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Family Strategies and Labor Market Behavior in Modern Russia - Grant # R04-9161. Project Team : Oxana Sinyavskaya, IISP Dilyara Iragimova , IISP, Marina Kartseva , CEFIR, Sergey Zakharov , CDHE. Rationales of the project. Family policy in Russia: addressed to married couples
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Family Strategies and Labor Market Behavior in Modern Russia - Grant # R04-9161 Project Team: Oxana Sinyavskaya, IISP Dilyara Iragimova, IISP, Marina Kartseva, CEFIR, Sergey Zakharov, CDHE
Rationales of the project Family policy in Russia: • addressed to married couples • assumes direct positive link between economic & housing situation and fertility • supports traditional family and gender roles Whether one can expect that this policy would be successful? MIR Workshop, Kiev, July 8, 2006
Objectives How do employment and fertility decisions correlate within families? What are their determinants?And what are the implication for employment and demographic policies? Goal: To reveal typical models of Russian people’s labor market and reproductive behavior for different types of households • To determine models of decision-making in households • To estimate labor supply for different types of households • To study causality between fertility and employment & estimate the probability of intentions to have a(nother) child MIR Workshop, Kiev, July 8, 2006
Database Russian Generations and Gender Survey: • a part of international GGP • conducted in summer 2004 • multistage probability sample • 11261 respondents from 32 regions • 1 respondent = 1 household • respondent speaks about him/herself, his/her partner, and household members • more than 2000 variables, • including questions on fertility history and intentions, current economic activity, couples decision-making, attitudes and values MIR Workshop, Kiev, July 8, 2006
Target population The following groups were excluded from the analysis: • Respondents in pension ages, i.e. of age 55 years old and over (females) and of age 60 and over (males), • Those with co-resident partners of pension ages, • Respondents of active ages, who are pensioners, ill or disabled for a long time or permanently, students, and those in military or alternative civilian services • Respondents with co-resident partners – pensioners, students, ill or disabled for a long time or permanently, students, and those in military or alternative civilian services. 6405 respondents of 18-54/59 years old, including 4192 peoplewith co-resident partners • Analysis of respondents and partners together – 10597 observations MIR Workshop, Kiev, July 8, 2006
Decision-making in partnerships MIR Workshop, Kiev, July 8, 2006
Female Labor Supply Main Hypotheses: • For women from “female-dominated” partnerships partner’s wage has no influence on their LS decision • Wage of partner matters for women from “male-dominated” partnerships • Wage of partner matters for women from “egalitarian” type of families MIR Workshop, Kiev, July 8, 2006
Female LS: Methodology • Logit-model: age – age of agent; age2 – age of agent (squared); Education: ed1- primary professional; ed2 – secondary professional; ed3 – higher professional; Family structure: ch_03 – number of children aged 0-3; ch_46 – number of children aged 4-6; ch_716 – number of children aged -716; num_ad – number of adults in the household; old_female – pre-retirement age female Decision-making type: female-dominated partnership; male-dominated partnership Information about partner: social_par– level of social security at partner’s job; linc_par – log of average monthly income of partner; Regional LM: rural – dummy for living in rural area; unemp_lev- regional unemployment level To estimate if there is significant variation across different types of households with respect to determinants of female labor supply we use interaction terms (variable of interest*dummy for family type) instead of estimating our equation on separate subsamples MIR Workshop, Kiev, July 8, 2006
Methodology: dependent variable MIR Workshop, Kiev, July 8, 2006
Female LS: Results MIR Workshop, Kiev, July 8, 2006
Reproductive intentions: methodology • “Do you personally want to have a (another) child now?”/ “Does your partner (spouse) want to have a(nother) child now?” • “yes” / “no” / “not sure” • Intentions = potential probability to give birth • Factors: • R’s personal characteristics (age, education, marriage, N of children born + employment status), • HH characteristics (incomes, potential grandma, housing), • attitudes (religiosity, family-child-gender values, decision-making mode) • settlement, region • Interactions of some factors * children already born MIR Workshop, Kiev, July 8, 2006
Probability of wanting a (another) child for a female respondents in partnerships MIR Workshop, Kiev, July 8, 2006
Probability of wanting a (another) child for a female respondents in partnerships MIR Workshop, Kiev, July 8, 2006
Probability of wanting a (another) child for a female respondents in partnerships MIR Workshop, Kiev, July 8, 2006
Relative variation of actual at the censor date and expected mean number of children ever born by age and education (All levels of education = 1). MIR Workshop, Kiev, July 8, 2006
Conclusions & Policy Implications • significant changes in family formation and fertility behavior • maximum potential of the expected fertility growth – 0.2 children per one woman • most unsatisfied with the actual number of children – women with higher education • family policy - at the group of well-educated women. MIR Workshop, Kiev, July 8, 2006
Conclusions & Policy Implications Effects on intentions to have a(nother) child • either economic variables or attitudes – no impact on intentions to give birth to the 1st child BUT significant on the intentions to have 2nd and further children • the family policy oriented at improving family wellbeing would have a certain effect on increasing the probability of the 2nd births • no negative effect of high incomes & female employment • family policy – at increasing births among employed women as well MIR Workshop, Kiev, July 8, 2006
Conclusions & Policy Implications Effects onprobability to be employed for women: • number of children - negative • non-labor incomes - negative • family policy: if benefits for mothers not related to female employment were increased - some women will leave their jobs • Potential grandmother – positive • development of affordable childcare institutions with comfortable working hours would increase female employment in a majority of families. MIR Workshop, Kiev, July 8, 2006
Conclusions & Policy Implications • decision-making about female employment: attitudes; in 50% - women decides for herself, while in only of 5% - only the man’s decision • man’s income and employment, other household characteristics - different effects on the female LS in partnerships with different decision-making models Family policy • supporting traditional families with one male breadwinner - only limited impact • increasing the compatibility of female employment and fertility - most effective for individualistic decision-making partnerhsips • should be more differentiated and flexible MIR Workshop, Kiev, July 8, 2006