Green returns to education: Does education affect pro-environmental attitudes and behaviors in China?

Table 7 summaries the responses to the environmental knowledge questions. In particular, it reports the proportion of respondents providing correct, incorrect and “do not know” answers to each of the ten environmental literacy questions. Overall, we observe a lack of envi- ronmental literacy among Chinese people. Most respondents could provide correct answers to the questions of automobile exhaust (81.2%) and abuse of fertilizers (83.6%), while the propor- tions of correct answers to the questions of acid rain, single species, domestic water pollution reports and air quality reports fail to exceed 50%. The question of domestic water pollution reports turns out to be the most difficult question for respondents, as the percentage of correct answer to that question (16.4%) is the lowest among the ten questions. Then, we construct an environmental knowledge score by awarding one point for each correct answer. Thereby the resulting score, Environmental knowledge, lies between 0 and 10. We relate this environmental knowledge score to educational attainment and report the results in Table 8. The coefficients on education are significantly positive, indicating that the level of education has a positive impact on environmental knowledge. This supports the notion that the education effects pass through environmental knowledge. Furthermore, we investigate the extent to which this mediating variable contributes to the effects of education on pro-environmental attitudes and behaviors. To achieve this goal, we

follow the literature [14,39] and perform a standard mediation analysis in which we assess how the coefficient of education changes when the mediating variable is added as controls to the regressions. Specifically, we compute the percent change in the magnitude for the coefficient of education when a particular mediator is added and interpret it as the proportion of effects of education that are explained by that mediator. Table 9 reports the results of the mediation analysis. We keep the sample in which all the variables are consistently available to ensure that the changes in the estimated coefficients across regressions are not driven by changes in the sample. Consequently, we end up with 3,401 observations for pro-environmental attitudes and 3,601 observations for pro-environ- mental behaviors. We report the corresponding benchmark estimates without the mediator in the columns (1) and (3) for the purpose of comparison. Columns (2) and (4) show the results when the variable Environmental knowledge is included as an explanatory variable. The Table 8. The effects of education on environmental knowledge. Environmental knowledge OLS 2SLS (1) (2) Education 0.191��� 0.340��� (0.013) (0.065) Controls Yes Yes Observations 3,601 3,601 First-stage estimation CSL 3.157��� (0.260) F-statistics 147.00 Note: The table reports the estimates from regressions of education on environmental knowledge. Column (1) uses OLS model for estimation, while column (2) uses 2SLS model for estimation. All regressions have the same controls

as in column (2) of Table 3, but their coefficients are suppressed for brevity. Robust standard errors are clustered at the cohort-city level and are reported in parentheses. ���, �� and � indicate 1%, 5% and 10% significance levels, respectively. https://doi.org/10.1371/journal.pone.0263383.t008 PLOS ONE Green returns to education PLOS ONE | https://doi.org/10.1371/journal.pone.0263383 February 3, 2022 16 / 20