## _wp1556 - 3. Definition and Sources of Data

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---

### I. Introduction — research focus and questions
- Objective:
  - examine drivers of female labor force participation (FLFP) in Japan and Korea in comparison with Nordic countries, with special attention to the composition of employment (regular vs. non-regular).
- Motivation:
  - increase in FLFP can boost growth by increasing labor supply; Japan and Korea face rapidly aging and shrinking populations (IMF, 2013).
- Key research questions:
  - What are the main drivers for FLFP in Japan and Korea?
  - Do regular employment and non-regular employment respond asymmetrically to different shocks?
  - What lessons can Japan and Korea learn from Nordic countries?
- Methodology:
  - Structural Vector Autoregressive (SVAR) model used for empirical analysis to account for endogeneity and correlated determinants of FLFP (e.g., simultaneity between childbirth and participation).

### II. Stylized facts — cross-country patterns and country snapshots
- Cross-country snapshot (19 OECD countries):
  - Japan and Korea: FLFP lower than the 19-country average; wage gaps and gender gaps in participation large.
  - 2012 wage comparisons:
    - women’s wage was 26 percent lower than men’s wage in Japan and 37 percent lower in Korea.
  - Male–female participation gaps:
    - female labor participation was about 25 percent lower than male LFP in Japan and 30 percent lower in Korea.
  - Fertility:
    - Japan and Korea among countries with low fertility rates.
  - Nordic countries (e.g., Norway, Finland): high FLFP and modest fertility rates; smaller gender gaps.
- Life-cycle employment profile:
  - Japan and Korea exhibit an M-shaped FLFP pattern with a drop in FLFP at age 25-29 and a moderate increase after 45-49; contrasts with Finland and Norway where no such drop is evident.
  - In Japan and Korea, women often drop out during prime working age and return as non-regular workers.
- Japan-specific facts:
  - FLFP: 65 percent in 2013, up from 55 percent in 1985.
  - Composition: among all female employees, 55 are non-regular workers, of which 60 percent are part-time workers.
  - Gender gaps:
    - Japan ranks 105th out of 136 countries in the World Economic Forum’s Global Gender Gap 2013.
    - Women earn on average just 71 percent of Japanese men (Goldman Sachs, 2014).
  - Leadership representation: female administrative/managerial workers only 11.1 percent in Japan (vs. 43.1 percent US and 34.5 percent UK; Cabinet Office, 2013).
  - Institutional features: two-tier tracking systems (sogo shoku vs. ippan shoku) contribute to underinvestment in female human capital and large wage gaps.
- Korea-specific facts:
  - FLFP: 55 percent in 2012.
  - Fertility rate: persistently low at 1.24.
  - Female representation in top management: 1 percent on boards and 2 percent in executive committees (McKinsey and Company, 2012).
  - Share of regular female workers rose from 20 percent in 1990 to nearly 40 percent in 2010; labor law change (starting in [2007]) limits fixed-term employment to a maximum of two years to encourage conversion to open-ended contracts.
- Nordic countries (Norway, Finland) facts:
  - Norway: FLFP rose from 44 to 76 percent in 2012; about 83 percent of mothers with small children are employed; fertility rates rose to about 1.8 percent.
  - Finland: FLFP rose from 44 to 73 percent in 2012; fertility rate 1.8; women make up 70 percent of public-sector employment.
  - Policy and cultural elements: comprehensive parental provisions, subsidized daycare, paid leave rights, strong paternal involvement relative to Asian peers, and policies designed to reduce incompatibility between employment and childbearing.

### III. Empirical analysis — data, methodology, and explanatory variables
- Model and sample:
  - Non-recursive five-variable SVAR estimated for Japan, Korea, Norway, and Finland over 1990–2012.
  - Variables: female labor force participation rate (or female regular and non-regular employment rates), child cash allowances, gender wage gap, fertility rate, female tertiary school enrollment rate.
  - Stationarity treatment: logarithm and first difference of variables.
- Data sources and coverage:
  - Main sources: Statistics Bureau of Japan, CEIC Asia Database, OECD Social Expenditure Database, World Bank.
  - Japan: annual data for 1997-2012.
  - Korea: annual data for 1990-2010 (data availability constraint).
  - Norway and Finland: data coverage 1990-2009 (OECD Social Expenditure Database and World Bank).
- Rationale for SVAR:
  - Addresses endogeneity among child allowances, gender wage gap, FLFP, fertility, and female tertiary enrollment.
  - Useful to trace dynamic transmission and timing of shocks to female labor employment.
- Explanatory variables and expected relationships:
  - Child allowances: may increase incentives to work or reduce them if transfers substitute for market earnings; effect may differ for regular vs. non-regular employment.
  - Fertility: relationship with FLFP has been negative historically but shifted positive after 1985 for OECD countries; policy and norm changes can offset substitution effects.
  - Gender wage gap: used as a proxy for gender inequality; larger gaps expected to discourage FLFP.
  - Female tertiary enrolment: higher education generally associated with higher FLFP, but Japan and Korea show rising education with persistent underutilization.

### IV. Empirical results — impulse responses and segmental dynamics
- General FLFP impulse-response findings (standardized to a 1-percent shock; percent changes reported):
  - Child cash allowances:
    - For most countries, child allowances reduce FLFP; Korea is an exception but estimate statistically insignificant.
  - Gender wage gap:
    - A greater gender wage gap reduces FLFP in Japan and Korea.
    - Effect statistically insignificant in Nordic countries.
  - Fertility rate:
    - Fertility is positively correlated with FLFP in all four countries.
- Japan — regular vs. non-regular employment (impulse-response distinctions):
  - Child allowance shock:
    - Regular female employment: negatively affected in the first year.
    - Non-regular female employment: positively affected.
    - Interpretation: child allowances in Japan increase non-regular employment rather than regular employment.
- Japan and Korea — asymmetric responses:
  - Child allowances can affect regular and non-regular employment asymmetrically:
    - In Japan and Korea, child allowances reduce regular female employment and can increase non-regular employment.
    - In Norway and Finland, child allowances increase regular female employment and discourage non-regular employment.
  - Gender wage gap shock effects:
    - An increase in the gender wage gap discourages regular female employment and increases non-regular female employment in Japan and Korea.
    - Female regular employment in Korea responds negatively by 1.4 percentage points to the gender wage gap (as opposed to 0.3 percentage points in Japan).
    - The gender wage gap effect is statistically insignificant in Norway and Finland.
  - Fertility effects:
    - Higher fertility is associated with higher regular female labor participation in both Asia and the Nordics.
    - In Korea, the positive impact of fertility on regular employment is 4.5 percentage points within one year, more than 10 times the effect in Japan.
  - Tertiary school enrolment:
    - Tertiary enrolment helps increase regular employment in Korea and the Nordics and reduces non-regular employment in those countries.
    - In Japan, tertiary school enrolment rate does not affect female labor employment significantly; many non-regular female workers in Japan often have college degrees.

### V. Public spending on family and child benefits (OECD-based broader definition)
- Overall spending patterns:
  - Total family benefits spending is more than twice as much in the Nordics compared to Japan and Korea.
  - Norway and Finland spend more than Japan and Korea in most family-benefit categories, except financial support via the tax system.
  - Japan spends about 0.5 percent of GDP on financial support for families through the tax system; Finland has no such policy.
- Child-related transfers and services:
  - Norway and Finland spend about three times as much on child-related transfers to families with children as Japan.
  - Korea spends very little in the child-related transfer category.
  - Korea spends about 0.7 percent of GDP on services for families with children; Japan spends 0.5 percent; the Nordics spend about 2 percent.
- Composition of family-related spending (including formal education):
  - Japan and Korea spend over 70 percent of total family-related spending on formal education; the Nordics spend about 63 percent.
  - Japan spends only 2.4 percent of the total on childcare compared to about 13 percent in the Nordics.
- Age breakdown of childcare spending:
  - Childcare services are generous for ages 0-5 in all countries, with Korea topping the group.
  - Childcare services drop to nearly zero for ages 6-11 in Japan and Korea; Norway and Finland continue to provide childcare for ages 6-11, devoting 24 and 15 percent of total childcare to age 6-11, respectively.
  - Limited availability of affordable after-school care in Japan and Korea can make it difficult for women with school-aged children to continue full-time work.
- Parental leave generosity:
  - Norway: total period of parental leave is 49 weeks at 100 percent coverage and can be extended to 54 weeks or longer with reduced benefits; parental leave can be extended up to 3 years with reduced benefits.
  - Finland: parental leave can be taken until the child reaches age 3; child allowance up to a child’s 9th birthday.
  - Japan: maternal and parental leave and allowance paid for 28 weeks.
  - Korea: maternal and parental leave and allowance paid for the entire birth year.

### VI. Policy discussions and recommendations
- Cash child allowances alone can be counterproductive for increasing regular female employment in Japan and Korea; they may incentivize non-regular employment to stay below income thresholds.
  - JPY 9.6 million (9.6 million (about USD 80 thousand)) is the threshold above which a family receives only one-third of the full childcare allowance; many married women prefer non-regular employment with lower pay so they do not exceed this combined-income threshold.
- Well-targeted and means-tested child allowances can still serve redistributional purposes, despite potential labor-market incidence effects.
- To increase the proportion of regular employment among women:
  - Shift emphasis from universal child cash handouts to policies that reduce the opportunity cost of regular employment (e.g., generous parental benefits tied to employment protections).
  - Expand provision of affordable and flexible childcare and early education, particularly for ages 6-11 (after-school care).
  - Improve access to parental leave and assure the ability to return to the same position after leave, especially for regular employees.
  - Address the gender wage gap to reduce disincentives for well-qualified women to take regular employment.
  - Encourage paternal involvement in childcare (e.g., explicit paternity leave) to support fertility and share caregiving responsibilities.
- Labor market and corporate measures:
  - Promote family-friendly policies and flexible work arrangements, including options for part-time work without compromising benefits and promotion prospects (flexicurity model exemplified by the Nordics).
  - Private-sector efforts to promote diversity and inclusion at the corporate level are crucial alongside government reforms.

### VII. Conclusions
- Increasing FLFP can unlock growth potential, especially in aging economies with abundant skilled female labor, but policy design matters for the type of employment women obtain.
- Child cash allowances and gender wage gaps in Japan and Korea contribute to higher shares of non-regular female employment and reduce regular female employment.
- Greater FLFP need not imply lower fertility when welfare provisions related to childbirth and secure return-to-work arrangements are in place; regular female employment is associated with higher fertility in the studied countries.
- Nordic experiences point to the effectiveness of higher public spending on early childhood education and childcare, more flexible and generous parental leave regimes, and promotion of paternal caregiving in supporting both FLFP and fertility.

### VIII. Key quantitative facts and indicators (preserved exactly)
- Japan FLFP: 65 percent in 2013; 55 percent in 1985.
- Japan: women’s wage was 26 percent lower than men’s wage in Japan (2012).
- Korea: women’s wage was 37 percent lower than men’s wage in Korea (2012).
- Japan: among all female employees, 55 are non-regular workers, of which 60 percent are part-time workers.
- Japan gender wage average: women earn on average just 71 percent of Japanese men (Goldman Sachs, 2014).
- Korea FLFP: 55 percent in 2012.
- Korea fertility rate: 1.24.
- Korea regular female workers: increased from 20 percent in 1990 to nearly 40 percent in 2010.
- Norway FLFP: rose from 44 to 76 percent in 2012.
- Norway: about 83 percent of mothers with small children are employed.
- Norway fertility: about 1.8 percent.
- Finland FLFP: rose from 44 to 73 percent in 2012.
- Finland fertility: 1.8.
- Finland: women make up 70 percent of public-sector employment.
- SVAR sample years and country coverage:
  - Japan: 1997-2012.
  - Korea: 1990-2010.
  - Norway and Finland: 1990-2009.

### IX. Appendix summary — The SVAR Model and data definitions
- SVAR approach and purpose:
  - nonrecursive structural VAR with contemporaneous feedback; structural disturbances assumed mutually uncorrelated; reduced-form and structural parameter relationships specified.
- Identification and restrictions:
  - n = 5 requires 10 restrictions for identification; Sims–Bernanke decomposition and Sims and Zha (2006) approach modified to permit nonrecursive contemporaneous restrictions.
- Endogenous variables, transformation, and stationarity:
  - child cash allowance; gender wage gap; FLFP (or female regular employment/female non-regular employment); fertility rate; female tertiary school enrolment.
  - Each variable is log-transformed and first-differenced.
- Contemporaneous structure (G0) presented in a 5×5 mapping; Female_Em replaced by female regular employment and female non-regular employment depending on specification.
- Appendix 3 — data definitions and sources (country-specific) lists series, available periods, and sources for Japan, Korea, Norway, and Finland (see country-specific entries for 1997-2012, 1990-2010, and 1990-2009 availability).

*Source: Content unit "_wp1556 - 3. Definition and Sources of Data" (excerpts provided).*

### References .............................................................................................................

### References

### Figures
- 1.    Selected OECD Countries: Gender Equality and FLFP, 2012 ...................................................................................... 22
- 2.    Japan, Korea, Norway and Finland: Age-Employment Profile, 1992. .......................................... 23
- 3.    Japan, Korea, Norway and Finland: Female Labor Force Participation Rate (FLFP), 1990-2012.24
- 4.    Japan, Korea, Norway and Finland: Share of Regular and Non-Regular Female Employment  ... 25
- 5.    Selected OECD: Female Labor Force Participation and Fertility Rate, 1970-1984 and 1985-2012 ...................................................................................................................................... 26
- 6.     Japan, Korea, Norway and Finland: The Impulse Response of FLFP Rate to Shocks, 1990-2012 ...................................................................................................................................... 27
- 7.    Japan: Impulse Responses of Female Employment to Shocks, 1997-2012 ................................... 28
- 8.    Korea: Impulse Responses of Female Employment to Shocks, 1990-2010 .................................. 29
- 9.    Japan and Korea: Labor Market Duality and Gender, 2002-2013 ................................................. 30
- 10.  Japan, Korea, Norway and Finland: Public Spending on Family Benefits in Cash, Services and Tax Measures, 2009 .............................................................................................................................. 31
- 11.  Japan, Korea, Norway and Finland: Public Spending on Families and Children, 2009 ................ 32
- 12.  Japan, Korea, Norway and Finland: Childcare, 2009 .................................................................... 33

### Appendices
- 1.    The    SVAR    Model    .......................................................................................................................... 33
- 2.    The Nordics: Impulse Responses of Female Employment ............................................................ 35

*Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1556.pdf*

### 3.    Definition and Sources of Data ...................................................................................

### _wp1556 - 3.    Definition and Sources of Data ...................................................................................

### I. INTRODUCTION — research focus and questions
- Objective: examine drivers of female labor force participation (FLFP) in Japan and Korea in comparison with Nordic countries, with special attention to the composition of employment (regular vs. non-regular).
- Motivation: increase in FLFP can boost growth by increasing labor supply; Japan and Korea face rapidly aging and shrinking populations (IMF, 2013).
- Key research questions:
  - What are the main drivers for FLFP in Japan and Korea?
  - Do regular employment and non-regular employment respond asymmetrically to different shocks?
  - What lessons can Japan and Korea learn from Nordic countries?
- Methodology: Structural Vector Autoregressive (SVAR) model used for empirical analysis to account for endogeneity and correlated determinants of FLFP (e.g., simultaneity between childbirth and participation).

### II. STYLIZED FACTS — cross-country patterns and country snapshots
- Cross-country snapshot (19 OECD countries):
  - Japan and Korea: FLFP lower than the 19-country average; wage gaps and gender gaps in participation large.
  - 2012 wage comparisons: women’s wage was 26 percent lower than men’s wage in Japan and 37 percent lower in Korea.
  - Male–female participation gaps: female labor participation was about 25 percent lower than male LFP in Japan and 30 percent lower in Korea.
  - Fertility: Japan and Korea among countries with low fertility rates.
  - Nordic countries (e.g., Norway, Finland): high FLFP and modest fertility rates; smaller gender gaps.
- Life-cycle employment profile:
  - Japan and Korea exhibit an M-shaped FLFP pattern with a drop in FLFP at age 25-29 and a moderate increase after 45-49; contrasts with Finland and Norway where no such drop is evident.
  - In Japan and Korea, women often drop out during prime working age and return as non-regular workers.
- Japan-specific facts:
  - FLFP: 65 percent in 2013, up from 55 percent in 1985.
  - Composition: among all female employees, 55 are non-regular workers, of which 60 percent are part-time workers.
  - Gender gaps:
    - Japan ranks 105th out of 136 countries in the World Economic Forum’s Global Gender Gap 2013.
    - Women earn on average just 71 percent of Japanese men (Goldman Sachs, 2014).
  - Leadership representation: female administrative/managerial workers only 11.1 percent in Japan (vs. 43.1 percent US and 34.5 percent UK; Cabinet Office, 2013).
  - Institutional features: two-tier tracking systems (sogo shoku vs. ippan shoku) contribute to underinvestment in female human capital and large wage gaps.
- Korea-specific facts:
  - FLFP: 55 percent in 2012 (10 percentage points lower than Japan).
  - Fertility rate: persistently low at 1.24 (lowest among 19 OECD countries).
  - Female representation in top management: 1 percent on boards and 2 percent in executive committees (McKinsey and Company, 2012).
  - Share of regular female workers rose from 20 percent in 1990 to nearly 40 percent in 2010; labor law change (starting in [2007]) limits fixed-term employment to a maximum of two years to encourage conversion to open-ended contracts.
- Nordic countries (Norway, Finland) facts:
  - Norway: FLFP rose from 44 to 76 percent in 2012; about 83 percent of mothers with small children are employed; fertility rates rose to about 1.8 percent.
  - Finland: FLFP rose from 44 to 73 percent in 2012; fertility rate 1.8; women make up 70 percent of public-sector employment.
  - Policy and cultural elements: comprehensive parental provisions, subsidized daycare, paid leave rights, strong paternal involvement relative to Asian peers, and policies designed to reduce incompatibility between employment and childbearing.

### III. EMPIRICAL ANALYSIS — data, methodology, and explanatory variables
- Model and sample:
  - Non-recursive five-variable SVAR estimated for Japan, Korea, Norway, and Finland over 1990–2012.
  - Variables: female labor force participation rate (or female regular and non-regular employment rates), child cash allowances, gender wage gap, fertility rate, female tertiary school enrollment rate.
  - Stationarity treatment: logarithm and first difference of variables.
- Data sources and coverage:
  - Main sources: Statistics Bureau of Japan, CEIC Asia Database, OECD Social Expenditure Database, World Bank.
  - Japan: annual data for 1997-2012.
  - Korea: annual data for 1990-2010 (data availability constraint).
  - Norway and Finland: data coverage 1990-2009 (OECD Social Expenditure Database and World Bank).
  - Note: more detailed data descriptions are in Appendix 3.
- Rationale for SVAR:
  - Addresses endogeneity among child allowances, gender wage gap, FLFP, fertility, and female tertiary enrollment.
  - Useful to trace dynamic transmission and timing of shocks to female labor employment.

- Explanatory variables and expected relationships:
  - Child allowances: may increase incentives to work or reduce them if transfers substitute for market earnings; effect may differ for regular vs. non-regular employment.
  - Fertility: relationship with FLFP has been negative historically but shifted positive after 1985 for OECD countries; policy and norm changes can offset substitution effects.
  - Gender wage gap: used as a proxy for gender inequality; larger gaps expected to discourage FLFP.
  - Female tertiary enrolment: higher education generally associated with higher FLFP, but Japan and Korea show rising education with persistent underutilization.

### IV. EMPIRICAL RESULTS — impulse responses and segmental dynamics
- General FLFP impulse-response findings (standardized to a 1-percent shock; percent changes reported):
  - Child cash allowances:
    - For most countries, child allowances reduce FLFP; Korea is an exception but estimate statistically insignificant.
    - Consistent with prior findings (e.g., Naz, 2004 for Norway).
  - Gender wage gap:
    - A greater gender wage gap reduces FLFP in Japan and Korea.
    - Effect statistically insignificant in Nordic countries, consistent with these countries having very small wage gaps.
  - Fertility rate:
    - Fertility is positively correlated with FLFP in all four countries (consistent with the post-1985 cross-country evidence).
- Japan — regular vs. non-regular employment (impulse-response distinctions):
  - Child allowance shock:
    - Regular female employment: negatively affected in the first year.
    - Non-regular female employment: positively affected.
    - Interpretation: child allowances in Japan increase non-regular employment rather than regular employment.
  - Policy/institutional explanation:
    - Eligibility criteria for child allowances based on family taxation may interact with labor supply decisions and employment type (example discussion begins but content truncated in source).

### V. Key quantitative facts and indicators (preserved exactly as in source)
- Japan FLFP: 65 percent in 2013; 55 percent in 1985.
- Japan: women’s wage was 26 percent lower than men’s wage in Japan (2012).
- Korea: women’s wage was 37 percent lower than men’s wage in Korea (2012).
- Japan: among all female employees, 55 are non-regular workers, of which 60 percent are part-time workers.
- Japan gender wage average: women earn on average just 71 percent of Japanese men (Goldman Sachs, 2014).
- Korea FLFP: 55 percent in 2012.
- Korea fertility rate: 1.24.
- Korea regular female workers: increased from 20 percent in 1990 to nearly 40 percent in 2010.
- Norway FLFP: rose from 44 to 76 percent in 2012.
- Norway: about 83 percent of mothers with small children are employed.
- Norway fertility: about 1.8 percent.
- Finland FLFP: rose from 44 to 73 percent in 2012.
- Finland fertility: 1.8.
- Finland: women make up 70 percent of public-sector employment.
- SVAR sample years and country coverage:
  - Japan: 1997-2012.
  - Korea: 1990-2010.
  - Norway and Finland: 1990-2009.

*Italicized source: Content unit "_wp1556 - 3.    Definition and Sources of Data" (excerpts provided).*

### 9.6 million (about USD 80 thousand) is eligible to receive the full amount of childcare allowance. On

### _wp1556 - 9.6 million (about USD 80 thousand) is eligible to receive the full amount of childcare allowance. On

### Empirical findings: impacts on female labor force participation (FLFP) and employment composition
- JPY 9.6 million (9.6 million (about USD 80 thousand)) is the threshold above which a family receives only one-third of the full childcare allowance; many married women prefer non-regular employment with lower pay so they do not exceed this combined-income threshold.  
- Child allowances can affect regular and non-regular employment asymmetrically:
  - In Japan and Korea, child allowances reduce regular female employment and can increase non-regular employment.
  - In Norway and Finland (the Nordics), child allowances increase regular female employment and discourage non-regular employment.
- Gender wage gap shock effects:
  - An increase in the gender wage gap discourages regular female employment and increases non-regular female employment in Japan and Korea.
  - Female regular employment in Korea responds negatively by 1.4 percentage points to the gender wage gap (as opposed to 0.3 percentage points in Japan).
  - The gender wage gap effect is statistically insignificant in Norway and Finland.
- Fertility effects:
  - Higher fertility is associated with higher regular female labor participation in both Asia and the Nordics.
  - In Korea, the positive impact of fertility on regular employment is 4.5 percentage points within one year, more than 10 times the effect in Japan.
  - Regularly employed workers’ access to paid and longer parental leave makes continued employment after childbirth more feasible; non-regular employees have fewer or no such benefits, so childbirth can reduce non-regular female participation.
- Tertiary school enrolment:
  - Tertiary enrolment helps increase regular employment in Korea and the Nordics and reduces non-regular employment in those countries.
  - In Japan, tertiary school enrolment rate does not affect female labor employment significantly; many non-regular female workers in Japan often have college degrees.

### Cross-country differences and institutional context
- Labor market duality and gender bias:
  - Japan: non-regular workers concentrated among women (and the elderly); many are voluntary part-time non-regular workers who work less than 35 hours a week.
  - Korea: non-regular workers found across genders; only 33 percent of non-regular workers work part-time, indicating many are involuntary full-time non-regular workers.
- Historical/institutional evolution:
  - Both Japan and Korea shifted away from long-term employment, enterprise unions, and seniority-based wages following prolonged economic recessions, increasing non-regular employment.
- Role of paternal involvement:
  - Nordic countries explicitly offer paternity leave; paternal involvement in childcare is linked to higher likelihood of having a second child.

### Public spending on family and child benefits (OECD-based broader definition)
- Overall spending patterns:
  - Total family benefits spending is more than twice as much in the Nordics compared to Japan and Korea.
  - Norway and Finland spend more than Japan and Korea in most family-benefit categories, except financial support via the tax system.
  - Japan spends about 0.5 percent of GDP on financial support for families through the tax system; Finland has no such policy.
- Child-related transfers and services:
  - Norway and Finland spend about three times as much on child-related transfers to families with children as Japan (cash transfers here include cash allowance plus income support for parental leave and single parent families).
  - Korea spends very little in the child-related transfer category.
  - Korea spends about 0.7 percent of GDP on services for families with children (e.g., childcare and early education); Japan spends 0.5 percent; the Nordics spend about 2 percent.
- Composition of family-related spending (including formal education):
  - Japan and Korea spend over 70 percent of total family-related spending on formal education; the Nordics spend about 63 percent.
  - Japan spends only 2.4 percent of the total on childcare compared to about 13 percent in the Nordics.
- Age breakdown of childcare spending:
  - Childcare services are generous for ages 0-5 in all countries, with Korea topping the group.
  - Childcare services drop to nearly zero for ages 6-11 in Japan and Korea; Norway and Finland continue to provide childcare for ages 6-11, devoting 24 and 15 percent of total childcare to age 6-11, respectively.
  - Limited availability of affordable after-school care in Japan and Korea can make it difficult for women with school-aged children to continue full-time work.
- Parental leave generosity:
  - Norway: total period of parental leave is 49 weeks at 100 percent coverage and can be extended to 54 weeks or longer with reduced benefits; parental leave can be extended up to 3 years with reduced benefits.
  - Finland: parental leave can be taken until the child reaches age 3; child allowance up to a child’s 9th birthday.
  - Japan: maternal and parental leave and allowance paid for 28 weeks.
  - Korea: maternal and parental leave and allowance paid for the entire birth year.

### Policy discussions and recommendations
- Cash child allowances alone can be counterproductive for increasing regular female employment in Japan and Korea; they may incentivize non-regular employment to stay below income thresholds.
- Well-targeted and means-tested child allowances can still serve redistributional purposes, despite potential labor-market incidence effects.
- To increase the proportion of regular employment among women:
  - Shift emphasis from universal child cash handouts to policies that reduce the opportunity cost of regular employment (e.g., generous parental benefits tied to employment protections).
  - Expand provision of affordable and flexible childcare and early education, particularly for ages 6-11 (after-school care).
  - Improve access to parental leave and assure the ability to return to the same position after leave, especially for regular employees.
  - Address the gender wage gap to reduce disincentives for well-qualified women to take regular employment.
  - Encourage paternal involvement in childcare (e.g., explicit paternity leave) to support fertility and share caregiving responsibilities.
- Labor market and corporate measures:
  - Promote family-friendly policies and flexible work arrangements, including options for part-time work without compromising benefits and promotion prospects (flexicurity model exemplified by the Nordics).
  - Private-sector efforts to promote diversity and inclusion at the corporate level are crucial alongside government reforms.

### Conclusions
- Increasing FLFP can unlock growth potential, especially in aging economies with abundant skilled female labor, but policy design matters for the type of employment women obtain.
- Child cash allowances and gender wage gaps in Japan and Korea contribute to higher shares of non-regular female employment and reduce regular female employment.
- Greater FLFP need not imply lower fertility when welfare provisions related to childbirth and secure return-to-work arrangements are in place; regular female employment is associated with higher fertility in the studied countries.
- Nordic experiences point to the effectiveness of higher public spending on early childhood education and childcare, more flexible and generous parental leave regimes, and promotion of paternal caregiving in supporting both FLFP and fertility.

*Source: IMF Working Paper content (pages 12–19 of the provided unit).*

### References

### _wp1556 - References

### References
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- Brewster, K. and R. Rindfuss (2000), “Fertility and women’s employment in industrialized countries”. Annual Review of Sociology 26: 271-96.
- Dao, M. et al (2014), “Strategies for Reforming Korea’s Labor Market to Foster Growth”, IMF Working Paper, WP/14/137.
- Del Boca et al. (2003), “Labor market participation of women and fertility: the effect of social policies”. Report prepared for the Rudolf de Benedetti Benedetti Foundation Conference, July. www.frdb.org/upload/file/copy_0_paper_delboca.pdf
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### Figures and Captions (selected)
- Figure 1. Selected OECD countries: Gender equality and FLFP, 2012
  - Source: OECD statistics and World Economic Forum Gender Gap Report.
  - Variables shown include: FLFP (percent); Gender wage gap (ratio); Fertility (ratio); FLFP/MLFP (percent); Female ter. school enrolment/Male ter. school enrolment (ratio); Political emowerment (index).
  - Country orderings illustrated include Sweden, Norway, Denmark, Canada, Netherlands, Finland, Germany, Australia, Portugal, Spain, UK, United States, France, Japan, Ireland, Belgium, Greece, Korea, Italy.

- Figure 2. Japan, Korea, Norway, Finland: Age-Employment Profile, 1992 (in percent)
  - Source: OECD Family Database.
  - Age groups: 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64.
  - Panels show Female Employment Profile Over the Life-Course by Country and Japan/Korea/Finland/Norway men vs women profiles.

- Figure 3. Japan, Korea, Norway and Finland: Female Labor Force Participation Rate, 1990-2012 (Percent)
  - Sources: World Bank dataBank.
  - Timeline: 1990, 1992, 1994, 1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012.

- Figure 4. Japan, Korea, Norway and Finland: Share of Regular and Non-regular Female Employment
  - Source: Labor Force Survey, Statistics Bureau, Japan; World Bank, CEIC and OECD.
  - Years compared: 1997 and 2012; Japan series 1997-2012 and Norway series 1990-2009 (percent; RHS = non-regular employment).

- Figure 5. Selected OECD: Female Labor Force Participation and Fertility Rate, 1970-1984 and 1985-2012
  - Source: OECD Labor Force Survey.
  - Regression lines: 1970-1984: y = -0.017x + 2.9124, R² = 0.1861; 1985-2012: y = 0.0121x + 0.9007, R² = 0.2785.

- Figure 6. Japan, Korea, Norway, and Finland: The impulse response of FLFP rate to shocks, 1990-2012
  - Sources: Authors’ calculations based on Statistics Bureau Japan, CEIC Asia Database, OECD Social Expenditure Database and World Bank dataBank.
  - Notes: Impulse responses presented over a 3-year period. All shocks standardized to a 1-percent shock. Vertical axis shows approximate percentage change. Confidence bands constructed by Monte Carlo simulation.
  - Vertical axis tick values shown include 0.012, -0.006, -0.004, -0.002, 0.000, 0.002, 0.004, 0.006, 0.008, 0.010 and other ranges down to -0.015 and up to 0.015 in some panels.

- Figure 7. Japan: The Impulse Responses of Female Employment to Shocks, 1997-2012
  - Panels (a)-(h) cover: regular and non-regular female employment responses to Child allowance shock, Gender wage gap shock, Fertility shock, Female Tertiary Enrollment Shock.
  - Sources: Authors’ calculations based on Statistics Bureau Japan, CEIC Asia Database and World Bank dataBank.
  - Notes: 3-year impulse responses; shocks standardized to a 1-percent shock. Vertical axis tick values include -0.0100 to 0.0075 and -0.0050 to 0.0100 ranges.

- Figure 8. Korea: The Impulse Responses of Female Employment to Shocks, 1990-2010
  - Panels (a)-(h) mirror Figure 7 structure for Korea.
  - Sources: Authors’ calculations based on CEIC Asia Database, OECD Social Expenditure Database and World Bank databank.
  - Notes: 3-year impulse responses; shocks standardized to a 1-percent shock. Vertical axis tick values include -0.03 to 0.04 and -0.0075 to 0.0125 ranges.

- Figure 9. Japan and Korea: Labor Market Duality and Gender, 2002-13 (Percent)
  - Sources: Labor Force Survey, Statistics Bureau, Japan and CEIC Asia Database.
  - Series plotted include: Non-regular workers / total workers (2002-2012), Non-regular female workers / total non-regular (2002-2012), Non-regular male workers / total male workers (2002-2012), Non-regular female workers / total female workers (2002-2012).

- Figure 10. Japan, Korea, Norway and Finland: Public Spending on Family Benefits in Cash, Services and Tax Measures, 2009 (Percent of GDP)
  - Sources: Public Spending on Family Benefits, OECD Family database.
  - Notes define components 1–4 and state: Total public spending on family benefits include 1,2 and 3 above.
  - Variables plotted include: Child-related cash transfer to family with children_1; Public spending on services for families with children_2; Financial support for families provided through the tax system_3; Total public spending on family benefits_4.

- Figure 11. Japan, Korea, Norway and Finland: Public spending on families and children, 2009 (in percent)
  - Source: OECD Family Database, 2009.
  - Japan breakdown: Cash benefits 16.9, Childcare 2.4, Other 7.8, Education 73.0.
  - Finland breakdown: Cash benefits 17.3, Childcare 12.8, Other 6.0, Education 63.9.
  - Norway breakdown: Cash benefits 16.2, Childcare 13.2, Other 7.5, Education 63.1.
  - Korea breakdown: Cash benefits 4.7, Childcare 12.9, Other 7.9, Education 74.6.

- Figure 12. Japan, Korea, Norway and Finland, Childcare, 2009 (Percent of total spending on childcare for children aged 0-11)
  - Source: Public Spending by Age of Children, OECD Family Database.
  - Age categories: age 0-5 and age 6-11.

*Source: _wp1556 - References (PDF).*

### Appendix 1.  The SVAR Model

### Appendix 1.  The SVAR Model

### SVAR approach and purpose
- The SVAR approach allows for contemporaneous feedback between variables while imposing the minimal structural restrictions.
- An analysis of contemporaneous relationships between female labor force participation and key relevant variables requires restrictions on the correlation structure of the residuals based on the theory.
- The nonrecursive structural VAR model is specified as:
  - tt eZLG)(, where G(L) is a matrix polynomial in the lag operator L, tZ is a n × 1 data vector, and et is a n × 1 structural disturbance vector.
  - et is serially uncorrelated and var(et) = Λ. Λ is a diagonal matrix where diagonal elements are the variances of structural disturbance; hence, structural disturbances are assumed to be mutually uncorrelated.
- The reduced-form equation is:
  - tt ZLBZ)(, where B(L) is a matrix polynomial (without the constant term) with lag operator L.
- G0 is a non-singular coefficient matrix of L0 in G(L), representing contemporaneous coefficients in the structural form; G0(L) is the coefficient matrix in G(L) without contemporaneous coefficient G0.
  - Relationship: )()(
0
0
LGGLG
- Parameters in reduced-form and structural form satisfy:
  - 1
0
1
0
)(

GGLB

### Identification and restrictions
- Only through sample estimates of Σ can the maximum likelihood estimates of Λ and G0 be obtained.
- The right-hand side of Equation (4) has n2 unknown parameters to be estimated. Because Σ contains n × (n + 1)/2 known parameters, at least n × (n − 1)/2 restrictions need to be imposed on G0 for identification.
  - In this case, n = 5 and we require 10 restrictions.
- To identify the structural shocks, a Sims–Bernanke decomposition of the non-recursive matrix and a variance–covariance matrix of the reduced-form VAR residual (εt) are used to generate the structural disturbance (et).
- For the restrictions on the contemporaneous structural parameters G0, the paper follows Sims and Zha (2006) and modifies their model to permit nonrecursive contemporaneous restrictions across different equations.

### Endogenous variables, transformation, and stationarity
- The vector of endogenous variables includes five variables:
  - child cash allowance
  - gender wage gap
  - FLFP (or female regular employment/female non-regular employment)
  - fertility rate
  - female tertiary school enrolment
- Each variable is log-transformed and first-differenced to ensure stationarity.

### Contemporaneous structure (G0) used in the paper
- The contemporaneous relationships between structural disturbances and reduced-form VAR residuals are presented as a 5×5 mapping (structural disturbances on left; reduced-form residuals on right). The paper presents this mapping as follows:

  enrolmenttertiaryFemale
  rateFertility
  EmFemaleorFLFP
  gapwageGender
  allowanceChild
  enrolmenttertiaryFemale
  rateFertility
  EmFemaleorFLFP
  gapwageGender
  allowanceChild
  g
  gg
  gg
  gggg
  gg
  g
  e
  e
  e
  e
  e
  
  
  
  
  
  __
  0.10.0530.00.0
  0.00.1430.041
  35340.13231
  250.0230.10.0
  0.0140.00.00.1

- Note: Female_Em in equation (5) is replaced by female regular employment and female non-regular employment depending on the model specifications.

### Economic reasoning behind contemporaneous structure
- Child allowances:
  - Included because they are generally considered to impact women’s fertility decision and to help alleviate the cost burden of raising children.
  - Expected to lead to higher fertility if effective.
  - Expected to affect women’s labor force participation, but effectiveness on participation rates is ambiguous and may be concentrated among low-income households with liquidity constraints; under such circumstances, increases in child allowances could lead to higher FLFP.
- Gender wage gap:
  - Used as a proxy for gender-based inequality, considered a main obstacle to women’s labor force participation.
  - Reverse causality is possible: lower female labor participation can widen the gender wage gap.
  - The model imposes a structure on the gender wage gap as a function of FLFP and education level in the second row.
- FLFP (female labor force participation):
  - Assumed to be affected contemporaneously by child allowances, the gender wage gap, FLFP itself, fertility, and the school enrollment rate (third row).
- Fertility rate:
  - Treated as simultaneously determined with FLFP because women’s decision to work is closely related to the decision to have children; treating one as exogenous would bias estimates.
  - Assumed to be related contemporaneously to child allowances and FLFP.
- Female tertiary school enrolment:
  - Can be affected by FLFP due to the tradeoff between attending school and working and/or having children.

---

### Appendix 3 — Data definitions and sources (country-specific)
- Notes: Definitions of non-regular workers vary slightly by data source. Examples given in source text:
  - Japan: non-regular employee categories include part-time worker, Arubaito (temporary worker), dispatched worker from temporary labor agency, entrusted employee, contract employee and other.
  - Korea: non-regular employees include self employed, unpaid family workers, temporary employee and daily workers.

- Japan (Available Period and Source):
  - Female regular employment: Female regular employment out of total female employment — 1997-2012 — Labor Force Survey, Statistics Bureau, Japan
  - Female nonregular employment: Female nonregular employment out of total female employment — 1997-2012 — Labor Force Survey, Statistics Bureau, Japan (Part-time worker,Arbeit (temporary worker),Entrusted employeeDispatched worker from temporary labor agency,Contract employee,Other)
  - Child benefits: Child benefits allowance — 1997-2012 — CEIC Asia Database
  - Gender wage gap: Japanese male wage minus Japanese female wage — 1997-2012 — CEIC Asia Database
  - Fertility rate: Total birth per woman — 1997-2012 — World Bank databank
  - Female tertiary school enrolment: Female tertiary school enrolment out of all tertiary enrolments — 1997-2012 — World Bank databank

- Korea (Available Period and Source):
  - Female regular employment: Female regular employment out of total female employment — 1990-2010 — CEIC Asia Database
  - Female nonregular employment: Female nonregular employment out of total female employment — 1990-2010 — CEIC Asia Database (Self-employed, Unpaid family worker,Temporary employee, Daily worker)
  - Child benefits: Cash benefits plus Benefits in kind (Public expenditure on family) — 1990-2010 — OECD Social Expenditure Database
  - Gender wage gap: Difference between male and female median wages divided by the male median wages — 1990-2010 — OECD Social Expenditure Database
  - Fertility rate: Total birth per woman — 1990-2010 — World Bank databank
  - Female tertiary school enrolment: Female tertiary school enrolment out of all tertiary enrolments — 1990-2010 — World Bank databank

- Norway (Available Period and Source):
  - Female regular employment: Female regular employment out of total female employment — 1990-2009 — World Bank databank
  - Female nonregular employment: Female nonregular employment out of total female employment — 1990-2009 — World Bank databank
  - Child benefits: Cash benefits plus Benefits in kind (Public expenditure on family) — 1990-2009 — OECD Social Expenditure Database
  - Gender wage gap: Difference between male and female median wages divided by the male median wages — 1990-2009 — OECD Social Expenditure Database
  - Fertility rate: Total birth per woman — 1990-2009 — World Bank databank
  - Female tertiary school enrolment: Female tertiary school enrolment out of all tertiary enrolments — 1990-2009 — World Bank databank

- Finland (Available Period and Source):
  - Female regular employment: Female regular employment out of total female employment — 1990-2009 — World Bank databank
  - Female nonregular employment: Female nonregular employment out of total female employment — 1990-2009 — World Bank databank
  - Child benefits: Cash benefits plus Benefits in kind (Public expenditure on family) — 1990-2009 — OECD Social Expenditure Database
  - Gender wage gap: Difference between male and female median wages divided by the male median wages — 1990-2009 — OECD Social Expenditure Database
  - Fertility rate: Total birth per woman — 1990-2009 — World Bank databank
  - Female tertiary school enrolment: Female tertiary school enrolment out of all tertiary enrolments — 1990-2009 — World Bank databank

*Appendix 1.  The SVAR Model*

---


_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1556.pdf_