Non-standard contingent employment and job satisfaction: A panel data analysis. Mark Wooden [Co-authors: Hielke Buddelmeyer, Duncan McVicar]
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1 Non-standard contingent employment and job satisfaction: A panel data analysis Mark Wooden [Co-authors: Hielke Buddelmeyer, Duncan McVicar]
2 Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and view reported in this paper, however, are those of the authors and should not be attributed to DSS or the Melbourne Institute.
3 Overview The research question Is non-standard contingent employment associated with low job satisfaction? Why is this important? High incidence Ongoing debate (e.g., Howe Inquiry) Previous research limited / has weaknesses Method Estimate FE models of job satisfaction BUC estimator (fixed effects ordered logit)
4 Definitional Issues Non-standard employment Any job other than a FT, permanent, wage & salary job Contingent employment No explicit or implicit long-term contract OR Minimum hours can vary in a non-systematic manner The measurement of worker well-being A self-reported measure of overall job satisfaction Contentious
5 Hypotheses Conventional Wisdom NS employment = low quality jobs = dissatisfied / unhappy workers Three key features: Lack of permanency = insecurity / anxiety Inferior conditions / entitlements Treated differently = marginalised
6 Previous Research (1 st Generation) Mostly cross-sectional* Meta-analysis (Wilkin 2013) Small negative: d = -.06 Varies with employment type: Temps = -.37 Direct hire =.-07 Contractors = +.06 Issues / Weaknesses Mostly small, non-rep samples Adaptation / changing expectations?
7 Previous Research (2 nd Generation) Longitudinal BHPS: Bardasi & Francesconi (2004); Green & Heywood (2011) Danish ECHP: D Addio et al (2004) Dutch SEP: de Graaf-Zijl (2012) German SOEP: Chadi & Hetschko (2013) HILDA: Green, Kler & Leeves (2010) Small(?) negative effects dominate Need for more research Replication (esp outside Europe) Estimates biased Potential for interaction effects mostly ignored
8 Hypotheses (Revisited) H1: NS emp = low satisfaction, but small H2: Size of effect will vary with emp type H3: Effects will differ b/w men & women H4: Less pronounced among v young / v old H5: Most pronounced for primary income earners, especially those w children H6: Less pronounced for most educated / skilled H7: Will diminish with tenure H8: Most pronounced for workers w irregular hrs
9 Data HILDA Survey (Release 11) Initial sample All persons in paid employment at ivw date Unbalanced panel: n=82,492; i=15,784 Job satisfaction = 11-point ordinal scale All things considered, how satisfied are you with your job Employment type = self-defined
10 Composition of Employment (%) Employment type Employee (b) Permanent / ongoing Contingent Fixed-term contract Casual Labour-hire Sub-total (c) Self-employed (b) Total (d) Notes: (a) All figures are weighted population estimates. (b) Owner managers of incorporated businesses have been classified as self-employed, and not as employees. (c) Included in this sub-total are a small number of employees employed on other arrangements. (d) Included in this total are unpaid family workers. Source: Unit-record data from HILDA Survey (release 11).
11 Mean Job Satisfaction by Employment Type & Sex Employment type Employees Males Permanent Casual Fixed-term Labour-hire Self-employed Notes: (1) All figures are weighted population estimates. (2) The definition of employee used here excludes owner managers of incorporated businesses. (3) Labour-hire workers employed on a fixed-term contract or casual basis have been classified here as labour-hire workers. Source: Unit-record data from HILDA Survey, waves 1 and 10 (release 11).
12 Mean Job Satisfaction by Employment Type & Sex Employment type Employees Males Females Permanent Casual Fixed-term Labour-hire Self-employed Notes: (1) All figures are weighted population estimates. (2) The definition of employee used here excludes owner managers of incorporated businesses. (3) Labour-hire workers employed on a fixed-term contract or casual basis have been classified here as labour-hire workers. Source: Unit-record data from HILDA Survey, waves 1 and 10 (release 11).
13 The Model: Fixed Effects Ordered Logit JS* it = α i + δ t + E it β + X it γ + E it.x it λ + ε it JS = 0 if JS* 0 = 1 if 0 < JS* μ 1 = 2 if μ 1 < JS* μ 2 = 10 if JS* > μ 9 JS = job satisfaction; E = employment type; X = individual time-specific controls; E.X = interaction effects
14 Estimation Issues Incidental parameters problem = conventional LL maximization not feasible Options: Treat as cardinal: estimate OLS (common) Maximize using brute force : LIMDEP (e.g., Green & Heywood 2011) Dichotomise outcome: estimate conditional FE binary logit (e.g., Bardasi & Francesconi 2004; D Addio et al 2007; de Graaf-Zijl 2012)
15 Our Estimator: Blow Up and Cluster (BUC) Due to Baetschmann et al (2011) Also uses conditional ML binary logit model Steps: 1. Outcome dichotomised, but at every possible point along the satisfaction scale. 2. Every person-year observation replaced by 10 copies (sample blown up ). 3. Binary logit estimated, with SEs adjusted for withinperson clustering. Estimates unbiased, even when T is small
16 Time-varying Controls Age; Marital / Partnership status; Education; LT health condition; Location (or remoteness). Usual hours of work; Job tenure; Supervisory responsibilities; Union membership; Occupation; Industry; Sector; Firm size. Survey wave; Interview conditions (presence of others); Survey mode; Observed LF status at next survey wave [controls for selectivity] Separate analyses for men and women. Also test for interactions with: Partner status x earner status x children Education; Tenure; Regularity of work schedule x weekly hours of work
17 Ordered Logit Estimates Males Without fixed effects Fixed effects Fixed effects (restricted sample) Casual -.204*** -.264*** -.395*** Fixed-term Labour-hire -.347*** -.305*** -.252*** Self-employed -.175*** * Females Casual Fixed-term Labour-hire -.179** -.189* -.235** Self-employed *** p<.01; ** p<.05; * p<.10.
18 Ordered Logit Estimates Males Without fixed effects Fixed effects Fixed effects (restricted sample) Casual -.204*** -.264*** -.395*** Fixed-term Labour-hire -.347*** -.305*** -.252*** Self-employed -.175*** * Females Casual Fixed-term Labour-hire -.179** -.189* -.235** Self-employed *** p<.01; ** p<.05; * p<.10.
19 Average Predicted Probabilities of Job Satisfaction (JS) P(JS 4) P(JS=5) P(JS=6) P(JS=7) P(JS=8) P(JS=9) P(JS=10) Men 21 to 59 years of age excluding full-time students Permanent Prob
20 Average Predicted Probabilities of Job Satisfaction (JS) P(JS 4) P(JS=5) P(JS=6) P(JS=7) P(JS=8) P(JS=9) P(JS=10) Men 21 to 59 years of age excluding full-time students Permanent Prob Casual Diff Fixed-term Diff Labour-hire Diff
21 Average Predicted Probabilities of Job Satisfaction (JS) P(JS 4) P(JS=5) P(JS=6) P(JS=7) P(JS=8) P(JS=9) P(JS=10) Men 21 to 59 years of age excluding full-time students Permanent Prob Casual Diff Fixed-term Diff Labour-hire Diff Women 21 to 59 years of age excluding full-time students Permanent Prob Casual Diff Fixed-term Diff Labour-hire Diff
22 Key Findings MEN Very robust negative associations w both casual and labour hire employment Diminishes w tenure Casual effect very pronounced for men w families No associations with fixed-term contract work WOMEN Only university-educated dissatisfied w casual Labour-hire workers less happy (though it is mainly the partnered secondary earners w kids)
23 Further Information Copy of paper Available as Melbourne Institute Working Paper Series no. 29/13. Forthcoming in Industrial Relations: A Journal of Economy & Society. To learn more about HILDA Survey (incl how to order it) Contact m.wooden@unimelb.edu.au
24 Extra Slides Results from tests of interaction effects follow
25 Interaction Effects: Partner x Earner status x Children Males Females Permanent, single, no kids Ref Ref Permanent, single, kids Permanent, partnered, primary earner, no kids Permanent, partnered, primary earner, kids Permanent, partnered, second earner, no kids Permanent, partnered, second earner, kids Casual, single, no kids -.392*** -.225* Casual, single, kids -.533**.187 Casual, partnered, primary earner, no kids Casual, partnered, primary earner, kids -.528*** Casual, partnered, second earner, no kids * Casual, partnered, second earner, kids -.854***.046
26 Interaction Effects: Partner x Earner status x Children Males Females Permanent, single, no kids Ref Ref Permanent, single, kids Permanent, partnered, primary earner, no kids Permanent, partnered, primary earner, kids Permanent, partnered, second earner, no kids Permanent, partnered, second earner, kids Casual, single, no kids -.392*** -.225* Casual, single, kids -.533**.187 Casual, partnered, primary earner, no kids Casual, partnered, primary earner, kids -.528*** Casual, partnered, second earner, no kids * Casual, partnered, second earner, kids -.854***.046
27 Interaction Effects w Education Males Females Casual -.292**.197* Fixed-term contract Labour-hire -.518** Medium education High education Medium education x Casual ** Medium education x Fixed-term Medium education x Labour-hire High education x Casual *** High education x Fixed-term High education x Labour-hire.641**.168
28 Interaction Effects w Education Males Females Casual -.292**.197* Fixed-term contract Labour-hire -.518** Medium education High education Medium education x Casual ** Medium education x Fixed-term Medium education x Labour-hire High education x Casual *** High education x Fixed-term High education x Labour-hire.641**.168
29 Interaction Effects w Tenure Males Females Casual -.385*** -.105* Fixed-term contract * Labour-hire -.231** -.235** Ln tenure -.206*** -.222*** Ln tenure x Casual.157***.128*** Ln tenure x Fixed-term contract Ln tenure x Labour-hire.168*.172*
30 Interaction Effects w Irregular Schedule Males Females Casual -.332*** Fixed-term contract Labour-hire ** Irregular work schedule -.134** Irregular x Casual Irregular x Fixed-term Irregular x Labour-hire -.592**.071
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