Happiness and the Environment: Finding out a relationship.

Happiness and the Environment: Finding out a relationship By Filipa Fiúza Lelé Master’s Dissertation in Environmental Economics and Management Supervised by: Professor Doctor Maria Cristina Guerreiro Chaves 2013 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP i Biographical Note Ana Filipa de Ribeiro Fiúza e Clemente Lelé born on December 5th 1986, in the city of Lisbon, capital of Portugal, attended Colégio Mira-Rio since pre-school until 9th grade. Continued her education at Escola Secundária da Portela where she graduated in 2004. Entered the Faculty of Economics, New University of Lisbon, concluding a degree in Economics, in January 2009. During this period, she attended an exchange program under the Erasmus program in the Economics Department of the University of Copenhagen, Denmark, in 2008. Before completing the degree, in October 2008, she began working first as an internal auditor and then as a project analyst at IAPMEI (Instituto de Apoio às Pequenas e Médias Empresas). A year after left the company to join the INOV Contacto Program, an internship in the Portuguese Trade and Investment Office in New York, USA. Upon her return, she worked at Parques de Sintra – Monte da Lua in management and planning, in the financial and administrative department. In September 2011, she enrolled in a Masters in Environmental Economics and Management at the University of Porto, Faculty of Economics, finishing the academic part in January 2013. Currently she is working on the dissertation project to conclude the above mentioned masters program. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP ii Acknowledgements Attending the Master in Environmental Economics and Management at University of Porto, Faculty of Economics, was a valuable experience. In the last couple of years, I had the chance of acquiring new knowledge and skills, as well as meeting many new and remarkable individuals. It was undoubtedly a journey that significantly contributed to my personal and professional growth. First and foremost, my deepest and profound appreciation goes to my beloved family, for always giving me care, stability, and encouragement in every aspect of my life. Their support is unconditional and was crucial to finish this project. I would like to express my gratitude to my dissertation advisor, Prof. Dr.ª Cristina Chaves, for her guidance. I am indebted for the assistance and help provided. I would also wish to thank all of my friends for support, patience, reassurance, inspiration, illuminating discussions, and for just being there. To each and every one of you, and you know who you are, my sincere appreciation. Finally, a cordial acknowledgment to Prof. Dr. Ruut Veenhoven for his permission to use his research data on life satisfaction. And to Prof. Dr. Francisco Vitorino Martins for his help defining the dataset. Lisbon, September 2013 _______________ (Filipa Fiúza Lelé) Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP iii Abstract Pollution is a serious issue that has been raising concern for decades. It negatively influences human lives in a wide variety of ways, much of these leading to decreases in overall well-being. GDP is the most broadly used measure of welfare, even though it was not built with that intent. It is discussed that there are better ways to evaluate well-being, such as self-reported levels of happiness and life satisfaction. Furthermore, the economics of happiness is a blooming area in contemporary economic research. This dissertation examines a group of 65 countries to try explaining divergences in self-reported levels of life satisfaction by reference to, among other indicators, air pollutants and environmental amenities, while controlling for economical, social, demographic, and cultural influences. This is done through the interpretations of the results of a constructed econometrical model. The regression analysis is done for the year 2000 and 2010. It is concluded that the variables most impacting life satisfaction on both years are GDP per capita, the percentage of Muslims and Buddhists, and the percentage of people over 65 years. From 2000 to 2010, environmental variables, such as CO2 and other greenhouse gases emissions per capita, the percentage of marine and terrestrial protected areas and the percentage of fossil fuel in total energy consumption became significant in explaining life satisfaction. This points to a positive shift in the relationship between well-being and the environment. It is also compared the situation in Portugal, a country going through a severe social crisis, with Denmark, where economically and socially all is stable, for the period between 1990 and 2010. While in the first, the improvement in environmental indicators was not enough to prevent life satisfaction from decreasing, in Denmark, with all social indicators stable, life satisfaction rose in this country with a better environment. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP iv Resumo O tema da poluição tem, há décadas, levantado sérias preocupações por todo o mundo. Esta tem uma influência nefasta na vida do ser humano, resultando em diminuições de bem-estar. O PIB é a medida de bem-estar mais usada a nível mundial, apesar de não ter sido construído com esse intuito. Na presente dissertação é discutido que existem formas mais adequadas de avaliar o bem-estar, como a felicidade e a satisfação com a vida. Ademais, a economia da felicidade é uma área em significante crescimento na economia contemporânea. Esta dissertação examina um grupo de 65 países como o objectivo de explicar divergências nos níveis de satisfação com a vida. Para tal, recorre-se a indicadores de poluição aérea e de amenidades ambientais, controlando influencias económicas, sociais, demográficas e culturais. Isto é conseguido através da interpretação dos resultados de análises de regressão com base num modelo econométrico construído, para os anos de 2000 e 2010. Conclui-se que as variáveis com impacto mais significativo em ambos os anos foram o PIB per capita, a percentagem de muçulmanos e budistas e a percentagem de população acima dos 65 anos. De 2000 para 2010, algumas variáveis ambientais, como as emissões de CO2 e outros gases de efeito de estufa per capita, a percentagem de áreas marítimas e terrestres protegidas e a percentagem de combustíveis fósseis no total de energia consumida, tornaram-se significativas na explicação da satisfação com a vida. Isto indica uma mudança positiva na relação entre bem-estar e o ambiente. Para o período de 1990 a 2010, é também comparada a situação de Portugal, três um país que se encontra no meio de uma grave crise social, com a Dinamarca, que passa por um período de estabilidade económica e social. Enquanto para o primeiro as melhorias a nível ambiental não foram suficientes para prevenir uma queda na satisfação com a vida, na Dinamarca, a estabilidade dos indicadores sociais, permitiu que a satisfação com a vida subisse com as melhorias ambientais. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP v Table of Contents 1. Introduction ................................................................................................................. 1 2. Literature Review ....................................................................................................... 3 2.1 GDP’s criticism ................................................................................................................. 3 2.1.1 Advantages and Drawbacks ........................................................................................ 3 2.1.2 Sustainability ............................................................................................................... 7 2.1.3 Alternative Indicators to GDP ..................................................................................... 9 2.1.4 The Problem of Overpopulation ................................................................................ 13 2.2 Happiness in Economics ................................................................................................. 15 2.2.1 Happiness, life satisfaction and subjective well-being .............................................. 15 2.2.2 Factors Influencing Happiness .................................................................................. 16 2.2.3 How to Measure Happiness ....................................................................................... 21 2.2.4 Happiness and Classical Utility ................................................................................. 22 2.3 The Environment and Happiness .................................................................................. 23 2.3.1 Pollutants: a short overview ...................................................................................... 23 2.3.2 Amenities................................................................................................................... 25 2.3.3 The tragedy of the commons ..................................................................................... 26 2.3.4 Pollution and Well-Being .......................................................................................... 28 3. Methodology .............................................................................................................. 32 3.1 Variables .......................................................................................................................... 33 3.1.1 Dependent variable .................................................................................................... 33 3.1.2 Independent variables ................................................................................................ 35 3.2 Model ............................................................................................................................... 37 4. Results ........................................................................................................................ 39 4.1 Results for 2000 ............................................................................................................... 42 4.2 Results for 2010 ............................................................................................................... 45 4.3 Correlation matrixes ...................................................................................................... 48 4.4 Comparing 2000 and 2010 ............................................................................................. 51 4.5 The case of Portugal and Denmark ............................................................................... 53 5. Conclusion ................................................................................................................. 56 6. References .................................................................................................................. 59 Appendix I ..................................................................................................................... 70 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP vi List of Tables Table 1 Definition of variables ....................... 37 Table 2 Summary of the data ....................... 39 Table 3 Regression results 2000 – All variables ....................... 42 Table 4 Regression results 2000 – Significant variables ....................... 44 Table 5 Regression results 2010 – All variables ....................... 46 Table 6 Regression results 2010 – Significant variables ....................... 47 Table 7 Correlation of variables, 2000 ....................... 49 Table 8 Correlation of variables, 2010 ....................... 50 Table I.1 Data for life satisfaction ....................... 71 Table I.2 Data for literacy rate ....................... 73 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP vii List of Figures Figure 1 Growth rate between 2000 and 2010 for all variables (average values) ........... 41 Figure 2 Life satisfaction evolution for Portugal and Denmark between 1990 and 2010 ........... 54 Figure 3 CO2 emissions per capita evolution for Portugal and Denmark between 1990 and 2010 ........... 55 Figure 4 Percentage of marine and terrestrial protected areas evolution for Portugal and Denmark between 1990 and 2010 ........... 55 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP viii List of Appendixes Appendix I Life satisfaction and literacy rate data ........................ 71 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 5 are extremely energy-intensive. Therefore, changing the output structure might in some cases minimize environmental damages but it cannot offset them1 (Røpke, 1997). GDP also doesn’t account for the natural capital, like fish stocks, forests, biodiversity, fossil energy, or metals, and its depreciation. There would have to be a sustainable use of this capital for a null effect on the economy (Bergh, 2009). From this framework was born the idea of green accounting, which is a wider take on national accounts that aims to include not only marketed natural resources but also non-marketed as well to incorporate the environment in economic discussion. There are several environmental effects already indirectly included in the system of national accounts, for example, losses in income from tourism due to pollution. However, even though these are accounted for, most are not directly recognizable, only public resources being exploited show up via royalty schemes. There is the need to integrate the use of the environment and natural resources on national accounts and reflect them in the measures of income and product (Hamilton, 1994). Well-being is also highly correlated with leisure. This is again not taken into account by GDP. As a matter of fact, it is entirely the opposite, as there is an opportunity cost for not being productive (Bergh, 2009). There are many unaccounted factors that weight in individual happiness or wellbeing. For example, having a job, a stable family, health, freedom, friends, or being part of a community. Within this framework, it is safe to say that individual income does not capture individual happiness; so it is highly unlikely that GDP would offer an accurate measure of social welfare at a macro level, especially when aggregated information continuously leads to losses (Bergh, 2009). If the economic agents and society as a whole credit GDP for influencing the economy and if this belief prompts pessimistic and optimistic reactions to fluctuations in GDP growth, then they become reality. Governments, banks, and international organizations reinforce this pro-cyclic phenomenon of GDP. Nevertheless, this creates the reverse effect of trust and economic stability when GDP grows. GDP, the most commonly used measure of economic activity, presents some other economical 1 From a global perspective, there is no point in altering the output structure for a less damaging one if the country will import environmentally harmful products from other countries. To the planet it does not matter where the harm occurs (Røpke, 1997). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 6 advantages. This indicator has also proven quite valuable in providing a rough estimate to future tax revenues, which in turn is fundamental to ascertain fair financial contributions of member states and to evaluate the possibility of international loans. For developing countries in particular, there is a more direct link between economic growth and welfare, meaning that GDP is more relevant. Ultimately, GDP provides a clear economic comparison between countries, guarantying data homogeneity; even not being an accurate measure for welfare it certainly has some advantages (Bergh, 2009). Individuals’ necessities can be broadly divided into two categories: lower and higher needs. The first, for example satisfying hunger and thirst, ought to be fulfilled prior to the second. In addition, there are certain goods and services in which the individuals’ needs are limited. Given this frame of reference, it is not coherent to assume that income and consumption growth are a good proxy to the satisfaction of elementary needs. Therefore, the increases in GDP may not reflect the same changes in welfare. Furthermore, there are several studies that suggest that since the mid 20th century, in most OECD countries, while GDP has grown, welfare hasn’t. There are empirical evidences that point to a split in GDP and welfare growth curve; after a period of growing at the same pace, the quality of life begins to deteriorate (Max-Neef, 1995 in Bergh, 2009). Individual well-being has several dimensions. According to Stiglitz et al. (2009), the basic ones are: “material living standards, health, education, personal activities including work, political voice and governance, social connections and relationships, environment (present and future conditions), and insecurity, of an economic as well as physical nature)” (Stiglitz et al., 2009, pp. 15). When trying to raise people’s level of well-being, efforts should be directed at these eight topics, and this should be a government’s concern when designing policies. These can be measured through surveys where individuals self-report their own levels of well-being. Therefore, Stiglitz et al. (2009) defend the necessity of creating a system of measurement that focuses on people’s well-being, in terms of sustainability, rather than economic production. This without totally disregarding GDP, as it is still valuable to monitor economic activity. These measures can and should complement each other to provide more and better information. The authors also recommend that instead of production the focus should be on income and consumption, and including non-market Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 7 activities and leisure. A recommendation made by the authors is that in the short-run, while the indicators cannot be adjusted, governments ought to try focusing more on net instead of gross measures of economic activity. This would include depreciation (and not forgetting environmental depreciation) that can account for differences in the structure of production, even though it is usually hard to calculate. However, the question of sustainability comes as a complement to the topic of well-being, and even tough they go together they should be analysed separately. Sustainability is about predicting the future to try guarantying at least the same level of well-being for the next generations (Stiglitz et al., 2009). 2.1.2 Sustainability “Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (WCED, 1987). Since this first notion of sustainable development was published, the concept has stretched to incorporate all scopes of present and future economic, social, and environmental well-being (Stiglitz et al., 2009). In the Brutland report, it was also stated that economic growth is fundamental to improving the conditions of life in developing countries and to fight environmental problems in all nations. This is due to the fact that the higher the GDP the easiest it is to make people more aware of the environmental problems, to make resource use more efficient, to find ways of substituting the use of scarce resources, and to develop new cleaner technologies2 (Røpke, 1997). Goodland (1995), on the other hand, argues that environmental sustainability does not allow economic growth, as it implies sustainable levels of production and consumption. Environmental sustainability emphasises the role natural resources, which provide renewable (forests) and exhaustible (minerals) physical inputs, incorporating them into the production process. In environmental sustainability models, the 2 This is in line with the theory behind the Environmental Kuznets Curve. There tends to be environmental degradation with economic growth but only until a certain point. Afterwards, economic growth continues rising and the environment begins improving. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 8 production process is also incremented with the disregarded life-support systems, such as atmosphere, water, and soil. Social sustainability deals with the preservation of lifesupport systems that come before environmental quality, such as poverty reduction. These two concepts are obviously highly correlated3 (Goodland, 1995). The key rules for maintaining the environment sustainable are to guaranty that (1) the rate of use is equal or lower than the natural regeneration rate when using renewable resources; and (2) the waste flows to the environment do not go over the capacity of the environment to assimilate them. These rates can easily change through population growth, technological progress, increased efficiency and catastrophes (Pearce, Turner, 1990). When speaking about environmental sustainability there is a need to point out that some actions have irreversible consequences. The extinction of a species cannot be changed, the species cannot be brought back. Tropical forests cannot be recreated. It is quite difficult to take any advantage of desertified land (Pearce, Turner, 1990). The concept of sustainability can be applied to well-being as the well-being of the next generations will depend on the quantity and quality of the resources passed to them by the current generation. These resources are not only in terms of natural capital but also physical, such as machines and buildings, and human, through education and research. And there is a present need to evaluate the durability of the current ways, i.e. to understand whether perpetuation of present trends can be maintained (Stiglitz et al., 2009). One conclusion from happiness research is that quality is more important than quantity; in neo-classic economic theory, the current economic theory, ceteris paribus, more is always better. With relation to the environment, one of the main implications of this research is that aligns with sustainable development. Sustainability tells us that there is a need to consume less and happiness research concludes that individuals need not to maintain or increase their levels of consumption to be happy. Environmental quality makes individuals happy (MacKerron, Mourato, 2009). 3 For instance, a society that does not over explore its resources has less chances of having a war (Goodland, 1995). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 9 2.1.3 Alternative Indicators to GDP Over time, several indicators were created in an attempt to substitute, improve, or complement GDP. As an example a non-comprehensive list of the most relevant indexes for this dissertation is developed. It is organized as follows: firstly, the most well-know indexes, with a focus on social components but not regarding the environment or happiness; secondly, indexes weighting the environment as well as well-being; lastly, two indexes that correlate happiness and the environment. a) Human Development Index (HDI) HDI, developed by the United Nations for the first time in 1990, is a composite index comprising the geometric means of education, life expectancy and income statistics. It aims to depict human well-being more directly and effectively than simple measures of consumption. (Kula et al., 2010). This indicator does not generate a monetary value and it presents an alternative to GDP to show that development is more than increasing national income. It is commonly used, mainly due to its transparency and simplicity, in media and policy as it allows comparisons between nations on the human development level. This is a socio-economic indicator and it does not comprise environmental measures (O'Neill, 2011). Reversely, HDI neglects the distribution of human development inside nations. Likewise, it does not account for other dimensions of welfare, such as human rights, security and political participation (Harttgen, Klasen, 2012). b) Human Poverty Indices (HPI) As the previous, these indices were formulated by the UNDP. HPI calculates deficiencies in the same three dimensions of human development as HDI. HPI-1 was created for developing economies and HPI-2 for developed countries. The latter also captures social exclusion. However, unlike in HDI, the distribution of individual wellbeing is taken into account. In the three dimensions, indicators of deprivation have been included (Kula et al., 2010). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 10 c) Fordham Index of Social Health (FISH) FISH reports well-being during different periods of life, with a total of 16 social indicators that put together provide an ample view of the social health of a nation. For children, it conveys infant mortality, child abuse, and poverty. For youth, it registers teenage suicides, drug use, and high-school dropout rate. For adults, it accounts for unemployment, average weekly earnings, health insurance coverage among those under age 65, poverty for those over 65, and out-of-pocket health-care costs for over 65. For people of all ages, it reports homicides, alcohol-related highway deaths, food stamp coverage, access to affordable housing, and income inequality (IISP, 2013). The indicators chosen are social in the sense that they are connected to all stages of life and to social institutions such as the labour market, social welfare programs, school, and family. As other indices did, FISH showed a similar growth pattern to GDP until late 1970s. From then on, it has decreased while GDP has increased (data for the USA) (IISP, 2013). d) Measure of Economic Welfare (MEW) MEW was created by Nordhaus and Tobin (1972) as a comprehensive quantification of the annual real consumption of households and public consumption, valued at market prices or at their equivalent in opportunity costs. It is based on GDP with alterations to allow the quantification of all market and non-marketed goods and services, like the excluded items leisure or the quality of the environment. MEW equals the sum of the value of GDP, leisure time, and unpaid work, minus the value of environmental damage (Kula et al., 2010). e) Index of Sustainable Economic Welfare (ISEW) ISEW is an advance on MEW, as it further adjusts GDP not only by adding a broader spectrum of harmful effects caused by economic growth but also through the exclusion of public spending on defence. Daly and Cobb created this indicator in 1989 for the USA. In this country and in most of the subsequence countries that have run ISEW, there is one common trade to be found. ISEW and GDP have parallel growth rate until the 1970s, from then on the former starts to decline while the latter continues rising (Castaneda, 1999). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 11 ISEW equals the sum of personal expenditure, public expenditure and value of unpaid work, minus public defence and the value of environmental damage (Bergh, 2009). The general thinking behind ISEW is to remove from personal consumption the expenses that do not contribute to an increase in welfare (defensive expenditures) and to include those that might (non-defensive expenditures), referring to adjustments not contemplated in traditional accounts (Castaneda, 1999). f) Genuine Progress Indicator (GPI) GPI is very similar to the ISEW but includes further specific items: voluntary work, criminality, divorce, leisure time, unemployment and damage to the ozone layer (Bergh, 2009). This indicator proposes to quantify the impacts of economic growth on sustainable welfare through monetary valuation. GPI is the sum of personal consumption expenditures adjusted for income inequality, non-defensive government expenditures, and non-market contributions to welfare, minus defensive private expenditures, costs of environmental degradation, and depreciation of the natural capital base (Posner, Costanza, 2011). g) Genuine Savings (GS) The World Bank has embraced GS, also known as Adjusted Net Savings, as one of their central indicators (Bergh, 2009). GS is based on the concept of green national accounts that is calculated by adding net investment in produced capital to investment in human capital minus the net depreciation of natural capital (Dietz, Neumayer, 2004). This indicator is based on traditional net savings to which are deducted estimates of capital consumption of produced assets, then added expenditures on education (as a proxy for value of investments in human capital), then deducted estimates of the depletion of a variety of natural resources, and at last pollution damages (including economic and health effects) are subtracted (The World Bank, 1997). h) Gross Sustainable Development Product (GSDP) GSDP measures the total value of production within a region over time and it is calculated resorting the market prices for goods and services of transactions in the Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 12 economy. This indicator was developed by the Global Community Assessment Centre as a substitute for GDP (GCAC, 2004). GSDP measures the economic impacts of environmental and health degradation or improvement; resource depletion, depreciation or appreciation or finding new resources; the impact of people activity on the environment; the impact of people activity on availability of resources and on economic development; the quality of the environment, people, resources and development and impact of changes in these on the national income and wealth; the impact of global concerns on the economy; welfare, quality of life and economic development of future generations; expenditures on pollution, health, floods, and car accidents; the resource stocks and productive capabilities of exploited people and ecosystems; the impact of economic growth on biological diversity; and the impacts of social costs and health costs on future generations and the nation's income (GCAC, 2004). i) Gross Environmental Sustainable Development Index (GESDI) GESDI proposes to measure the quality of growth and development with more than 200 indicators of non-market values. These are structured around physical, biological, health, social and cultural components that influence a society. They are mainly divided in four areas: people (includes dimensions of social, economic, psychological, physical and spiritual indicators as well as literacy, rights, justice, diversity, community, peace and conflict, legal and political, etc.); available resources; environment; and economic development (GCAC, 2004). j) Social Progress Index (SPI) SPI, developed by Michael Porter, evaluates the provision of social and environmental needs to the people in each country. The index is constituted by 52 indicators, which are divided through three areas (equally weighted) of basic human needs, foundations of well-being, and opportunity. The index concludes that economic development is a necessary condition but not a sufficient one for social progress, and that a country’s overall degree of development disguises social and environmental forces and challenges (The Social Progress Imperative, 2013). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 13 k) Gross National Happiness (GNH) The King of Bhutan, whose country ranked low on GDP, first expressed the idea of GNH in the 1980s. This indicator, developed in this country, aims to account for all values relevant to life on earth. This is in alignment with the concept of mixed economy, which states that markets cannot regulate themselves on all aspects needing some government intervention (Tideman, 2011). GNH measures the extent to which a population approaches a sufficient level in an array of dimensions instead of simply aggregating happiness or using its average. There are nine equally weighted dimensions of well-being to GNH, which are: psychological well-being, use of time, community vitality, culture, health, education, environment, living standards, and governance (Ura, 2008 in Bates, 2009). It has the drawback of being hard to compare satisfaction and happiness among populations and the possibility of being more focused on well-being rather than living and social conditions (Fleurbaey, 2009). l) Happy Planet Index (HPI) HPI is a measure of sustainable well-being, comprising data on life expectancy, experienced well-being and ecological footprint. The results rank countries on how many long and happy lives they produce per unit of environmental input. This indicator, contrary to many others that emphasize economic activity, focuses on current and future well-being demonstrating that the western model of development is not sustainable. HPI equals experienced well-being, multiplied by life expectancy and divided by ecological footprint (NEF, 2013). 2.1.4 The Problem of Overpopulation Economic growth on its own represents numerous social costs. Our planet does not offer unlimited resources and with exponential economic and population growth only starvation, diseases and conflicts can level food supply and population (Malthus, 1798). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 14 Several authors defend that the world is or will rapidly be overpopulated, that there will be too many of us in the near future for our life style to be maintained. The most well known of these being Thomas Malthus, known as the father of demographics. In 1798 he wrote An Essay on the Principle of Population where it is defended that while population grows in a geometrical way, food supply only grows arithmetically. According to Malthus, if, for example, a country starts at place where the means of subsistence are just the necessary to support its people, the population will grow quicker than the food supply. This means that there will be a decrease in the real value of labour whilst the value of provisions will rise. Workers will then have to work more just to earn the same. During this period, there is a likelihood of naturally appearing restraints to population (there are incentives to have fewer children), the employers will be able to hire more people (as labour is cheaper) and ultimately the ratio of people to food will stabilize. This exercise for a fictitious country, which can easily be extrapolated to the whole world, leads to a vicious cycle as after a period of equilibrium the tendency is for the cycle to repeat itself (Malthus, 1798). Another way for this cycle to play out would be if instead of a check in population growth conflicts arose. This has a higher probability of happening if there is a sudden rapid increase of people. This discussion has been put aside for the past decades for some reasons. On the one hand, fertility levels have been falling considerably, particularly in the developed world. On the other hand, in the past century the world has experienced a technological growth like no other ever seen before, therefore technological progress has been contradicting the Malthusian theory and pushing this discussion away from the economists’ eyes. Also, religious and political views have influenced this discussion, as this is a very controversial topic that goes against the ideological foundations of many individuals (Brander, 2007). These arguments only reinforce the idea that GDP, especially by itself, as a measure of social welfare is not enough and it does not accurately represent the needs of society. It was Simon Kuznets himself, the creator of GDP, who said that a measure of national income was not a measure of national welfare. Moreover, there is a necessity of overcoming a consumerist perspective, as consumption does not necessarily lead to well-being. The fact that trends in GDP and social indicators were once aligned but Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 21 afterwards abandoned) and China. In both, there was a severe rise in unemployment and most benefits were lost. China’s overall life satisfaction has seen no increase in the last two decades, in spite of much higher incomes on average, which allows again conjecturing that the job and benefits losses had a much greater effect on happiness than a rise in earnings. Much like China is the example of East Germany, a transition country. Comparing the periods before and after the changes, it is possible to see that following the transition there was a substantial increase in satisfaction with the environment and availability of goods. However, in health, work, and childcare, the variation was vastly negative. The outcomes of these comparisons tell us yet again that countries welfare cannot be judge solely on GDP per capita nor should government policies be focused on that alone. There are many other factors, some with much higher effect that impact overall and individual life satisfaction, which need to be taken into account when drawing policies. 2.2.3 How to Measure Happiness Over the past few years, many more researchers have become interested in the study of happiness, mainly in self-reports of happiness. Data on this subject is usually gathered through surveys where the respondent is asked a general question about his own level of happiness (Di Tella, MacCulloch, 2006; Welsch, 2009). “There are a number of different measurement techniques available to capture subjective well-being [...]. These can be distinguished along two dimensions: cognition, the evaluative or judgmental component of well-being (usually assessed with questions asking about satisfaction with life overall); and affect, the pleasure-pain component of well-being (Diener, 1984). With regard to the latter, it is common to distinguish further between positive affect (e.g., happiness, joy) and negative affect (e.g., anger, sadness), treating them as independent.” (Frey, Stutzer, 2013, pp. 434) The most common method to measure happiness is a straightforward individual questionnaire with questions related to income, job, health, and overall satisfaction. Their answers can be either in discrete terms with verbal categories (bad/good) or numerical categories (1-10) (Oswald, 1997; van Praag, 2007; Welsch, 2009; Stutzer, Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 22 Frey, 2010). People are considered to be suitable reviewers of their own overall life quality, therefore this kind of measure can provide valuable information (Stutzer, Frey, 2010). There are other approaches to measure happiness, for example the Experience Sampling Method, where information is collected on the actual experiences of individuals in real time in their natural environments; the Day Reconstruction Method, where people are asked on how satisfied they felt at several times throughout the day; the U (“unpleasant”)-Index, where it is described the portion of time that an individual passes in an unpleasant state each day; Brain Imaging, where magnetic resonance imaging is used to scan individual brain activity for association of positive and negative affect; and the Life Satisfaction Approach, where “the marginal utility of public goods or the disutility of public bads is estimated by correlating the amount of public goods or public bads with individuals’ reported subjective well-being” (Frey, Stutzer, 2013, pp. 441). 2.2.4 Happiness and Classical Utility “Utility is a term used in economics to measure the relative satisfaction from, or desirability of pursuing one course of action rather than another.” (Frey, Stutzer, 2013, 431) In the prevailing economic theory, utility is captured through consumption and choices between alternatives; economists are taught to infer preferences from observed choices, see what people do instead of hearing what they say (Di Tella, MacCulloch, 2006; Frey, Stutzer, 2010). However, many authors defend the study of happiness in economics as a more appropriate proxy for utility, instead of the now in use GDP, as people are often biased when selecting amongst alternatives (Welsh, 2009; Frey, Stutzer, 2010; Frey, Stutzer, 2013). For example, it is appealing for individuals to eat candy, and this in fact raises their utility in the short run, nonetheless, afterwards they realize that it would have been better not to not have done it (Stutzer, 2009 in Frey, Stutzer, 2013). In standard economic theory, this act would have increased utility when in fact it does the opposite. Basing utility on revealed preferences doesn’t account for Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 23 consumers not always making the best choices for themselves. This is one of the main critics to the GDP, some actions give the wrong signal, increasing GDP when it should decrease and vice-versa. The study of happiness allows correcting these biases (Frey, Stutzer, 2013). The study of individual happiness is, therefore, based on subjective views that people have on their own lives. And, while some argue that people often don’t proper estimate their own utility levels, which can be pointed as a criticism for using selfreported happiness as a measure of well-being. For example, it frequently happens to overestimate the effect of particular events in one’s life and the capacity of adaptation to them (Stutzer, Frey, 2012). Others defend the exact opposite. For instance, Ferrer-iCarbonell (2013) states that there has been empirical proof over the past years validating the predictive ability of the happiness reports and their link with individuals’ behaviour. 2.3 The Environment and Happiness 2.3.1 Pollutants: a short overview The USA Environmental Protection Agency (EPA, 2010) defines pollution as “the presence of a substance in the environment that because of its chemical composition or quantity prevents the functioning of natural processes and produces undesirable environmental and health effects”. According to the European Environmental Agency, there are two distinct kinds of pollution harming the environment: point source pollution, produced by a “stationary location or fixed facility from which pollutants are discharged” (EEA, 2013); and non-point source pollution, caused from diffuse sources. The atmosphere is mostly composed by compounds containing sulphur, nitrogen, carbon, and halogen. Air pollution occurs when concentrations of these compounds are sufficiently elevated, exceeding regular levels, to produce a measurable effect on humans, animals, vegetation, or materials. Methane, ethane, propane, and butane are composed of carbon atoms (Seinfeld, Pandis, 2006). According to the EPA, Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 24 the six most common pollutants are ground-level ozone, particulate matter, carbon monoxide, nitrogen oxides, sulphur dioxide, and lead (EPA, 2012d). Ozone develops “through chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOC) in the presence of sunlight. Emissions from industrial facilities and electric utilities, motor vehicle exhaust, gasoline vapors, and chemical solvents are some of the major sources of NOx and VOC” (EPA, 2012b). Particulate matter (PM) is a composite combination of very tiny particles and liquid droplets, consisting of components such as acids (nitrates and sulfates), organic chemicals, metals, and soil or dust particles (EPA, 2013b). Carbon monoxide (CO) is a gas resulting from combustion process that is presented with no odour or colour (EPA, 2012a). Nitrogen dioxides (NO2) are extremely reactive gasses rapidly created through vehicle, power plants, and off-road equipment emissions. NO2 leads to the creation of ground-level ozone, particle pollution, and negative effects on the respiratory system (EPA, 2013a). Sulfur dioxides (SO2) are extremely reactive gases created through “fossil fuel combustion at power plants (73%) and other industrial facilities (20%)” (EPA, 2013c). Lead (Pb) is a metal that can be located in nature and in manufactured products. Nowadays, leaded aviation gasoline is the primary source for lead emissions (EPA, 2012c). Water is fundamental for existence, just as air. However, drinkable water is a limited resource in our planet and maintaining its quality is vital (WHO, 2013b). There are seven types of water pollution: surface water pollution, ground water pollution, oxygen depleting, nutrients, microbiological, suspended matter and chemical. These can be caused by sewage and wastewater, marine dumping, industrial waste, radioactive waste, oil pollution, underground storage leaks, atmospheric deposition, global warming, and eutrophication. All are harmful for humans and animals, especially after long-term exposure (EPA, 2013d). The main water pollutants are biological oxygen demand (BOD) and suspended solids (SS). “Organic water pollutants are oxidized by naturally-occurring microorganisms. This 'biological oxygen demand' removes dissolved oxygen from the water and can seriously damage some fish species which have adapted to the previous dissolved oxygen level. Low levels of dissolved oxygen may enable disease causing pathogens to survive longer in water. Organic water pollutants can also accelerate the growth of algae, which will crowd out other plant species. The eventual death and Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 25 decomposition of the algae is another source of oxygen depletion as well as noxious smells and unsightly scum. The most common measure for BOD is the amount of oxygen used by micro-organisms to oxidize the organic waste in a standard sample of pollutant during a five-day period” (Hettige et al., 1995, pp. 37). Suspended solids are “small particles of non-organic, non-toxic solids suspended in waste water [that] will settle as sludge blankets in calm-water areas of streams and lakes. This can smother plant life and purifying micro-organisms, causing serious damage to aquatic ecosystems. The loss of purifying micro-organisms enables pathogens to live longer, raising the risk of disease. When organic solids are part of the sludge, their progressive decomposition will also deplete oxygen in the water and generate noxious gases” (Hettige et al., 1995, 37). 2.3.2 Amenities “Environmental amenities are defined as all those natural assets including green spaces that are aesthetic, ecological, and economic in nature, as well as those that have a physical or psychological effect on human health, such as pollution control, noise abatement, and the provision of recreational opportunities.” (Tyrväinen, Miettinen, 2000 in Gupta et al., 2009) Environmental amenities are associated to the quality and quantity of the natural resources of one’s community, such as lakes, rivers, forests, croplands, pastureland, under water bodies, shoreline, climate, light, and parks, and to the quality and quantity of the air, water, noise, and waste present in the environment (Marans, 2003; Poudyal et al., 2008; Wu, 2006). They are also directly linked with physical health (Marans, 2003; Poudyal et al., 2008). Financial investments can go a long way to increase, improve, and encourage the use of natural amenities by improving areas of open space, restoring rundown properties, constructing outdoor facilities, improving street cleanliness, improving public areas, and creating cycling and walking paths (Poudyal et al., 2008). These investments create economical return as they make surrounding areas more attractive to Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 26 investors (house developing, businesses, services), increase migration to the region, and raise property value (Tajibaeva et al., 2008). Environmental amenities are mostly non-excludable, which means that it is hard to exclude non-payers from enjoying its benefits and in turn disincentives individual investment. Therefore, many researchers defend that the investment in natural amenities should come from the government (Haddock, 2004). Nonetheless, individuals prize environmental amenities. These are usually valuated through proximity. For example, there is a positive effect of being close to coast that weakens with increasing distancing. The exact opposite occurs with proximity to waste facilities. Therefore, geography has a significant impact on well-being (Brereton et al., 2008). 2.3.3 The tragedy of the commons Each individual is constantly using available goods, space, and resources that belong to the entire population. The individual benefit captured is obvious and the impact caused seems harmless. The rational individual rapidly concludes that the benefits outweigh his losses, which results in the tragedy of the commons, a concept popularized by Garrett Hardin in the 1960s. The main point defended by Hardin, an extrapolation from the prisoner’s dilemma, states that what is common to the individuals will be exploited until exhaustion (Hardin, 1968). A common good is a finite resource whose use will lead to extinction. The author resorts to a very clarifying example. He conceives a pasture for cattle shared by a community. Not having any type of control or limits to its use, each individual will try to make the most use of the field without worrying with its sustainability in the long run. This will lead to the pasture’s exhaustion and consequent extinction of the resource as it is impossible to maximize two variables, either one has more animals or a sustainable pasture (Hardin, 1968). Nature has the capacity of selfregeneration but not if resources are over-exploited, as the example describes and as it is being experienced nowadays (Dasgupta, Ehrlich, 2013). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 27 Hardin assumes that the individual is rational (as described by Adam Smith), therefore his goal is to maximize his own gains. Thus, there will always be an incentive to place one more animal on the pasture as each one brings an individual gain whilst the loss is distributed among all. In this context, it is necessary to re-evaluate individual freedom because maximizing one’s gains does not correspond to the society’s optimal point (contradicting Adam Smith’s theory). Also, it is assumed that the pasture is limited; that it won’t hold an infinite number of cattle (Hardin, 1968). This tragedy is what affects the environment, a common, nowadays. This happens not only due to an excessive use of resources but also through pollution. For the rational individual, the cost of not treating sewage, chemicals, radioactive material, or not producing dangerous and harmful fumes is smaller than if he would. There is no incentive to interiorize the externalities. If all the population is composed by rational individuals, then everyone will act in this way leading to a tragedy of the commons, as the water and air that surround us are accessible to all (Hardin, 1968). This is only made harder by the mobility of the pollutants, through river flows, animals, and wind (Dasgupta, Ehrlich, 2013). In a reverse way, environmental amenities, as parks or beautiful landscapes, can be analysed in the same way. They are highly valued by individuals but its optimal is challenging to estimate. Given that they are common goods, one cannot be excluded from its enjoyment. This in turn creates an incentive to understate the real demand for environmental amenities, due to free riders (Eagle, 2004). History has shown us that with continuous rise in population common goods are disappearing due to over-exploitation. Since the creation of private properties, fishing areas, and hunting laws, there is a pattern of privatization or restriction to the common good as its demand increases. It is also what has been happening in the environmental area. There are laws regarding water treatment, residues, garbage, countries that enforce recycling, incentives to the development of renewable energies, the Kyoto protocol (for example, the carbon credit market), and tight laws for activities or products with higher environmental impact, as factories, insecticides, or fertilizers. The goal is to internalize the cost of polluting or destroying natural resources, as externalities are mostly not selfcorrecting, and avoid the tragedy of the commons in the environment (Hardin, 1968). These externalities are a result of the choices made by each individual. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 28 Consumption is known to bring about these consequences, for present and future generations. Modern practices of consumerism incentivize constant new purchases and money spending just for the sake of it (Dasgupta, Ehrlich, 2013). Neo-classical theory states that, all things the same, more is always better. This is quite problematic, as all other things never always remain the same. This view that promotes more production and consumption imposes severe consequences on all other things (MacKerron, Mourato, 2009). But consumption is driven not only through competition but also for the desire of fitting in. This is more observable and of especially concern in developed societies, as the environmental consequences are steep. For example, individuals tend to have a car if people in their circle also have them, together with the discovered evidence that the choice of make and model of the vehicle is driven by competition with peers. This only leads to more cars and more used up oil. This is just one of many examples where today’s consumption social conventions are environmentally damaging. On top of these rich countries issues, there is happening a resource-intensive increase in the consumption of goods and services in developing nations (Dasgupta, Ehrlich, 2013). Technological progress has been pointed out by many as the miracle solution for nearly all environmental issues. However, there has to be incentives for the creation of new technologies. And as so many are not sensible or downplay the importance of the environmental challenges that the world is facing it is unrealistic to expected big technological improvements in the near future. Furthermore, history has revealed the extinction of many societies due to over-use of their natural resources and degradation of local environment (Dasgupta, Ehrlich, 2013). 2.3.4 Pollution and Well-Being Pollution is affecting climate in an array of ways, for example increasing global average temperature, abrupt changes in regional weather patterns, melting glaciers, decreasing crop yields, escalating intensity of storms, forest fires, droughts, flooding and heat waves, rising of sea level, and reducing biodiversity. Furthermore, all these impacts are much more likely to affect the poorest nations that have less capacity to adapt and fight these consequences and in turn widens the gap between richer and Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 29 poorer countries (Stern, 2008). The economic results of climate change, according to several studies, are usually reflected on variations in productivity in areas such as agriculture, energy, and tourism. These changes can have either positive or negative consequences subject to time and place (Rehdanz, Maddison, 2005). Particularly in the developing countries, water and air pollution have become topics that raise serious concerns. Since there is hardly any waste treatment and pollutant controls (such as for fertilizers or industrial chemicals), many severe health issues have been arising. The World Health Organization (WHO) estimates 2 million deaths a year due to water contamination alone, many more if air pollution is accounted for (highly driven by megacities and their heavy fog) (Biswas et al., 2012). And WHO also estimates that environmental factors represent about 24% of the total burden of disease (data for 2008), with increasing chronic conditions. Children are the most burdened, as they have higher concentrations of pollutants due to having less body weight than adults; the elderly and the poor are also higher risk groups (Stiglitz et al., 2009). Air quality, in addition to health and property, influences individual’s reported well-being, the higher the pollution the more negative is the effect. Luechinger (2009, in Oswald, 2012) shows that German people’s happiness is affected by the quantity of SO2 in the air. Levinson (2012) calculates the monetary value that people seem to be predisposed to spend, about $35 for an enhancement of one standard deviation in air quality for one day, in the USA. Ferrer-i-Carbonell and Gowdy (2007) study the relationship between concern for ozone pollution and threat to biodiversity, and individual’s well-being in the United Kingdom. The authors find a statistically significant negative correlation concerning environmental degradation and well-being (around 81% of the individuals demonstrate concern for the ozone layer) and a statistically significant positive connection between caring for animal extinction and well-being (about 85% of the individuals revealed concern for the extinction of species), the latter being coherent with other findings, which show that individuals care about biodiversity (Nunes, van den Bergh, 2001, in Ferrer-i-Carbonell, Gowdy, 2007). Even after controlling for psychological traits, the preceding conclusions are not challenged (Ferrer-i-Carbonell, Gowdy, 2007). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 30 Another factor associated with increasing pollution is the shadow economy. It is been known to comprise many pollution intensive activities, “such as leather tanning, brick making, metal working, resource extraction, urban transportation with old and inefficient vehicles, and production in small scale or family-based factories” (Biswas et al., 2012, pp. 114), all of which do not tend to follow environmental standards. Biswas et al., using a panel data from 1999-2005 for over 100 countries, established that an increase in the underground economy increases pollution (results hold when controlling for additional causes of pollution). Still, controlling corruption can restrain this effect. Noise pollution has been identified in literature as an influence on well-being, particularly associated with roads and airports (Rehdanz, Maddison, 2008; Weinhold, 2008). Chronic airport noise exposure has a negative impact at an economical, physical, and psychological level, affecting not only life satisfaction but also house satisfaction (Weinhold, 2008). It is an issue that seems to disturb different people in different ways, as some are more sensible to noise than others (Walters, 1975 in Weinhold, 2008). Weinhold (2008) found that respondents to happiness surveys that ticked the higher boxes of complaint with noise were significantly unhappier than the rest, as a highly significant level. As the urbanization increases, so will noise pollution, as people level in areas of increasing high density and housing prices. The negative effect can be minimized by better acoustic insulation of dwellings, an area left wide open for governments to legislate. Pollution can cause insomnia, stress, hearing problems, high blood pressure, heart diseases, lower immune system, birth defects, and respiratory diseases (PasschierVermeer, Passchier, 2000 and Gouveia, Maisonet, 2005 in MacKerron, Mourato, 2013). A polluted environment seems to have a negative effect on individual’s well-being. Welsch (2006, in Ferrer-i-Carbonell, 2013) found an inverse correlation between selfreported satisfaction with life and lead and nitrogen. Natural environments have long been positively correlated to better health, wellbeing and happiness. Authors MacKerron and Mourato (2013) have conducted an experiment that allowed them to conclude, at a highly statistically significant level, this exact correlation. They propose three explanations. On the one hand, science has shown that experiences in nature tend to reduce stress in the nervous system. On the other hand, natural environments are associated with lower pollution, which causes mental Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 37 3.2 Model To estimate the impact of environmental pollutants and amenities on life satisfaction, the following model is constructed using the variables described in table 1 for two separate years, 2000 and 201012: The GDP per capita variable is included both in its level, as the other variables, and as a quadratic variable (Rehdanz, Maddison, 2005). Table 1 – Definition of variables Variable Definition LSatisf Average score of self-reported life satisfaction GDP cap GDP per capita in 2005 USD converted using market exchange rates Inf Annual inflation rate (%) - consumer prices Unemp Annual rate of unemployment GDP growth Annual GDP growth rate (%) CO2 cap Annual emissions of CO2 (metric tons per capita) PM Concentrations of PM10 (micrograms per cubic meter) Methane cap Annual emissions of Methane (metric tons per capita) Nitrous cap Annual emissions of Nitrous oxide (metric tons per capita) Other gases cap Annual emissions of other greenhouse gases (metric tons per capita) Forest area Percentage of forest area Protected areas Percentage of terrestrial and marine protected areas Fossil Fuels Percentage of fossil fuel energy consumption Popdens Population density in persons per square kilometre Urbpop Percentage of the population living in urban areas Age 0-14 Proportion of the population under 15 years Age >65 Proportion of the population over 65 years Lit Percentage of the population age 15 and above who can, with understanding, read and write a short, simple statement on their everyday life 12 i – countries; t – periods of time Equation 1 Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 38 Freed CL Index of personal freedom - Civil liberties Christian Proportion of the population who are Christian Muslim Proportion of the population who are Muslim Hindu Proportion of the population who are Hindu Buddhist Proportion of the population who are Buddhist Life exp Life expectancy in years Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 39 4. Results In table 2 are displayed the range of the variables, their means and standard deviations. Table 2 – Summary of the data 2000 2010 Growth rate between 2000-2010 (average values) Average Standard deviation Minimum Maximum Average Standard deviation Minimum Maximum Lstatisf 2,67 0,43 1,72 3,58 2,93 0,43 1,78 3,67 9,74% GDP cap 15655,70 17448,14 474,63 72394,19 17855,34 18756,53 854,32 81385,29 14,05% Inf 8,33 14,75 -1,71 96,09 3,80 4,08 -1,09 28,19 -54,38% Unemp 9,14 6,20 1,40 32,20 9,14 5,09 3,50 32,00 0,00% GDP growth 4,17 2,49 -4,30 10,00 3,50 3,32 -4,94 13,09 -16,07% CO2 cap 6,10 4,70 0,68 20,25 6,22 4,51 0,78 21,36 1,97% PM 43,38 33,14 11,54 168,92 28,72 20,09 9,26 112,01 -33,79% Methane cap 1,46 1,15 0,29 6,67 1,38 1,06 0,32 5,68 -5,48% Nitrous cap 0,73 0,59 0,13 3,95 0,62 0,45 0,10 2,36 -15,07% Other gases cap 0,13 0,21 0,00 1,28 0,20 0,22 0,00 1,13 53,85% Forest area 32,90 18,97 0,06 73,74 32,96 18,40 0,07 72,91 0,18% Protected areas 11,49 9,88 0,05 50,18 13,19 10,24 0,05 50,19 14,80% Fossil Fuels 74,82 18,35 25,62 99,70 74,02 18,24 17,51 97,45 -1,07% Popdens 108,52 109,41 2,49 476,13 116,85 117,38 2,87 508,86 7,68% Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 40 2000 2010 Growth rate between 2000-2010 (average values) Average Standard deviation Minimum Maximum Average Standard deviation Minimum Maximum UrbPop 67,09 15,69 24,37 97,12 69,99 15,10 30,39 97,46 4,32% Age 0-14 24,95 8,71 14,32 44,06 21,85 7,89 13,29 41,52 -12,42% Age >65 10,56 4,94 3,13 18,26 11,86 5,44 3,37 22,96 12,31% Lit 92,80 9,94 52,31 100,00 94,47 8,15 62,75 100,00 1,80% Free CL 2,62 1,42 1,00 7,00 2,25 1,45 1,00 6,00 -14,12% Christian 66,63 32,63 0,10 99,00 66,63 32,63 0,10 99,00 0,00% Muslim 11,70 27,71 0,10 99,00 11,70 27,71 0,10 99,00 0,00% Hindu 1,45 9,84 0,00 79,50 1,45 9,84 0,00 79,50 0,00% Buddhist 1,69 5,95 0,00 36,20 1,69 5,95 0,00 36,20 0,00% Life exp 73,38 5,07 54,78 81,08 75,83 5,32 52,08 82,84 3,34% Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 41 Figure 1– Growth rate between 2000 and 2010 for all variables (average values) From 2000 to 2010, considering the country sample, there was a +9,74% increase in average self-reported life satisfaction. GDP per capita also increased on average, +14,05%. The average of the inflation rate decreased more than half, -54,38%. Average unemployment level was maintained. The emissions of CO2 (+1,97%) per capita increased slightly and the emissions of methane and nitrous oxide per capita decreased slightly. The average concentration of particulate matter had a significant decrease (-33,79%). The average percentage of forest area showed no significant change, much as the percentage of fossil fuel in total energy consumption. But the percentage of protected area increased +14,80%. The percentage of the population under 15 years decreased on average and the opposite was verified for the percentage of people over 65 years. -60.00% -40.00% -20.00% 0.00% 20.00% 40.00% 60.00% Lstatisf GDP cap Inf Unemp GDP growth CO2 cap PM Methane cap Nitrous cap Other gases cap Forest area Protected areas Fossil Fuels Popdens UrbPop Age 0-14 Age >65 Lit Free CL Christian Muslim Hindu Buddhist Life exp Growth rate between 2000-2010 (average values) Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 42 4.1 Results for 2000 There were estimated two regressions for the year 20001; one with all the variables and a second one were the not statistically relevant ones were removed. The results of the first one are presented in Table 4. This regression has a R2 of 82,62%, which is regarded as elevated. However, there are many variables with a high p-value that need to be excluded from the regression, as they have no statistical significance. Variables are considered significant at 5% significance level. Table 3 – Regression results 2000 – All variables 1 The software used for all regressions was EViews 8. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 43 The following variables were considered not significant in explaining life satisfaction: GDP growth, CO2, methane, nitrous oxide, and other greenhouse gases emissions per capita, concentration of particulate matter, percentage of forest area and protected areas, percentage of fossil fuel in total energy consumption, literacy rate, the index of freedom, population density, and percentage of the population living in urban areas. Therefore, a new regression for the same year is estimated without them. The results are presented in table 6. Table 4 – Regression results 2000 – Significant variables This regression has a R2 of 79,91%, slightly lower than the previous one, which was expected as there are less independent variables. In this regression, GDP per capita and its quadratic function are the most statistically significant explanatory variables. The former has a positive coefficient sign, which means that it is expected for a country with a higher GDP per capita to have a higher life satisfaction. This is in agreement with the literature previously discussed. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 44 Unemployment is also highly significant in explaining life satisfaction. Its negative coefficient sign translates into the expectations of a country with a higher unemployment rate having a lower life satisfaction value. The same is verified for inflation. In 2000, no environmental variable was considered statistically significant. The percentage of people over 65 years impacts negatively life satisfaction. The percentage of Muslims, Hindus and Buddhists impact negatively life satisfaction, at a 5% significance level. The higher the percentage of religious people of these three religions the lower was life satisfaction. Life expectancy had a negative statistically significant impact on life satisfaction. This result was contrary to the expected and defended in the literature. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 45 4.2 Results for 2010 As for the year 2000, there were estimated two regressions for 2010; one with all the variables and a second one were the not statistically relevant ones were removed. The results of the first one are presented in Table 6. This regression has a R2 of 84,24%, which is high especially considering that there are 65 observations. However, there are some variables with a high p-value that need to be excluded from the regression, as they have no statistical significance. Variables are considered significant at 5% significance level. Table 5 – Regression results 2010 – All variables Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 46 The following variables were considered not significant to explain life satisfaction: unemployment rate, inflation rate, GDP growth, nitrous oxide and methane emissions per capita, concentration of particulate matter, population density, the index of freedom, life expectancy and the percentage of people under 15 years. Therefore, a new regression for the same year is estimated without them. The results are presented in table 7. Table 6 – Regression results 2010 – Significant variables This regression has a R2 of 82,80%, slightly lower than the previous one, which was expected as there are less independent variables. In this regression, the emissions of CO2 and other greenhouse gases per capita are statistically significant. The coefficient signs are negative, which may mean that individuals value their health as they associate pollution with poorer health. The percentage of fossil fuel in total energy consumption impacts life satisfaction negatively. The environmental amenities percentage of marine Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 53 4.5 The case of Portugal and Denmark In Portugal, overall self-reported life satisfaction has shown a decreasing tendency between 1990 and 2010. During these years, GDP per capita increased, inflation dropped, and the literacy rate increased, as did life expectancy. When comparing these three realities to a country such as Denmark, a pioneer country in environmental laws (Jänicke, 2005), the picture is quite different. Over the 20 years between 1990 and 2010, life satisfaction increased in this nation, as did GDP per capita. Figure 2 – Life satisfaction evolution for Portugal and Denmark between 1990 and 2010 Environmentally, Portugal was not in 2010 worse off than in 1990, the emissions of CO2, methane, nitrous oxide, and other greenhouse gases per capita barely increased and the concentration of particulate matter decrease more than 50%. In Denmark, during the period between 1990 and 2010, the per capita emissions of CO2, methane, nitrous oxide, and other greenhouse gases diminished. The concentration of particulate matter decreased by nearly half in twenty years. The level of CO2 per capita is higher in Denmark than in Portugal, however in former the decrease has been more significant than in the latter. 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Life Satisfaction Portugal Dinamarca Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 54 Figure 3 – CO2 emissions per capita evolution for Portugal and Denmark between 1990 and 2010 There were in Portugal in 2010 more forests and protected areas than in 1990. The same happened in Denmark. Nonetheless, Portugal has a higher growth rate of percentage of marine and terrestrial protected areas than Denmark. Figure 4 – Percentage of marine and terrestrial protected areas evolution for Portugal and Denmark between 1990 and 2010 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 CO2 per capita Portugal Dinamarca 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Protected areas Portugal Dinamarca Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 55 The percentage of fossil fuels as a total of energy consumption diminished 5% in twenty years in Portugal. In Denmark, there was a decrease of more than 10% in this variable, most likely due to many investments made in renewable energy sources. However, even with all these progresses, average well-being still decreased in Portugal and increased in Denmark. In these twenty years, Portugal lost 5% of people under 15 years and gained the same in people over 65 years. At the same time, unemployment raised 6% (from 5% in 2000 to 11% in 2010). This created a social crisis stronger than any economical or environmental improvements could ever over turn. There is no financial security with unemployment rising. Also, the relative increase of population over 65 years and the relative decrease of population under 15 years raise concerns with the short and long term sustainability of social security. It creates added pressure on the working class as taxes increase to counterbalance this new reality. When a country is going through times of social uncertainty, the environmental reality takes a back seat in people and government’s priorities. In Denmark, the inflation rate and the unemployment rate were much unaltered during this period, as were the percentages of people under 15 years and over 65 years. Here is a society still not much going to the aging process other countries are (e.g. Portugal) and without an unemployment crisis. The social stability lived in the country allows people to have other priorities and value different scenarios. Danish people, free of social crisis, can thus for give importance to the environmental quality of their surroundings. As so many improvements happened in the environmental field in Denmark, the average life satisfaction of the country increased. Even though these conclusions hold for individuals, the same should not be applied to the government. They have the obligation to put environmental concerns in the same degree of importance as social and economical issues. For once, it is the government’s role to protect its citizens from harm and potential diseases that pollutants can cause (Stern et al., 1985). They also have the responsibility of guarantying the preservation of the environment for future generations, given equal importance to all dimensions of sustainable development, economical, social, and environmental (Stiglitz et al., 2009). Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 56 5. Conclusion This dissertation’s purpose was to determine if there was an impact supported by statistical evidence of the environment on subjective well-being. To achieve this aim a sample of 65 countries were chosen and data were collected for the years 2000 and 2010 in order to make an evolutionary comparison between the two years. The dependent variable chosen was self-reported life satisfaction measured through surveys administered to individuals across time and countries. As explanatory variables to account for pollution and environmental amenities, the following were chosen: emissions of CO2, methane, nitrous oxide and other greenhouse gases per capita, concentration of particulate matter, percentage of forest area, percentage of marine and terrestrial protected areas, and percentage of fossil fuel of total energy consumption. These comprise some of the most harmful air pollutants and important environmental amenities. To fully understand what influences happiness, it were included in model economical, social and demographical variables: GDP per capita, inflation rate, unemployment rate, GDP growth, population density, percentage of urban population, percentage of people under 15 years, percentage of people over 65 years, literacy rate (as a proxy for education), the weight of major religions and life expectancy (as a proxy for health). An econometric model was constructed with the variables above-mentioned and regressions analyses were run, one with all the variables and another with the statistically significant ones for each year. For both years, one of the most significant variables in explaining life satisfaction was GDP per capita, with a positive impact. As it has been previously argued, even though this is not the only factor influencing well-being it certainly has its importance. The percentage of people over 65 years impacts negatively life satisfaction, both in 2000 and in 2010, as people associate being part of an aging society with a load on social security and potential taxes increases. There are no significant environmental variables in 2000. However, what is interesting to notice is that several environmental variables that were non-significant in 2000 became significant in explaining life satisfaction in 2010. This happened with the emissions of CO2 and other greenhouse gases per capita, the percentage of fossil fuel in Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 57 total energy consumption and the percentage of protected areas. For all these variables, the coefficient sign was the expected. These results suggest that people are becoming more aware of environmental issues and valuing more environmental amenities, correlating them to their own well-being. Some reasons are pointed out to explain the lack of a stronger relationship between environmental variables and life satisfaction. On one hand, there is a disassociation between environmental problems and health issues, which usually only manifest at a latter age. On the other hand, pollution is still much associated with economic growth, which only shows a need to pursue less polluting ways of production and consumption. To complement the econometrical analysis, a statistical comparison was made between Portugal, a country going through a severe social crisis, and Denmark, a socially stable nation, for the period comprised between 1990 and 2010, on an early average. It was possible to verify that with increasing unemployment rates there is not enough room for individuals to value environmental improvements, Portugal had diminishing life satisfaction ratings with increasing unemployment rates. However, with unchanging unemployment rates, as happened in Denmark, and all other social variables stagnated, individuals were able to enjoy environmental progressions. Life satisfaction rose in this county between 1990 and 2010. It is crucial to have in mind that pollution affects people in an extensive variety of ways, mainly through health problems and consequences of climate change. And there is a governmental obligation to mitigate these effects, not only through tighter environmental laws and inspections but also through raising environmental awareness. It is also of importance to notice that GDP, the main economical and welfare indicator used in the world, does not account pollution, environmental degradation, stock depletion, species extinctions, or the benefits of environmental amenities. Therefore, there is the space to complement GDP with other indicators, through direct adjustments or in combination with several other measurements. Subjective well-being, through data on self-reported happiness or life satisfaction, can be a great complementary tool for governments throughout the world. It will impel them to stop prioritizing economic growth and start focusing more on what really makes people happy and better off. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 58 Given that the economics of happiness has been growing in the last decades and that it is starting to have an important role in contemporary economics, in the next few years it will be possible to redo this work with more data, countries and years wise. This analysis could in the future be extended to include further environmental variables, such as water pollutants that to date do not have significant available data to be incorporated in the model. Many pollutants and environmental amenities vary immensely not just among countries, but also within countries. It would be interesting to apply this study to a region level. The adaptation effect has also not been included in the model. All this is deferred to future research. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 59 6. References Bates, W. (2009), “Gross national happiness”, Asian-Pacific Economic Literature, Vol. 23, No. 2, pp. 1-16. Bergh, J. (2009), “The GDP Paradox”, Journal of Economic Psychology, Vol. 30, No. 2, pp. 117-135. Biswas, A. K., Farzanegan, M. R., Thum, M. (2012), “Pollution, Shadow Economy and Corruption: Theory and Evidence”, Journal of Ecological Economics, Vol. 75, pp. 114125. Blanchflower, David G., Oswald, Andrew J. (2004), “Well-being over time in Britain and the USA”, Journal of Public Economics, Vol. 88, pp. 1359-1386. Brander, J. A. (2007), “Viewpoint: Sustainability: Malthus revisited?”, Canadian Journal of Economics, Vol. 40, No. 1, pp. 1-38. Brereton, Finbarr, Clinch, Peter J., Ferreira, Susana (2008), “Happiness, geography and the environment”, Ecological Economics, Vol. 65, pp. 386-396. Caporale, Guglielmo Maria, Georgellis, Yannis, Tsitsianis, Nicholas, Ping, Ya (2009), "Income and happiness across Europe: Do reference values matter?", Journal of Economic Psychology, Vol. 30, No. 1, pp. 42-51. Castaneda, B. E. (1999), “An index of sustainable economic welfare (ISEW) for Chile”, Journal of Ecological Economics, Vol. 28, No. 2, pp. 231-244. Cattaneo, Matias D., Galiani, Sebastian, Gertler, Paul J., Martinez, Sebastian, Titiunik, Rocio (2009), “Housing, Health and Happiness”, American Economic Journal: Economic Policy, Vol. 1, No. 1, pp. 75-105. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 60 CDIAC (2013), “Ranking of the world's countries by 2010 total CO2 emissions”. Retrieved August 22, 2013, from Carbon Dioxide Information Analysis Center: http://cdiac.ornl.gov/trends/emis/top2010.tot. CIA (2013), “The World Factbook”. Retrieved August 20, 2013, from Central Intelligence Agency: https://www.cia.gov/library/publications/the-worldfactbook/fields/2103.html. Clark, Andrew E., Oswald, Andrew J. (1994), “Unhappiness and unemployment”, The Economic Journal, Vol. 104, pp. 648-659. Costanza, Robert, Fisher, Brendan, Ali, Saleem, Beer, Caroline, Bond, Lynne, Boumans, Roelof, Danigelis, Nicholas L., Dickinson, Jennifer, Elliot, Carolyn, Farley, Joshua, Gayer, Diane Elliot, Glenn, Linda MacDonald, Hudspeth, Thomas, Mahoney, Dennis, McCahill, Laurence, McIntosh, Barbara, Reed, Brian, Rizvi, S. Abu Turab, Rizzo, Donna M., Simpatico, Thomas, Snapp, Robert (2007), “Quality of life: An approach integrating opportunities, human needs, and subjective well-being”, Ecological Economics, Vol. 61, pp. 267-276. Dasgupta, P. S., Ehrlich, P. R. (2013), “Pervasive Externalities at the Population, Consumption, and Environment Nexus”, Science, Vol. 340, No. 6130, pp. 324-328. Di Tella, Rafael, MacCoulloch, Robert (2006), “Some Uses of Happiness Data in Economics”, Journal of Economic Perspectives, Vol. 20, No. 1, pp. 25-46. Di Tella, Rafael, MacCoulloch, Robert, Oswald, Andrew J. (2001), “Preferences over Inflation and Unemployment: Evidence from Surveys of Happiness”, The American Economic Review, Vol. 91, No. 1, pp. 335-341. Diener, E., Emmons, Robert A., Larsen, Randy J., Griffin, Sharon (1985), “The Satisfaction with Life Scale”, Journal of Personality Assessment, Vol. 1, pp. 71-75. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 61 Diener, E., Oishi, Shigehiro, Lucas, Richard E. (2009), “Subjective Well-Being: The Science of Happiness and Life Satisfaction”, in Snyder, C. R., Lopez, Shane J. (2009), Oxford Handbook of Positive Psychology, New York, NY, USA: Oxford University Press, Inc., pp. 187-194. Dietz, S., Neumayer, E. (2004), “Genuine savings: a critical analysis of its policyguiding value”, International Journal of Environment and Sustainable Development, Vol. 3, No. 3, pp. 276-292. Eagle, Steven J. (2004), “Environmental Amenities, Private Property, and Public Policy”, Natural Resources Journal, Vol.44, pp. 425-444 Easterlin, R. A. (2013), “Happiness, Growth, and Public Policy”, Economic Inquiry, Vol. 51, No. 1, pp. 1-15. EconStats (2012), “Unemployment rate”. Retrieved August 21, 2013, from EconStats: http://www.econstats.com/weo/V027.htm. EEA (2013), “European Environmental Agency”. Retrieved August 07, 2013, from European Environmental Agency: http://www.eea.europa.eu/themes/water/waterpollution/themes/water/wise-help-centre/glossary-definitions/direct-point-source. EES (2012), “The European Social Survey”. Retrieved September 04, 2013, from European Social Survey: http://ess.nsd.uib.no. EPA (2010), “Terms of the Environment”. Retrieved August 07, 2013, from Environmental Protection Agency: http://www.epa.gov/region4/rcra/bflr/2011bfgranteeworkshop/brownfieldsgrantsresourc efiles/aboutbrownfields/glossaryofenvironmentalterms-2010july.pdf. EPA (2012a), “Carbon Monoxide”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/carbonmonoxide/. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 62 EPA (2012b), “Ground Level Ozone”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/ozonepollution/. EPA (2012c), “Lead in Air”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/lead/. EPA (2012d), “Six Common Air Pollutants”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/urbanair/. EPA (2013a), “Nitrogen Dioxide”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/nitrogenoxides/. EPA (2013b), “Particulate Matter (PM)”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/particlepollution/. EPA (2013c), “Sulfur Dioxide”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www.epa.gov/airquality/sulfurdioxide/. EPA (2013d), “Water Resources”. Retrieved August 12, 2013, from Environmental Protection Agency: http://www2.epa.gov/learn-issues/water-resources#our-waters. Ferreira, Susuna, Moro, Mirko (2010), “ On the Use of Subjective Well-Being Data for Environmental Valuation”, Environmental and Resource Economics, Vol. 46, pp. 249273. Ferrer-i-Carbonell, Ada (2013), “Happiness Economics”, SERIEs, Vol. 4, pp. 35-60. Ferrer-i-Carbonell, Ada, Gowdy, J. M. (2007), “Environmental degradation and happiness”, Journal of Ecological Economics, Vol. 60, No. 3, pp. 509-516. Fleurbaey, M. (2009), “Beyond GDP: The Quest for a Measure of Social Welfare”, Journal of Economic Literature, Vo. 47, No. 4, pp. 1029-1075. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 69 Veenhoven, R. (2010), “Happy Life Years in 149 nations 2000-2009, Rankreport Happy Life Years”. Retrieved August 20, 2013, from World Database of Happiness: http://worlddatabaseofhappiness.eur.nl/hap_nat/findingreports/RankReport_HappyLife Years.php. Veenhoven, R. (2013), “States of Nations: Data file to be used for the cross-national analysis of happiness”. Retrieved August 15, 2013, from World Database of Happiness: http://worlddatabaseofhappiness.eur.nl/statnat/statnat_fp.htm. WCED (1987), “Our common future”, Report of the World Commission on Environment and Development. Weinhold, D. (2008), “How big a problem is noise pollution? A brief happiness analysis by a perturbable economist”, University Library of Munich, Germany, No. 9885. Welsch, Heinz (2009), “Implications of happiness research for environmental economics”, Ecological Economics, Vol. 68, pp. 2735-2742. Weitzman, Martin L. (1994), “On the “Environmental” Discount Rate”, Journal of Environmental Economics and Management, Vol. 26, pp. 200-209. WHO (2013b), “Water”. Retrieved August 12, 2013, from World Health Organization: http://www.who.int/topics/water/en/. Wu, JunJie (2006), “Environmental amenities, urban sprawl, and community characteristics”, Journal of Environmental Economics and Management, Vol. 52, No. 2, pp. 527-547. Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 70 Appendix I Table I.1 – Life Satisfaction data For 2000 For 2010 Country name Lsatisf Year Reference Lsatisf Year Reference Australia 3,06 2000 Veenhoven (2013) 3,07 2010 Veenhoven (2013) Austria 3,11 2002 ESS (2013) 3,10 2006 ESS (2013) Belgium 3,08 2000 Veenhoven (2013) 3,16 2010 Veenhoven (2013) Bolivia 2,95 2000 Veenhoven (2013) 3,09 2010 Veenhoven (2013) Brazil 2,61 2000 Veenhoven (2013) 3,45 2010 Veenhoven (2013) Bulgaria 2,08 2001 Veenhoven (2013) 2,20 2010 Veenhoven (2013) Canada 3,36 2000 Veenhoven (2013) 3,11 2010 Veenhoven (2013) Chile 2,28 2000 Veenhoven (2013) 3,12 2010 Veenhoven (2013) China 2,75 1999 Veenhoven (2013) 2,71 2007 WVS (2011) Colombia 2,40 2000 Veenhoven (2013) 3,46 2010 Veenhoven (2013) Costa Rica 2,64 2000 Veenhoven (2013) 3,44 2010 Veenhoven (2013) Croatia 2,79 2004 Veenhoven (2013) 2,78 2010 Veenhoven (2013) Czech Republic 2,84 2001 Veenhoven (2013) 2,90 2010 Veenhoven (2013) Denmark 3,58 2000 Veenhoven (2013) 3,67 2010 Veenhoven (2013) Ecuador 1,86 2000 Veenhoven (2013) 3,14 2010 Veenhoven (2013) Egypt 2,14 2000 WVS (2011) 2,31 2008 WVS (2011) El Salvador 2,34 2000 Veenhoven (2013) 3,07 2010 Veenhoven (2013) Estonia 2,44 2001 Veenhoven (2013) 2,77 2010 Veenhoven (2013) Finland 3,10 2000 Veenhoven (2013) 3,33 2010 Veenhoven (2013) France 2,94 2000 Veenhoven (2013) 2,99 2010 Veenhoven (2013) Germany 2,96 2000 Veenhoven (2013) 3,08 2010 Veenhoven (2013) Greece 2,61 2000 Veenhoven (2013) 2,36 2010 Veenhoven (2013) Guatemala 2,64 2000 Veenhoven (2013) 3,31 2010 Veenhoven (2013) Honduras 2,63 2000 Veenhoven (2013) 3,32 2010 Veenhoven (2013) Hungary 2,54 2001 Veenhoven (2013) 2,42 2010 Veenhoven (2013) Iceland 3,44 2004 ESS (2013) 3,62 2010 Veenhoven (2013) India 2,06 2001 WVS (2011) 2,32 2006 WVS (2011) Indonesia 2,78 2001 WVS (2011) 2,76 2006 WVS (2011) Iraq 2,09 2004 WVS (2011) 1,78 2006 WVS (2011) Ireland 3,21 2000 Veenhoven (2013) 3,24 2010 Veenhoven (2013) Israel 2,81 2001 WVS (2013) 3,22 2010 Veenhoven (2013) Italy 2,88 2000 Veenhoven (2013) 2,76 2010 Veenhoven (2013) Japan 2,59 2000 WVS (2011) 2,64 2010 Veenhoven (2013) Jordan 2,24 2001 WVS (2011) 2,88 2007 WVS (2011) Latvia 2,54 2001 Veenhoven (2013) 2,60 2010 Veenhoven (2013) Lithuania 2,29 2001 Veenhoven (2013) 2,55 2010 Veenhoven (2013) Luxembourg 3,27 2000 Veenhoven (2013) 3,34 2010 Veenhoven (2013) Macedonia 2,05 2001 WVS (2011) 2,51 2010 Veenhoven (2013) Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 71 For 2000 For 2010 Country name Lsatisf Year Reference Lsatisf Year Reference Mexico 2,71 2000 Veenhoven (2013) 3,27 2010 Veenhoven (2013) Moldova 2,28 2001 WVS (2011) 2,18 2006 WVS (2011) Morocco 2,42 2001 WVS (2011) 2,10 2007 WVS (2011) Netherlands 3,38 2000 Veenhoven (2013) 3,48 2010 Veenhoven (2013) Nicaragua 2,16 2000 Veenhoven (2013) 3,21 2010 Veenhoven (2013) Norway 3,19 2002 ESS (2013) 3,25 2010 ESS (2013) Panama 2,78 2000 Veenhoven (2013) 3,41 2010 Veenhoven (2013) Paraguay 2,14 2000 Veenhoven (2013) 3,15 2010 Veenhoven (2013) Peru 1,72 2000 Veenhoven (2013) 2,97 2010 Veenhoven (2013) Poland 2,65 2001 Veenhoven (2013) 2,92 2010 Veenhoven (2013) Portugal 2,60 2000 Veenhoven (2013) 2,34 2010 Veenhoven (2013) Romania 2,00 2000 Veenhoven (2013) 2,33 2010 Veenhoven (2013) Russia 2,68 2000 Veenhoven (2013) 2,40 2010 ESS (2013) Slovakia 2,48 2001 Veenhoven (2013) 2,88 2010 Veenhoven (2013) Slovenia 3,04 2001 Veenhoven (2013) 3,04 2010 Veenhoven (2013) South Africa 2,53 2001 WVS (2011) 2,88 2007 WVS (2011) South Korea 2,49 2001 WVS (2011) 2,56 2005 WVS (2011) Spain 2,98 2000 Veenhoven (2013) 2,88 2010 Veenhoven (2013) Sweden 3,34 2000 Veenhoven (2013) 3,46 2010 Veenhoven (2013) Switzerland 3,26 2002 ESS (2013) 3,32 2010 ESS (2013) Turkey 2,26 2001 Veenhoven (2013) 2,75 2010 Veenhoven (2013) Ukraine 2,26 2001 Veenhoven (2013) 2,06 2010 ESS (2013) United Kingdom 3,20 2000 Veenhoven (2013) 3,31 2010 Veenhoven (2013) United States 3,38 2001 Veenhoven (2013) 3,06 2010 Veenhoven (2013) Uruguay 2,36 2000 Veenhoven (2013) 3,24 2010 Veenhoven (2013) Venezuela 2,82 2000 Veenhoven (2013) 3,43 2010 Veenhoven (2013) Vietnam 2,61 2001 WVS (2011) 2,84 2006 WVS (2011) Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 72 Table I.2 – Literacy rate data For 2000 For 2010 Country Name Lit Year Reference Lit Year Reference Australia 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Austria 98,00 CIA (2013) 98,00 CIA (2013) Belgium 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Bolivia 86,72 2001 The World Bank (2013) 91,17 2009 The World Bank (2013) Brazil 86,37 2000 The World Bank (2013) 90,38 2010 UNESCO (2012) Bulgaria 98,20 2001 The World Bank (2013) 98,35 2011 The World Bank (2013) Canada 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Chile 95,72 2002 The World Bank (2013) 98,55 2009 The World Bank (2013) China 90,92 2000 The World Bank (2013) 94,27 2010 The World Bank (2013) Colombia 92,80 2004 The World Bank (2013) 93,37 2010 The World Bank (2013) Costa Rica 94,87 2000 The World Bank (2013) 96,16 2010 The World Bank (2013) Croatia 98,15 2001 The World Bank (2013) 98,83 2010 The World Bank (2013) Czech Republic 99,00 2011 CIA (2013) 99,00 2011 CIA (2013) Denmark 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Ecuador 90,98 2001 The World Bank (2013) 91,85 2010 The World Bank (2013) Egypt 71,41 2005 The World Bank (2013) 72,05 2010 The World Bank (2013) El Salvador 79,83 2004 The World Bank (2013) 84,49 2010 The World Bank (2013) Estonia 99,77 2000 The World Bank (2013) 99,80 2010 The World Bank (2013) Finland 100,00 2000 CIA (2013) 100,00 2000 CIA (2013) France 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Germany 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Greece 95,99 2001 The World Bank (2013) 97,19 2010 The World Bank (2013) Guatemala 69,10 2002 The World Bank (2013) 75,18 2010 The World Bank (2013) Honduras 80,01 2001 The World Bank (2013) 84,76 2010 The World Bank (2013) Hungary 99,03 2004 The World Bank (2013) 99,05 2010 The World Bank (2013) Iceland 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) India 61,01 2001 The World Bank (2013) 62,75 2006 UNESCO (2012) Indonesia 90,38 2004 The World Bank (2013) 92,81 2010 UNESCO (2012) Iraq 74,05 2000 The World Bank (2013) 78,17 2010 The World Bank (2013) Ireland 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Israel 97,10 2004 CIA (2013) 97,10 2004 CIA (2013) Italy 98,42 2001 The World Bank (2013) 98,93 2010 The World Bank (2013) Japan 99,00 2002 CIA (2013) 99,00 2002 CIA (2013) Jordan 89,89 2003 The World Bank (2013) 92,55 2010 The World Bank (2013) Latvia 99,75 2000 The World Bank (2013) 99,78 2010 The World Bank (2013) Lithuania 99,65 2001 The World Bank (2013) 99,70 2010 The World Bank (2013) Luxembourg 100,00 2000 CIA (2013) 100,00 2000 CIA (2013) Macedonia 96,13 2002 The World Bank (2013) 97,27 2010 The World Bank (2013) Mexico 90,54 2000 The World Bank (2013) 93,07 2010 The World Bank (2013) Moldova 96,65 2000 The World Bank (2013) 98,52 2010 The World Bank (2013) Morocco 52,31 2004 The World Bank (2013) 67,08 2011 UNESCO (2012) Netherlands 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Happiness and the Environment: Finding out a relationship Filipa Fiúza Lelé, Master in Environmental Economics and Management, FEP 73 For 2000 For 2010 Country Name Lit Year Reference Lit Year Reference Nicaragua 76,68 2001 The World Bank (2013) 78,00 2005 The World Bank (2013) Norway 100,00 CIA (2013) 100,00 CIA (2013) Panama 91,90 2000 The World Bank (2013) 94,09 2010 The World Bank (2013) Paraguay 90,27 1992 The World Bank (2013) 93,87 2010 The World Bank (2013) Peru 87,67 2004 The World Bank (2013) 89,59 2007 The World Bank (2013) Poland 99,41 2004 The World Bank (2013) 99,52 2010 The World Bank (2013) Portugal 87,95 1991 The World Bank (2013) 95,18 2010 The World Bank (2013) Romania 97,30 2002 The World Bank (2013) 97,68 2010 The World Bank (2013) Russia 99,44 2002 The World Bank (2013) 99,58 2010 The World Bank (2013) Slovakia 99,60 2004 CIA (2013) 99,60 2004 CIA (2013) Slovenia 99,65 2004 The World Bank (2013) 99,69 2010 The World Bank (2013) South Africa 82,40 1996 The World Bank (2013) 92,98 2011 UNESCO (2012) South Korea 97,90 2002 CIA (2013) 97,90 2002 CIA (2013) Spain 96,49 1991 The World Bank (2013) 97,75 2010 The World Bank (2013) Sweden 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Switzerland 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Turkey 87,37 2004 The World Bank (2013) 92,66 2010 UNESCO (2012) Ukraine 99,43 2011 The World Bank (2013) 99,71 2010 The World Bank (2013) United Kingdom 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) United States 99,00 2003 CIA (2013) 99,00 2003 CIA (2013) Uruguay 96,78 1996 The World Bank (2013) 98,07 2010 The World Bank (2013) Venezuela 92,98 2001 The World Bank (2013) 95,51 2009 The World Bank (2013) Vietnam 90,16 2000 The World Bank (2013) 93,18 2010 The World Bank (2013)