document_title: World Happiness Report

question_text: the most happy country in the world 2018

root

text: World Happiness Report

text: Annual Report Topics[edit]

text: World Happiness Reports were issued in 2012, 2013, 2015, 2016 (an update), 2017 and 2018. In addition to ranking countries happiness and well-being levels, each report has contributing authors and most focus on a subject. The data used to rank countries in each report is drawn from the Gallup World Poll,[18] as well as other sources such as the World Values Survey, in some of the reports. The Gallup World Poll questionnaire[19] measures 14 areas within its core questions: (1) business & economic, (2) citizen engagement, (3) communications & technology, (4) diversity (social issues), (5) education & families, (6) emotions (well-being), (7) environment & energy, (8) food & shelter, (9) government and politics, (10) law & order (safety), (11) health, (12) religion and ethics, (13) transportation, and (14) work.

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text: 2018 World Happiness Report[edit]

text: The 2018 reiteration was released on 14 March and focused on the relation between happiness and migration. As per 2018 Happiness Report, Finland is the happiest country in the world,[20] with Norway, Denmark, Iceland, and Switzerland holding the next top positions. The World Happiness Report 2018 ranks 156 countries by their happiness levels, and 117 countries by the happiness of their immigrants. The main focus of this year’s report, in addition to its usual ranking of the levels and changes in happiness around the world, is on migration within and between countries. The overall rankings of country happiness are based on the pooled results from Gallup World Poll surveys from 2015–2017, and show both change and stability. Four countries have held the top spot in the last four reports: Denmark, Switzerland, Norway and now Finland. All the top countries tend to have high values for all six of the key variables that have been found to support well-being: income, healthy life expectancy, social support, freedom, trust and generosity. Among the top countries, differences are small enough that year-to-year changes in the rankings are to be expected.

text: The analysis of happiness changes from 2008–2015 shows Togo as the biggest gainer, moving up 17 places in the overall rankings from 2015. The biggest loser is Venezuela, down 2.2 points. Five of the report’s seven chapters deal primarily with migration, as summarized in Chapter 1. For both domestic and international migrants, the report studies the happiness of those migrants and their host communities, and also of those in the countryside or in the country of origin. The results are generally positive. Perhaps the most striking finding of the whole report is that a ranking of countries according to the happiness of their immigrant populations is almost exactly the same as for the rest of the population. The immigrant happiness rankings are based on the full span of Gallup data from 2005 to 2017, sufficient to have 117 countries with more than 100 immigrant respondents. The ten happiest countries in the overall rankings also make up ten of the top eleven spots in the ranking of immigrant happiness. Finland is at the top of both rankings in this report, with the happiest immigrants, and the happiest population in general. While convergence to local happiness levels is quite rapid, it is not complete, as there is a ‘footprint’ effect based on the happiness in each source country. This effect ranges from 10% to 25%. This footprint effect explains why immigrant happiness is less than that of the locals in the happiest countries, while being greater in the least happy countries.

text: 2016 World Happiness Report (Update)[edit]

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showDescriptions

The 2016 World Happiness Report -Rome Addition was issued in two parts as an update. Part one had four chapters: (1) Setting the Stage, (2) The Distribution of World Happiness, (3) Promoting Secular Ethics, and (4) Happiness and Sustainable Development: Concepts and Evidence. Part two has six chapters: (1) Inside the Life Satisfaction Blackbox, (2) Human Flourishing, the Common Good, and Catholic Social Teaching, (3) The Challenges of Public Happiness: An Historical-Methodological Reconstruction, (4) The Geography of Parenthood and Well-Being: Do Children Make Us Happy, Where and Why?, and (5) Multidimensional Well-Being in Contemporary Europe: An Analysis of the Use of a Self-Organizing Map Applied to Share Data.
Chapter 1, Setting the Stage is written by John F. Helliwell, Richard Layard, and Jeffrey Sachs. This chapter briefly surveys the happiness movement (“Increasingly, happiness is considered to be the proper measure of social progress and the goal of public policy.”) gives an overview of the 2016 reports and synopsis of both parts of the 2016 Update Rome Addition.
Chapter 2, The Distribution of World Happiness is written by John F. Helliwell, Hailing Huang, and Shun Wang. This chapter reports happiness levels of countries and proposes the use of inequalities of happiness among individuals as a better measure for inequality than income inequality, and that all people in a population fare better in terms of happiness when there is less inequality in happiness in their region. It includes data from the World Health Organization and World Development Indicators, as well as Gallup World Poll. It debunks the notion that people rapidly adapt to changes in life circumstances and quickly return to an initial life satisfaction baseline, finding instead that changes in life circumstances such as government policies, major life events (unemployment, major disability) and immigration change people’s baseline life satisfaction levels. This chapter also addresses the measure for affect (feelings), finding that positive affect (happiness, laughter, enjoyment) has much “large and highly significant impact” on life satisfaction than negative affect (worry, sadness, anger). The chapter also examines differences in happiness levels explained by the factors of (1) social support, (2) income, (3) healthy life, (4) trust in government and business, (5) perceived freedom to make life decisions and (6) generosity.
Chapter 3, Promoting Secular Ethics is written by Richard Layard, This chapter argues for a revival of an ethical life and world, harkening to times when religious organizations were a dominant force. It calls on secular non-profit organizations to promote “ethical living in a way that provides inspiration, uplift, joy and mutual respect”, and gives examples of implementation by a non-profit founded by Richard Layard,[21] the chapter author, Action for Happiness, which offers online information from positive psychology and Buddhist teachings.
Chapter 4, Happiness and Sustainable Development: Concepts and Evidence is written by Jeffrey Sachs. This chapter identifies ways that sustainable development indicators (economic, social and environmental factors) can be used to explain variations in happiness. It concludes with a report about an appeal to include subjective well-being indicators into the UN Sustainable Development Goals (SDGs).
Part Two 2016 Special Rome Edition was edited by Jeffrey Sacks, Leonardo Becchetti and Anthony Arnett.
Chapter 1, Inside the Life Satisfaction Blackbox is written by Leonardo Becchetti, Luisa Carrado,[22] and Paolo Sama. This chapter proposes using quality of life measurements (a broader range of variables that life evaluation) in lieu of or in addition to overall life evaluations in future World Happiness Reports.
Chapter 2, Human Flourishing, the Common Good, and Catholic Social Teaching is written by Anthony Annett. This chapter contains explanations for three theories: (1) It is human nature to broadly define happiness and understand the connection between happiness and the common good, (2) that the current understanding of individuality is stripped of ties to the common good, and (3) that there is a need to restore the common good as central value for society. The chapter also proposes Catholic school teachings as a model for restoring the common good as a dominant value.
Chapter 3, The Challenges of Public Happiness: An Historical-Methodological Reconstruction is written by Luigino Bruni and Stefano Zemagni. This chapter contemplates Aristotelian concepts of happiness and virtue as they pertain to and support the findings in the World Happiness Reports regarding the impact of social support, trust in government, and equality of happiness.
Chapter 4, The Geography of Parenthood and Well-Being. Do Children Make Us Happy, Where and Why? is written by Luca Stanca.[23] This chapter examines other research findings that children do not add happiness to parents. Using data from the World Values Survey, it finds that, with the exception of widowed parents, having children has a negative effect on life satisfaction for parents in 2/3 of the 105 countries studied, with parents in richer countries suffering more. Once parents are old, life satisfaction increases. The chapter concludes that “existing evidence is not conclusive” and a statement that the causes for the low life satisfaction levels may be that for richer countries, having children is valued less, and in poorer countries, people suffer in financial and time costs when they have children.
Chapter 5, Multidimensional Well-Being in Contemporary Europe: Analysis of the Use of Self-Organizing Map Allied to SHARE Data is written by Mario Lucchini, Luca Crivelli[24] and Sara della Bella. This chapter contains a study of well-being data from older European adults. It finds that this chapter’s study results were consistent with the World Happiness Report 2016 update: positive affect (feelings) have a stronger impact on a person’s satisfaction with life than do negative affect (feelings).

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text: 2015 World Happiness Report[edit]

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The 2015 World Happiness Report has eight chapters: (1) Setting the Stage, (2) The Geography of World Happiness, (3) How Does Subjective Well-being Vary Around the World by Gender and Age?, (4) How to Make Policy When Happiness is the Goal, (5) Neuroscience of Happiness, (6) Healthy Young Minds Transforming the Mental Health of Children, (7) Human Values, Civil Economy, and Subjective Well-being, and (8) Investing in Social Capital.
Chapter 1, Setting the Stage is written by John F. Helliwell, Richard Layard and Jeffrey Sachs. This chapter celebrates the success of the happiness movement (“Happiness is increasingly considered a proper means of social progress and public policy.”), citing the OECD Guidelines on Measuring Subjective Well-being, a referendum in the EU requiring member nations to measure happiness, and the success of the World Happiness reports (with readership at about 1.5 million), and the adoption of happiness by the government of the United Arab Emirates, and other areas. It sets an aspiration of the inclusion of subjective well-being into the 2015 Sustainable Development Goals (not fulfilled), and outlines the 2015 report. It also address the use of the term Happiness, identifying the cons (narrowness of the term, breath of the term, flakiness), and defining the use of the term for the reasons that the 2011 UN General Assembly Resolution 65/309 Happiness Towards A Holistic Approach to Development[25] and April 2012 UN High Level Meeting: Well-being and Happiness: Defining a New Economic Paradigm,[26] Bhutan’s Gross National Happiness[27] philosophy, the term’s “convening and attention attracting power,” and the asset in a “double usage of happiness” as an emotional report and life evaluation.
Chapter 2, The Geography of Happiness is written by John F. Helliwell, Hailing Huang and Shun Wang. This chapter reports the happiness of nations measured by life evaluations. It includes color coded maps and an analysis of six factors the account for the differences: (1) social support in terms of someone to count on in times of need, (2) GDP per capita (income), (3) life expectancy (in terms of healthy years), (4) sense of corruption in government and business (trust), (5) perceived freedom to make life decisions, and (6) generosity. The first three factors were found to have the biggest impact on a population’s happiness. Crisis (natural disasters and economic crisis) the quality of governance, and social support were found to be the key drivers for changes in national happiness levels, with the happiness of nations undergoing a crisis in which people have a strong sense of social support falling less than nations where people do not have a strong sense of social support.
Chapter 3, How Does Subjective Well-being Vary Around the Globe by Gender and Age? is written by Nicole Fortin, John F. Helliwell and Shun Wang. This chapter uses data for 12 experiences: happiness (the emotion), smiling or laughing, enjoyment, feeling safe at night, feeling well rested, and feeling interested, as well as anger, worry, sadness, depression, stress and pain to examine differences by gender and age. Findings reported include that there is not a lot of difference in life evaluations between men and women across nations or within ages in a nation (women have slightly higher life evaluations than men: 0.09 on a ten-point scale). It reports that overall happiness falls into a U shape with age on the x axis and happiness on the y, with the low point being middle age (45-50) for most nations (in some happiness does not go up much in later life, so the shape is more of a downhill slide), and that the U shape holds for feeling well rested in all regions. If finds that that men generally feel safer at night than women but, when comparing countries, people in Latin America have the lowest sense of safety at night, while people in East Asia and Western Europe have the highest sense of safety at night. It also finds that as women age their sense of happiness declines and stress increases but worry decreases, as all people age their laughter, enjoyment and finding something of interest also declines, that anger is felt everywhere almost equally by men and women, stress peaks in the Middle Ages, and women experience depression more than men. It finds that where older people are happier, there is a sense of social support, freedom to make life choices and generosity (and income does not factor in as heavily as these three factors).
Chapter 4, How to Make Policy When Happiness is the Goal is written by Richard Layard and Gus O’Donnell. This chapter advocates for a “new form of cost-benefit analysis” for government expenditures in which a “critical level of extra happiness” yielded by a project is established. It contemplates the prioritization of increasing happiness of the happy vs. reducing misery of the miserable, as well as the issues of discount rate (weight) for the happiness of future generations. It includes a technical annex with equations for calculating the maximization for happiness in public expenditure, tax policy, regulations, the distribution of happiness and a discount rate.
Chapter 5, Neuroscience of Happiness is written by Richard J. Dawson and Brianna S. Schuyler. This chapter reports on research in brain science and happiness, identifying four aspects that account for happiness: (1) sustained positive emotion, (2) recovery of negative emotion (resilience), (3) empathy, altruism and pro-social behavior, and (4) mindfulness (mind-wandering/affective sickness). It concludes that the brain’s elasticity indicates that one can change one’s sense of happiness and life satisfaction (separate but overlapping positive consequences) levels by experiencing and practicing mindfulness, kindness, and generosity; and calls for more research on these topics.
Chapter 6, Healthy Young Minds: Transforming the Mental Health of Children is written by Richard Layard and Ann Hagell.[28] This chapter identifies emotional development as of primary importance, (compared to academic and behavioral factors) in a child’s development and determination of whether a child will be a happy and well-functioning adult. It then focuses on the issue of mental illness in children, citing the statistic that while worldwide 10% of the world's children (approximately 200 million) suffer from diagnosable mental health problems, even in the richest nations, only one quarter of these children of them are in treatment. It identifies the action steps to treating children with mental health problems: local community-lead child well-being programs, training health care professions to identify mental health problems in children, parity of esteem for mental and physical problems and treatment, access to evidence-based mental health treatment for families and children, promotion of well-being in schools with well-being codes that inform the organizational behavior of schools, training teachers to identify mental health in children, teachings of life skills, measuring of children’s well-being by schools, development of free apps available internationally to treat mental illness in teens, and inclusion of mental health with the goal of physical health in the Sustainable Development goals. The chapter lists the benefits of treating children’s mental health: improved educational performance, reduction in youth crimes, improved earnings and employment in adulthood, and better parenting of the next generation.
Chapter 7, Human Values, Civil Economy and Subjective Well-being is written by Leonardo Bechhetti,[29] Luigino Bruni and Stefano Zamagni. This chapter begins with a critique of the field of economics ("Economics today looks like physics before the discovery of electrons"), identifying reductionism in which humans are conceived of as 100% self-interested individuals (economic reductionism), profit maximization is prioritized over all other interests (corporate reductionism), and societal values are narrowly identified with GDP and ignore environmental, cultural, spiritual and relational aspects (value reductionism). The chapter them focuses on a theoretical approach termed "Civil Economy paradigm", and research about it demonstrating that going beyond reductionism leads to greater socialization for people and communities, and a rise in priority of the values of reciprocity, friendship, trustworthiness, and benevolence. It makes the argument that positive social relationships (trust, benevolence, shared social identities) yield happiness and positive economic outcomes. It ends with recommendations for move from the dominant model of elite-competitive democracy to a participatory/deliberative model of democracy with bottom-up political and economic participation and incentives for non-selfish actions (altruistic people) and corporations with wider goals than pure profit (ethical and environmentally responsible corporations).
Chapter 8, Investing in Social Capital is written by Jeffrey Sachs. This chapter focuses on “pro-sociality” (“individuals making decisions for the common good that may conflict with short-run egoistic incentives”). It identifies pro-social behaviors: honesty, benevolence, cooperation and trustworthiness. It recommends investment in social capital through education, moral instruction, professional codes of conduct, public censure and condemnation of violators of public trust, and public policies to narrow income inequalities for countries where there is generalized distrust of government and business, pervasive corruption and lawless behavior (such as tax evasion).

text: 2013 World Happiness Report[edit]

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The 2013 World Happiness Report has eight chapters: (1) Introduction, (2) World Happiness: Trends, Explanations and Distribution, (3) Mental Illness and Unhappiness, (4) The Objective Benefits of Subjective Well-being, (5) Restoring Virtue Ethics in the Quest for Happiness, (6) Using Well-being as a Guide to Policy, (7) The OECD Approach to Measuring Subjective Well-being, and (8) From Capabilities to Contentment: Testing the Links between Human Development and Life Satisfaction.
Chapter 1, Introduction is written by John F. Helliwell, Richard Layard and Jeffrey Sachs. It synopsizes the chapters and gives a discussion of the term happiness.
Chapter 2, World Happiness: Trends, Explanations and Distributions is written by John F. Helliwell and Shun Wang. It provides ratings among countries and regions for satisfaction with life using the Cantril Ladder, positive and negative affect (emotions), and log of GDP per capita, years of healthy life expectancy, having someone to count on in times of trouble, perceptions of corruption, prevalence of generosity, and freedom to make life choices.
Chapter 3, Mental Illness and Unhappiness is written by Richard Layard, Dan Chisholm, Vikram Patel, and Shekhar Saxel. It identifies the far ranging prevalence of mental illness around the world (10% of the world's population at one time) and provides the evidence showing that "mental illness is a highly influential - and...the single biggest - determinant of misery." It concludes with examples of interventions implemented by countries around the world.
Chapter 4, The Objective Benefits of Subjective Well-being is written by Jan-Emmanuel de Neve, Ed Diener, Louis Tay and Cody Xuereb. It provides an explanation of the benefits of subjective well-being (happiness) on health & longevity, income, productivity & organizational behavior, and individual & social behavior. It touches on the role of happiness in human evolution through rewarding behaviors that increase evolutionary success and beneficial to survival.
Chapter 5, Restoring Virtue Ethics in the Quest for Happiness is written by Jeffrey Sachs. It argues that "a renewed focus on the role of ethics, and in particular of virtuous behavior, in happiness could lead us to new and effective strategies for raising individual, national and global well-being," looking to the eightfold noble path (the teachings of the dharma handed down in the Buddhist tradition that encompass wise view/understanding, wise intention, wise speech, wise action, wise livelihood, and effort, concentration and mindfulness), Aristotelian philosophy (people are social animals, "with individual happiness secured only within a political community...[which] should organize its institutions to promote virtuous behavior), and Christian doctrine of St. Thomas Aquinas ("placing happiness in the context of servicing God's will"). It gives an explanation of the evolution of the field of economics up t the "failures of hyper-commercialism" and suggests an antidote based on four global ethical values: (1) non-violence and respect for life, (2) justice and solidarity, (3) honesty and tolerance, and (4) mutual esteem and partnership.
Chapter 6, Using Well-being as Guide to Public Policy is written by Gus O'Donnell. This chapter gives a status report on the issues governments grapple with in adopting well-being and happiness measures and goals for policy, from understanding the data or establishing whether a specific policy improves well-being, to figuring out how to "incorporate well-being into standard policy making." It provides examples of efforts to measure happiness and well-being from Bhutan, New Zealand, South Africa, the UK, and cities and communities in the USA, Canada, Australia and Tasmania. It identifies the key policy areas of health, transport and education for policy makers to focus on and includes discussions about interpersonal comparability (concentrating on "getting people out of misery" instead of making happy people happier), discount rate (do we invest more in happiness for people today or in the future?) and putting a monetary value on happiness for policy trade off decisions (e.g. If "a 10% reduction in noise increase SWB by one unit, then we can infer that a 10% reduction is "worth" $1,000" when $1,000 would increase a person's SWB by one unit).
Chapter 7, The OECD Approach to Measuring Subjective Well-being is written by Martine Durand and Conal Smith. This chapter was written the same year the OECD issued its Guidelines on Measuring Subjective Well-being,[30] and is a synopsis of such. It includes a definition for subjective well-being: life evaluation (a person's reflection on their life and life circumstances), affect (positive and negative emotions) and eudaimonia; core measures, a discussion on data collection processes, survey and sample design, other aspects of using subjective well-being metrics, and ideas on how policy-makers can use subjective well-being data. It surveys the status of wealthy countries subjective well-being data collection process, and identifies future directions of experimentation and better income measures, citing the Easterlin Paradox as the basis for this call.
Chapter 8, From Capabilities to Contentment: Testing the Links between Human Development and Life Satisfaction is written by Jon Hall.[31] This chapter explains the components of human development using objective metrics: (1) education, health and command over income and nutrition resources, (2) participation and freedom, (3) human security, (4) equity, and (5) sustainability; key findings of the Human Development Index (HDI) ("weak relationship between economic growth and changes in health and education" as well as life expectancy), and examines the relationship between the HDI and happiness, finding that (1) components of the HDI "correlate strongly with better life evaluations," and (2) there is a strong relationship between life evaluation and the "non-income HDI." It contemplates measurement of conditions of life beyond the HDI that are important to well-being: (1) better working conditions, (2) security against crime and physical violence, (3) participation in economic and political activities, (4) freedom and (5) inequality. The concludes with the statements that the HDI and SWB have similar approaches and importantly connected, with the two disciplines offering alternative and complementary views of development.

text: 2012 World Happiness Report[edit]

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The 2012 World Happiness Report was issued at the UN High Level Meeting Well-being and Happiness: Defining a New Economic Paradigm[32] by editors John F. Helliwell, Richard Layard and Jeffrey Sachs. Part one has an introduction (chapter 1) and three chapters: (2) the State of World Happiness, (3) Causes of Happiness and Misery, Some Policy Implications. Part two has three chapters, each a case study, of Bhutan, the United Kingdom Office of National Statistics, and the OECD.
Chapter 1, The Introduction is by Jeffrey Sachs and references Buddha and Aristotle, identifies today's era as the anthropocene, and identifies the reasons GDP is not a sufficient measure to guide governments and society.
Chapter 2, The State of World Happiness, is written by John F. Helliwell and Shun Wang,[33] and contains a discussion of subjective well-being measures that ranges from the validity of subjective well-being measures to the seriousness of happiness, happiness set points and cultural comparisons, and it includes data from the Gallup World Poll, European Social Survey, and the World Values Survey.[34]
Chapter 3, The Causes of Happiness and Misery is written by Richard Layard, Andrew Clark,[35] and Claudia Senik,[36] and contemplates research on the impact on happiness of the external factors of income, work, community and governance, values and religion, as well as the internal factors of mental health, physical health, family experience, education, and gender and age.
Chapter 4, Some Policy Implications, written by John F. Helliwell, Richard Layard and Jeffrey Sachs, calls for a greater understanding on how governments can measure happiness, the determinants of happiness, and use of happiness data and findings about determinants for policy purposes. It also highlights the role of GDP ("GDP is important but not all that is important") as a guide to policy makers, the importance that policy makers should place on providing opportunities for employment; the role of happiness in policy making ("Making happiness an objective of governments would not therefore lead to the “servile society,” and indeed quite the contrary...Happiness comes from an opportunity to mold one’s own future, and thus depends on a robust level of freedom."); the role of values and religion ("In well-functioning societies there is widespread support for the universal value that we should treat others as we would like them to treat us. We need to cultivate social norms so that the rich and powerful are never given a feeling of impunity vis-à-vis the rest of society."); calls for wider access to psychological therapies in a section on mental health citing the fact that one third of all families are affected by mental illness; identifies improvements in physical health as "probably the single most important factor that has improved human happiness" and calls out the rich-poor gap in health care between rich and poor countries; calls on workplace and governmental policies that encourage work-life balance and reduce stress, including family support and child care; and states that "Universal access to education is widely judged to be a basic human right..." The chapter concludes with a philosophical discussion.
Chapter 5, Case Study: Bhutan Gross National Happiness and the GNH Index is written by Karma Ura,[37] Sabine Alkire,[38] and Tsoki Zangmo. It gives a short history of the development of the Gross National Happiness (GNH) concept in Bhutan, and an explanation of the GNH index, data collection and data analysis process, including the rating methodology to determine if an individual experiences happiness sufficiency levels, as well as the policy and lifestyle implications
Chapter 6, Case Study: ONS Measuring Subjective Well-being: The UK Office of National Statistics Experience is written by Stephen Hicks. It covers the basis for the creation of the Measuring National Well-being Programme[39] in the UK's Office of National Statistics[40] (ONS), and the development of their methodology for measuring well-being.
Chapter 5, Case Study OECD Guidelines on Measuring Subjective Well-being is an explanation about the process and rationale the OECD was undertaking to develop its Guidelines on Measuring Subjective Well-being,[41] which it issued in 2013.

text: International rankings[edit]

text: Data is collected from people in over 150 countries. Each variable measured reveals a populated-weighted average score on a scale running from 0 to 10 that is tracked over time and compared against other countries. These variables currently include: real GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of corruption. Each country is also compared against a hypothetical nation called Dystopia. Dystopia represents the lowest national averages for each key variable and is, along with residual error, used as a regression benchmark.

text: 2018 report[edit]

text: As per the 2018 Happiness Index, Finland is the happiest country in the world. Norway, Denmark, Iceland and Switzerland hold the next top positions. The report was published on 14 March 2018 by UN. The full report can be read at 2018 Report. The World Happiness Report is a landmark survey of the state of global happiness. The World Happiness Report 2018, which ranks 156 countries by their happiness levels, and 117 countries by the happiness of their immigrants, was released on March 14th at a launch event at the Pontifical Academy of Sciences in the Vatican.

text:
Overall Rank

Country

Score

GDP per capita

Social support

Healthy life expectancy

Freedom to make life choices

Generosity

Perceptions of corruption

1
 Finland
7.632
1.305
1.592
0.874
0.681
0.192
0.393

2
 Norway
7.594
1.456
1.582
0.861
0.686
0.286
0.340

3
 Denmark
7.555
1.351
1.590
0.868
0.683
0.284
0.408

4
 Iceland
7.495
1.343
1.644
0.914
0.677
0.353
0.138

5
  Switzerland
7.487
1.420
1.549
0.927
0.660
0.256
0.357

6
 Netherlands
7.441
1.361
1.488
0.878
0.638
0.333
0.295

7
 Canada
7.328
1.330
1.532
0.896
0.653
0.321
0.291

8
 New Zealand
7.324
1.268
1.601
0.876
0.669
0.365
0.389

9
 Sweden
7.314
1.355
1.501
0.913
0.659
0.285
0.383

10
 Australia
7.272
1.340
1.573
0.910
0.647
0.361
0.302

11
 Israel
7.190
1.244
1.433
0.888
0.464
0.262
0.082

12
 Austria
7.139
1.341
1.504
0.891
0.617
0.242
0.224

13
 Costa Rica
7.072
1.010
1.459
0.817
0.632
0.143
0.101

14
 Ireland
6.977
1.448
1.583
0.876
0.614
0.307
0.306

15
 Germany
6.965
1.340
1.474
0.861
0.586
0.273
0.280

16
 Belgium
6.927
1.324
1.483
0.894
0.583
0.188
0.240

17
 Luxembourg
6.910
1.576
1.520
0.896
0.632
0.196
0.321

18
 United States
6.886
1.398
1.471
0.819
0.547
0.291
0.133

19
 United Kingdom
6.814
1.301
1.559
0.883
0.533
0.354
0.272

20
 United Arab Emirates
6.774
2.096
0.776
0.670
0.284
0.186
N/A

21
 Czech Republic
6.711
1.233
1.489
0.854
0.543
0.064
0.034

22
 Malta
6.627
1.270
1.525
0.884
0.645
0.376
0.142

23
 France
6.489
1.293
1.466
0.908
0.520
0.098
0.176

24
 Mexico
6.488
1.038
1.252
0.761
0.479
0.069
0.095

25
 Chile
6.476
1.131
1.331
0.808
0.431
0.197
0.061

26
 Taiwan
6.441
1.365
1.436
0.857
0.418
0.151
0.078

27
 Panama
6.430
1.112
1.438
0.759
0.597
0.125
0.063

28
 Brazil
6.419
0.986
1.474
0.675
0.493
0.110
0.088

29
 Argentina
6.388
1.073
1.468
0.744
0.570
0.062
0.054

30
 Guatemala
6.382
0.781
1.268
0.608
0.604
0.179
0.071

31
 Uruguay
6.379
1.093
1.459
0.771
0.625
0.130
0.155

32
 Qatar
6.374
1.649
1.303
0.748
0.654
0.256
0.171

33
 Saudi Arabia
6.371
1.379
1.331
0.633
0.509
0.098
0.127

34
 Singapore
6.343
1.529
1.451
1.008
0.631
0.261
0.457

35
 Malaysia
6.322
1.161
1.258
0.669
0.356
0.311
0.059

36
 Spain
6.310
1.251
1.538
0.965
0.449
0.142
0.074

37
 Colombia
6.260
0.960
1.439
0.635
0.531
0.099
0.039

38
 Trinidad & Tobago
6.192
1.223
1.492
0.564
0.575
0.171
0.019

39
 Slovakia
6.173
1.210
1.537
0.776
0.354
0.118
0.014

40
 El Salvador
6.167
0.806
1.231
0.639
0.461
0.065
0.082

41
 Nicaragua
6.141
0.668
1.319
0.700
0.527
0.208
0.128

42
 Poland
6.123
1.176
1.448
0.781
0.546
0.108
0.064

43
 Bahrain
6.105
1.338
1.366
0.698
0.594
0.243
0.123

44
 Uzbekistan
6.096
0.719
1.584
0.605
0.724
0.328
0.259

45
 Kuwait
6.083
1.474
1.301
0.675
0.554
0.167
0.106

46
 Thailand
6.072
1.016
1.417
0.707
0.637
0.364
0.029

47
 Italy
6.000
1.264
1.501
0.946
0.281
0.137
0.028

48
 Ecuador
5.973
0.889
1.330
0.736
0.556
0.114
0.120

49
 Belize
5.956
0.807
1.101
0.474
0.593
0.183
0.089

50
 Lithuania
5.952
1.197
1.527
0.716
0.350
0.026
0.006

51
 Slovenia
5.948
1.219
1.506
0.856
0.633
0.160
0.051

52
 Romania
5.945
1.116
1.219
0.726
0.528
0.088
0.001

53
 Latvia
5.933
1.148
1.454
0.671
0.363
0.092
0.066

54
 Japan
5.915
1.294
1.462
0.988
0.553
0.079
0.150

55
 Mauritius
5.891
1.090
1.387
0.684
0.584
0.245
0.050

56
 Jamaica
5.890
0.819
1.493
0.693
0.575
0.096
0.031

57
 South Korea
5.875
1.266
1.204
0.955
0.244
0.175
0.051

58
 Northern Cyprus
5.835
1.229
1.211
0.909
0.495
0.179
0.154

59
 Russia
5.810
1.151
1.479
0.599
0.399
0.065
0.025

60
 Kazakhstan
5.790
1.143
1.516
0.631
0.454
0.148
0.121

61
 Cyprus
5.762
1.229
1.191
0.909
0.423
0.202
0.035

62
 Bolivia
5.752
0.751
1.223
0.508
0.606
0.141
0.054

63
 Estonia
5.739
1.200
1.532
0.737
0.553
0.086
0.174

64
 Paraguay
5.681
0.835
1.522
0.615
0.541
0.162
0.074

65
 Peru
5.663
0.934
1.249
0.674
0.530
0.092
0.034

66
 Kosovo
5.662
0.855
1.230
0.578
0.448
0.274
0.023

67
 Moldova
5.640
0.657
1.301
0.620
0.232
0.171
0.000

68
 Turkmenistan
5.636
1.016
1.533
0.517
0.417
0.199
0.037

69
 Hungary
5.620
1.171
1.401
0.732
0.259
0.061
0.022

70
 Libya
5.566
0.985
1.350
0.553
0.496
0.116
0.148

71
 Philippines
5.524
0.775
1.312
0.513
0.643
0.120
0.105

72
 Honduras
5.504
0.620
1.205
0.622
0.459
0.197
0.074

73
 Belarus
5.483
1.039
1.498
0.700
0.307
0.101
0.154

74
 Turkey
5.483
1.148
1.380
0.686
0.324
0.106
0.109

75
 Pakistan
5.472
0.652
0.810
0.424
0.334
0.216
0.113

76
 Hong Kong
5.430
1.405
1.290
1.030
0.524
0.246
0.291

77
 Portugal
5.410
1.188
1.429
0.884
0.562
0.055
0.017

78
 Serbia
5.398
0.975
1.369
0.685
0.288
0.134
0.043

79
 Greece
5.358
1.154
1.202
0.879
0.131
0.000
0.044

80
 Tajikistan
5.358
0.474
1.179
0.598
0.503
0.214
0.136

81
 Montenegro
5.347
1.017
1.279
0.729
0.259
0.111
0.081

82
 Croatia
5.321
1.115
1.161
0.737
0.380
0.120
0.039

83
 Dominican Republic
5.302
0.982
1.441
0.614
0.578
0.120
0.106

84
 Algeria
5.295
0.979
1.154
0.687
0.077
0.055
0.135

85
 Morocco
5.254
0.779
0.797
0.669
0.460
0.026
0.074

86
 China
5.246
0.989
1.142
0.799
0.597
0.029
0.103

87
 Azerbaijan
5.201
1.024
1.161
0.603
0.430
0.031
0.176

88
 Lebanon
5.199
0.965
1.166
0.785
0.292
0.187
0.034

89
 Macedonia
5.185
0.959
1.239
0.691
0.394
0.173
0.052

90
 Jordan
5.161
0.822
1.265
0.645
0.468
0.130
0.134

91
 Nigeria
5.155
0.689
1.172
0.048
0.462
0.201
0.032

92
 Kyrgyzstan
5.131
0.530
1.416
0.594
0.540
0.281
0.035

93
 Bosnia and Herzegovina
5.129
0.915
1.078
0.758
0.280
0.216
0.000

94
 Mongolia
5.125
0.914
1.517
0.575
0.395
0.253
0.032

95
 Vietnam
5.103
0.715
1.365
0.702
0.618
0.177
0.079

96
 Indonesia
5.093
0.899
1.215
0.522
0.538
0.484
0.018

97
 Bhutan
5.082
0.796
1.335
0.527
0.541
0.364
0.171

98
 Somalia
4.982
0.000
0.712
0.115
0.674
0.238
0.282

99
 Cameroon
4.975
0.535
0.891
0.182
0.454
0.183
0.043

100
 Bulgaria
4.933
1.054
1.515
0.712
0.359
0.064
0.009

101
   Nepal
4.880
0.425
1.228
0.539
0.526
0.302
0.078

102
 Venezuela
4.806
0.996
1.469
0.657
0.133
0.056
0.052

103
 Gabon
4.758
1.036
1.164
0.404
0.356
0.032
0.052

104
 Palestinian Territories
4.743
0.642
1.217
0.602
0.266
0.086
0.076

105
 South Africa
4.724
0.940
1.410
0.330
0.516
0.103
0.056

106
 Iran
4.707
1.059
0.771
0.691
0.459
0.282
0.129

107
 Ivory Coast
4.671
0.541
0.872
0.080
0.467
0.146
0.103

108
 Ghana
4.657
0.592
0.896
0.337
0.499
0.212
0.029

109
 Senegal
4.631
0.429
1.117
0.433
0.406
0.138
0.082

110
 Laos
4.623
0.720
1.034
0.441
0.626
0.230
0.174

111
 Tunisia
4.592
0.900
0.906
0.690
0.271
0.040
0.063

112
 Albania
4.586
0.916
0.817
0.790
0.419
0.149
0.032

113
 Sierra Leone
4.571
0.256
0.813
0.000
0.355
0.238
0.053

114
 Congo (Brazzaville)
4.559
0.682
0.811
0.343
0.514
0.091
0.077

115
 Bangladesh
4.500
0.532
0.850
0.579
0.580
0.153
0.144

116
 Sri Lanka
4.471
0.918
1.314
0.672
0.585
0.307
0.050

117
 Iraq
4.456
1.010
0.971
0.536
0.304
0.148
0.095

118
 Mali
4.447
0.370
1.233
0.152
0.367
0.139
0.056

119
 Namibia
4.441
0.874
1.281
0.365
0.519
0.051
0.064

120
 Cambodia
4.433
0.549
1.088
0.457
0.696
0.256
0.065

121
 Burkina Faso
4.424
0.314
1.097
0.254
0.312
0.175
0.128

122
 Egypt
4.419
0.885
1.025
0.553
0.312
0.092
0.107

123
 Mozambique
4.417
0.198
0.902
0.173
0.531
0.206
0.158

124
 Kenya
4.410
0.493
1.048
0.454
0.504
0.352
0.055

125
 Zambia
4.377
0.562
1.047
0.295
0.503
0.221
0.082

126
 Mauritania
4.356
0.557
1.245
0.292
0.129
0.134
0.093

127
 Ethiopia
4.350
0.308
0.950
0.391
0.452
0.220
0.146

128
 Georgia
4.340
0.853
0.592
0.643
0.375
0.038
0.215

129
 Armenia
4.321
0.816
0.990
0.666
0.260
0.077
0.028

130
 Myanmar
4.308
0.682
1.174
0.429
0.580
0.598
0.178

131
 Chad
4.301
0.358
0.907
0.053
0.189
0.181
0.060

132
 Congo (Kinshasa)
4.245
0.069
1.136
0.204
0.312
0.197
0.052

133
 India
4.190
0.721
0.747
0.485
0.539
0.172
0.093

134
 Niger
4.166
0.131
0.867
0.221
0.390
0.175
0.099

135
 Uganda
4.161
0.322
1.090
0.237
0.450
0.259
0.061

136
 Benin
4.141
0.378
0.372
0.240
0.440
0.163
0.067

137
 Sudan
4.139
0.605
1.240
0.312
0.016
0.134
0.082

138
 Ukraine
4.103
0.793
1.413
0.609
0.163
0.187
0.011

139
 Togo
3.999
0.259
0.474
0.253
0.434
0.158
0.101

140
 Guinea
3.964
0.344
0.792
0.211
0.394
0.185
0.094

141
 Lesotho
3.808
0.472
1.215
0.079
0.423
0.116
0.112

142
 Angola
3.795
0.730
1.125
0.269
0.000
0.079
0.061

143
 Madagascar
3.774
0.262
0.908
0.402
0.221
0.155
0.049

144
 Zimbabwe
3.692
0.357
1.094
0.248
0.406
0.132
0.099

145
 Afghanistan
3.632
0.332
0.537
0.255
0.085
0.191
0.036

146
 Botswana
3.590
1.017
1.174
0.417
0.557
0.042
0.092

147
 Malawi
3.587
0.186
0.541
0.306
0.531
0.210
0.080

148
 Haiti
3.582
0.315
0.714
0.289
0.025
0.392
0.104

149
 Liberia
3.495
0.076
0.858
0.267
0.419
0.206
0.030

150
 Syria
3.462
0.689
0.382
0.539
0.088
0.376
0.144

151
 Rwanda
3.408
0.332
0.896
0.400
0.636
0.200
0.444

152
 Yemen
3.355
0.442
1.073
0.343
0.244
0.083
0.064

153
 Tanzania
3.303
0.455
0.991
0.381
0.481
0.270
0.097

154
 South Sudan
3.254
0.337
0.608
0.177
0.112
0.224
0.106

155
 Central African Republic
3.083
0.024
0.000
0.010
0.305
0.218
0.038

156
 Burundi
2.905
0.091
0.627
0.145
0.065
0.149
0.076

text: 2017 report[edit]

text: The 2017 report features the happiness score averaged over the years 2014-2016. For that timespan, Norway was the overall happiest country in the world, even though oil prices had dropped. Close behind were Denmark, Iceland and Switzerland in a tight pack. Four of the top five countries follow the Nordic model. All the top ten countries had high scores in the six categories. The ranked follow-on countries in the top ten are: Finland, the Netherlands, Canada, New Zealand, Australia, and Sweden.

text: Table of data for 2017:[42]

text:
Overall Rank

Change in rank

Country

Score

Change in score

GDP per capita

Social support

Healthy life expectancy

Freedom to make life choices

Generosity

Trust

Residual

1
 3
 Norway
7.537
 0.039
1.616
1.534
0.797
0.635
0.362
0.316
2.277

2
 1
 Denmark
7.522
 0.004
1.482
1.551
0.793
0.626
0.355
0.401
2.314

3

 Iceland
7.504
 0.003
1.481
1.611
0.834
0.627
0.476
0.154
2.323

4
 2
  Switzerland
7.494
 0.015
1.565
1.517
0.858
0.620
0.291
0.367
2.277

5

 Finland
7.469
 0.056
1.444
1.540
0.809
0.618
0.245
0.383
2.430

6
 1
 Netherlands
7.377
 0.038
1.504
1.429
0.811
0.585
0.470
0.283
2.295

7
 1
 Canada
7.316
 0.088
1.479
1.481
0.835
0.611
0.436
0.287
2.187

8

 New Zealand
7.314
 0.020
1.406
1.548
0.817
0.614
0.500
0.383
2.046

9

 Australia
7.284
 0.029
1.484
1.510
0.844
0.602
0.478
0.301
2.065

10

 Sweden
7.284
 0.007
1.494
1.478
0.831
0.613
0.385
0.384
2.098

11

 Israel
7.213
 0.054
1.375
1.376
0.838
0.406
0.330
0.085
2.802

12
 2
 Costa Rica
7.079
 0.008
1.110
1.416
0.760
0.580
0.215
0.100
2.899

13
 1
 Austria
7.006
 0.113
1.487
1.460
0.815
0.568
0.316
0.221
2.139

14
 1
 United States
6.993
 0.111
1.546
1.420
0.774
0.506
0.393
0.136
2.218

15
 4
 Ireland
6.977
 0.070
1.536
1.558
0.810
0.573
0.428
0.298
1.774

16

 Germany
6.951
 0.043
1.488
1.473
0.799
0.563
0.336
0.277
2.016

17
 1
 Belgium
6.891
 0.038
1.464
1.462
0.818
0.540
0.232
0.251
2.124

18
 2
 Luxembourg
6.863
 0.008
1.742
1.458
0.845
0.597
0.283
0.319
1.620

19
 4
 United Kingdom
6.714
 0.011
1.442
1.496
0.805
0.508
0.493
0.265
1.704

20
 4
 Chile
6.652
 0.053
1.253
1.284
0.819
0.377
0.327
0.082
2.510

21
 7
 United Arab Emirates
6.648
 0.075
1.626
1.266
0.727
0.608
0.361
0.324
1.735

22
 5
 Brazil
6.635
 0.317
1.107
1.431
0.617
0.437
0.162
0.111
2.769

23
 4
 Czech Republic
6.609
 0.013
1.353
1.434
0.754
0.491
0.088
0.037
2.452

24
 2
 Argentina
6.599
 0.051
1.185
1.440
0.695
0.495
0.109
0.060
2.614

25
 4
 Mexico
6.578
 0.200
1.153
1.211
0.710
0.413
0.121
0.133
2.837

26
 4
 Singapore
6.572
 0.167
1.692
1.354
0.949
0.550
0.346
0.464
1.216

27
 3
 Malta
6.527
 0.039
1.343
1.488
0.822
0.589
0.575
0.153
1.557

28
 1
 Uruguay
6.454
 0.091
1.218
1.412
0.719
0.579
0.175
0.178
2.172

29
 10
 Guatemala
6.454
 0.130
0.872
1.256
0.540
0.531
0.283
0.077
2.894

30
 5
 Panama
6.452
 0.249
1.234
1.373
0.706
0.550
0.211
0.071
2.307

31
 1
 France
6.442
 0.036
1.431
1.388
0.844
0.470
0.130
0.173
2.006

32
 1
 Thailand
6.424
 0.050
1.128
1.426
0.647
0.580
0.572
0.032
2.040

33
 2
 Taiwan
6.422
 0.043
1.434
1.385
0.794
0.361
0.258
0.064
2.127

34
 3
 Spain
6.403
 0.042
1.384
1.532
0.889
0.409
0.190
0.071
1.928

35
 1
 Qatar
6.375

1.871
1.274
0.710
0.604
0.330
0.439
1.145

36
 5
 Colombia
6.357
 0.124
1.071
1.402
0.595
0.477
0.149
0.047
2.616

37
 3
 Saudi Arabia
6.344
 0.035
1.531
1.287
0.590
0.450
0.148
0.273
2.065

38
 5
 Trinidad and Tobago
6.168

1.361
1.380
0.520
0.519
0.325
0.009
2.053

39
 2
 Kuwait
6.105
 0.134
1.633
1.260
0.632
0.496
0.228
0.215
1.640

40
 5
 Slovakia
6.098
 0.020
1.325
1.505
0.713
0.296
0.137
0.024
2.098

41
 1
 Bahrain
6.087
 0.131
1.488
1.323
0.653
0.537
0.173
0.257
1.656

42
 5
 Malaysia
6.084
 0.079
1.291
1.285
0.619
0.402
0.417
0.066
2.004

—
—
 Europe[Note 1]
6.080
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

43
 5
 Nicaragua
6.071
 0.079
0.737
1.287
0.653
0.448
0.302
0.131
2.514

44
 7
 Ecuador
6.008
 0.032
1.001
1.286
0.686
0.455
0.150
0.140
2.290

45
 1
 El Salvador
6.003
 0.065
0.910
1.182
0.596
0.432
0.078
0.090
2.715

46
 11
 Poland
5.973
 0.138
1.292
1.446
0.699
0.520
0.158
0.059
1.798

47
 2
 Uzbekistan
5.971
 0.016
0.786
1.549
0.498
0.658
0.416
0.247
1.817

48
 2
 Italy
5.964
 0.013
1.395
1.445
0.853
0.256
0.173
0.028
1.813

49
 7
 Russia
5.963
 0.107
1.282
1.469
0.547
0.374
0.052
0.033
2.206

50
 2
 Belize
5.956

0.908
1.081
0.450
0.548
0.240
0.097
2.632

51
 2
 Japan
5.920
 0.001
1.417
1.436
0.913
0.506
0.121
0.164
1.363

52
 8
 Lithuania
5.902
 0.089
1.315
1.474
0.629
0.234
0.010
0.012
2.228

53
 15
 Algeria
5.872
 0.483
1.092
1.146
0.618
0.233
0.069
0.146
2.568

54
 14
 Latvia
5.850
 0.290
1.261
1.405
0.639
0.326
0.153
0.074
1.994

55

 Moldova
5.838
 0.059
0.729
1.252
0.589
0.241
0.209
0.010
2.808

56
 2
 South Korea
5.838
 0.003
1.402
1.128
0.900
0.258
0.207
0.063
1.880

57
 14
 Romania
5.825
 0.297
1.218
1.150
0.685
0.457
0.134
0.004
2.177

58
 1
 Bolivia
5.823
 0.001
0.834
1.228
0.474
0.559
0.226
0.060
2.443

59
 6
 Turkmenistan
5.822
 0.164
1.131
1.493
0.438
0.418
0.250
0.259
1.833

60
 6
 Kazakhstan
5.819
 0.100
1.285
1.384
0.606
0.437
0.202
0.119
1.785

61
 1
 North Cyprus
5.810
 0.039
1.347
1.186
0.835
0.471
0.267
0.155
1.549

62
 1
 Slovenia
5.758
 0.010
1.341
1.453
0.791
0.573
0.243
0.045
1.313

63
 1
 Peru
5.715
 0.028
1.035
1.219
0.630
0.450
0.127
0.047
2.207

64
 2
 Mauritius
5.629
 0.019
1.189
1.210
0.638
0.491
0.361
0.042
1.698

65
 4
 Cyprus
5.621
 0.075
1.356
1.131
0.845
0.355
0.271
0.041
1.621

66
 6
 Estonia
5.611
 0.094
1.321
1.477
0.695
0.479
0.099
0.183
1.358

67
 6
 Belarus
5.569
 0.233
1.157
1.445
0.638
0.295
0.155
0.156
1.723

68
 1
 Libya
5.525
 0.090
1.102
1.358
0.520
0.466
0.152
0.093
1.835

69
 9
 Turkey
5.500
 0.111
1.198
1.338
0.638
0.301
0.047
0.100
1.879

70

 Paraguay
5.493
 0.045
0.933
1.507
0.579
0.474
0.224
0.091
1.685

71
 4
 Hong Kong
5.472
 0.014
1.552
1.263
0.943
0.491
0.374
0.294
0.555

72
 10
 Philippines
5.430
 0.151
0.858
1.254
0.468
0.585
0.194
0.099
1.973

73
 13
 Serbia
5.395
 0.218
1.069
1.258
0.651
0.209
0.220
0.041
1.947

74
 6
 Jordan
5.336
 0.033
0.991
1.239
0.605
0.418
0.172
0.120
1.791

75
 16
 Hungary
5.324
 0.179
1.286
1.343
0.688
0.176
0.078
0.037
1.716

76
 3
 Jamaica
5.311
 0.199
0.926
1.368
0.641
0.474
0.234
0.055
1.612

—
—
 World
5.305[Note 2]
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

77
 3
 Croatia
5.293
 0.195
1.223
0.968
0.701
0.256
0.248
0.043
1.854

78
 1
 Kosovo
5.279
 0.122
0.951
1.138
0.541
0.260
0.320
0.057
2.011

79
 4
 China
5.273
 0.028
1.081
1.161
0.741
0.473
0.029
0.023
1.765

80
 12
 Pakistan
5.269
 0.137
0.727
0.673
0.402
0.235
0.315
0.124
2.792

81
 2
 Indonesia
5.262
 0.052
0.996
1.274
0.492
0.443
0.612
0.015
1.429

82
 38
 Venezuela
5.250
 0.834
1.128
1.431
0.617
0.154
0.065
0.064
1.789

83
 5
 Montenegro
5.237
 0.076
1.121
1.238
0.667
0.195
0.198
0.088
1.729

84
 6
 Morocco
5.235
 0.084
0.878
0.775
0.598
0.408
0.032
0.088
2.456

85
 4
 Azerbaijan
7.342
 0.057
1.154
1.152
0.541
0.398
0.045
0.181
1.762

86
 3
 Dominican Republic
5.230
 0.075
1.079
1.402
0.575
0.553
0.187
0.114
1.319

87
 12
 Greece
5.227
 0.194
1.289
1.239
0.810
0.096
0.000
0.043
1.749

88
 5
 Lebanon
5.225
 0.096
1.075
1.130
0.735
0.289
0.264
0.038
1.695

89
 5
 Portugal
5.195
 0.072
1.315
1.367
0.796
0.498
0.095
0.016
1.108

90
 3
 Bosnia and Herzegovina
5.182
 0.019
0.982
1.069
0.705
0.204
0.329
0.000
1.892

91
 13
 Honduras
5.181
 0.310
0.731
1.144
0.583
0.348
0.236
0.073
2.066

92
 3
 Macedonia
5.175
 0.054
1.065
1.208
0.645
0.326
0.254
0.060
1.617

93
 17
 Somalia
5.151
 0.289
0.023
0.721
0.114
0.602
0.292
0.282
3.117

94
 2
 Vietnam
5.074
 0.013
0.789
1.277
0.652
0.571
0.235
0.088
1.462

95
 8
 Nigeria
5.074
 0.199
0.784
1.216
0.057
0.395
0.231
0.026
2.365

96
 4
 Tajikistan
5.041
 0.045
0.525
1.271
0.529
0.472
0.249
0.146
1.849

97
 13
 Bhutan
5.011
 0.185
0.885
1.340
0.496
0.502
0.474
0.173
1.140

98
 13
 Kyrgyzstan
5.004
 0.181
0.596
1.394
0.553
0.455
0.429
0.039
1.537

99
 8
   Nepal
4.962
 0.169
0.480
1.179
0.504
0.440
0.394
0.073
1.891

—
—
 Soviet Union
4.959[Note 3]
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

100
 1
 Mongolia
4.955
 0.048
1.027
1.493
0.558
0.394
0.338
0.033
1.111

101
 15
 South Africa
4.829
 0.370
1.055
1.385
0.187
0.479
0.139
0.073
1.511

102
 4
 Tunisia
4.805
 0.240
1.007
0.868
0.613
0.290
0.050
0.087
1.890

103
 5
 Palestinian Territories
4.775
 0.021
0.716
1.156
0.566
0.255
0.114
0.089
1.879

104
 16
 Egypt
4.735
 0.373
0.990
0.997
0.520
0.282
0.129
0.114
1.702

105
 24
 Bulgaria
4.714
 0.497
1.161
1.434
0.708
0.289
0.113
0.011
0.996

106
 5
 Sierra Leone
4.709
 0.074
0.368
0.984
0.006
0.319
0.293
0.071
2.668

107
 7
 Cameroon
4.695
 0.182
0.564
0.946
0.133
0.430
0.236
0.051
2.334

108
 3
 Iran
4.692
 0.121
1.157
0.712
0.639
0.249
0.387
0.049
1.499

109

 Albania
4.644
 0.011
0.996
0.804
0.731
0.381
0.201
0.040
1.490

110

 Bangladesh
4.608
 0.035
0.587
0.735
0.533
0.478
0.172
0.124
1.979

111
 2
 Namibia
4.574

0.964
1.098
0.339
0.520
0.077
0.093
1.482

112
 10
 Kenya
4.553
 0.197
0.560
1.068
0.310
0.453
0.445
0.065
1.652

113
N/A
 Mozambique
4.550
N/A
0.234
0.871
0.107
0.481
0.322
0.179
2.356

114
 5
 Myanmar
4.545
 0.150
0.367
1.123
0.398
0.514
0.838
0.189
1.115

115
 13
 Senegal
4.535
 0.316
0.479
1.180
0.409
0.378
0.183
0.115
1.790

116
 10
 Zambia
4.514
 0.281
0.636
1.003
0.258
0.462
0.250
0.078
1.827

117
 5
 Iraq
4.497
 0.078
1.103
0.979
0.501
0.289
0.200
0.107
1.319

118
 16
 Gabon
4.465
 0.344
1.198
1.156
0.357
0.312
0.044
0.076
1.323

119
 4
 Ethiopia
4.460
 0.048
0.339
0.865
0.353
0.409
0.313
0.165
2.016

120
 3
 Sri Lanka
4.440
 0.025
1.010
1.260
0.625
0.561
0.491
0.074
0.419

121

 Armenia
4.376
 0.016
0.901
1.007
0.638
0.198
0.083
0.027
1.521

122
 4
 India
4.315
 0.089
0.792
0.754
0.455
0.470
0.232
0.092
1.519

123
 7
 Mauritania
4.292
 0.091
0.648
1.272
0.285
0.096
0.202
0.137
1.652

124
 1
 Congo (Brazzaville)
4.291
 0.019
0.809
0.832
0.290
0.435
0.121
0.080
1.724

125
 1
 Georgia
4.286
 0.034
0.951
0.571
0.650
0.309
0.054
0.252
1.500

126
 1
 Congo (Kinshasa)
4.280
 0.044
0.092
1.229
0.191
0.236
0.246
0.060
2.225

127
 8
 Mali
4.190
 0.117
0.476
1.281
0.169
0.307
0.183
0.105
1.668

128
 11
 Ivory Coast
4.180
 0.264
0.603
0.905
0.049
0.448
0.201
0.130
1.845

129
 11
 Cambodia
4.168
 0.261
0.602
1.006
0.430
0.633
0.386
0.068
1.043

130
 3
 Sudan
4.139

0.660
1.214
0.291
0.015
0.182
0.090
1.687

131
 7
 Ghana
4.120
 0.156
0.667
0.874
0.296
0.423
0.257
0.025
1.578

132
 9
 Ukraine
4.096
 0.228
0.895
1.395
0.576
0.123
0.270
0.023
0.814

133
 13
 Uganda
4.081
 0.342
0.381
1.130
0.218
0.443
0.326
0.057
1.526

134
 11
 Burkina Faso
4.032
 0.293
0.350
1.043
0.216
0.324
0.251
0.120
1.727

135
 7
 Niger
4.028
 0.172
0.162
0.993
0.269
0.364
0.229
0.139
1.874

136
 4
 Malawi
3.970
 0.186
0.233
0.513
0.315
0.467
0.287
0.073
2.082

137
 7
 Chad
3.936
 0.173
0.438
0.954
0.041
0.162
0.216
0.054
2.071

138
 7
 Zimbabwe
3.875
 0.318
0.376
1.083
0.197
0.336
0.189
0.095
1.598

139
N/A
 Lesotho
3.808
N/A
0.521
1.190
0.000
0.391
0.157
0.119
1.430

140
 1
 Angola
3.795
 0.071
0.858
1.104
0.050
0.000
0.098
0.070
1.614

141
 13
 Afghanistan
3.794
 0.434
0.401
0.582
0.181
0.106
0.312
0.061
2.151

142
 5
 Botswana
3.766
 0.208
1.122
1.222
0.342
0.505
0.099
0.099
0.378

143
 10
 Benin
3.657
 0.173
0.431
0.435
0.210
0.426
0.208
0.061
1.886

144
 4
 Madagascar
3.644
 0.051
0.306
0.913
0.375
0.189
0.209
0.067
1.585

145
 9
 Haiti
3.603
 0.425
0.369
0.640
0.277
0.030
0.489
0.100
1.697

146
 1
 Yemen
3.593
 0.131
0.592
0.935
0.310
0.249
0.104
0.057
1.346

147
 4
 South Sudan
3.591
 0.241
0.397
0.601
0.163
0.147
0.286
0.117
1.880

148
 2
 Liberia
3.533
 0.089
0.119
0.872
0.230
0.333
0.267
0.039
1.673

149
 2
 Guinea
3.507
 0.100
0.245
0.791
0.194
0.349
0.265
0.111
1.552

150
 5
 Togo
3.495
 0.192
0.305
0.432
0.247
0.380
0.197
0.096
1.837

151
 1
 Rwanda
3.471
 0.044
0.369
0.946
0.326
0.582
0.253
0.455
0.540

152
 4
 Syria
3.462
 0.393
0.777
0.396
0.501
0.082
0.494
0.151
1.062

153
 4
 Tanzania
3.349
 0.317
0.511
1.042
0.365
0.390
0.354
0.066
0.621

154
 3
 Burundi
2.905

0.092
0.630
0.152
0.060
0.204
0.084
1.683

155
N/A
 Central African Republic
2.693
N/A
0.000
0.000
0.019
0.271
0.281
0.057
2.066

text: 2013–2015 averaged ranking[edit]

text:
showTable

Legend:[43]

  Explained by: GDP per capita
  Explained by: Social support
  Explained by: Healthy life expectancy

  Explained by: Freedom to make life choices
  Explained by: Generosity
  Trust or absence of corruption, as explained by the publicly perceived absence of corruption in government and business[44]
Italics: States with limited recognition and disputed territories

Overall Rank[45][46]

Country

Score

Change OverPrior Year

GDP per capita

Social support

Healthy life expectancy

Freedom to make life choices

Generosity

Trust

1

 Denmark

7.526

 -0.401

2

  Switzerland

7.509

 0.035

3

 Iceland

7.501

 0.000

4

 Norway

7.498

 0.082

5

 Finland

7.413

 -0.259

6

 Canada

7.404

 -0.041

7

 Netherlands

7.339

 -0.119

8

 New Zealand

7.334

 -0.097

9

 Australia

7.313

 0.002

10

 Sweden

7.291

 -0.017

11

 Israel

7.267

 0.258

12

 Austria

7.119

 -0.003

13

 United States

7.104

 -0.261

14

 Costa Rica

7.087

 -0.171

15

 Puerto Rico

7.039

 0.446

16

 Germany

6.994

 0.486

17

 Brazil

6.952

 0.474

18

 Belgium

6.929

 -0.311

19

 Ireland

6.907

 -0.238

20

 Luxembourg

6.871

 0.000

21

 Mexico

6.778

 0.225

22

 Singapore

6.739

 0.099

23

 United Kingdom

6.725

 -0.161

24

 Chile

6.705

 0.826

25

 Panama

6.701

 0.191

26

 Argentina

6.650

 0.457

27

 Czech Republic

6.596

 0.126

28

 United Arab Emirates

6.573

 -0.161

29

 Uruguay

6.545

 0.804

30

 Malta

6.488

 0.000

31

 Colombia

6.481

 0.399

32

 France

6.478

 -0.336

33

 Thailand

6.474

 0.631

34

 Saudi Arabia

6.379

 -0.794

35

 Taiwan

6.379

 0.190

36

 Qatar

6.375

 0.000

37

 Spain

6.361

 -0.711

38

 Algeria

6.355

 0.000

39

 Guatemala

6.324

 0.211

40

 Suriname

6.269

 0.000

41

 Kuwait

6.239

 0.164

42

 Bahrain

6.218

 0.000

43

 Trinidad and Tobago

6.168

 0.336

44

 Venezuela

6.084

 -0.762

45

 Slovakia

6.078

 0.814

46

 El Salvador

6.068

 0.572

47

 Malaysia

6.005

 -0.132

48

 Nicaragua

5.992

 1.285

49

 Uzbekistan

5.987

 0.755

50

 Italy

5.977

 -0.735

51

 Ecuador

5.976

 0.966

52

 Belize

5.956

 -0.495

53

 Japan

5.921

 -0.446

54

 Kazakhstan

5.919

 0.322

55

 Moldova

5.897

 0.959

56

 Russia

5.856

 0.738

57

 Poland

5.835

 0.098

58

 South Korea

5.835

 0.295

59

 Bolivia

5.822

 0.322

60

 Lithuania

5.813

 -0.069

61

 Belarus

5.802

 0.165

62

 Northern Cyprus

5.771

 0.000

63

 Slovenia

5.768

 -0.044

64

 Peru

5.743

 0.730

65

 Turkmenistan

5.658

 0.000

66

 Mauritius

5.648

 0.000

67

 Libya

5.615

 0.000

68

 Latvia

5.560

 0.872

69

 Cyprus

5.546

 -0.692

70

 Paraguay

5.538

 0.536

71

 Romania

5.528

 0.310

72

 Estonia

5.517

 0.165

73

 Jamaica

5.510

 -0.698

74

 Croatia

5.488

 -0.333

75

 Hong Kong

5.458

 -0.053

76

 Somalia

5.440

 0.000

77

 Kosovo[Note 4]

5.401

 0.298

78

 Turkey

5.389

 0.216

79

 Indonesia

5.314

 0.295

80

 Jordan

5.303

 -0.638

81

 Azerbaijan

5.291

 0.642

82

 Philippines

5.279

 0.425

83

 People's Republic of China

5.245

 0.525

84

 Bhutan

5.196

 0.000

85

 Kyrgyzstan

5.185

 0.515

86

 Serbia

5.177

 0.426

87

 Bosnia and Herzegovina

5.163

 0.263

88

 Montenegro

5.161

 -0.035

89

 Dominican Republic

5.155

 0.070

90

 Morocco

5.151

 0.000

91

 Hungary

5.145

 0.070

92

 Pakistan

5.132

 -0.374

93

 Lebanon

5.129

 0.059

94

 Portugal

5.123

 -0.282

95

 Macedonia

5.121

 0.627

96

 Vietnam

5.061

 -0.299

97

 Somaliland region

5.057

 0.000

98

 Tunisia

5.045

 0.000

99

 Greece

5.033

 -1.294

100

 Tajikistan

4.996

 0.474

101

 Mongolia

4.907

 0.298

102

 Laos

4.876

 -0.344

103

 Nigeria

4.875

 0.075

104

 Honduras

4.871

 -0.375

105

 Iran

4.813

 -0.507

106

 Zambia

4.795

 0.381

107

   Nepal

4.793

 0.135

108

 Palestinian Territories[Note 5]

4.754

 0.321

109

 Albania

4.655

 0.021

110

 Bangladesh

4.643

 0.170

111

 Sierra Leone

4.635

 1.028

112

 Iraq

4.575

 0.000

113

 Namibia

4.574

 -0.312

114

 Cameroon

4.513

 0.413

115

 Ethiopia

4.508

 0.000

116

 South Africa

4.459

 -0.686

117

 Sri Lanka

4.415

 0.037

118

 India

4.404

 -0.750

119

 Myanmar

4.395

 0.000

120

 Egypt

4.362

 -0.996

121

 Armenia

4.360

 -0.226

122

 Kenya

4.356

 -0.044

123

 Ukraine

4.324

 -0.701

124

 Ghana

4.276

 -0.600

125

 Republic of the Congo

4.272

 0.000

126

 Georgia

4.252

 0.561

127

 Democratic Republic of the Congo

4.236

 0.000

128

 Senegal

4.219

 -0.328

129

 Bulgaria

4.217

 0.373

130

 Mauritania

4.201

 0.052

131

 Zimbabwe

4.193

 0.639

132

 Malawi

4.156

 -0.205

133

 Sudan

4.139

 0.000

134

 Gabon

4.121

 0.000

135

 Mali

4.073

 0.059

136

 Haiti

4.028

 0.274

137

 Botswana

3.974

 -0.765

138

 Comoros

3.956

 0.000

139

 Ivory Coast

3.916

 0.000

140

 Cambodia

3.907

 0.045

141

 Angola

3.866

 0.000

142

 Niger

3.856

 -0.144

143

 South Sudan

3.832

 0.000

144

 Chad

3.763

 -0.025

145

 Burkina Faso

3.739

 -0.170

146

 Uganda

3.739

 -0.356

147

 Yemen

3.724

 -0.754

148

 Madagascar

3.695

 -0.285

149

 Tanzania

3.666

 -0.460

150

 Liberia

3.622

 -0.080

151

 Guinea

3.607

 0.000

152

 Rwanda

3.515

 -0.700

153

 Benin

3.484

 0.154

154

 Afghanistan

3.360

 0.000

155

 Togo

3.303

 0.100

156

 Syria

3.069

 0.000

157

 Burundi

2.905

 0.000

text: Criticism[edit]

text: Metrics[edit]

text: Some argue that questioning on overall life status leads humans to overweight income concerns, rather than happiness. For instance Colombia came 37th in the 2018 World Happiness Index but 1st by daily emotional experience.[47] In 2012 "A Gallup survey on happiest countries had a completely different list [compared with the World Happiness Index], with Panama first, followed by Paraguay, El Salvador, and Venezuela". Similarly a Pew survey of 43 countries in 2014 (which excluded most of Europe) had Mexico, Israel and Venezuela finishing first, second and third.[48]

text: Others point out that the ranking results are counterintuitive when it come to some dimensions, for "instance if rate of suicide is used as a metric for measuring unhappiness, (the opposite of happiness), then quite some of the countries which are ranked among the top 20 happiest countries in the world will also feature among the top 20 with the highest suicide rates in the world."[49]

text: Methodology[edit]

text: From an econometric perspective, some statisticians argue the statistical methodology mentioned in the first world happiness report using 9 domains is unreliable.[50]

text: Others argue that the World Happiness Report model uses a limited subset of indicators used by other models and does not use an Index function like peer econometric models such as Gross National Well-being Index 2005, Sustainable Society Index of 2008[51], OECD Better Life Index of 2011, and Bhutan Gross National Happiness Index of 2012, and Social Progress Index of 2013.

text: Other critics point out that Happiness Surveys are contradictory in Ranking because of the varying methodologies. They also argue that the surveys are inherently flawed. "No matter how carefully parsed the data may be, a survey based on unreliable answers isn't worth a lot."

text: Philosophical concerns[edit]

text: From a philosophical perspective, critics argue that measuring of happiness of a grouping of people is misleading because happiness is an individual matter. They state "the Dalai Lama, Gandhi, Tolstoy and several others, happiness is an individual choice that is independent of the society, its structures and enabling or dis-enabling conditions and not something to be measured using variables that can only capture a nation’s well-being. This means therefore that one cannot really talk of a happy or unhappy nation, but of happy or unhappy individuals."[52]


document_title: Rabbit rabbit rabbit

question_text: where did the saying white rabbits come from

text: Rabbit rabbit rabbit

text: Origins and history[edit]

text: The exact origin of the superstition is unknown, though it was recorded in Notes and Queries as being said by children in 1909:

text: "My two daughters are in the habit of saying 'Rabbits!' on the first day of each month. The word must be spoken aloud, and be the first word said in the month. It brings luck for that month. Other children, I find, use the same formula."[1]

text: In response to this note another contributor said that his daughter believed that the outcome would be a present, and that the word must be spoken up the chimney to be most effective; another pointed out that the word rabbit was often used in expletives, and suggested that the superstition may be a survival of the ancient belief in swearing as a means of avoiding evil.[2] People continue to express curiosity about the origins of this superstition[3] and draw upon it for inspiration in making calendars[4] suggestive of the Labors of the Months, thus linking the rabbit rabbit superstition to seasonal fertility.

text: It appeared in a work of fiction in 1922:

text: "Why," the man in the brown hat laughed at him, "I thought everybody knew 'Rabbit, rabbit, rabbit.' If you say 'Rabbit, rabbit, rabbit'—three times, just like that—first thing in the morning on the first of the month, even before you say your prayers, you'll get a present before the end of the month."[5]

text: Chapter 1 of the Trixie Belden story The Mystery of the Emeralds (1962) is titled “Rabbit! Rabbit!” and discusses the tradition:

text: Trixie Belden awoke slowly, with the sound of a summer rain beating against her window. She half-opened her eyes, stretched her arms above her head, and then, catching sight of a large sign tied to the foot of her bed, yelled out, “Rabbit! Rabbit!” She bounced out of bed and ran out of her room and down the hall. “I’ve finally done it!” she cried [...] “Well, ever since I was Bobby’s age I’ve been trying to remember to say ‘Rabbit! Rabbit!’ and make a wish just before going to sleep on the last night of the month. If you say it again in the morning, before you’ve said another word, your wish comes true.” Trixie laughed."[6]

text: In the United States the tradition appears especially well known in northern New England[7][8][9] although, like all folklore, determining its exact area of distribution is difficult. The superstition may be related to the broader belief in the rabbit or hare being a "lucky" animal, as exhibited in the practice of carrying a rabbit's foot for luck.[10]

text: During the mid-1990s, U.S. children's cable channel Nickelodeon helped popularize the superstition in the United States as part of its "Nick Days," where during commercial breaks it would show an ad about the significance of the current date, whether it be an actual holiday, a largely uncelebrated unofficial holiday, or a made-up day if nothing else is going on that specific day. (The latter would be identified as a "Nickelodeon holiday.") Nickelodeon would promote the last day of each month as "Rabbit Rabbit Day" and to remind kids to say it the next day, unless the last day of that specific month was an actual holiday, such as Halloween or New Year's Eve.[11] This practice stopped by the late 1990s.

text: Rabbits have not always been thought of as lucky, however. In the 19th century, for example, fishermen would not say the word while at sea,[12][13] in South Devon to see a white rabbit in one's village when a person was very ill was regarded as a sure sign that the person was about to die.[14]

text: In other traditions[edit]

text: There is another folk tradition which may use a variation "Rabbit", "Bunny", "I hate/love Grey Rabbits" or "White Rabbit" to ward off smoke that the wind is directing into your face when gathered around a campfire.[15] It is thought that this tradition may be related to the tradition of invoking the rabbit on the first of the month. Others conjecture that it may originate with a North American First Nation story about smoke resembling rabbit fur.[16] This tradition may be more of a social tradition in a group setting than a genuine belief that certain words will change the wind direction, and may be more of a childhood tradition than an adult one. Children have sometimes adapted from Rabbit to "Pink Elephant" or other comical derivatives.[17] Because of this more mutable usage, historical record of this is even more scarce than other more static meanings.

text: As with all folklore, its truth is made evident even in its only occasional fulfillment: should the wind then appear to change direction, others will interpret the use of such an expression as evidence of its effectiveness and will then tend to adopt and repeat its use. That multiple instances of its ineffectiveness also exist is discounted in light of the "fact" that it appeared to work once.

text: Other variants[edit]

text: As with most folklore, which is traditionally spread by word of mouth, there are numerous variants of the superstition, in some cases specific to a certain time period or region.

text:
"When I was a very little boy I was advised to always murmur 'White rabbits' on the first of every month if I wanted to be lucky. From sheer force of unreasoning habit I do it still—when I think of it. I know it to be preposterously ludicrous, but that does not deter me." – Sir Herbert Russell, 1925.[18]
"Even Mr. Roosevelt, the President of the United States, has confessed to a friend that he says 'Rabbits' on the first of every month—and, what is more, he would not think of omitting the utterance on any account." – Newspaper article, 1935.[19]
"On the first day of the month say 'Rabbit! rabbit! rabbit!' and the first thing you know you will get a present from someone you like very much." Collected by the researcher Frank C. Brown in North Carolina in the years between 1913 and 1943.[20]
"If you say 'Rabbit, rabbit, rabbit' the first thing when you wake up in the morning on the first of each month you will have good luck all month." Collected by Wayland D. Hand in Pennsylvania before 1964.[20]
"Say 'Rabbit, rabbit, rabbit' at the first of the month for good luck and money." Collected by Ernest W. Baughman in New Mexico before 1964.[20]
"...it must be 'White Rabbit' ... but you must also say 'Brown Rabbit' at night and walk downstairs backwards." Reported in a small survey that took place in Exeter, Devon in 1972.[21]
"Ever since I was 4 years old, I have said 'White Rabbits' at the very moment of waking on every single first day of every single month that has passed." Simon Winchester, 2006.[22]
"...the more common version 'rabbit, rabbit, white rabbit' should be said upon waking on the first day of each new month to bring good luck." Sunday Mirror, 2007.[23]

tag: ul


document_title: Drought in the United Kingdom

question_text: when was the last time the uk had a drought

text: Drought in the United Kingdom

text: Definition and comparison with other countries[edit]

text: A drought is usually defined as an extended period of weather (usually around 3 weeks) when less than a third of the usual precipitation falls.[4]

text: In the United Kingdom an absolute drought is currently defined "as a period of at least 15 consecutive days when there is less than 0.2 mm (0.008 inches) of rainfall",[4] although before the 1990s a drought was defined as "15 consecutive days with less than 0.25 mm (0.01 inches) rain on any one day". This previous definition sometimes led to confusion, as many argued, "if less than 0.25 mm of rain each day fell in 30 days, is that 2 droughts? And if 0.26 mm fell after 25 days, is the drought over?" This led to the new definition, but many believe hindsight is the best way to judge if a drought has occurred.[5]

text: In the longer term, drought in the United Kingdom can also be defined as "a 50% deficit over three months, or a 15% shortfall over two years".[6]

text: Compared to other countries, the United Kingdom definition of a drought is much less severe. In Libya in the Sahel region, a drought is usually only recognized after two years without any measurable rainfall. If this were to happen in the United Kingdom, the consequences would be disastrous.[4]

text: A different type of drought is the hydrological or agricultural drought. In this case there is moisture in the soil, but little is getting to vegetation, either because it is frozen (which can occur in severely cold winters in the United Kingdom) or because of very high temperatures which mean that the rate of evapotranspiration exceeds the rate of uptake of water from the plant (which can be seen in the United Kingdom, on hot days, when plants wilt as their stores of water are depleted).[6]

text: A hydrological drought can occur after a relatively dry winter, when the soil moisture storage, reservoirs and water table have not risen enough to counteract the warm summer weather. These sorts of conditions can persist over several years, even with above average rainfall, as the rainfall only slowly percolates through the water stores and replenishes them.[6]

text: Causes[edit]

text: The main cause for a long spell of dry weather in the United Kingdom is usually a blocking anticyclone (often the Azores high) system that forces other low pressure systems around it, usually to the northwest. This can happen any time of year, but brings hot sunny weather in summer and dry, cold and foggy weather in winter. This is why in dry spells the northwest of the United Kingdom actually often receives above average rainfall, as depressions and associated fronts are pushed towards the north.[4]

text: A severe drought in the United Kingdom needs to have the high pressure in charge of the weather for an extended period, commonly for weeks or even months at a time. Most often sea surface temperature anomalies in the Atlantic and intensification of the mid latitude westerlies in the Pacific can bring a stable anticyclone, meaning that the pressure can remain above average for weeks, or even months at a time, allowing the heat to build and dry weather to continue during the anticyclonic system.

text: Notable events[edit]

text: Several notable droughts in the United Kingdom have occurred in recorded history, some of these in the 21st century. They can be divided into two categories, the meteorological drought where little or no rain fell over a relatively short period and the hydrological drought, where below average rainfall has occurred over an extended period.

text: Meteorological droughts[edit]

text: One of the most severe meteorological droughts in recent times was in 1976, when a dry 1975-76 winter was followed by one of the hottest and driest summers since records began. The drought effectively began in October 1975, but with low temperatures and therefore low evaporation rates during the winter, the below average rainfall did not present an immediate problem. As the dry winter ended and was followed by the hot and particularly dry summer of 1976, the drought became one of the most famous in United Kingdom history.

text: The drought became a serious problem in late spring. In April, no rain fell in parts of Cornwall; and then in June, no rain fell over Devon and Kent. In August no precipitation was measured in North Wales. This meant that in some places, less than half the average rainfall was measured from October 1975 to August 1976. For example, in Kew, just 235 mm (9.25 inches) of rain was measured over that period, which was 43% of the average, meaning the amount of rainfall was comparable to a semi-arid climate. In Devon and Dorset, some locations received no rainfall for 45 consecutive days through July and August, another United Kingdom record. This was on top of another three periods of absolute drought, totalling 58 days with no measurable precipitation.

text: The lack of rain can be attributed to the high pressure system over the United Kingdom at the time, which meant average pressure was 5 millibars above the expected for the summer months.

text: This drought was intensified by the exceptional heat that continued through it. Records were set for the heat as well as the lack of rain, resulting in very high evaporation rates. From 23 June, temperatures were over 32 °C (90 °F) for two consecutive weeks around the United Kingdom, peaking at 35.6 °C (96.1 °F) on 28 June at Mayflower Park in Southampton. This still is the highest ever June temperature since records began. The highest temperature in the summer was 35.9 °C (96.6 °F) at Cheltenham on 3 July.[7] The effects of the drought included substantial and long-lasting changes to the tree composition of forests. The European Beech was severely affected by the drought and took around twenty years to recover. To date, its growth has failed to recover completely, reaching only about 75% of their pre-drought growth rates,[8] even decades after the drought. Additionally, death due to drought resulted in the loss of around 15% of the mature beech trees in the forest. In contrast,the sessile oak did not suffer any death or growth suppression due to drought, but instead benefited from reduced competition with beech. Sessile oak growth increased suddenly after the drought and remained unusually high until the 1990s, when beech recovered and regained dominance. European Beech dominates temperate forests over large areas of Europe, but is considered to be particularly drought-sensitive and is predicted to be outcompeted by more drought-tolerant species in many regions as the climate warms.

text: Another event like the 1976 drought was in the summer of 2003. This was also notable for the temperatures, with 100 °F being hit in the United Kingdom for the first time since records began, with a top temperature of 38.5 °C (101.3 °F) recorded in Faversham, Kent, and some places recording up to, or above, 40 °C (104 °F) unofficially. This drought and the associated heat wave affected the whole of Europe, not just the United Kingdom, as with the 1976 event. The average temperature was the highest since 1868, measured over February to September. This added to the severity of the drought, with high rates of evaporation. The summer ranked as the 4th highest for potential evaporation since 1961, and this evaporation alone exceeded rainfall totals across a third of the United Kingdom.

text:
The United Kingdom had its driest February to October period since 1921, and in the drought period had conditions only comparable to the previous conditions of 1976. Over the whole of the United Kingdom, the rainfall totals were the 3rd lowest since records began in 1900, and in some regions only 25% of the average rainfall fell in this period. Scotland suffered during this period as it had its driest spell since the 1955 drought, and coupled with a dry winter here (England and Wales had relatively wet winters as depressions were forced south) this led to a hydrological drought here too. Also, with several local convective thunderstorms missing specific areas, some localities had exceptionally low rainfall totals, compared to the average, with some places having their driest February to October since 1697.
The drought ended in October when a low pressure system finally arrived to bring substantial rain to the United Kingdom. Some areas in Southern England had more rain in this 6 day period than they had received in the previous 3 months. Fortunately the preceding winter of 2002-2003 was relatively wet, which reduced the severity of the drought greatly, unlike the dry 1975-76 winter which led into 1976.[9]

text: Hydrological droughts[edit]

text: A significant hydrological drought occurred in the United Kingdom between 1995 and 1998, when the warm, dry summers were followed by dry, cool winters. This meant that over the three years, the lack of winter precipitation failed to counteract the dry summers, so slowly the water table fell, and reservoir water levels began to fall.[6] Water levels were only replenished after some exceptionally wet years from 1999 to 2002. Similar conditions were felt between 2003 and 2006, with only the record breaking rainfall of 2007 and 2008 replenishing the water levels.[7]

text: Impact[edit]

text: United Kingdom droughts have similar consequences to other droughts elsewhere in the world. The first of these is river and reservoir levels begin to drop as rainfall fails to counteract evaporation.[4]

text: As drought conditions continue, groundwater levels drop and this provides excellent conditions for fires to develop. With hot, dry weather and no moisture underground, trees lose moisture and become very flammable in dry conditions. This leads to wildfires which usually is the main impact of drought in the United Kingdom, with moorland vegetation such as heather badly affected as the peat bogs dry out. Also, these fires can continue, even when seemingly put out, as the smoldering peat re-ignites the dry vegetation. However, during severe droughts, many trees can burn, and people's lives can be at risk, as in the 1976 drought when a fire encroached on a hospital, and only a wind direction change saved the patients' lives. As embers can be transported easily, and if drought is severe enough, fires can start miles away from their original position as they are transported by wind and even dust devils. With these situations, roads are often closed to prevent loss of life and further damage. These fires also can destroy wildlife habitats, and this can also threaten wildlife.[7]

text: Often, in severe droughts, crops can fail as the soil does not contain sufficient moisture to keep them alive and this is usually the largest economic impact with £500 million ($830 million) worth of damage from failed crops in 1976. Another, more subtle impact is the insurance claims from damage to houses and businesses from fire and subsidence (caused by the dry and shrunken soil), sometimes amounting to over £50 million ($83 million) in severe droughts.[7]

text: Responses and management[edit]

text: The responses to drought in England are managed by the Environment Agency. There are four stages to drought management, applying to both businesses and homes.

text: The first of these is a media campaign, urging people to save water and thus avoid the need to take specific measures. For example, use a water butt to collect any rainfall.

text: If drought continues, and water levels continue to decrease, further measures are brought in to save water. This includes a hosepipe ban, which forbids the use of hosepipes, and can be applied to hot tubs, pressure washers and other similar devices in a future drought. These measures were brought in, particularly the ban on hosepipes, in 1976 and 2006.

text: The third stage involves conserving any non-essential supplies of water. These measures are brought in when no precipitation is forecast and water supplies are already very low. The options include:

text:
widening the hosepipe bans, to include sprinklers,
drastic measures such as banning cleaning of buildings, vehicles and windows or the filling of swimming pools.

text: These measures were also brought in during the 1976 drought.

text: The fourth and final stage involves drastic measures of water rationing to all businesses and homes in the United Kingdom in an emergency drought order. The measures are brought in only in exceptional conditions of extended periods with little or no rainfall. This means no water supplies at certain times of the day, or allowing water for a specific amount of time. Standpipes and water tankers can be used as a last resort to have only set amounts of water given to each household in a neighbourhood. Again, these measures were used during the 1976 drought.[10][11]

text: Also, each area in the United Kingdom has its own drought plan, for the event of any future drought.[12]