1 / 26

Stylized Facts

The Gender- Specific Effect of Working Hours on Family Happiness in South Korea Robert Rudolf and Seo-Young Cho Georg-August-Universität Göttingen. Stylized Facts.

cleta
Download Presentation

Stylized Facts

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Gender-SpecificEffectof Working Hourson Family Happiness in South KoreaRobert Rudolf and Seo-Young ChoGeorg-August-Universität Göttingen

  2. Stylized Facts South Korea: long working hours, high femaleeducation, traditional genderroles, low female labor forceparticipation • graduallydecreasingworkinghoursoverthe last twodecades; adoptionof 5-day workingweek in 2004  Still 2nd longestworkinghours in the OECD in 2009! • Korea amongthelowestfemalelaborforceparticipationrates in the OECD (61.5%amongthoseaged 20-54 (JP 71%; GER 81%)) • Korea withlowest time spent on „unpaidwork“ in OECD, also lowest time spent on childcare (OECD, 2011) • Korea ranksverylow on male houseworkparticipation (17%) • High femaleeducationoften „toincreaselikelihoodto find a well-educatedhusband“ (Lee, 1998): women 50.5% of all college graduates in 2005 • Part-time workin mostcasesonlyavailable in low-skilledjobs • Before marriage education and labor forceparticipationofwomenpositively related, after marriage negatively (Lee et al., 2008)

  3. Introduction • Paper objectives: • Extendhappinessliterature‘sspatialcoverageto East Asia • Estimationoftheeffectofoverallworkinghoursreduction on familyhappiness • Evidencefrom a societywithvery strong traditional genderroles • Useoflatestorderedlogitfixed-effectsestimators • Findings: • Reduction in workinghoursmakesKoreanfamilieshappier • Part-time jobs still dispreferred („아르바이트“, so-called „Arbeit“) • Strong gender-specificeffects: • Husbands derivemuchhigher utility from working than wives even after controlling for income • Wives most happy whenhousewifeorworking31-40h andwhentheirhusbandworksfull time • Husbands most happy when workingfull time withoutovertimehours (31-50h)

  4. Presentation Outline I. Background • Data andMethodology • Satisfaction Regression Results a) Life Satisfaction b) Hoursand Job Satisfaction IV. Family Division of Labor • ConcludingRemarks

  5. I. Background (Theory) Employmentas a meansofsocialinclusionandself-fulfillment: • Positive welfaregainseven after controlling forincome(Clark and Oswald 1994; Winkelmann and Winkelmann 1998)  Positiveincentiveforfemaleengagement in labormarket AkerloffandKranton‘sgenderidentityhypothesis (2000): • individual behaviorlargelydeterminedbyourvariousidentities, particularlybyourgender, andrelatedexpectedbehaviors • Negativeincentiveforfemaleengagement in labormarket in societieswithvery traditional genderroles Time constraint (housework + marketwork + … = 24h/day) Labor marketconstraints (part-time options, childcare, etc.)

  6. I. Background (EmpiricalEvidence) Booth and Van Ours (2008, The Economic Journal): BHPS, GB Findings: controlling for family income, women prefer working to not-working; theirlifesatisfaction peaks at 30-40 hours; yettheirhoursandjobsatisfactionishighestbelow 30 hours; men most happy with full-time work Booth and Van Ours (2009, Economica): HILDA Survey, Australia Findings: women indifferent between not-working and part-time job, working more than 35 hours decreases their satisfaction; men most happy when workingfull-time between 35 and 50 hours  Part-time jobs in GB andAustralia: solutionforthepursuitofbothexpectedgenderidentityasthemain family care-taker andself-fulfillment via marketwork

  7. II. Data andMethodology Data used • 11 wavesoftheKorean Labor and Income Panel Study (KLIPS) from 1998 to 2008 • Nationallyrepresentative longitudinal studyof urban Koreanhouseholdsmodelled after theUS‘s NLS and PSID • 1998 startedwith 5,000 householdsand 13,783 individuales aged 15 orolder (76.5% maintainedthroughout all waves) • Broadinformation on education, employment, demographic, andsocio-economic variables

  8. II. Data andMethodology Sample restrictions • Marriedandco-residingcoupleslivingwithchildren • Women aged 20-54 (prime yearsofmotherhood) • Menaged 20-64 (husbandsoftenolderthanwivesand a highpercentage still workingwith 64) • Unbalancedpanel, thusminimumrequirementthat an individual ispresent in at least twowaves • Resulting sample: 25,461 person-yearobservationsforwomenand 25,214 person-yearobservationsformen

  9. II. Data andMethodology • Life satisfaction: • “Overall, how satisfied or dissatisfied are you with your life?” • Job satisfaction (onlyfromwave 3 onwards): • “Overall, how satisfied or dissatisfied are you with your main job?” • HoursSatisfaction: • “How satisfied or dissatisfied are you with regard to your main job on the following aspects?”  “Working Hours” • Respondentsareaskedtochooseamong: 5 (verysatisfied) 4 (satisfied) 3 (neithersatisfiednordissatisfied) 2 (dissatisfied) 1 (verydissatisfied)

  10. II. Data andMethodology

  11. II. Data andMethodology

  12. II. Data andMethodology

  13. II. Data andMethodology

  14. II. Data andMethodology Fixed-effectsorderedlogitestimation • Orderedlogitinconsistentifunobservablescorrelatedwithcovariates (e.g. personalitytraitwithoccupationstatus) • Thusfixedeffectsmodelsusuallyestimated in subjective well-beingliterature: • Psychology/sociology: cardinalinterpretationofsatisfactionscores, linear FE • Economics: ordinalapproaches, nostandardworkhorseyet • Recentadvances: Fixed-effectsorderedlogitestimators (e.g. Ferrer-i-Carbonell andFrijters, 2004; Baetschmann, Staub and Winkelmann, 2011)

  15. III. Results

  16. Table 4 cont’d

  17. Robustnesschecks (1) Different reference groups in life satisfaction regressions (2) Earnings instead of household income (Interesting finding: Women value men’s earnings higher than their own) (3) Separate working hours dummies for wage vs. non-wage employed (wage-employed slightly happier) • Subjective health as additional control (only available from wave 6, problematic because endogenous)  No changes in main results

  18. IV. Gender-specific time-usepatterns

  19. V. Concludingremarks • ReductionofworkinghoursmadeKoreanfamilieshappier • Still strong gender-specificeffectsofworkinghours on happiness due to strong traditional genderroles • Menderivemuchhigherbeyond-incomeutilityfromworkingthanwomen • Controlling forfamilyincome, womenaremost happy whenbeinghousewivesorworking 31-40 hours; menwhenworking 31-50 hours • Part-time jobsno alternative in Korea yet due tolowqualitynature • Resultssupportgender-identityhypothesis • Results robust to different fixed-effectsestimatorsandchanges in model specification

  20. V. Concludingremarks • PolicyImplications: • Further hoursofworkreductions • Equalityofchancesattheworkplace • Encouragingchange in genderidentities • Flexible jobandchildcaresolutions • Create part-time jobs in high-skilledsector

  21. Thankyouforyourattention.

  22. II. Data andMethodology Fixed-effectsorderedlogitestimation • Ferrer-i-Carbonell andFrijters (FF-estimator): individual fixedeffectsuiand individual-specificthresholdsλikareintroducedintothe model; thisallowsreformulationoftheordinallogitas a binomiallogit • Baetschmann, Staub and Winkelmann (2011) showthatthe FF-estimatorisslightlydownwardbiasedsincecutoffpointsarechosenendogenously • Theysuggest an ownestimator: BUC-estimator • BUC-estimatorperformsbest in Monte-Carlo simulations

  23. II. Data andMethodology Fixed-effectsorderedlogitestimation Wechosetoapply BUC-estimator, FF-estimator, and linear FE Why FF still necessary? • FF-estimatorconvergestothetruevalueasN ↑, T ↑, and K ↓ as in the case of our sample • Comparability of results with Booth and Van Ours, who use FF-estimator (2008, 2009) • BUC performance needs further validations under different circumstances (e.g. extreme distributions, unbalanced panel) Why linear FE additionally? • Linear FE shown to produce similar results in satisfaction regressions (Ferrer-i-Carbonell and Frijters, 2004) • Straightforward interpretation

More Related