Policy Research Working Paper 10438 A Review of Human Development and Environmental Outcomes Diego Ambasz Anshuman Gupta Harry Anthony Patrinos Education Global Practice May 2023 Policy Research Working Paper 10438 Abstract As climate change and its impact on the physical environ- direct and indirect pathways – including cognitive and ment become increasingly evident, its relationship with noncognitive factors through which improved education human development outcomes is becoming a key area of can lead to better environmental behaviors. Of the 31 stud- research. While numerous researchers have studied the ways ies reviewed, a majority (27 studies) present observational in which the immediate environment affects human capital, findings, while only a few (four studies, or 13 percent) use literature on the impact of human capital on the environ- a quasi-experimental design to establish causality. The few ment remains scarce. Despite the heightened interest in causal studies suggest that it is possible to change attitudes understanding the linkages between human development but more difficult to change environmental behaviors. The outcomes and environmental factors, most studies of this review raises the key question of whether policies aimed relationship are theoretical, correlational, or observational, at improving climate change awareness through education thus lacking causality. This paper surveys the literature and can effectively produce long-lasting changes in pro-environ- explores how evidence can be established for policies focus- mental behaviors. Much more work is needed to advance ing on human development and environmental outcomes. understanding of how human capital policy can help mit- The paper presents a conceptual framework incorporating igate or promote adaptation to climate change. This paper is a product of the Education Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at hpatrinos@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team A Review of Human Development and Environmental Outcomes Diego Ambasz Anshuman Gupta Harry Anthony Patrinos1 World Bank World Bank World Bank JEL: Q54; I25 Keywords: Education; human capital; climate change 1 Paper prepared under the Advancing the Human Development Agenda within the EU’s Green Deal (ID: P175948). Thanks to Ana-Maria Boromisa, Karla J. Mcevoy, and Maria Ustinova for comments. All errors are our own and the views expressed here are not to be attributed to the World Bank Group. 1. Introduction Environmental conditions, such as those pertaining to natural resources and climate, are intrinsically linked to human development outcomes in numerous ways. For example, exposure to poor air and water quality among populations is linked to birth defects and cognitive deficits in children (Ferguson et al. 2013). Similarly, workers in mining industries are known to have lower life expectancy due to exposure to heavy metals and toxic environmental conditions, and children living in more polluted environments display higher levels of chronic absenteeism (MacNaughton et al. 2017; Bangay and Blum 2010). On the other hand, human development outcomes such as improved educational attainment in turn may be linked to better environmental outcomes through pathways such as increased awareness about environmental issues and improved access to resources to address them. Is there a link between human development outcomes and environmental outcomes? If so, are there ways to establish a causal relationship? What is the impact of schooling on climate actions, including attitudes, behaviors, and outcomes? We answer these questions by first surveying the literature that investigates the impact of environmental changes on human development outcomes. Then, with more focus, we look at the impact of human development on environmental outcomes, while also assessing the strength of such associations. Despite the heightened interest in understanding the linkages between human development outcomes and environmental factors, most studies of this relationship are only theoretical, correlational, or observational, thus lacking causality. We look at causal estimates of the impact of educational interventions on different environmental outcomes. We explore how evidence can be established for policies focusing on human development and environmental outcomes. We find that there are ways to causally estimate the impact of education on climate outcomes and propose approaches. The broader relationships between economic development and environmental outcomes have been a topic of enquiry for researchers for a long time. The seminal paper by Grossman and Krueger (1995) was among the first to study this relationship using a global dataset. Using panel data (1977- 1990) on four environmental indicators (urban air pollution, the state of the oxygen regime in river basins, fecal contamination of river basins, and contamination of river basins by heavy metals), the authors find that environmental outcomes initially worsen with increasing per capita GDP but eventually witness a U-shaped recovery as incomes increase above a critical threshold. The authors suggest that as countries prosper economically, their citizens demand better environmental conditions, thus improving environmental standards. The study validated the presence of the Environmental Kuznets Curve and was followed by further research to replicate and extend the initial findings (see Goklany 1999; Panayotou 1995). A later cross-sectional study by Jha and Murthy (2003) also highlights a similar relationship. The authors construct a composite environmental degradation index (EDI) for 174 countries using six indicators of environmental degradation or pollution and identify its relationship with the Human Development Index (HDI). The study suggests an inverted N-curve that indicates that countries with high levels of development and lower values of HDI rank contribute more to environmental degradation while mid-ranking countries have the least levels of environmental degradation. Similarly, the paper by Dogan and Inglesi-Lotz (2020) considers how changes in economic 2 structure from developing to developed countries in the European Union (EU) relate to carbon emissions. They find that carbon emissions increase initially as countries move from agriculture to manufacturing, but a rising share of the service sector and increasing per capita incomes leads to reduced emissions, thus confirming the U-shaped curve. A more recent paper by Mrabet et al. (2021) uses panel data for 16 Middle Eastern and North African countries (period 1990–2016) to examine the relationship between Ecological Footprint and HDI. They find that improving HDI will harm the environment in the early stages of development by increasing the Ecological Footprint, but as the country develops, further increases in human development will result in lower levels of environmental degradation. These findings thus suggest that human development and political stability can have a positive effect on the environment through better education and health care systems. However, validating these mechanisms and establishing a causal relationship still requires further research. The remainder of the paper proceeds as follows. The next section presents a synthesis of literature to establish that climate change can indeed affect human development outcomes. It also presents an overview of the adaptation and mitigation measures that can reduce the negative impact of climate change. While some interventions, such as risk assessment of buildings and disaster management, can aid adaptation and reduce climate vulnerabilities, others, such as curriculum redesign and promoting research in universities, can enable mitigation. The last section then shifts focus to the literature on the linkages between education and climate change and presents a possible framework to study these linkages. The last part of that section also presents compulsory schooling laws as one instrument that can be used to establish causal linkages. 2. Impact of Climate on Human Development The influence of our physical environment and climate on human development outcomes such as educational attainment and child mortality has been studied by researchers in different contexts and regions of the world. While weather changes can directly affect human development outcomes by disrupting access to infrastructure such as schools or hospitals, availability of staff (teachers, doctors and nurses, etc.), and increasing incidence of diseases, research in countries across the globe has shown that changes in weather patterns can also affect cognitive performance, rate of skill formation, work behavior, workforce migration, and labor market participation (see Deuster 2021; Das 2020; Li 2020; Zivin and Neidell 2014). Park et al. (2021) use data for 58 countries and 12,000 US school districts with detailed weather and academic calendar information to show that the rate of learning decreases with an increase in the number of hot school days. These negative effects are further compounded in poorer countries and can be up to three times higher for students from low-income groups. Zivin et al. (2018) in their study further show that even though the negative effect of long-term temperature changes may be reduced due to compensatory behavior, short-run changes can lead to statistically significant decreases in cognitive performance (also see Zivin et al. 2020). A similar study by Cook (2021) using the difference-in-difference methodology to assess the impact of flooding on education outcomes and cognitive performance among school children in Canada finds that exposure to floods can reduce performance by up to 7 percent of a standard 3 deviation. However, the effects are less pronounced for students living in high-rise apartment buildings and newer construction areas that are less prone to flooding, thus suggesting that adaptive measures can play a role in reducing the impact of climate change on human development outcomes. Similarly, research on health outcomes also indicates that negative environmental conditions can create long-term negative impact on health indicators of citizens. Researching the link between temperature inversion events and air pollution in Sweden, Jans et al. (2018) show that such events can increase air pollution (PM10 levels) by 25 percent and children’s respiratory health problems by 5.5 percent with low-income children being the worse affected. Arceo et al. (2016) have previously shown that the effect of air pollution on infant mortality can be higher in developing countries as compared to developed countries. Studying the impact of increasing oceanic acidity on early-childhood mortality and development, Armand and Taveras (2020) have gathered data on more than 1.5 million births taking place over the last 50 years in 36 developing countries. The study finds that in coastal areas, a 0.01 unit increase in acidity can lead to 2 additional neonatal deaths per 1,000 live births. Ebi and Hess (2020) further suggest that increased exposure to climate hazards has increased risks of deaths and injuries from extreme events, infectious diseases, and food and water insecurity in Europe. They propose simultaneous government policies and investments in social and health protections aimed at reducing inequities and investments in climate change mitigation and adaptation to reduce these health risks. 2.1. Adaptation and Mitigation Measures to Reduce the Impact of Climate Change As highlighted above, human development outcomes are frequently affected by environmental conditions while interventions targeting human development can in turn affect environmental outcomes. Numerous studies have advanced the role that human development interventions can play in adapting to and mitigating climate change. Bangay and Blum (2010) argue that a robust education system can equip and empower people to deal with climate uncertainties. They also present a generalized sequential framework to identify education responses ranging from provision of adequate educational infrastructure in the short term (adaptation) to equipping learners with the requisite skills, knowledge, and attributes to deal with future challenges in the long term. Adaptation measures can include a variety of interventions that improve resilience or direct human behavior towards adaptation strategies. Instances of such short-term interventions include disaster- proofing infrastructure, adapting to seasonality changes, and building disaster preparedness capacity to respond to climate emergencies. According to the World Bank’s World Development Report (2010), tackling climate change will require the expansion of some measures such as insurance and social protection as well as innovation in the implementation of others such as urban and infrastructure planning. DFID’s report on Education, Climate and Environment (Blum 2015) further emphasizes the role that education and educational infrastructure can play in building the resilience of communities (particularly poor and vulnerable population groups) to climate and environmental change, and the potential opportunities provided by low carbon technology and environmentally sensitive construction and design in that process. 4 Other adaptation measures include introducing innovative policies that can change human behaviors through nudges and increasing awareness. Li (2020), for example, highlights the role that job flexibility can play in shaping people’s adaptation to extreme weather. The study finds that when their residential areas are affected by extreme weather, workers with the flexibility to work at home reduced work time at their workplace by as much as 45 minutes on average, primarily because they wanted to avoid exposure to adverse climate during travel. Without this flexibility, workers made no changes to their work hours, thus suggesting that job flexibility improves workers’ welfare by providing the choice of location adaptation. The European Commission (2019) too has pushed for policies that harness existing complementarities between efficiency, innovation, human capital, job quality, fairness, and improved working conditions to improve productivity while ensuring environmental sustainability. It identifies childcare and long- term care, education and training, skills, mobility, and housing as key policy intervention areas which could enhance sustainability and speed up the convergence of Member States’ socio- economic performance. Mitigation measures on the other hand may include updating curriculum and assessments, teacher education reforms, orientation towards new ‘low carbon’ technologies and sustainable futures, which can have a positive impact on environmental outcomes in the longer term. For example, research by Yao et al. (2020) has shown that advanced human capital, in the form of additional tertiary schooling, is associated with a reduction in CO2 emissions between 50 and 65 percent. The findings of the paper suggest that the social benefits of investing in advanced human capital offer a promising avenue for addressing climate change without impeding economic growth. Another possible avenue to promote mitigating measures is through increased investments in research and development activities. Recent IEA estimates suggest that achieving global energy and climate change ambitions consistent with a 50 percent reduction of energy-related CO2 emissions in 2050 (with respect to 2007 levels) would require a two to fivefold increase in public R&D spending (Dechezleprêtre et al. 2016). OECD too, in its report titled ‘Promoting Technological Innovation to Address Climate Change’ (2011) highlights the need to formulate flexible yet predictable, long- term policies that can incentivize innovations in a broad portfolio of complementary fields, and not just energy, "climate-friendly" or 'environmental' R&D. It also emphasizes enabling international collaboration between emerging countries and small OECD economies to enable easier transfer of knowledge and technologies. It is thus quite evident that the education sector can play an increasingly important role in adapting to as well as mitigating climate change. While studies have explored numerous possible interventions such as building resilient infrastructure and improving educational attainment, considerable research is still required on the pathways through which these interventions can impact climate change. The following section presents an overview of current literature addressing this aspect. 3. Impact of Schooling on Climate We now turn to the question of the impact of schooling on climate actions, including attitudes, behaviors, and outcomes. While numerous adaptation and mitigation measures have been proposed by policy makers and think tanks, empirical evidence on the causal effect of education on climate 5 literacy and pro-environmental behaviors remains scarce. Moreover, most of the research that does exist is theoretical, correlational, or observational (see, for example, Torgler and Garcia-Valinas 2007; McCright and Dunlap 2011; Kahan et al. 2012; Lee et al. 2015; O’Neill et al. 2020) or small- scale experiments that focused on the impact of specially designed education about the causes and consequences of global warming on public understanding of climate change risks of a nonrepresentative sample (Ranney and Clark 2016; Rumore et al. 2016). The studies have used a variety of outcomes, including waste generation and recycling, purchase of organic foods, water saving behavior, demand for eco-labeling, attitudes toward sustainability, environmental concern, energy use, willingness to pay premium for green electricity, and contributions and actions regarding the environment and studied their relationship to educational attainment (Meyer 2015). Most of these observational studies find positive effects (for example, Bellows et al. 2008; Blend and van Ravenswaay 1999; Brecard et al. 2009; Callan and Thomas 2006; De Silva and Pownall 2014; Duggal et al. 1991; Ek and Soderholm 2008; Ferrara and Missios 2005; Gilg and Barr 2006; Klineberg et al. 1998; Kriström and Kiran 2014; Monier et al; Reschovsky and Stone 1994; Rowlands et al. 2003; Smith 1995; Teisl et al. 2008; Torgler and García-Valiñas 2007; Xiao et al. 2013). A few find negative effects (Grafton 2014; Johnston et al. 2001; Poortinga et al. 2004; Thompson and Kidwell 1998) or no effects (Berk et al. 1993; Millock and Nauges 2014; Wessells et al. 1999). Table 1 presents a summary of the key findings from these studies, while an overview of all the studies included has been provided as Appendix A. A broader systematic review by Ardoin, Bowers and Gaillard (2020) on the research on environmental education's contributions to conservation and environmental quality outcomes resulted in the analysis of 105 studies. The study documented strongly positive environmental education outcomes overall. However, their quality checks looked for studies that could document impact, but it is not clear if the studies were randomized or causal. Table 1: Summary of findings of studies on relationship between education and pro-environmental behaviors Aspects of environmental Nature of relationship with Studies included behavior educational factors Resource (water and energy) Studies find a weak or insignificant Berk et al. 1993 conservation relationship with total years of Ek and Soderholm 2008 education or highest level of Gilg and Barr 2006 education Grafton 2014 Kriström and Kiran 2014 Poortinga et al. 2004 Rowlands et al. 2003 Waste reduction and recycling Studies found a positive relationship Callan and Thomas 2006 with the level of education achieved Duggal et al. 1991 Ferrara and Missios 2005 Reschovsky and Stone 1994 Sustainable food purchases Most studies find a positive Bellows et al. 2008 relationship with total years of Blend and van Ravenswaay 1999 education; some studies find a Brecard et al. 2009 negative relationship with level of Johnston et al. 2001 education Millock and Nauges 2014 Monier et al. 2009 Thompson and Kidwell 1998 Wessells et al. 1999 6 Aspects of environmental Nature of relationship with Studies included behavior educational factors Zepeda and Li 2007 Environmental awareness and Studies find a positive relationship De Silva and Pownall 2014 concern with total years of education as well Klineberg et al. 1998 as level of education Smith 1995 Teisl et al. 2008 Torgler and García-Valiñas 2007 Xiao et al. 2013 Hence, it remains inconclusive whether differences in climate literacy across education groups are the direct result of education affecting people’s attitudes towards climate change, or whether these differences are due to other factors that may or may not be directly observable such as differences in early life experiences, family background, political ideologies, and inborn predispositions (Powdthavee 2021). Therefore, while previous evidence suggests a positive correlation between education and environmental behavior, unobserved characteristics that might cause individuals to attain more education and cause individuals to be environmentally conscious make it difficult to infer causality from this evidence. It is thus essential to introduce mechanisms of exogenous variations in schooling such as compulsory schooling legislations to overcome the endogeneity issue and establish causality. 3.1. The Linkages between Education and Climate Change: Toward a Conceptual Framework Establishing the impact of schooling on climate also requires understanding the pathways that could lead from increased educational attainment to improved environmental outcomes. Authors have previously established the role that increased schooling can play in changing an individual’s cognitive skills (e.g., Pekkala Kerr 2013). Dahmann (2017) further suggests that cognitive skills, which includes innate abilities to reason and process information as well as learned knowledge or behavior, can improve through increased instructional time and a multiplier-effect on the skills gained during the early years. Other authors such as Mcguire (2015) and Powdthavee (2021) have suggested that improved cognitive skills, especially attitudes and behaviors gained through schooling can equip individuals to process information on climate change better and faster thus providing one pathway from schooling to pro-environmental behavior. While improved cognitive skills provides one direct pathway, there are other indirect pathways that may be at play as well. Hwang et al. (2000) in their study based at the Kwang-Reung Arboretum in the Republic of Korea suggest that in addition to cognitive factors, there are affective and situational factors that play a role in ensuring responsible environmental behavior. Affective factors include feelings and emotions whereas situational factors include economic conditions and access to information or resources. The study finds that an individual’s belief in their ability to bring about change plays a critical role in determining their actions and hence education should focus on building critical thinking and action skills that can enable individuals to take their own decisions. Levy et al. (2016) in their study with approximately 3,000 adults in Israel further analyze 7 how different dimensions of cognitive and affective factors relate to environmental behavior. The study finds that affective factors (environmental concern and a willingness to act) are the strongest predictors followed by cognitive aspects such as action-related knowledge and social knowledge. Besides the cognitive and affective factors, the role of situational factors has also been studied in some detail. Chankrajang and Muttarak (2017) suggest that better education results in better earnings, improved access to information, and increased access to resources that can enable individuals to take mitigating action. For example, higher earning households have command over resources such as installing renewable energy sources at home or willingness to pay carbon taxes. Also, knowing where to get information on how to reduce emissions or what adaptations to take can allow individuals to change behavior appropriately. With the causal effect of education on income previously well established in literature (see Heckman et al. 2016) this establishes an indirect pathway from education to improved environmental behavior (Figure 1). Increased Earnings Ability to act (Access to resources and (Adaption and information) Mitigation) Improved Cognitive Skills Pro-Environmental Education (Attitudes and Behavior) Behavior Decision making Increased Demand (for environmental ability action) Figure 1: Direct and Indirect pathways from improved education to pro-environmental behavior While the model provides a possible framework to establish the role that education can play in addressing climate change, determining direction of causality requires more evidence from large- scale studies in an analytical model with variations in educational attainment where environmental behavior is an outcome variable and might lead to improved environmental outcomes.2 2 For example, increased willingness to pay for green electricity can lead to faster decarbonization, resulting in improved air quality and mitigation of climate change. The linkages between changes in behavior and environmental outcomes need to be further examined. 8 3.2. Establishing Causality in Educational Research Establishing causal relationships between education and later life outcomes such as incomes, employability, and even voting behavior has been of interest for many decades. While there is overwhelming evidence for the positive impact that schooling can have, researchers have been cautious in drawing strong inferences about the causal effect of schooling especially in the absence of experimental evidence. However, the emergence of large-scale microeconomic datasets such as OECD’s Programme for International Student Assessment (PISA), Trends in International Mathematics and Science Study (TIMSS), and Progress in International Reading Literacy Study (PIRLS) has provided researchers with more tools to study these relationships. It is now possible to deploy econometric methods such as instrumental variables, regression-discontinuity, propensity score matching, difference-in- difference, and different sorts of fixed-effects specifications to establish causality. Cordero and Cristóbal (2017) provide a comprehensive overview of literature that uses such quasi-experimental techniques. The authors also provide examples of studies that have used such techniques to establish the impact of various school education policies. Particularly, the difference-in-difference approach and instrument variables strategy have been most frequently used for comparison between public and private schools, or to study the effects of class size, tracking, instructional time, teaching methods, school entry age, etc. The authors further suggest creating longitudinal datasets to further causal research in the sector. Schlotter et al. (2011) provide further examples for the applications of these causal methods and the issues faced in aggregation of relevant data. Other techniques that have been suggested include using co-twin control designs on many monozygotic twin pairs to understand the impact of schooling on factors such as political knowledge (Weinschenk and Dawes 2019), wages (Bingley et al. 2009), and health (Fujiwara and Kawachi 2009). Heckman et al. (2016) and Card (1999) further present theoretical models that build on variations of the simple static models presented by Becker (1964) to estimate the private returns to education. However, estimating the social returns using these models remains a limitation. Thus, while numerous methods have been advanced to causally estimate the ex-post returns for education, the lack of large-scale panel data limits generalizability of these results. Using compulsory schooling laws as a source of exogenous variation is thus one possible way to overcome this limitation especially because many countries have historically introduced or made changes to their compulsory schooling laws at different times. The next sub-section presents an overview of some studies that make use of these laws to establish causality. 3.3. Compulsory Schooling as an Instrument and Its Use in Climate Research Numerous studies have used changes in compulsory schooling laws, where some individuals are randomly forced to stay in school longer than their peers, as a natural experiment to research the effect of educational attainment on various aspects of human development. For example, Angrist and Krueger (1991), using longitudinal data from the U.S. Censuses of 1960, 1970, and 1980 for men show that compulsory school attendance laws can have a positive effect on schooling and earnings (see also Domnisoru 2021). The authors further suggest that compulsory schooling laws 9 can improve educational attainment and thus have an associated effect on other social and environmental factors. This is further confirmed by Lleras‐Muney (2002; see also Grenet 2013) who shows that legally requiring children to attend school for one more year increased educational attainment by about 5 percent. Furthermore, the study uses data from the 1960, 1970, and 1980 U.S. censuses in conjunction with changes in compulsory schooling between 1915 to 1939 to establish that each year of additional schooling can reduce mortality by 3-6 percent. Other researchers have used the onset of compulsory schooling law changes to estimate the returns to schooling in the República Bolivariana de Venezuela (Patrinos and Sakellariou 2005), the Netherlands (Levin and Plug 1999), Australia (Leigh and Ryan 2008), Sweden (Card 2001), Ireland (Callan and Harmon 1999), Türkiye (Patrinos, Psacharopoulos and Tansel 2021), the United States (Harmon and Walker 1995), for example. In Europe, Brunello, Fort and Weber (2009), using data from 12 European countries show that compulsory school reforms significantly affect educational attainment, especially among individuals belonging to the lowest quantiles of the distribution of ability. There is also evidence that additional education reduces conditional wage inequality, and that education and ability are substitutes in the earnings function. Aparicio and Kuehn (2017) use data from 31 European countries to find that educational attainment is a key factor for understanding why some individuals migrate and others do not. The authors suggest that individuals moving from low to medium part of the education distribution are less likely to migrate across countries for employment. Other uses of compulsory schooling laws to obtain causal estimates have been used in mortality studies (e.g., Albouy and Lequien 2009; Gathmann et al. 2015), health (e.g., Kemptner et al. 2011), crime (e.g., Bell et al. 2016), religion (e.g., Hungerman 2014), preferences (e.g., Yang 2021), and immigration (e.g., Cavaille and Marshall 2018). 3.4. Use of Compulsory Schooling Laws to Study the Impact on Environmental Behaviors There has recently been some interest in using regression discontinuity design with changes in compulsory schooling laws to analyze whether more schooling improves climate change literacy and pro-environmental attitudes and behaviors later in life. Using the raising of school leaving age (ROSLA) law from September 1972 which increased school leaving age from 15 to 16 years in England as a natural experiment, Powdthavee (2021) shows that remaining in school because of the reform causally reduces people’s unwillingness to change their behaviors for the environment and their perception that climate change is too far in the future to worry. However, Powdthavee finds little evidence that more education improves the pro-environmental behaviors of those who were affected by the reform. This raises an important question of whether policies aimed at improving climate change awareness through education can effectively produce long-lasting changes in pro-environmental behaviors. For Europe as a region, using a regression discontinuity design to instrument for educational attainment, Meyer (2015) uses changes in compulsory education laws in the 20th century as a source of exogenous variation. Meyer finds strong evidence of a positive average treatment effect of increased education on pro-environmental behavior. Using two waves of Eurobarometer surveys, he finds a positive local average treatment effect for 7 of 8 pro-environmental behaviors. An analysis of related questions on the survey supports the notion that education causes individuals to be more concerned with social welfare and to accordingly behave in a more environmentally friendly manner (Meyer 2015). However, the study is restricted to 14 European countries where 10 majority of the educational reforms increased the minimum schooling level to 9 or 10 thus limiting the findings to the lower end of schooling distribution. A wider sample incorporating a larger number of countries with reforms encompassing both primary and secondary schooling may provide more generalizable results. The few studies that focus on developing countries unearth different results. For example, Chankrajang and Muttarak (2017) adopt an instrument variable strategy with self-reported pro- environmental behaviors as the dependent variable and supply of education (number of teachers per 1,000 children) as an instrument in Thailand. They find that improving education levels can have a positive impact on knowledge-based environmentally friendly actions but may not have the same effect on cost-saving pro-environmental actions such as minimizing use of electricity and water, or willingness to pay environmental taxes. Similar research in Philippines by Hoffman and Muttarak (2020) using Propensity Score Matching finds that additional year of schooling significantly increases the probability of pro-environmental actions by 3.3 percent. However, the study uses cross-sectional non-experimental data thus lacking causality. These studies further highlight the need for further research on the linkages between human development and environmental outcomes in a representative sample of countries using long-range panel data and changes in compulsory schooling laws to establish causality. The various studies using compulsory schooling laws as instruments to study the impact on human development outcomes are summarized in Table 2. Table 2: Summary of Studies using Compulsory Schooling Laws as Instruments to Study Impact on Climate Outcomes Country, Dependent Education Data Controls Methods Result Reference year variable variable England, Cross- Climate Education Month of Causal: RD - (+) willingness Powdthavee 2021 Wales 2012, section change level birth, sex compulsory to change 2014 literacy; pro- schooling behavior for environmental laws environment; no behaviors effect on behaviors Europe 2007, Cross- Pro- Education Age, Causal: RD - (+) pro- Meyer 2015 2011 section environmental level country compulsory environmental behaviors fixed schooling behaviors effects laws Thailand Cross- Environmental Education Age, Causal: IV - (+) knowledge Chankrajang and 2013 section attitudes; level Occupation compulsory based pro- Muttarak 2017 willingness to , Wage, schooling, environmental pay for Sex teachers per actions; no cost- environmental 1000 students saving action; no tax impact on concern for global warming; no impact on pay Philippines Pro- Education Non-Causal: (+) increased Hoffmann and 2015 environmental level PSM knowledge; Muttarak 2020 behaviors some effect on behavior 11 4. Conclusion Human development and environmental outcomes are intrinsically linked and affect each other in numerous ways. While there is vast literature on the role that environmental conditions can play in human development outcomes, the role of human development interventions in environmental outcomes is far more difficult to ascertain. Researchers have often linked economic growth with human development and suggested that as economies develop, they initially witness a period of increased environmental degradation followed by a U-shaped recovery. The nature of this relationship suggests that there may be certain human development factors such as education and per capita income at play in determining the relationship between economic growth and environmental outcomes. Human development interventions have also been a way to address environmental degradation. Numerous adaptive and mitigative measures ranging from risk assessment of key infrastructure to redesigning curriculums and promoting research in universities have been suggested by policy practitioners and thinktanks over the years. While the type of interventions suggested are broadly based on the rationale that educated individuals are likely to be more environmentally conscious, a causal relationship has proven to be quite elusive. The paper synthesizes the vast literature on the interlinkages between human development interventions and environmental outcomes. While most of these studies have documented a positive correlation between education and environmental behavior, unobserved characteristics make it difficult to infer causality because there may well be omitted variables that cause individuals to attain more education and cause individuals to be environmentally conscious. We assess compulsory schooling laws as a possible instrument to determine causality. Changes in compulsory schooling laws over the years have been used by researchers as a natural experiment in a regression discontinuity design to study the effect of educational attainment on factors ranging from returns to schooling to migration. While authors have used the methodology to study the effect of education on pro-environmental behaviors, evidence on whether policies aimed at improving climate change awareness through education can effectively produce long-lasting changes in pro-environmental behaviors remains inconclusive. Thus, creating a broader dataset incorporating education law changes over a longer time-period along with other confounding variables for a representative sample of developing and developed countries might provide robust results and help design better human development policies in the future. 12 References Acemoglu, D. and Angrist, J. (2001). How large are human–capital externalities? Evidence from compulsory-schooling laws. 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Journal of Environmental Economics and Management, 104:102365. 22 Appendix A: Summary of Observational Studies on Relationship between Schooling and Climate Attitudes and Behavior Dependent Education Controls Methods Result Reference variable variable Waste generation Not specified Not specified Not specified No relationship Ayalon et al. 2014 Frequency of Not specified Shopping engagement, political Bivariate (+) for both bivariate Bellows et al. purchasing affiliation, age, food production associations and and multivariate 2008 organic foods knowledge OLS models Water saving Years of Social desirability index, LA Quasi-MLE Poisson (+) but statistically Berk et al. 1993 behavior education indicator, income, occupation, regression insignificant children at home, own dwelling, have pool, have lawn or garden Intention to Years of Price, type of eco-labeling, Contingent choice, (+) for probability of Blend and van purchase eco- completed grocery vs. supermarket, Cragg Double- eco-labeled purchase, Ravenswaay labeled apples education frequency of buying organic Hurdle Model, Tobit insignificant for 1999 apples, income, household size, Model quantity of eco-labeled age, gender purchase Desire for eco- Proxied with Environmental attitudes, Ordered probit (+) for intellectual Brecard et al. labeling of fish professional seaside frequentation, age, regression profession 2009 situation gender, marital status, country effects, localization of habitat Municipal solid Percentage of Population, income per capita, Simultaneous (+) quadratic Callan and waste, municipal town with median age, housing density, equations, 3SLS relationship between Thomas 2006 recycling baccalaureate price of waste disposal, education and education frequency of collections, municipal recycling recycling grants 4 attitudes toward High school, Gender, mortgage owner, age, OLS, matching (+) for college De Silva and sustainability (1 to college no. of children, income, estimation education in 3 of 4 Pownall 2014 10 scale) indicators regional/city controls attitudes. (+) for high school education in 1 attitude Newspaper and Percent Family median income, OLS (+) in most of the Duggal et al. glass recycling population over availability of curbside pickup models 1991 25 with 4 or more years of college WTP for green Indicator for Electricity price, electric Probit regression (+) in 1 of 3 reported Ek and electricity university heating, self-image controls, models Soderholm 2008 degree perception of green benefits, gender, age, presence of social norm Recycling Highest Price, weekly recycling, free Ordered probit (+) for post-grad in 4 of Ferrara and participation (7 education level units, unit limit, mandatory regression 7 recycling categories, Missios 2005 categories) attained recycling, home ownership, several other education income, household size, age levels (+) for some recycling categories Water saving Level of formal None Cluster analysis Significant differences Gilg and Barr behavior education in education levels 2006 across clusters 23 Dependent Education Controls Methods Result Reference variable variable Several water Years of post- None Correlation (−) for plugging sink Grafton 2014 saving behaviors secondary coefficient while washing dishes, education recycling rainwater, taking shower instead of bath; no relationship for turn off water while brushing teeth, water garden in coolest part of day Preferences for Indicator for at Member of environmental Contingent choice, (−) for Norwegian Johnston et al. eco-labeled least a 4-yr organization, frequency of logit model households, 2001 seafood degree consuming seafood, seafood insignificant for USA budget, gender, age, income households 4 measures of Years of Gender, age, ethnicity, size of Logistic, Poisson (+) for almost all Klineberg et al. environmental education town, income, political regressions specifications and 1998 concern ideology, religiosity measures of concern WTP for green Years of post- Income, member of OLS, Tobit, Hurdle (+) for WTP for green Kriström and energy, electricity secondary environmental organization, model, Exponential energy, no significant Kiran 2014 demand education energy behavior index, index of type II Tobit relationship for concern for climate change, electricity demand home size, household size, home type, years in residence, urban, age, gender, marital status, employment status Organic food Indicator for at Not reported Not specified No significant Millock and consumption least one-year relationship Nauges 2014 post-high school education Purchase of Not specified Income, age, family size Discrete choice, (+) in increasing cross- Monier et al. organic eggs and multivariate logit complementarity 2009 milk between choices of organic products Energy use Level of Age, income, household size, OLS (−) for home energy Poortinga et al. education, units self-enhancement, use, (+) for transport 2004 not specified environmental quality, self- energy use direction, openness to change, maturity, family, health and safety, achievement, new environmental paradigm, concern about global warming 5 household Indicators for Measures for availability and Probit regression Beyond HS degree (+) Reschovsky and recycling level of knowledge of recycling for 3 behaviors, Stone 1994 behaviors education programs, household size, bachelor's (+) for 4 (beyond HS marital status, gender, age, behaviors, graduate (+) degree, number of hours worked per for 4 behaviors bachelor's week, income degree, and graduate or professional degree) 24 Dependent Education Controls Methods Result Reference variable variable Willingness to Indicators for None Spearman's (+) association Rowlands et al. pay premium for highest level correlation 2003 green electricity achieved (high school or less, some college, bachelor’s degree, graduate degree) Contributing Years of Income, gender, age, race, Probit regression (+) for recycling, not Smith 1995 money to education, support of environmental laws, statistically significant environmental college major science, and environmental for other behaviors, groups, signing knowledge majors mostly not petition about significant environmental issues, recycling Credibility of Years of Gender, age, some Simultaneous (+) for credibility and Teisl et al. 2008 ecolabel education environmental belief/concern equations, Ordered importance of ecolabel, information, measures probit (−) for perceived perceived environmental environmental friendliness friendliness of vehicle, importance of label information Purchase of Indicators for Cosmetic defects, price, Random utility (−) for graduate or Thompson and organic produce level of income, age, number of discrete choice professional degree Kidwell 1998 education children in household, gender, model (college degree distance to grocery store and graduate or professional degree) Willingness to Formal Age, gender, marital status, Ordered probit (+) for informal Torgler and prevent education (age employment status, trust, regression education (robust), (+) García-Valiñas environmental at which membership in environmental for formal education 2007 damage completed org., geographic identification, (not robust) formal size of town, regional and time education), controls informal education (discussing politics) Preferences for Indicator for at frequency of fish purchases, Contingent choice, No significant Wessells et al. eco-labeled least high weekly seafood budget, trust in logit model relationship 1999 seafood school degree certifying agencies, region, gender, principal shopper, member of environmental organization, subscription to environmental magazine, beliefs on overfishing 25 Dependent Education Controls Methods Result Reference variable variable 6 measures of Number of Gender, income, residence, age, Structural equation (+) for composite Xiao et al. 2013 environmental years of non-admin job, admin job, modeling (SEM) environmental concern concern schooling Chinese Communist Party variable affiliation Purchase of Indicator for at Number of children, gender, Zepeda and Li organic food least four years age, race, religion, political 2007 of college identity, income, food expenditures, cooking controls, knowledge/familiarity variables, personal connection variables, intention to act variables, opportunity variables 26