An increase in the share of non-standard workers is likely to contribute to increased individual earnings dispersion, but the impact on household income depends on:  “ Demography”: in which household do NSW live (alone or with other earners?)  “Earnings”: what is the contribution from NSW earnings at the household level (main or secondary earners?)  “Incomes”: what is the position of NSW workers in the overall income distribution (how much non-labour sources— e.g. investment, benefits received?) 21/30

Non-standard work is a common feature at the household level 41% of all working households include a non-standard worker Source: EU-SILC, KLIPS for Korea, HILDA for Australia and SLID (2009) for Canada. 41% 22/30

Only about half of non-standard workers are the main earners in their families Share of non-standard workers as main earners, breakdown by household type Source: EU-SILC (2010), KLIPS (2010), HILDA (2010), SLID (2009) 23/30

Households with only non-standard worker(s) earn much less than households with a SW Median earnings ratio (One earner SW households = 1), 2010 Source: EU-SILC (2010), KLIPS (2010), HILDA (2010), SLID (2009) 2 NSWs households Mixed SW/NSW households 58% 24/30

* Distributional position of household income by quintile of individual earnings for non- standard workers, OECD 15 average, 2010 Individuals in NSW are not necessarily at the lower end when looking at household income 2/3 of NSW in the bottom quintile of individual earnings move up the distribution in terms of household income Source: EU-SILC (2010), KLIPS (2010), HILDA (2010), SLID (2009) 25/30

Almost one third of the poor and two thirds of the working poor are in NSW households Note: The poverty line is defined as 50% of the median equivalised household income for the entire population. Source: EU-SILC, HILDA for Australia, KLIPS for Korea and SLID (2009) for Canada. Distribution of the poor by household employment type, OECD average /30

Households with only NSW face a higher risk of poverty than those with a SW Poverty rates of households by employment pattern NSW 23% SW 3% Mixed 2.5% Jobless 42% Note: The poverty line is defined as 50% of the median equivalised household income for the entire population. Source: EU-SILC, HILDA for Australia, KLIPS for Korea and SLID (2009) for Canada. 27/30

 Non-standard work is increasing and it contributes a significant part to the employment growth in OECD countries,  Great heterogeneity within non-standard workers; the term “non-standard” may not be interpreted as the same notion of “precarious”,  “Stepping-stone” effects for non-standard work exist in most countries, but they depend on the type of non- standard work and there are trade-offs involved,  Temporary workers often face considerable wage penalties and experience greater earnings instability, Take away (1) 28/30

 Inequality and poverty impacts of non-standard work depend also on the “demographic” and “household income” aspects,  About 1/2 of NSW are the main earners,  Only 1/3 of low-earnings NSW are at the bottom of the household income,  There is no straightforward link between growing NSW and rising income inequality and poverty,  Nevertheless, for “pure” NSW households they are disproportionately likely to be poor: - 40% lower in household earnings, - 23% are in poverty. Take away (2) 29/30

Thank you for your attention!