Air pollution
We obtain the city-by-year level of PM2.5 concentrations from 1998 to 2016 from NASA SEDAC. On the basis of the year of birth, we define the year prior to birth year as the prenatal period. The birth city recorded by CFPS can be used to identify the city where the adolescent’s prenatal mother is located.[1] Therefore, we can match the individual information and city-level air pollution based on year and place of birth.
Mental health
The data on mental health and individual characteristics are from the CFPS. The CFPS is a nationally representative survey carried out by Peking University with funding from the Chinese government. The CFPS was launched in 2010, and follow-up surveys were conducted in 2012, 2014, 2016, and 2018. The stratified three-stage probability proportional size sampling method was used to select respondents in the sample area.[2] The CFPS includes more than 16,000 households comprising approximately 42,500 individuals in 25 provinces. It also collects detailed demographic information of respondents and their children, such as gender, age, education level, and birth information (e.g., birth date, birth place, birth order, and birth weight). The CFPS also includes two sets of questionnaires to measure respondents’ mental health.
The mental health conditions of adolescents aged 10 to 15 years are the key outcome of this study.[3] The CFPS includes the Kessler Psychological Distress Scale to illicit the anxiety-depression spectrum mental distress of respondents. The Kessler Psychological Distress Scale, developed by Ron Kessler and Dan Mroczek in 1992, is a widely used self-report measure of psychological distress (Adhvaryu, Fenske, and Nyshadham 2019; Andrew and Slade 2001; Mitchell and Beals 2011). In the 2010 and 2014 waves of CFPS, 6-question Kessler Psychological Distress Scale (K6) was used to assess the anxiety and depression of respondents. The K6 is an abbreviated version of the 10-question Kessler Psychological Distress Scale (K10). Weiss and Lunsky (2011) and Easton et al. (2017) show that K6 and K10 are consistent. Thus, the K6 performs as well as the K10 does. The reliability of K6 has been established in various contexts, including China (Chan 2014). The K6 comprises six questions about the respondents’ emotional status in the last month. In particular, respondents are asked (1) “How often did you feel depressed and you could not be cheered up no matter what you were doing,” (2) “How often did you feel nervous,” (3) “How often did you feel upset and you could not remain calm,” (4) “How often did you feel hopeless about the future,” (5) “How often did you feel that everything was difficult,” and (6) “How often did you feel that life was meaningless.” Each question is rated on the 5-point Likert scale, including 0 (not at all), 1 (a little of the time), 2 (half of the time), 3 (most of the time), and 4 (all the time). We follow Kessler et al. (2003) to add up the scores of the six questions and define a dummy variable, “severe mental illness,” which takes a value of 1 if the sum of the K6 test passes 12 and 0 if otherwise.
In the 2012 and 2016 waves of CFPS, CES-D was used to measure the depression of respondents. The CES-D was developed by Radloff (1977). Studies have demonstrated the validity and reliability of CES-D for depressive symptoms (Radloff 1977; Radloff 1991; Crawford et al. 2011). The CES-D is applicable for adolescents up to the elderly and for the Chinese (Cheng and Chan 2005). The CES-D comprises 20 questions inquiring about the respondents’ emotional states in the past week. Table 8 in the Appendix lists these questions. Each question is rated on the 5-point Likert scale ranging from 0 (not at all or less than 1 day) to 5 (nearly every day). We follow Radloff (1991) to add up the scores of 20 questions and define a dummy variable, “severe mental illness,” which takes a value of 1 if the sum of the K20 test passes 27 and 0 if otherwise.
The performance of the K6 is comparable with that of the CES-D (Sakurai et al. 2011). For most of our analysis, we pool 4 years of data together. The underlying assumption is that the “severe mental illness” measures are consistent when measured by K6 and CES-D. We use the inverse of the number of times an individual is observed in the sample as the sample weight because some individuals are observed multiple times. We also separately estimate the sample for the mental illness variable constructed by K6 and CES-D questionnaires to provide robust results.
Demographic and survey data
We also obtain birth outcomes, mental health conditions of mothers, parenting styles, and other mechanism variables from the CFPS. In the 2010, 2012, 2014, and 2016 waves of the CFPS, five questions are selected to measure the authoritarian parenting style of parents, including “the parents/guardians would tell you the reasons when they asked you to do something,” “the parents/guardians liked to talk with you,” “the parents/guardians told stories to you,” “the parents/guardians praised you,” and “the parents attended parent–teacher meetings at school.” Each question has five options, including 1 (never), 2 (rarely), 3 (sometimes), 4 (often), and 5 (always). If the adolescents were asked about their parents’ parenting style in a wave, they would not be asked the same question in the next waves. We add all scores of the five questions and define a dummy variable to measure whether parents adopt the authoritarian parenting style. The authoritarian parenting style means that parents take their ideas as the center, do not communicate with their children emotionally, and conduct controlled education to children through punishment and forcing children to be obedient. If the total score of parenting style is less than 22, we believe that parents adopt the authoritarian parenting style to educate their children, and the dummy variable is equal to 1; otherwise, it is equal to 0.
Meteorological condition
The weather data comes from the NMIC, which records annual surface climate data from 1951 to 2019, including wind speed, rainfall, temperature, and humidity. According to the location information of the meteorological stations, we match the station-level weather data with the individual-level data in the following steps. First, we collect all station-level weather data in one city and calculate the annual average city-level weather data. Second, if a city has no weather station, we collect the station-level weather data from the stations in the same province and calculate the annual average city-level weather data. We test the correlation of IV with other explanatory variables in in Appendix Table 9.
Summary statistics
Table 1 provides the summary statistics of the main variables. Panel A reports the individual characteristics of adolescents. The average concentration of PM2.5 is 27.6 μg/m3, which is higher than 10 μg/m3, the annual average guideline value for PM2.5 by the WHO air quality guidelines. Moreover, 2.5% of adolescents have a severe mental illness. The average birth year of adolescents is 2002. The proportion of males is approximately 53%, with an average of one sibling. Only 0.4% of adolescents have migrated between cities.
Table 1 Summary statistics
|
Mean
(1)
|
Std. Dev
(2)
|
Observation
(3)
|
Panel A. Individual characteristics of adolescents
|
Fetal exposure to PM2.5 (μg/m3)
|
27.666
|
12.317
|
6,143
|
Mental health
|
0.025
|
0.157
|
6,143
|
Year of birth
|
2,001.608
|
2.117
|
6,143
|
Boy (yes = 1)
|
0.531
|
0.499
|
6,143
|
Age
|
11.985
|
1.627
|
6,143
|
Number of siblings
|
0.970
|
0.903
|
6,143
|
Cross-city migration (yes = 1)
|
0.004
|
0.062
|
6,143
|
|
|
|
|
Panel B. Parents and family characteristics
|
|
|
|
Father’s age
|
40.558
|
5.270
|
6,143
|
Mather’s age
|
38.665
|
5.140
|
6,143
|
Father’s childbearing age
|
28.574
|
5.060
|
6,143
|
Mather’s childbearing age
|
26.680
|
4.900
|
6,143
|
Father’s years of education
|
7.508
|
4.078
|
6,143
|
Mather’s years of education
|
6.380
|
4.444
|
6,143
|
Total family income (yuan)
|
41,238.6
|
61,722.25
|
6,143
|
|
|
|
|
Panel C. Mechanism variables
|
|
|
|
Birth weight
|
3.194
|
0.577
|
5,017
|
Breastfeeding
|
0.871
|
0.335
|
6,136
|
Premature birth
|
0.033
|
0.177
|
5,594
|
Mother’s mental health
|
0.043
|
0.203
|
5,288
|
Authoritarian parenting style
|
0.979
|
0.145
|
4,289
|
Absent
|
0.150
|
0.358
|
885
|
Quarrel
|
1.042
|
2.742
|
5,588
|
|
|
|
|
Panel D. Weather condition
|
|
|
|
Wind speed
|
2.171
|
0.758
|
6,143
|
Rainfall
|
921.950
|
510.40
|
6,143
|
Temperature
|
14.537
|
4.921
|
6,143
|
Humidity
|
69.384
|
8.2
|
6,143
|
Notes: Household income is adjusted to income based on the 2010 period using the consumer price index. Cross-city migration means that the city of birth is different from the city of survey.
Panel B reports the parental and household characteristics. The average age of fathers and mothers is 41 and 39 years old, respectively. The average age at which fathers and mothers have a child is 29 and 27 years old, respectively. The education years of fathers and mothers are 7.5 and 6.4 years, respectively, which are both lower than the 9 years of compulsory education. The probable reason for this scenario among parents is that China’s compulsory education law has not yet been formally implemented[4] when they had reached school age. The average household income, adjusted for the 2010 price index, is 41,239 yuan.
Panel C reports the mechanism variables. The mean birth weight of adolescents is 3.2 kg, and 6.9% of the adolescents’ birth weights are less than 2.5 kg. Approximately 87% of adolescents achieved the standard breastfeeding duration when they were born, and 3.3% were born prematurely. The average number of quarrels with their mothers in the last month is 1. Moreover, 97.9% of mothers adopt the authoritarian parenting style for their children.
Panel D shows the city-level weather conditions. The average annual wind speed is 2.17 m/s, the average total annual rainfall is 921.95 mm, the average temperature is 14.54 °C, and the average annual humidity is 69.38%.
Empirical Strategy
The most immense challenge of our identification is the endogeneity of PM2.5 exposure because individuals may take adaptation measures to avoid PM2.5 exposure. For example, families may reduce the frequency of outdoor activities to reduce respiratory particle uptake when air pollution is severe. If their residential areas suffer from longstanding air pollution, families may move to other cities to keep their children safe. If these cautious parents contribute considerably to children’s development, the estimate of interest is biased downward. Our solution is to find an IV that is orthogonal to individual mental health conditions but can affect PM2.5 concentration.
IV estimation
Following Cai et al. (2016), Hering and Poncet (2014), and Shi and Xu (2018), we use the average 2 min wind speed of 10 m above ground as the IV. First, high wind speed leads to a favorable dispersion condition of pollutants in the air. This finding has been proved in astrological studies. Second, the children’s performance does not respond directly to wind speed. No evidence shows that wind adversely affects human health and even those living near wind turbines (Knopper et al. 2014). One may worry that parents’ location choice may also depend on wind speed. This scenario occurs at slight odds. However, our IV remains valid as long as the parents’ location choices concerning the wind are not due to their consideration of children.
The two-stage least square (2SLS) estimation includes the following:
Since the children’s psychological status may be correlated at the city level, all standard errors are clustered at the city level. Given that some individuals may be observed several times, the inverse of the observed times of individuals in the data is used as the weight in the regression in the present study.
Hence, the estimation is a linear probability model. Angrist (2001) finds that the linear probability model is effective in the second stage. Moreover, the estimation coefficient is easy to explain when the result variable is binary and 2SLS estimation is used. In this study, the probit model and IV–probit model with IVs are also used for estimation in robustness checks, and the results are consistent with the main findings (Table 10).[7]
[1] We assume that adolescents were born in the same city where they were conceived, which is a relatively loose assumption because it is rare that the city where the mother was pregnant is different from where they gave birth.
[2] In the first stage, 144 sample districts/counties and 32 sample districts/towns were selected from 5 “large provinces” and 20 “small provinces.” In the second stage, 640 villages were selected based on the first stage. In the third stage, 28–42 households were selected from each village.
[3] CFPS only use K6 and CES-D for the assessment of the mental health status of individuals aged 10 and over.
[4] Since the compulsory education law came into effect in 1986, individuals born in 1979 or later can enjoy the compulsory education law. Although all samples were surveyed in 2016, fathers and mothers, with an average age of 41 and 39, were born in 1975 and 1977 and did not fully enjoy the compulsory education law.
[5] We add the household incomes by 1 and take the logarithm for those who were reported to have a value of zero.
[6] The age of the parents can be identified according to the childbearing age of the parents and the age of the teenagers. Therefore, no control over the age of the parents exists.
[7] In particular, the IV probit model shows that a 1 μg/m3 increase in prenatal PM2.5 exposure considerably increases the probability of severe mental illness for adolescents aged 10–15 years by 0.14%.