Children Left Behind in China: The Role of School Fees

[i] RuMiC, Rural–Urban Migration in China; SD, standard deviation; Max, maximum; Min, minimum; HP, Hodrick–Prescott.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.

[i] Notes: Each column presents the results from separate IV regressions with different independent variables, where the IV is the one-year lag of shocks to public education spending. The dependent variable is a dummy variable that equals 1 if there is at least one child living with the household head and 0 otherwise. The regressions use the median school fees reported in the migrant household sample as a regressor. Different sets of control variables are included in different columns. R-squared values are not reported, instead RMSE, the sample standard deviation of the differences between the predicted values and observed values, is reported under each column. Standard errors in parentheses are clustered at the city level. Prob > χ2 is the p-value of the chi-square test of overall significance. F statistics of the first-stage regressions are also reported. ***p < 0.01, **p < 0.05, and *p < 0.1. FE, fixed effects; RMSE, root mean square error; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.

[i] Notes: Each column presents the results from separate IV regressions with different independent variables, where the IV is the 1-year lag of shocks to public education spending. The dependent variable is the numbers of children living with their parents in the house-hold. The regressions use the median school fees reported in the migrant household sample as a regressor. Similar to Table 2, household head’s demographics and original province FE are controlled in all the columns, and additional sets of control variables are included in columns 2 and 3. R-squared values are not reported. Instead, RMSE, the sample standard deviation of the differences between the predicted values and observed values, is reported under each column. Standard errors in parentheses are clustered at the city level. Prob > χ2 is the p-value of the chi-square test of overall significance. F statistics of the first-stage regressions are also reported. **p < 0.05, FE, fixed effects; HH, household; RMSE, root mean square error; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.

[i] Notes: Each column presents the results from separate IV regressions with different school fee measures and different independent variables, where the IV is the 1-year lag of shocks to public education spending. The dependent variable is girl representativeness – defined as girls as a share of the number of migrant children divided by girls as a share of the total number of children in the household. Regressions use the median school fees reported in the migrant household sample as a regressor. Similar to Table 2, household head’s demographics and original province FE are controlled in all the columns, and additional sets of control variables are included in columns 2 and 3. R-squared values are not reported, instead RMSE, the sample standard deviation of the differences between the predicted values and observed values, is reported under each column. Standard errors in parentheses are clustered at the city level. Prob > χ² is the p-value of the chi-square test of overall significance. F statistics of the first stage regressions are also reported. *p < 0.1. FE, fixed effects; HH, household; RMSE, root mean square error; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.

[i] Notes: Each column presents the results from separate IV regressions with different school fee measures and different independent variables, where the IV is the 1-year lag of shocks to public education spending. The dependent variable is a dummy variable that equals 1 if there is at least one child living with the household head in urban areas and 0 otherwise. The different measures of school fees under columns (1)–(7) are defined as follows: Column (1), log median school fees (including tuition fees, food and accommodation, remedial classes, and other fees) reported in the migrant sample; column (2), log median tuition fees reported in the migrant household sample; columns (3) and (4), log 25th percentile and 75th percentile school fees reported in the migrant household sample; column (5), median school fees (in ’000 yuan) reported in the migrant household sample; column (6), log median school fees reported in the urban household sample; and column (7), log median tuition fees reported in the urban household sample. Columns (8)–(11) use the same measures of school fees as in column (1). In column (8), household income per capita is included as a control variable. In column (9), social protection spending per capita at the city level is included as a control variable. In column (10), the shocks generated by HP filter with smoothing parameter 6.25 is used as an instrument. In column (11), the sum of the public education spending shocks in 2005 and 2006 (linear filter) is used as an instrument. All regressions include the following controls: household heads’ demographics, household heads’ working variables, within province dummy variable, growth rate of student–teacher ratio, housing prices in 2007, industry FE, and original province FE. Standard errors in parentheses are clustered at the city level. **p < 0.05, HP, Hodrick–Prescott; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.

[i] Notes: Each column presents the results from separate IV regressions with different independent variables, where the IV is the 1-year lag of shocks to public education spending. The dependent variable is a dummy variable that equals 1 if there is at least one child living with the household head and 0 otherwise. Regressions use the median school fees reported in the migrant household sample as a regressor. Similar to Table 2, household head’s demographics and original province FE are controlled in all the columns, and additional sets of control variables are included in columns 2 and 3. R-squared values are not reported, instead RMSE, the sample standard deviation of the differences between the predicted values and observed values, is reported under each column. Standard errors in parentheses are clustered at the city level. Prob > χ² is the p-value of the chi-square test of overall significance. F statistics of the first-stage regressions are also reported. ***p < 0.01, FE, fixed effects; HH, household; IV, instrumental variable; OLS, ordinary least squares; RMSE, root mean square error; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2009 and China City Statistical Yearbook 2002–2009.

[i] Notes: Each column presents the results from separate IV regressions with different school fee measures and different independent variables, where the IV is the 1-year lag of shocks to public education spending. The dependent variables in columns (1)–(3) are defined as follows: column (1), dummy variable indicating underweight (BMI<18.5); column (2), dummy variable indicating overweight (BMI>25); column (3), subjective health score on a 1–5 scale, with a larger score indicating more satisfaction; for migrant children, this question is answered by themselves; for left-behind children, this question is answered by their migrant parents. R-squared values are not reported. Instead, the RMSE, the sample standard deviation of the diferences between the predicted values and observed values, is reported under each column. Standard errors in parentheses are clustered at the city level. Prob > χ² is the p-value of the chi-square test of overall significance. F statistics of the first stage regressions are also reported. ***p < 0.01, **p < 0.05, and *p < 0.1. FE, fixed effects; RMSE, root mean square error; BMI, body mass index; RUMiC, Rural–Urban Migration in China.

Sources: RUMiC 2008 and China City Statistical Yearbook 2002–2008.