Article Figures & Data
Figures
- Figure 1
Male Fraction of Births by Birth Order in China
Notes: Data are from Ebenstein (2010). China introduced its family planing policy in 1979, which is represented by the vertical line. The figure shows that more boys than girls have been born in China over the past decades, but first births are exceptions.
Tables
All Stock Market Participants Mean Min. Max. Mean Min. Max. (1) (2) (3) (4) (5) (6) Panel A: Overall Stock market participation 0.056
(0.230)
0
1
1
(0)
1
1
Stock share 0.018
(0.115)
0
1
0.400
(0.363)
0
1
Risky-asset market participation 0.084
(0.278)
0
1
1
(0)
1
1
Risky-asset share 0.032
(0.153)
0
1
0.489
(0.367)
0
1
Observations 4,363 245 Sex Ratio < Q1 Sex Ratio > Q3 Mean p-Value Mean p-Value First Son First Daughter (H1: SD ≠ 0) First Son First Daughter H1: SD ≠ 0) (1) (2) (3) (4) (5) (6) Panel B: First-Son versus First-Daughter Families Stock market participation 0.043
(0.202)
0.046
(0.210)
0.807
0.059
(0.236)
0.032
(0.177)
0.018
Stock share 0.020
(0.117)
0.020
(0.126)
0.933
0.023
(0.125)
0.013
(0.104)
0.092
Risky-asset market participation 0.064
(0.245)
0.068
(0.252)
0.813
0.097
(0.296)
0.050
(0.218)
<0.01
Risky-asset share 0.030
(0.149)
0.036
(0.166)
0.566
0.046
(0.182)
0.022
(0.129)
<0.01
Observations 469 457 507 560 Notes: Data on county-level sex ratios are from the 2010 China population census. Data on other variables are from the 2013 CHFS. Panel A is based on our sample of CHFS households. Stock-market participants are families that hold a stock account. Panel B is based on four subgroups: first-son and first-daughter families in counties with a balanced sex ratio (smaller than the first quartile Q1, 1.09) or a high sex ratio (larger than the third quartile Q3, 1.22). Statistics are weighted by CHFS sampling weights. Standard deviations are given in parentheses.
Mean All First Son First Daughter Difference, SD p-Value (H1: Diff. ≠ 0) (1) (2) (3) (4) (5) First son 0.518
(0.500)
Father’s age 39.52
(5.719)
39.54
(5.769)
39.51
(5.666)
0.030
[0.173]
0.655
Father’s schooling years 9.170
(3.313)
9.149
(3.263)
9.193
(3.367)
−0.044
[0.104]
0.530
Father’s hukou (urban = 1) 0.227
(0.419)
0.226
(0.418)
0.229
(0.420)
−0.003
[0.014]
0.845
Father’s political status (CCP = 1) 0.114
(0.318)
0.104
(0.305)
0.126
(0.332)
−0.022
[0.010]
0.129
Mother’s age 37.62
(5.815)
37.74
(5.852)
37.50
(5.775)
0.240
[0.176]
0.331
Mother’s schooling years 8.347
(3.659)
8.328
(3.548)
8.367
(3.776)
−0.039
[0.115]
0.820
Mother’s hukou (urban = 1) 0.215
(0.411)
0.217
(0.412)
0.213
(0.409)
0.004
[0.013]
0.132
Mother’s political status (CCP = 1) 0.031
(0.173)
0.031
(0.173)
0.031
(0.174)
−0.000
[0.006]
0.882
First child’s age 11.68
(4.105)
11.69
(4.057)
11.67
(4.158)
0.020
[0.127]
0.856
Region of residence (urban = 1) 0.485
(0.500)
0.476
(0.500)
0.496
(0.500)
−0.020
[0.015]
0.319
Ethnicity (minority = 1) 0.128
(0.334)
0.126
(0.332)
0.130
(0.336)
−0.004
[0.010]
0.640
Observations 4,363 2,246 2,117 Notes: Data are from the 2013 CHFS. Statistics are based on our sample of CHFS households. Statistics are weighted by CHFS sampling weights. Standard deviations are given in parentheses. Standard errors are given in square brackets.
Stocks All Risky Assets Dependent Variable Participation Share Participation Share (1) (2) (3) (4) First son (β1) −0.229***
(0.062)
−0.069**
(0.032)
−0.089
(0.080)
−0.011
(0.045)
Sex ratio (β2) −0.027
(0.179)
−0.001
(0.075)
−0.085
(0.199)
0.038
(0.097)
First son × sex ratio (β3) 0.326**
(0.160)
0.168*
(0.101)
0.555***
(0.206)
0.227**
(0.115)
Percentage increase: sex ratio+1 SD 52.2 81.7 59.4 64.2 Observations 4,363 4,363 4,363 4,363 R-squared 0.271 0.194 0.304 0.256 Dependent variable mean 0.056 0.018 0.084 0.032 Model LPM OLS LPM OLS Other controls Yes Yes Yes Yes First son × other controls Yes Yes Yes Yes Prefecture fixed effects Yes Yes Yes Yes First son × prefecture fixed effects Yes Yes Yes Yes ↵Notes: Data on county-level sex ratios are from the 2010 China population census. Data on other variables are from the 2013 CHFS. Results are estimated using Equation 1 based on our sample of CHFS households. Percentage increase with a one standard deviation increase in the sex ratio is 0.09 β3/sample mean. Other controls include various parental and household characteristics—both parents’ age, education, hukou, political status, and occupational dummies, plus age of the first child, region of residence, and ethnicity. Interactions of the first-son dummy with these variables as well as prefecture fixed effects are also controlled for. Regressions are weighted by CHFS sampling weights. Standard errors clustered at the county level are given in parentheses. *p < 0.1, **p < 0.05, ***p < 0.01.
Dependent variable Stock-Market Participation (1) (2) (3) (4) (5) (6) (7) First son (β1) −0.235***
(0.068)
−0.387***
(0.104)
−0.515***
(0.154)
Proportion of sons (β1) −0.310***
(0.076)
−0.330***
(0.082)
Having any son (β1) −0.199***
(0.073)
−0.228***
(0.077)
Sex ratio (β2) −0.021
(0.180)
−0.188
(0.390)
−0.099
(0.309)
−0.098
(0.223)
−0.092
(0.222)
−0.176
(0.290)
−0.174
(0.288)
First son × sex ratio (β3) 0.321**
(0.161)
0.657*
(0.386)
0.705*
(0.403)
Proportion of sons × sex ratio (β3) 0.460**
(0.232)
0.455*
(0.231)
Having any son × sex ratio (β3) 0.464*
(0.280)
0.462*
(0.279)
# children −0.004
(0.006)
−0.007
(0.006)
−0.013
(0.009)
First son × # children 0.002
(0.009)
Proportion of sons * # children 0.008
(0.012)
Having any son × # children 0.013
(0.011)
Observations 4,363 2,726 2,216 4,363 4,363 4,363 4,363 R-squared 0.271 0.236 0.246 0.264 0.264 0.210 0.210 Other controls Yes Yes Yes Yes Yes Yes Yes Son × other controls Yes Yes Yes Yes Yes Yes Yes Prefecture fixed effects Yes Yes Yes Yes Yes Yes Yes Son × prefecture fixed effects Yes Yes Yes Yes Yes Yes Yes ↵Notes: Data on county-level sex ratios are from the 2010 China population census. Data on other variables are from the 2013 CHFS. Results are estimated using Equation 1 based on our sample of CHFS households. Column 2 includes one-child families. Column 3 includes one-child families with a child above the age of six. Other controls include various parental and household characteristics—both parents’ age, education, hukou, political status, and occupational dummies, plus age of the first child, region of residence, and ethnicity. Interactions of the first-son dummy with these variables as well as prefecture fixed effects are also controlled for. Regressions are weighted by CHFS sampling weights. Standard errors clustered at the county level are given in parentheses. *p<0.1, **p< 0.05, ***p<0.01.
Dependent Variable Stock-Market Participation (1) (2) (3) (4) (5) (6) First son (β1) −0.228***
(0.063)
−0.221***
(0.072)
−0.251***
(0.064)
−0.251***
(0.093)
−0.314***
(0.089)
−0.170
(0.221)
Sex ratio (β2) −0.022
(0.176)
−0.034
(0.168)
−0.032
(0.181)
−0.023
(0.172)
0.052
(0.175)
−0.068
(0.155)
First son × sex ratio (β3) 0.337**
(0.160)
0.344**
(0.167)
0.320*
(0.187)
0.339**
(0.170)
0.273*
(0.157)
0.334*
(0.179)
Average household wealth, k 0.022
(0.028)
−0.007
(0.031)
First son × average household wealth −0.015
(0.048)
−0.060
(0.039)
Average household income, k 0.002*
(0.001)
0.003***
(0.001)
First son × average household income −0.000
(0.001)
−0.003***
(0.001)
Gender wage differential, m-f, k 0.001
(0.005)
−0.015***
(0.005)
First son × gender wage differential 0.011**
(0.005)
0.031***
(0.006)
Proportion with insurance 0.212
(0.155)
0.091
(0.187)
First son × proportion with insurance 0.067
(0.174)
0.088
(0.193)
Average # children −0.083**
(0.035)
−0.039
(0.042)
First son × average # children 0.066
(0.043)
0.035
(0.047)
Hausman test p-value 0.780 0.993 0.653 0.877 0.568 0.671 Observations 4,363 4,363 4,363 4,363 4,363 4,363 R-squared 0.270 0.273 0.273 0.272 0.271 0.328 Other controls Yes Yes Yes Yes Yes Yes First son × other controls Yes Yes Yes Yes Yes Yes Prefecture fixed effects Yes Yes Yes Yes Yes Yes First son × prefecture fixed effects Yes Yes Yes Yes Yes Yes ↵Notes: Data on county-level sex ratios are from the 2010 China population census. Data on other variables are from the 2013 CHFS. Results are estimated using Equation 1 based on our sample of CHFS households. The null hypothesis of the Hausman test is that the effect of high sex ratios is equal to that in the baseline—Column 1 of Table 3. Other controls include various parental and household characteristics—both parents’ age, education, hukou, political status, and occupational dummies, plus age of the first child, region of residence, and ethnicity. Interactions of the first-son dummy with these variables, as well as prefecture fixed effects, are also controlled for. Regressions are weighted by CHFS sampling weights. Standard errors clustered at the county level are given in parentheses. *p< 0.1, **p<0.05, ***p< 0.01.
Risk-Taking Measure Dependent Variable All Bottom 25% Middle Top 25% (1) (2) (3) (4) (5) (6) (7) First son × sex ratio 0.666**
(0.267)
1.633**
(0.754)
1.767**
(0.797)
0.743*
(0.435)
0.548
(0.433)
−0.217
(0.836)
−0.650
(0.938)
First son × sex ratio × skewness 0.093
(0.085)
−0.050
(0.047)
−0.134
(0.124)
Observations 4,363 1,140 1,140 2,113 2,113 1,110 1,110 R-squared 0.307 0.372 0.377 0.236 0.238 0.399 0.401 Dependent variable mean 0.131 0.142 0.142 0.128 0.128 0.123 0.123 Model LPM LPM LPM LPM LPM LPM LPM First son Yes Yes Yes Yes Yes Yes Yes Sex ratio Yes Yes Yes Yes Yes Yes Yes First son × skewness Yes Yes Yes Sex ratio × skewness Yes Yes Yes Other controls Yes Yes Yes Yes Yes Yes Yes First son × other controls Yes Yes Yes Yes Yes Yes Yes Prefecture fixed effects Yes Yes Yes Yes Yes Yes Yes First son × prefecture fixed effects Yes Yes Yes Yes Yes Yes Yes ↵Notes: Data on county-level sex ratios are from the 2010 China population census. Data on other variables are from the 2013 CHFS. Results are estimated using Equation 1 based on our sample of CHFS households and income subgroups. Other controls include various parental and household characteristics—both parents’ age, education, hukou, political status, and occupational dummies, plus age of the first child, region of residence, and ethnicity. Interactions of the first-son dummy with these variables, as well as prefecture fixed effects, are also controlled for. Regressions are weighted by CHFS sampling weights. Standard errors clustered at the county level are given in parentheses. *p<0.1, **p<0.05, ***p<0.01.
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