Chapter

Chapter 6C. Korea

Editor(s):
Kalpana Kochhar, Sonali Jain-Chandra, and Monique Newiak
Published Date:
February 2017
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Author(s)
Mai Dao, Davide Furceri, Jisoo Hwang and Meeyeon Kim 

Unemployment rates have decreased in Korea over the past decade despite a slowdown in the quantity of goods and services produced there. The overall unemployment rate declined from about 4½ percent in 2000 to about 3½ percent in 2014. The Korean unemployment rate is currently among the lowest in Organisation for Economic Co-operation and Development (OECD) countries. However, the existence of a two-tiered labor market (which includes a high share of nonregular workers) and the underemployment in some segments of the population (notably, youth and women) are important labor market challenges which contribute to lower potential growth.

This analysis focuses on the underemployment of women, provides an analysis of trends and determinants of female labor force participation in Korea and other OECD countries, and includes an empirical analysis that points toward reforms that could boost female participation over the medium term. Based on the results, the benefits of comprehensive structural reforms are likely to be considerable over the medium term. In particular, comprehensive policy reforms aimed at reducing labor market distortions that inhibit labor force participation could increase female participation rates by about 8 percentage points over the medium term, which would reduce by a third the gap between the rates of male and female participation. Examples of such reforms include making the tax treatment of second earners in households more neutral in comparison with that of single earners, increasing childcare benefits, and facilitating more part-time work opportunities.

Korea’s Female Labor Force Participation Rate

Female labor force participation has increased markedly in Korea over the last two decades, from about 50 percent in 1990 to 62 percent in 2011, but significant gender differences persist (Figure 6.23). In particular, male participation rates are still 20 percentage points higher than those for females, with the gender gap particularly high—above 30 percent—for prime working-age groups (ages 30–34, 35–39, and 40–44) (Figure 6.24).

Figure 6.23.Trends in Korean Labor Force Participation Rates, 1980–2014

Source: Organisation for Economic Co-operation and Development.

Figure 6.24.Korea’s Labor Force Participation Gender Gap, 2014

(Percent)

Source: Organisation for Economic Co-operation and Development.

Female participation rates are not only low compared with those for men in Korea, but are also low compared with female participation rates in other OECD countries. In fact, female labor force participation rates in Korea are among the lowest in the OECD (see Figure 6.25) and almost 20 percentage points below those prevailing in the best performing countries—Denmark, Finland, Iceland, Norway, and Sweden.

Figure 6.25.Female Participation Rates Across Countries, 2014

(Percent)

Source: Organisation for Economic Co-operation and Development.

Removing policy distortions that prevent female participation is key to fostering growth and reducing inequality, even if part of the cross-country differences in participation rates may simply mirror differences in sociocultural factors. First, higher female participation rates can increase the labor supply, offsetting downward pressures from population aging and thereby boosting potential output over the medium term. Second, as preferences for female participation tend to be higher than the actual female participation rates, removing market distortions that inhibit female participation can lead to a higher level of aggregate income and welfare. Third, reducing the gap between male and female participation can help to reduce inequality.

The next section assesses the roles of various factors determining the pattern of female participation rates in Korea compared with other OECD countries, focusing on policy instruments that can be used to reduce market distortions and raise the female participation rates.

Determinants of Female Labor Force Participation in Korea

The determinants of labor force participation in Korea compared with other OECD countries are estimated using panel regressions for an unbalanced sample of 30 OECD countries over the period 1985–2011. In detail, the following difference-in-difference equation is estimated:

in which LPR indicates the female labor force participation rates; αi are the country fixed effects, which capture unobserved factors including sociocultural ones; τt are time fixed effects which capture the impacts of common and country-specific unobserved shocks affecting the participation rates; and X is a set of policy variables that have been found in the literature to be robust determinants of female participation (Jaumotte 2003). In order to make the results country specific for Korea, all variables are considered as deviations with respect to Korea’s ones. The set of explanatory variables include: (1) the tax wedges between second earners and single individuals (computed as the ratio of the tax on second earners to the average tax rate of a single individual with the same gross income), (2) childcare benefits (calculated as the increase in household disposable income from childcare benefits), (3) tax incentives to part-time work, (4) public spending on preprimary education, (5) social expenditures on families,1 (6) the female and male unemployment rates, (7) the wage gaps between males and females, (8) the degrees of employment protection legislation, (9) the numbers of children per woman (measured by the ratios of children ages 0–14 to women ages 15–64), (10) the female tertiary education rates, and (11) the logs of GDP per capita. Additional variables found to be typically associated with female participation rates, such as child subsidies and paid parental leave, have not been included due to limited time series availability for Korea.2

The results from the estimation of equation 1 are reported in Table 6.3. The first column of the table presents the results for the baseline specification, which includes both time and country fixed effects and focuses on the key policy determinants typically found in the literature to affect female participation (Jaumotte 2003). The main results are that: (1) the wedge between the tax rates of second earners and single individuals has a negative impact on female labor force participation,3 (2) an increase in childcare benefits has a statistically significant and large impact in boosting female participation rates, (3) tax incentives to part-time work tend to increase female participation, and (4) an increase in the probability of being employed (proxied by unemployment outcomes for both males and females) tends to improve participation. In contrast, public spending on preprimary education and on families does not have a significant impact on female labor force participation in Korea compared with other countries. The results, particularly for the tax wedge and childcare benefits, are robust to different specifications, different sets of controls, and step-wise regression (columns II through VII).4 Finally, while endogeneity may be an issue, particularly for the measures of unemployment rates, the results are robust to endogeneity checks and instrumental variable regression (Table 6.4).

Table 6.3.Determinants of Female Labor Force Participation in Korea
BaselineRobustness Checks
Independent variable(1)(II)(III)(IV)(V)(VI)(VII)1
Tax second earner−0.182**−0.339***−0.230**−0.189**−0.264***−0.309**−0.350***
(−2.12)(−3.73)(−2.46)(−2.43)(−3.19)(−2.25)(−4.20)
Childcare benefits0.389**0.448**0.467**0.263*0.359**0.811***0.559***
(2.18)(2.06)(2.30)(1.81)(2.18)(3.15)(3.45)
Tax incentive to part time0.281*0.372*0.1790.216*0.032−0.513
(1.68)(1.80)(0.98)(1.76)(0.22)(−1.06)
Public spending on preprimary−0.002−0.005−0.002−0.005
education (log)(−0.45)(−0.77)(−0.58)(−0.22)
Public expenditure on family (log)0.0050.011−0.0510.015
(0.40)(1.37)(−0.84)(0.57)
Male unemployment (log)−0.030**−0.041***−0.046***−0.046***−0.038*−0.041**
(−2.34)(−3.56)(−4.24)(−3.88)(−1.78)(−2.34)
Female unemployment (log)−0.025**−0.011−0.006−0.015*0.001
(−2.24)(−0.91)(−0.52)(−1.07)(0.03)
Number of children (log)0.0680.041***0.290***0.324
(0.57)(3.67)(4.10)(0.88)
Employment protection−0.024
legislation (log)(−0.23)
Wage gap (log)−0.002
(−0.17)
Female tertiary education (log)−0.085
(−0.82)
GDP per capita (log)0.051
(1.11)
Country-specific time trendsNoYesNoNoNoNoNo
Time fixed effectsYesNoNoYesYesYesYes
N2372372373333336666
Adjusted FC’0.990.990.990.990.980.990.99
Sources: Organisation for Economic Co-operation and Development; and IMF staff calculations.Note: Country fixed effects included but not reported. T-statistics based on robust standard errors in parentheses, *p < 0.1; **p < 0.05; ***p < 0.01.

Results based on stepwise regression.

Table 6.4.Determinants of Korean Female Labor Force Participation, OLS versus IV
Ordinary Least SquaresInstrumental Variable1
Independent variable(I)(II)
Tax second earner−0.339***−0.196**
(−3.73)(−1.99)
Childcare benefits0.448**0.426**
(2.06)(2.49)
Tax incentive to part time0.372*0.329*
(1.80)(1.94)
Public spending on pre-primary education (log)−0.005−0.009
(−0.77)(−1.00)
Public expenditure on family (log)0.0110.001
(1.37)(0.06)
Male unemployment (log)−0.041***−0.026
(−3.56)(−1.06)
Female unemployment (log)−0.011−0.029
(−0.91)(−1.00)
Number of children (log)0.041***0.064
(3.67)(0.52)
Kleibergen-Paap statistic p-value in parentheses)19.864
(0.02)
Hansen J statistic (p-value in parentheses)5.946
(0.65)
Country-specific time trendsYesNo
Time fixed effectsNoYes
N237237
Adjusted R20.990.99
Sources: Organisation for Economic Co-operation and Development; and IMF staff calculations.Notes: Country fixed effects included but not reported. T-statistics based on robust standard errors in parentheses, * p < 0.1; ** p < 0.05; *** p < 0.01.

Public expenditures on preprimary education and family, number of children, and unemployment rates instrumented by their Jagged values (up to 3 lags), as well as all exogenous variables of the model.

The results presented in Table 6.5 suggest that the effects of these variables vary across different age groups. First, these policies do not seem to significantly affect participation for those ages 55–64. Second, while the tax wedge and child-care benefits affect female participation in all other age groups, part-time regulations seem to significantly affect participation only of women ages 25–39.

Table 6.5.Determinants of Korean Female Labor Force Participation by Age Group
Dependent variable15–2425–3940–5455–64
Tax second earner−0.955***−0.151*−0.289**−0.457
(−2.05)(−1.72)(−2.52)(−1.61)
Childcare benefits2.603**0.474**0.523*−0.472*
(2.15)(2.06)(1.93)(−1.86)
Tax incentive to part time0.3000.462*0.2170.950
(0.41)(2.26)(0.92)(1.32)
Male unemployment (log)−0.031−0.047***−0.038**0.003
(−0.53)(−4.47)(−2.20)(0.07)
Female unemployment (log)−0.020−0.003−0.009−0.086*
(−0.20)(−0.21)(−0.59)(−1.83)
Time fixed effectsYesYesYesYes
N212212212212
Adjusted R20.970.990.990.29
Sources: Organisation for Economic Co-operation and Development; and IMF staff calculations.Notes: Country fixed effects and the controls presented in Table 6.3 included but not reported. T-statistics based on robust standard errors in parentheses, * p < 0.1; ** p < 0.05; *** p < 0.01.

Finally, it is important to stress that although policy actions can in principle boost female participation rates in Korea, much of the cross-country variation in female labor force participation is captured by country fixed effects, suggesting that unobserved factors including differences in sociocultural factors and institutional features play the most important roles. The compelling question then is: What would be the potential impact of reforms aimed at reducing labor market distortions?

Policy Simulation

In order to illustrate the potential impact of policy measures on female labor force participation, a number of policy scenarios can be simulated using the results of the estimated equation presented in the previous section. Before turning to the analysis, however, it is important to highlight the limitations of this approach. First, the results are sensitive to the uncertainties associated with the estimates of the effects of structural policies on labor force participation. Second, the simulations assume it is possible to disentangle the effects of specific reforms, abstracting from the complementarity of these reforms and the appropriate sequence of implementation. Third, financing requirements associated with the simulated policy changes may imply a need for significant increases in (other) tax rates with repercussions on labor force participation. These general equilibrium effects have not been taken into account in the simulations, which therefore may give a biased picture of the effects of policy reforms (Jaumotte 2003). With these caveats in mind, this analysis can still provide some indication of the magnitude of the effects of such reforms in boosting female labor force participation in Korea over the medium term.

The effects of structural reforms on Korea’s female labor force participation are computed by simulating a convergence of policy settings toward those prevailing in benchmark countries, identified as those with the lowest restrictions. In detail, the potential female participation gains (gi) from these structural reforms are simulated as:

in which βi is, for each indicator I, the estimated parameter of the effect of structural reform on female labor force participation reported in the first column of Table 6.2, and Ik and Ib are the values of the indicators in Korea and in the benchmark countries, respectively.

The average participation gain from a reform in the tax treatment of second earners is about ½ percentage point. Policies aimed at reducing unemployment would lead to an increase of about 1.4 percentage points. Reform of the tax incentives to part-time work would result in an increase of about 2 percentage points. Finally, reforms aimed at closing the gap between Korea and the benchmark countries in terms of childcare benefits would result in a significant increase in participation of about 4 percentage points. Combining these scenarios, the results suggest that a comprehensive set of reforms aimed at reducing the distortions captured by these indicators would lead to an increase in female participation rates of about 8 percentage points over the medium term, which would imply a reduction of the gap between male and female participation of about 33 percent.

Conclusions

After a period of exceptional growth, there has been a gradual slowdown in Korean economic growth since the mid-1990s. Although this slowdown has not translated into rising unemployment rates (which have continued to decline and are among the lowest among OECD countries), labor market segmentation and the underemployment of some segments of the population, notably women, are important labor market challenges that also contribute to lower potential growth. Boosting Korea’s female labor force participation requires a comprehensive set of structural reforms aimed at:

  • Increasing investment in public childcare and childcare benefits

  • Improving work-life balance by facilitating more part-time work opportunities

  • Making the tax treatment of second earners in households more neutral compared with that of single earners

  • Addressing the two-tiered labor market to improve job opportunities for women

This analysis suggests that the benefits of such reforms are likely to be considerable over the medium term. In particular, comprehensive policy reforms aimed at reducing labor market distortions that inhibit labor force participation could increase female participation rates by about 8 percentage points over the medium term, which would reduce by a third the gap between the rates of male and female participation. Examples of such reforms include making the tax treatment of second earners in households more neutral in comparison with that of single earners, increasing childcare benefits, and facilitating more part-time work opportunities.

Indeed, these measures are consistent with the Korean authorities’ broad reform agenda for tackling labor market duality and boosting the employment rate to 70 percent by 2017. This “70 Percent Roadmap” shifts the focus of job creation from the current male, manufacturing, and conglomerate orientation toward females, services, and small- and medium-sized enterprises.

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A version of this analysis was published as Dao and others 2014.

Public expenditure on families is composed of (1) child-related cash transfers to families with children: child allowances, with payment levels that in some countries vary with the ages of the children, and public income support payments during periods of parental leave; (2) public spending on services for families with children: direct financing and subsidizing of providers of childcare and early education facilities, public childcare support through earmarked payments to parents, public spending on assistance for young people and residential facilities, and public spending on family services including center-based facilities and home help services for families in need; and (3) financial support for families provided through the tax system: tax expenditures toward families including tax exemptions (for example, income from childcare benefits that is not included in the tax base), child tax allowances (amounts for children that are deducted from gross income and not included in taxable income), and child tax credits (amounts that are deducted from tax liabilities).

Jaumotte (2003), based on a sample of 20 OECD countries (excluding Korea), finds that childcare subsidies and parental leave have positive effects on female participation rates.

The tax wedge is computed as the ratio of Tax second earner to Tax single individual. The tax second earner is calculated as: Tax second earner = 1(Household Net Income)B(Household Net Income)A(Household Net Income)B(Household Net Income)A

in which A represents the case in which the wife does not earn any income and B the case in which the wife’s gross earnings are 67 percent that of the average production worker. The tax single individual is computed using the same formula, although in this situation the household is only made up of the individual. Note that the specification with time fixed effects is equivalent to a regression in which all variables are demeaned from Korea’s. The results presented in column II, which do not consider time fixed effects, are qualitatively similar, even though the effects of the tax wedge, childcare benefits, and tax incentives to part-time are larger in absolute values.

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