The impact of expected child-rearing expenses on childbirth based on the matching of two Korean panel data

International Journal of Child Care and Education Policy

Table 3 Impact of expected child-rearing cost on childbirth: total and in accordance with income level

Dependent variable: childbirth = 1, no childbirth = 0	Total	Low income	High income
Panel A: No additional explanatory variables
Expected child-rearing cost	−0.00221*	−0.00402*	−0.00038
Expected child-rearing cost	(0.00107)	(0.00221)	(0.00247)
Pseudo R ²	0.0554	0.0698	0.0351
Panel B: Added the age of mothers and employment status to variables
Expected child-rearing cost	−0.00207*	−0.00325*	0.00014
Expected child-rearing cost	(0.00119)	(0.00177)	(0.00136)
Pseudo R ²	0.0784	0.0950	0.0487
Panel C: Added family structures (such as living with grandparents) to variables
Expected child-rearing cost	−0.00102	−0.00132	−0.00068
Expected child-rearing cost	(0.00228)	(0.00154)	(0.00291)
Pseudo R ²	0.1201	0.1154	0.0685
Panel D: Added the level of parents’ education to variables
Expected child-rearing cost	−0.00084	−0.00192	0.00321
Expected child-rearing cost	(0.00144)	(0.00141)	(0.00261)
Pseudo R ²	0.1751	0.1458	0.1384
Number of samples	3052	1526	1526

This is a logit regression conducted based on dependent variables, childbirth history of women of childbearing age in KLoWF for five years from 2007 to 2012, and explanatory variables, variable of nurturing costs imputed using PSKC. The classification between low-income and high-income classes was based on median income in the sample. Coefficient values presented in the table are the marginal effect of logit regression (dp/dx). If prospect cost of nurturing children increases by ₩100,000, this is interpreted as a change of childbirth intention. Values in parentheses are robust standard error
*, **, and *** means statistical significance at the significance level of 10, 5, and 1%, respectively