Can Risk Perception Alter Son Preference? Evidence from Gender-Imbalanced Rural China

Figures & data

Figure 1. Path diagram of the model.

Notes: The measurement models are the dashed rectangles; the structural model is the solid rectangle. Latent variables are shown as ellipses; observed variables are presented by rectangles. The arrows represent hypothesised direct effect.

Table 1. Constructs, survey items, and standardised factor loadings

Constructs	Survey items	Factor loadings
Value of sons (VOS) α = 0.866	Old age support	0.798***
	Financial support	0.789***
	Day-to-day care	0.821***
	Carrying on the family lineage and prestige	0.740***
Gender role attitudes (GRA) α = 0.659	The domain for men is in public and the domain for women is within household	0.612***
	Earning money to support the family should be done by men	0.669***
	The development of the husband is more important than the development of the wife	0.659***
	For women, having a good marriage is better than a career	0.359***
Risk perception (RP) α = 0.758	Male marital difficulties	0.506***
	Exorbitant marriage expenses	0.454***
	Forced bachelor families face enormous economic pressure	0.705***
	Forced bachelor families face problems of old age support	0.689***
	Trafficking in women and children	0.273***
	Female personal safety	0.504***
	Increasing crime rate due to more unmarried men	0.553***

Notes: N = 1032; RMSEA = 0.059; CFI = 0.924; TLI = 0.908; SRMR = 0.045; ***p < 0.01.

Table 2. Estimation results of the structural model

Direct effect	Coefficient	Std. Err	Standardised coefficient
Dependent variable: stated son preference
Value of sons	0.267***	0.037	0.287
Gender role attitudes	0.087**	0.043	0.086
Risk perception	−0.097**	0.038	−0.091
Gender^a	−0.162**	0.069	−0.075
Education level	−0.018	0.012	−0.052
Age	0.006	0.004	0.055
Income level	0.004	0.042	0.003
Dependent variable: value of sons
Gender role attitudes	0.399***	0.048	0.367
Risk perception	0.207***	0.043	0.179
Gender^a	−0.351***	0.077	−0.152
Education level	−0.050***	0.014	−0.134
Age	−0.004	0.004	−0.030
Income level	−0.087*	0.047	−0.063
Dependent variable: gender role attitudes
Risk perception	0.166***	0.045	0.157
Gender^a	−0.133	0.083	−0.062
Education level	−0.074***	0.015	−0.219
Age	0.015***	0.005	0.129
Income level	−0.006	0.051	−0.004

Notes: N = 1032; RMSEA = 0.051 (90% confidence interval: 0.047, 0.056); CFI = 0.908; TLI = 0.888; SRMR = 0.044; ^abase category: male; ***p < 0.01; **p < 0.05; *p < 0.10.

Table 3. Bootstrapping indirect effects of gender role attitudes and value of sons

Indirect effect						Bootstrapping
						90% CI
				Standardised coefficient	Std. Err	LLCI	ULCI	p-Value
RP→	GRA→	SSP		0.013	0.009	−0.001	0.120	0.028
RP→	VOS→	SSP		0.051***	0.015	0.027	0.000	0.075
RP→	GRA→	VOS→	SSP	0.016***	0.005	0.008	0.002	0.025
RP→	GRA→	VOS		0.057***	0.017	0.029	0.001	0.086

Notes: RP: risk perception; SSP: stated son preference; GRA: gender role attitudes; VOS: value of sons; ***p < 0.01; **p < 0.05; *p < 0.10.

Table A1. Descriptive statistics (N = 1032)

(strongly disagree = 1, strongly agree = 5)	Mean	SD
Stated son preference	2.30	1.08
Latent variable: value of sons	2.56	0.94
Old age support	2.60	1.11
Financial support	2.53	1.10
Day-to-day care	2.48	1.09
Carrying on the family lineage and prestige	2.65	1.17
Latent variable: gender role attitudes	3.14	0.87
The domain for men is in public and the domain for women is within household	3.28	1.21
Earning money to support the family should be done by men	3.23	1.24
The development of the husband is more important than the development of the wife	3.28	1.26
For women, having a good marriage is better than a career	2.78	1.25
Latent variable: risk perception	3.40	0.67
Male marital difficulties	3.70	0.93
Exorbitant marriage expenses	3.86	0.92
Forced bachelor families face enormous economic pressure	3.41	1.01
Forced bachelor families face problems of old age support	3.32	1.03
Trafficking in women and children	3.11	1.22
Female personal safety	3.46	1.07
Increasing crime rate due to more unmarried men	2.97	1.12

Note: The underlined values are the mean values and standard deviations of the latent variables. There is no statistical significance.

Table B1. Estimation results of the structural model: Risk perception related to male marriage squeeze

Direct effect	Coefficient	Std. Err	Standardised coefficient
Dependent variable: stated son preference
Value of sons	0.263***	0.037	0.283
Gender role attitudes	0.087**	0.043	0.086
Risk perception related to male marriage squeeze	−0.080**	0.039	−0.075
Dependent variable: value of sons
Gender role attitudes	0.394***	0.048	0.363
Risk perception related to male marriage squeeze	0.212***	0.044	0.184
Dependent variable: gender role attitudes
Risk perception related to male marriage squeeze	0.183***	0.047	0.172

Notes: N = 1032; RMSEA = 0.049 (90% confidence interval: 0.043, 0.055); CFI = 0.935; TLI = 0.916; SRMR = 0.037; ***p < 0.01; **p < 0.05; *p < 0.10. Covariates are similar as in Table 2 and are omitted.

Table B2. Bootstrapping indirect effects of gender role attitudes and value of sons: risk perception related to male marriage squeeze

Indirect effect						Bootstrapping
						90% CI		p-Value
				Standardised coefficient	Std. Err	LLCI	ULCI
RPM→	GRA→	SSP		0.015	0.010	−0.001	0.031	0.125
RPM→	VOS→	SSP		0.052***	0.015	0.027	0.077	0.001
RPM→	GRA→	VOS→	SSP	0.018***	0.006	0.008	0.027	0.002
RPM→	GRA→	VOS		0.063***	0.018	0.032	0.093	0.001

Notes: RPM: risk perception related to male marriage squeeze; SSP: stated son preference; GRA: gender role attitudes; VOS: value of sons; ***p < 0.01; **p < 0.05; *p < 0.10.

Table B3. Estimation results of the structural model: Risk perception related to female safety issues

Direct effect	Coefficient	Std. Err	Standardised coefficient
Dependent variable: stated son preference
Value of sons	0.267***	0.037	0.285
Gender role attitudes	0.080*	0.044	0.078
Risk perception related to female safety issues	−0.116***	0.041	−0.108
Dependent variable: value of sons
Gender role attitudes	0.424***	0.048	0.388
Risk perception related to female safety issues	0.145***	0.046	0.127
Dependent variable: gender role attitudes
Risk perception related to female safety issues	0.062	0.051	0.059

Notes: N = 1032; RMSEA = 0.043 (90% confidence interval: 0.037, 0.049); CFI = 0.951; TLI = 0.934; SRMR = 0.037; ***p < 0.01; **p < 0.05; *p < 0.10. Covariates are similar as in Table 2 and are omitted.

Table B4. Bootstrapping indirect effects of gender role attitudes and value of sons: risk perception related to female safety issues

Indirect effect						Bootstrapping
						90% CI		p-Value
				Standardised coefficient	Std. Err	LLCI	ULCI
RPF→	GRA→	SSP		0.005	0.006	−0.005	0.014	0.426
RPF→	VOS→	SSP		0.036***	0.014	0.013	0.059	0.009
RPF→	GRA→	VOS→	SSP	0.007	0.006	−0.003	0.017	0.281
RPF→	GRA→	VOS		0.023	0.021	−0.011	0.058	0.278

Notes: RPF: risk perception related to female safety issues; SSP: stated son preference; GRA: gender role attitudes; VOS: value of sons. ***p < 0.01; **p < 0.05; *p < 0.10.

Table B5. Selection on unobservables

	Stated son preference
	Uncontrolled	Controlled
Coefficient	−0.006	−0.014
R-squared	0.001	0.124
δ(β = 0)		−5.068
β(δ = 1)		−0.017

Notes: δ designates the ratio of selection on unobservables to selection on observables that would be required to fully attribute our results to omitted variable bias (β= 0); β is derived from imposing the reasonable assumption that selection on unobservables is equally as important as selection on observables (δ = 1); δ and β are calculated using $R_{\max }$=1.3$\tilde{\mathrm{R}}.$ A negative value of delta is generated when the correlations between observables and the treatment, and between unobservables and treatment, have opposing signs. The variables were constructed by aggregating corresponding items. See Oster (2019) for details.

Oster, E. (2019). Unobservable selection and coefficient stability: Theory and evidence. Journal of Business & Economic Statistics, 37(2), 187–204. doi:10.1080/07350015.2016.1227711

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Data availability statement

The data and codes are available upon request.