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Statistical Appendix 1 for Chapter 2 of Report 2021

John F. Helliwell, Haifang Huang, Shun Wang, and Max Norton March 18, 2021

1 Data Sources and Variable Definitions

• Happiness score or subjective well- (variable name ladder): The survey measure of SWB is from the Feb 26, 2021 release of the World Poll (GWP) covering years from 2005 to 2020. Unless stated otherwise, it is the na- tional average response to the question of life evaluations. The English wording of the question is “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?” This measure is also referred to as Cantril life ladder, or just life ladder in our analysis.

• The of GDP per capita (variable name gdp) in purchasing power parity (PPP) at constant 2017 international dollar prices are from the October 14, 2020 update of the World Development Indicators (WDI). The GDP figures for , , Palestine, , and Ymen are from the Penn World Table 9.1.

– GDP per capita in 2020 are not yet available as of December 2020. We extend the GDP-per-capita time series from 2019 to 2020 using - specific forecasts of real GDP growth in 2020 first from the OECD Eco- nomic Outlook No 108 (December 2020) and then, if missing, forecasts from World Bank’s Global Economic Prospects (Last Updated: 06/08/2020). The GDP growth forecasts are adjusted for with the subtraction of 2018-19 population growth as the projected 2019-20 growth.

• Healthy (HLE). Healthy life expectancies at birth are based on the data extracted from the World Organization’s (WHO) Global Health Observatory data repository (Last updated: 2020-09-28). The data at the source are available for the years 2000, 2005, 2010, 2015 and 2016. To match this report’s sample period (2005-2020), interpolation and extrapolation are used.

1 • Social support (or having someone to count on in times of trouble) is the national average of the binary responses (either 0 or 1) to the GWP question “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?”

• Freedom to make life choices is the national average of responses to the GWP question “Are you satisfied or dissatisfied with your freedom to choose what you do with your life?”

is the residual of regressing national average of response to the GWP question “Have you donated money to a charity in the past month?” on GDP per capita.

Perception: The measure is the national average of the survey re- sponses to two questions in the GWP: “Is corruption widespread throughout the government or not” and “Is corruption widespread within businesses or not?” The overall perception is just the average of the two 0-or-1 responses. In case the perception of government corruption is missing, we use the perception of business corruption as the overall perception. The corruption perception at the national level is just the average response of the overall perception at the individual level.

• Positive affect is defined as the average of three positive affect measures in GWP: happiness, laugh and enjoyment in the Gallup World Poll waves 3-7. These measures are the responses to the following three questions, respectively: “Did you experience the following feelings during A LOT OF THE DAY yes- terday? How about Happiness?”, “Did you smile or laugh a lot yesterday?”, and “Did you experience the following feelings during A LOT OF THE DAY yesterday? How about Enjoyment?” Waves 3-7 cover years 2008 to 2012 and a small number of in 2013. For waves 1-2 and those from wave 8 on, positive affect is defined as the average of laugh and enjoyment only, due to the limited availability of happiness.

• Negative affect is defined as the average of three negative affect measures in GWP. They are worry, sadness and anger, respectively the responses to “Did you experience the following feelings during A LOT OF THE DAY yesterday? How about Worry?”, “Did you experience the following feelings during A LOT OF THE DAY yesterday? How about Sadness?”, and “Did you experience the following feelings during A LOT OF THE DAY yesterday? How about Anger?”

• Gini of household income reported in the Gallup World Poll (variable name giniIncGallup). The income variable is described in Gallup’s “WORLDWIDE RESEARCH AND CODEBOOK” (Updated July 2015) as “Household Income International Dollars [...] To calculate income, respondents are asked to report their household income in local . Those respondents who have difficulty answering the question are presented a set of ranges in local

2 currency and are asked which group they fall into. Income variables are cre- ated by converting local currency to International Dollars (ID) using purchasing power parity (PPP) ratios.” The gini measure is generated using STATA com- mand ineqdec0 by WP5-year with sample weights.

• GINI index from the World Bank (variable name giniIncWB and giniIncW- Bavg) from the World Development Indicators. The variable labeled at the source as “GINI index (World Bank estimate)”, series code “SI.POV.GINI”. According to the source, the data source is “World Bank, Development Re- search Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments.” The variable giniIncWB is an unbalanced panel of yearly index. The data avail- ability is patchy at the yearly frequency. The variable giniIncWBavg is the average of giniIncWB starting from year 2000. The average does not imply that a country has the gini index in all years since then. In fact, most do not.

• Institutional trust: The first principal component of the following five measures: confidence in the national government, confidence in the judicial system and courts, confidence in the honesty of elections, confidence in the local police force, and perceived corruption in business. This principal component is then used to create a binary measure of high institutional trust using the 75th percentile in the global distribution as the cutoff point; this way a country whose population tends to have a low level of institutional trust in the global distribution will have a low average institutional trust at the national level. This measure is not available for all countries since not all surveys in all countries ask all of the questions that are used to derive the principal component.

2 Coverage, Summary Statistics and Regression Tables

WP5 is GWP’s coding of countries including some sub-country territories such as . Not all the countries and territories appear in all the years. Our analysis does not cover all of the country/territories that have valid happiness scores. The 2018-2020 ranking of happiness scores includes 149 countries/territories; only two third of them (95 to be precise) have survey information in 2020. The remaining countries’ ranking are based on surveys in 2018 and 2019. The chapter also report average happiness scores from the 2017-2019 period; as we noted in the text, the scores are slightly different from those reported in WHR 2020 because of the late arrival of data for 15 countries; their 2019 survey data were not released to the WHR team for analysis until after the publication of WHR 2020. The late arrival causes only minor changes. To appear in regression analysis that uses data from outside the GWP survey, a wp5-year pair needs to have the necessary external information (GDP, healthy life ex- pectancy, etc). The regression analysis thus does not necessarily cover all of the coun-

3 tries/territories in the GWP. Nor does it necessarily cover all the countries/territories that are ranked by their happiness scores in this report. The underlying principle is that we always use the largest available sample. For different kind of analysis/ranking, the largest available samples can be different. Regions: Some of the analysis includes dummy indicator for regions, namely West- ern , Central and Eastern Europe, Commonwealth of Independent States, Southeast , , , America and , North Amer- ica and ANZ, Middle East and North , and Sub-Saharan Africa. A later set of tables list individual countries by their region grouping.

3 Imputed Missing Values in Our Exercise of Ex- plaining Ladder Scores with Six Factors

We do not make use of any imputed missing values in our rankings of happiness and its supporting factors. The only place where we make use of imputation is when we try to decompose a country’s average ladder score into components explained by six hypothesized underlying determinants (GDP per person, healthy life expectancy, social support, perceived freedom to make life choice, generosity and perception of corruption). A small number of countries have missing values in one or more of these factors. The most prominent is about the perception of corruption in businesses and governments. In several countries, the relevant questions were not asked in the Gallup World Poll. For these countries we impute the missing values using the “control of corruption” indicator from the Worldwide Governance Indicators (WGI) project. Specifically, the imputed is calculated as the predicted value using estimates from a model that regresses Gallup World Poll’s perception of corruption on WGI’s control of corruption. In all, less than 10 countries, listed in a later table, have the measure of corruption perception imputed in this way. In a few cases, countries are missing one or more of the happiness factors in the most recent years, but the information is available in earlier years; for example they may have GDP statistics in 2017 but not in the period from 2018 to 2020. In this case we use the information from the last available year. There is a limit of 3 years for how far back we go in search of those missing values. A few territories/countries do not have data on healthy life expectancy in the World Health Organization’s (WHO) Global Health Observatory data repository. For Hong Kong, we calculate the health life-to-life expectancy ratio using estimates reported in “Healthy life expectancy in Hong Kong Special Administrative Region of ,” by C.K. Law, & P.S.F. Yip, published at the Bulletin of the World Health Organization, 2003, 81 (1). The same ratio information for Swaziland in the period 2005-2010 can be found in “Healthy life expectancy for 187 countries, 1990 - 2010: a systematic analysis for the Global Burden Disease Study 2010,” by Joshua A Salomon et al, The Lancet, Volume 380, Issue 9859. We then multiply the ratios for Hong Kong and Swaziland, respectively, with their life expectancy time series in the WDI to get the health life expectancy up to 2017. The time series is then extrapolated to the end of our sample period. The Lancet

4 article also provides information for Taiwan and the Palestinian Territories. But the WDI does not provide life expectancy data for these two regions. For these two, we use their 2010 healthy life expectancy. For , we adjust its time series of life expectancy (available in the World Development Indicators) to a time series of health life expectancy by assuming that its health life-to-life expectancy ratio equals to the world average. Northern is missing GDP per capita, Healthy, life expectancy, as well as the measure of Generosity; we use the statistics of Cyprus instead. We note again we do not use any of the imputed values to generate country rankings. We use them only for our decomposition exercises, and the ranking of countries do not depend on those exercises.

5 Table 1: Number of ladder (WP16) observations for WP5-years - Part 1 Country/territory (ID) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

United States (1) 1001 1225 1004 1003 1005 1008 2094 1005 2048 1019 1032 1013 1004 1026 1007 (2) 999 1024 1105 2112 2053 5296 4186 1149 1000 1000 1000 1000 1000 2070 1002 (3) 1006 1001 3000 1007 2050 1008 1006 1001 1015 1006 (4) 996 1000 1000 2010 2027 2007 2013 1000 1000 1000 1000 1000 1000 1040 (5) 1004 1006 1150 2052 2038 2022 1077 2036 2035 1012 1000 1002 1003 1045 1043 (6) 1000 1016 1007 2016 2000 2000 2000 1000 1000 1000 1000 1012 1002 1001 1012 Syria (7) 1209 2100 2035 2041 2043 1022 1002 (8) 995 1001 1004 999 1000 1001 2000 1000 2003 1002 1001 1000 1000 2059 1000 (9) 1001 1502 2484 3122 1030 1000 3012 1000 1000 1000 1000 1600 1000 1091 (10) 1180 1000 1050 1080 1080 1000 3000 1000 1000 1000 1000 1000 1000 2192 (11) 1048 1200 1000 1000 1000 1000 3000 1000 1000 1000 1000 1000 1000 3072 1013 (12) 1037 1204 1001 1002 1000 9239 13408 750 2000 1000 1000 1000 1000 1025 1000 (13) 1002 1220 1006 1000 1004 1001 2005 751 2000 1000 1000 1000 1000 1025 1000

6 (14) 1001 1221 3016 2010 1007 9105 13269 751 2014 1000 2000 1000 1000 1025 1000 (15) 1000 1000 1000 1001 1000 1000 751 2002 1003 1000 1001 1002 1029 1006 (16) 1003 1022 1002 1003 1002 1001 1006 2004 1037 1000 1001 1011 1025 1005 (17) 1000 1004 1009 1005 1000 1006 2003 1004 2000 1000 1000 1000 1000 1025 1000 (18) 1002 1008 1008 1005 1000 1005 2007 1004 2000 1000 1000 1000 1000 1025 1000 (19) 1000 1000 1000 2000 1029 1000 1000 1000 1000 1000 1000 1000 1080 1010 (20) 1025 1010 1008 1008 1014 1004 1019 1003 1000 1000 1000 1000 1080 1001 (21) 1001 1072 2082 1000 1005 1001 1008 1000 1000 1000 1000 1004 (22) 1022 1000 1000 1000 1008 1000 1000 998 1001 1001 1001 1002 1080 (23) 1000 1001 1000 1002 1002 1006 1000 750 2001 1000 1000 1000 1001 1025 1000 (24) 1002 1000 1000 1000 1000 1000 1003 1000 1000 1000 1000 1000 1080 1002 (25) 1004 1009 1001 1000 1000 1005 1001 753 2002 1005 1000 1000 1000 1025 1000 (26) 1300 1004 1040 1003 3507 1000 2009 1001 1000 1000 1002 1058 1009 Hong Kong S.A.R. of China (27) 800 751 755 756 1028 1006 2017 1005 1007 1004 1005 (28) 1095 1000 2551 1005 1001 1000 1000 1000 1000 1000 1000 1000 1040 (29) 1000 1150 3000 1000 1000 1000 2000 1001 2006 1003 1003 1002 1003 1023 1016 China (30) 3730 3733 3712 3833 4151 4220 9413 4244 4696 4265 4373 4141 3649 3709 3503 (31) 2100 3186 2000 3010 6000 3518 10080 5540 3000 3000 3000 3000 3000 6643 9453 Venezuela (32) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1000 (33) 1029 1038 1032 1031 1043 1042 1002 2006 1007 1004 1001 1000 1000 3001 1002 Table 2: Number of ladder (WP16) observations for WP5-years - Part 2 Country/territory (ID) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Mexico (34) 1007 999 1000 1000 1000 1000 2000 1000 1017 1031 1000 1000 1034 1001 1010 (35) 1000 1000 1000 1000 1000 2000 1002 1000 1000 1000 1000 3000 1004 (36) 1000 1000 2200 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1001 1008 (37) 1000 1000 1000 1000 1000 1000 1000 1008 1008 1000 1000 1000 1000 1000 1001 (38) 1002 1001 1001 1000 1000 1000 1000 1000 1000 1000 1000 1000 1010 1095 1057 Palestinian Territories (39) 1000 1000 1000 2014 2000 2000 2000 1000 1000 1000 1000 1000 1000 1090 (40) 1000 1000 1000 1000 1000 1000 1000 1008 1000 1000 1000 1000 1000 1010 1000 (41) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1016 (42) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1042 (43) 1000 1000 1000 1000 1008 1008 1000 1000 1000 1000 1000 (44) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (45) 1001 1000 1000 1000 1000 1000 2000 1000 1000 1000 1000 1000 1000 1060 1019 (46) 1355 1010 1005 1011 1007 1013 2003 1021 2025 1011 1016 1005 1009 1031 1006

7 (47) 1000 1205 1005 1000 1010 1002 1002 2002 1001 1004 1003 1001 1047 1003 (48) 1200 1000 1000 1000 1000 1000 2000 1000 1000 1000 1000 1000 1000 2090 1000 (49) 1033 1000 1000 1000 1030 1000 2031 1030 1062 1062 1104 1109 1083 (50) 1023 1015 1016 1008 1000 1000 2000 1017 1000 1000 1039 1002 1012 2000 (51) 1410 1006 1038 1019 1000 1000 2000 1000 1000 1000 1000 1000 1000 2000 1000 (52) 1000 1000 1024 1000 1000 1000 1000 1000 1000 1000 1000 1600 1000 1000 1002 (53) 1001 1000 1000 1000 1000 1000 2504 1070 1000 (54) 1020 1020 1020 1020 1020 1600 1000 1100 1000 (55) 1028 750 750 750 1000 1008 500 2001 1007 1004 1001 1001 1042 1002 (56) 1000 1000 1000 1000 (57) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1002 1114 (60) 1500 1000 1004 1000 1000 1000 1000 2222 1003 (61) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1130 (62) 1000 1000 1984 2000 2000 1000 1008 1000 1000 1000 1000 1000 1100 (63) 1000 1000 1000 1000 1000 1000 1000 1000 (64) 1000 1000 1000 1000 1000 1000 1000 1008 1008 1000 1000 1000 1000 1000 (65) 1504 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (66) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (67) 1001 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1026 (68) 1100 1000 1000 1000 1000 1001 2000 1000 2000 1000 1000 1000 1015 1016 1005 Table 3: Number of ladder (WP16) observations for WP5-years - Part 3 Country/territory (ID) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Taiwan Province of China (69) 1002 1000 1000 1001 1000 1000 2000 1000 1000 1000 1000 1030 1000 (70) 1010 2000 1000 1000 2000 1000 1000 1000 1000 1000 1000 1127 (71) 1092 1114 1091 1077 1013 1007 1052 1032 1036 1034 1039 1053 1061 1128 (72) 1000 1000 1080 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1003 (73) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1000 (74) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1000 (75) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1000 (76) 2011 2949 2019 2042 4000 2000 3000 2000 2000 2000 2000 2000 2000 3003 2022 (77) 1102 1066 1074 1081 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1001 (78) 1000 1000 1000 1000 1000 1000 1008 1000 1000 1000 1000 1000 1000 (79) 1000 1000 1000 1000 1200 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (80) 1000 1000 1000 1000 1000 1008 1008 1000 1000 1000 1000 1133 (81) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1082 1004

8 (82) 1002 1002 1000 1000 1006 1000 1000 1000 1000 1000 1000 1000 1000 1000 (83) 981 1000 1000 1006 1029 1035 999 1000 999 1000 1000 1080 1000 (84) 1000 2001 2027 1002 1001 1016 1000 1100 (87) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1060 1000 (88) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 (89) 1004 1001 2000 1004 1001 1000 2000 1000 1000 1000 1000 1025 1000 (90) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 (92) 2128 2032 2010 1000 1002 1005 2004 1010 1064 1060 1009 (94) 502 504 (95) 1000 1020 1020 (96) 1000 1000 1003 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1001 (97) 2002 1002 1000 1009 1005 1010 1001 1000 1000 1000 1000 1080 1001 (99) 1003 2000 1006 1000 1000 1000 1000 1000 1000 1001 1080 1000 (100) 1000 1000 1000 1000 1000 (102) 1000 1000 1000 1000 1000 (103) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1111 (104) 1007 1023 1108 1009 1007 1009 1003 1001 1032 1040 1008 1040 1000 1060 1000 (105) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (106) 2000 2000 2000 1000 1000 1000 Congo (Kinshasa) (107) 1000 1000 1000 1000 1000 1000 1000 1000 Table 4: Number of ladder (WP16) observations for WP5-years - Part 4 Country/territory (ID) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Congo Brazzaville (108) 1000 1000 500 1000 1000 1000 1000 1000 1000 1090 (109) 1000 1009 1029 1029 1000 1000 1000 1000 1000 1000 1000 1080 1002 (110) 1000 Cyprus (111) 1000 502 1005 1005 500 500 2000 1029 1006 1008 1026 1043 1005 Djibouti (112) 1000 2000 1000 1000 (114) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1078 1000 (115) 1067 1061 1001 1000 1000 1003 1003 1000 1000 1000 1000 1000 1000 1000 1000 (116) 1000 1001 1000 1006 1001 1000 1000 1000 1000 1000 1000 1000 1000 1080 1000 (119) 1003 1001 601 608 1007 1004 1010 1000 1000 1000 1000 1000 1080 1000 (121) 1010 1005 1000 1000 1000 750 2001 1000 1000 1000 1000 1025 1000 (122) 1000 1000 1008 1008 1000 1000 1000 1000 1070 (124) 1021 1000 1000 1015 1014 1000 1000 1000 1000 1000 1000 1000 1000 1100 (125) 1000 1000 1008 1000 1000 1000 1000 1000 1140

9 (127) 501 (128) 505 500 504 504 504 504 504 504 504 504 500 (129) 1000 1000 1000 1002 1000 1002 1000 1000 1000 1000 1000 1000 1000 1000 (130) 502 1002 502 596 529 500 504 501 (131) 990 2001 2000 2000 2000 1003 2010 1009 1011 1000 2097 1000 Ireland (132) 1000 1001 500 1001 1000 1000 1000 2000 1000 1000 1000 1000 1025 1000 (134) 1000 1008 1000 1000 1000 1000 1000 1000 1021 (135) 543 506 504 504 504 501 (137) 1000 2002 2004 2000 1000 1008 1013 2000 1000 1000 2023 (138) 1000 1017 513 515 1006 1001 1000 1002 1001 1019 1002 1021 1080 1001 (139) 1000 1000 1000 1000 (140) 1000 1000 1000 1000 1000 1000 1000 1000 1000 (141) 1002 1006 1001 1007 1004 1040 (143) 1015 1007 506 500 1001 1000 1000 1000 1000 1000 1000 1000 1000 1080 1002 (144) 500 1002 1000 1001 500 2000 1000 1000 1000 1000 1025 (145) 1042 1008 1000 1018 1025 1020 1000 1024 1024 1008 1008 1080 1003 (146) 1012 1233 1000 1011 1000 1000 1000 1000 2008 1002 1000 1060 (147) 1000 (148) 508 1008 1004 1004 500 2013 1002 1011 1004 1010 1027 1001 (150) 1000 1000 1000 1000 1000 1059 1000 Table 5: Number of ladder (WP16) observations for WP5-years - Part 5 Country/territory (ID) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Mongolia (153) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1070 1000 (154) 834 1003 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 1004 (155) 1000 1000 1000 1005 1002 1000 (157) 1002 1000 1003 1002 1000 1000 2000 1050 1050 1000 1000 1000 1000 2095 (158) 1001 1000 1000 1012 1000 1003 1000 1000 1000 1000 1000 1000 1000 1080 (160) 1001 1000 1004 2000 1005 2000 1000 1000 1025 1000 (161) 2016 (163) 1005 1000 1004 1018 1000 1000 1001 1000 1000 1000 1000 1000 1000 1080 (164) 1001 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 2000 1079 (165) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 (166) 1007 1002 2002 1000 1001 1001 2020 1021 1008 1000 1003 1026 1002 (167) 500 500 (168) 2028 1000 1032 2000 1000

10 (173) 1556 1008 1000 1001 1023 1030 1000 1000 1000 1000 1000 1080 1002 (175) 1018 1007 1012 1007 1004 1000 1000 1000 1000 1000 1080 1001 (176) 1009 500 1002 1001 1000 1001 2020 1002 1000 1000 1000 1025 1001 (178) 1000 1000 1191 (181) 1784 1808 2000 1000 1000 (182) 504 (183) 1000 1000 1110 (184) 1000 1003 1000 2010 501 1000 1000 1000 1025 1000 (185) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 3000 1080 1000 (186) 1000 1000 1120 (187) 1000 1000 1000 1000 1000 1000 1000 1000 1130 (189) 508 502 504 504 504 (190) 1006 2085 2034 2053 1053 1056 1000 1001 1001 1001 1000 1003 (191) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1089 (193) 1013 2054 2066 2036 2016 1000 1002 2903 1855 1850 1857 1413 2928 (194) 1004 1004 1005 1000 1000 1000 1009 1000 1000 1000 1000 1000 1000 1080 1001 (195) 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1080 (197) 1000 2000 2000 2000 2000 1000 1000 1000 1000 1000 1000 1140 Kosovo (198) 1046 1047 1000 1017 1047 1024 1000 1001 1000 1000 1000 1000 1088 1000 region (199) 2000 2000 2000 1000 (202) 500 502 2004 1000 1000 1000 1050 (205) 1000 1000 1000 1000 Figure 1: County-by-country trajectory plots - part 1

Afghanistan Albania Algeria 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Angola Argentina Armenia 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Australia Austria Azerbaijan 8 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Bahrain Bangladesh Belarus 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Belgium Belize Benin 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Bhutan Bolivia Bosnia and Herzegovina 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Botswana Brazil Bulgaria 6 8 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Burkina Faso Burundi Cambodia 5 4 5 4 4 3 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Cameroon Canada Central African Republic 6 8 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Chad Chile China 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

11 Figure 2: County-by-country trajectory plots - part 2

Colombia Comoros Congo (Brazzaville) 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Congo (Kinshasa) Costa Rica Croatia 5 8 6 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Cuba Cyprus Czech Republic 6 8 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Denmark Djibouti Dominican Republic 6 8 5 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Ecuador Egypt El Salvador 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Estonia Ethiopia Finland 5 8 6 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

France Gabon Gambia 8 5 5 6 4 4 4 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Georgia Germany Ghana 8 6 5 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Greece Guatemala Guinea 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Guyana Haiti Honduras 6 5 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

12 Figure 3: County-by-country trajectory plots - part 3

Hong Kong S.A.R. of China Hungary Iceland 6 8 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

India Indonesia Iran 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Iraq Ireland Israel 8 8 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Italy Ivory Coast Jamaica 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Japan Jordan Kazakhstan 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Kenya Kosovo Kuwait 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Kyrgyzstan Laos Latvia 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Lebanon Lesotho Liberia 6 5 5 4 4 4 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Libya Lithuania Luxembourg 6 8 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Madagascar Malawi Malaysia 5 5 6 4 4 4 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

13 Figure 4: County-by-country trajectory plots - part 4

Maldives Mali Malta 5 8 5 4 6 4 3 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Mauritania Mauritius 5 8 6 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Moldova Montenegro 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Morocco Mozambique Myanmar 6 5 5 4 4 4 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Namibia Nepal Netherlands 5 6 8 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

New Zealand Nicaragua Niger 8 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Nigeria North Cyprus North Macedonia 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Norway Oman Pakistan 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Palestinian Territories Panama Paraguay 5 8 6 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Peru Philippines Poland 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

14 Figure 5: County-by-country trajectory plots - part 5

Portugal Qatar Romania 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Russia Rwanda Saudi Arabia 8 6 4 6 4 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Senegal Serbia Sierra Leone 6 5 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Singapore Slovakia Slovenia 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Somalia Somaliland region South Africa 6 6 5 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

South Korea South Sudan Spain 8 8 4 6 6 3 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Sri Lanka Sudan Suriname 5 5 6 4 4 4 3 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Swaziland Sweden Switzerland 5 8 8 4 6 6 3 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Syria Taiwan Province of China Tajikistan 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Tanzania Thailand Togo 8 4 4 6 3 3 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

15 Figure 6: County-by-country trajectory plots - part 6

Trinidad and Tobago Tunisia Turkey 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Turkmenistan Uganda Ukraine 5 6 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

United Arab Emirates United Kingdom 8 8 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Uruguay Uzbekistan Venezuela 8 6 6 6 4 4 4 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Vietnam Yemen Zambia 6 5 6 4 4 4 3 2 2 2 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020 2006 2008 2010 2012 2014 2016 2018 2020

Zimbabwe 5 4 3 2 2006 2008 2010 2012 2014 2016 2018 2020

16 Table 6: Summary statistics for country-year observations with valid happiness scores - Fullest sample Variable Mean Std. Dev. Min. Max. N Life Ladder 5.47 1.12 2.38 8.02 1949 Positive affect 0.71 0.11 0.32 0.94 1927 Negative affect 0.27 0.09 0.08 0.70 1933 Log GDP per capita 9.37 1.15 6.64 11.65 1913 Social support 0.81 0.12 0.29 0.99 1936 Healthy life expectancy at birth 63.36 7.51 32.3 77.10 1894 Freedom to make life choices 0.74 0.14 0.26 0.99 1917 Generosity 0 0.16 -0.34 0.70 1860 Perceptions of corruption 0.75 0.19 0.04 0.98 1839

Table 7: Summary statistics for country-year observations with valid happiness scores - Period from 2005 to 2008 Variable Mean Std. Dev. Min. Max. N Life Ladder 5.44 1.13 2.81 8.02 328 Positive affect 0.71 0.1 0.36 0.89 324 Negative affect 0.25 0.07 0.09 0.47 326 Log GDP per capita 9.21 1.19 6.68 11.37 327 Social support 0.81 0.13 0.29 0.98 326 Healthy life expectancy at birth 61.45 8.42 40.3 74.2 324 Freedom to make life choices 0.71 0.15 0.26 0.97 319 Generosity 0.02 0.17 -0.31 0.48 293 Perceptions of corruption 0.77 0.18 0.06 0.98 313

17 Table 8: Summary statistics for country-year observations with valid happiness scores - Period from 2008 to 2010 Variable Mean Std. Dev. Min. Max. N Life Ladder 5.46 1.11 2.81 7.97 348 Positive affect 0.71 0.11 0.36 0.9 341 Negative affect 0.24 0.08 0.08 0.47 343 Log GDP per capita 9.27 1.17 6.72 11.59 346 Social support 0.81 0.12 0.29 0.98 343 Healthy life expectancy at birth 62.28 7.96 32.3 74.8 340 Freedom to make life choices 0.70 0.15 0.26 0.97 341 Generosity 0.01 0.16 -0.31 0.54 345 Perceptions of corruption 0.76 0.19 0.04 0.98 337

Table 9: Summary statistics for country-year observations with valid happiness scores - Period from 2017 to 2019 Variable Mean Std. Dev. Min. Max. N Life Ladder 5.51 1.11 2.38 7.86 433 Positive affect 0.71 0.11 0.32 0.9 429 Negative affect 0.29 0.09 0.09 0.6 429 Log GDP per capita 9.43 1.16 6.64 11.65 420 Social support 0.81 0.12 0.32 0.98 432 Healthy life expectancy at birth 64.55 6.83 45.2 77.10 420 Freedom to make life choices 0.79 0.12 0.37 0.99 430 Generosity -0.02 0.16 -0.34 0.65 418 Perceptions of corruption 0.73 0.18 0.07 0.96 407

Table 10: Summary statistics for country-year observations with valid happiness scores - Period from 2018 to 2020 Variable Mean Std. Dev. Min. Max. N Life Ladder 5.61 1.08 2.38 7.89 381 Positive affect 0.71 0.1 0.32 0.89 377 Negative affect 0.29 0.09 0.08 0.54 377 Log GDP per capita 9.52 1.11 6.64 11.65 362 Social support 0.82 0.11 0.42 0.98 381 Healthy life expectancy at birth 65.36 6.56 48.2 77.10 369 Freedom to make life choices 0.8 0.11 0.37 0.97 378 Generosity -0.02 0.15 -0.34 0.56 361 Perceptions of corruption 0.72 0.19 0.07 0.96 359

18 Table 11: Regressions to Explain Average Happiness across Countries (Pooled OLS with year fixed effects)

Ladder PosAffect NegAffect LadderAgain (1) (2) (3) (4) Log GDP per capita 0.349 -.013 0.004 0.372 (0.07)∗∗∗ (0.01) (0.008) (0.069)∗∗∗ Social support 2.253 0.252 -.322 1.903 (0.359)∗∗∗ (0.047)∗∗∗ (0.051)∗∗∗ (0.374)∗∗∗ Healthy life expectancy at birth 0.031 0.001 0.002 0.028 (0.01)∗∗∗ (0.001) (0.001)∗∗ (0.01)∗∗∗ Freedom to make life choices 1.217 0.369 -.081 0.54 (0.3)∗∗∗ (0.041)∗∗∗ (0.041)∗∗ (0.291)∗ Generosity 0.652 0.132 0.025 0.387 (0.269)∗∗ (0.029)∗∗∗ (0.027) (0.266) Perceptions of corruption -.638 0.019 0.099 -.714 (0.285)∗∗ (0.026) (0.023)∗∗∗ (0.277)∗∗∗ Positive affect 1.936 (0.345)∗∗∗ Negative affect 0.419 (0.412) Year 2005 0.414 -.011 0.024 0.428 (0.083)∗∗∗ (0.009) (0.008)∗∗∗ (0.081)∗∗∗ Year 2006 -.007 0.011 -.003 -.018 (0.059) (0.009) (0.009) (0.059) Year 2007 0.24 0.017 -.029 0.226 (0.061)∗∗∗ (0.009)∗∗ (0.007)∗∗∗ (0.06)∗∗∗ Year 2008 0.336 0.023 -.041 0.315 (0.058)∗∗∗ (0.008)∗∗∗ (0.007)∗∗∗ (0.062)∗∗∗ Year 2009 0.23 0.017 -.024 0.21 (0.057)∗∗∗ (0.008)∗∗ (0.008)∗∗∗ (0.057)∗∗∗ Year 2010 0.147 0.012 -.028 0.138 (0.047)∗∗∗ (0.007)∗ (0.006)∗∗∗ (0.048)∗∗∗ Year 2011 0.162 0.002 -.023 0.172 (0.048)∗∗∗ (0.008) (0.006)∗∗∗ (0.05)∗∗∗ Year 2012 0.135 0.013 -.017 0.12 (0.041)∗∗∗ (0.007)∗∗ (0.006)∗∗∗ (0.044)∗∗∗ Year 2013 0.032 0.01 -.008 0.019 (0.04) (0.005)∗ (0.006) (0.041) Year 2015 -.002 -.003 0.002 0.006 (0.04) (0.005) (0.004) (0.039) Year 2016 -.036 -.005 0.015 -.029 (0.048) (0.005) (0.005)∗∗∗ (0.046) Year 2017 0.04 -.014 0.02 0.062 (0.055) (0.006)∗∗ (0.006)∗∗∗ (0.052) Year 2018 0.072 -.009 0.023 0.084 (0.062) (0.007) (0.007)∗∗∗ (0.059) Year 2019 0.047 -.011 0.022 0.062 (0.064) (0.007) (0.007)∗∗∗ (0.062) Year 2020 0.057 -.022 0.03 0.091 (0.073) (0.008)∗∗∗ (0.007)∗∗∗ (0.07) Obs. 1712 1709 1711 1708 e(N-clust) 155 155 155 155 e(r2-a) 0.757 0.472 0.297 0.774

Notes: 1). Standard errors in parentheses. *, **, and *** indicate statistical significance at 10 percent, 5 percent and 1 percent levels. All standard errors are cluster-adjusted at the country level. The row “e(N-clust)” indicates the number of countries. 2). See section “Data Sources and Variable Definitions” for more information. 19 Table 12: Regressions to Explain Average Happiness across Countries (Pooled OLS without year fixed effects)

Ladder PosAffect NegAffect LadderAgain (1) (2) (3) (4) Log GDP per capita 0.361 -.011 0.0005 0.382 (0.069)∗∗∗ (0.01) (0.008) (0.068)∗∗∗ Social support 2.310 0.268 -.346 1.844 (0.354)∗∗∗ (0.045)∗∗∗ (0.05)∗∗∗ (0.37)∗∗∗ Healthy life expectancy at birth 0.029 0.0009 0.003 0.027 (0.01)∗∗∗ (0.001) (0.001)∗∗∗ (0.01)∗∗∗ Freedom to make life choices 1.056 0.34 -.032 0.39 (0.277)∗∗∗ (0.037)∗∗∗ (0.037) (0.27) Generosity 0.702 0.142 0.007 0.42 (0.265)∗∗∗ (0.028)∗∗∗ (0.027) (0.264) Perceptions of corruption -.649 0.017 0.102 -.700 (0.279)∗∗ (0.026) (0.023)∗∗∗ (0.275)∗∗ Positive affect 1.988 (0.355)∗∗∗ Negative affect 0.185 (0.385) year-1

year-2

year-3

year-4

year-5

year-6

year-7

year-8

year-9

year-11

year-12

year-13

year-14

year-15

year-16

Obs. 1712 1709 1711 1708 e(N-clust) 155 155 155 155 e(r2-a) 0.752 0.465 0.245 0.77

Notes: 1). Standard errors in parentheses. *, **, and *** indicate statistical significance at 10 percent, 5 percent and 1 percent levels. All standard errors are cluster-adjusted at the country level. The row “e(N-clust)” indicates the number of countries. 2). See section “Data Sources and Variable Definitions” for more information. 20 Figure 7: Ranking of Happiness: 2018-2020 (Part 1); those with a * before ranking do not have 2020 information

1. Finland(7.842) 2. Denmark(7.620) 3. Switzerland(7.571) 4. Iceland(7.554) 5. Netherlands(7.464) 6. Norway(7.392) 7. Sweden(7.363) *8. Luxembourg(7.324) 9. New Zealand(7.277) 10. Austria(7.268) 11. Australia(7.183) 12. Israel(7.157) 13. Germany(7.155) 14. Canada(7.103) 15. Ireland(7.085) *16. Costa Rica(7.069) 17. United Kingdom(7.064) 18. Czech Republic(6.965) 19. United States(6.951) 20. Belgium(6.834) 21. France(6.690) 22. Bahrain(6.647) 23. Malta(6.602) 24. Taiwan Province of China(6.584) 25. United Arab Emirates(6.561) 26. Saudi Arabia(6.494) 27. Spain(6.491) 28. Italy(6.483) 29. Slovenia(6.461) *30. Guatemala(6.435) 31. Uruguay(6.431) *32. Singapore(6.377) 33. Kosovo(6.372) 34. Slovakia(6.331) 35. Brazil(6.330) 36. Mexico(6.317) *37. Jamaica(6.309) 38. Lithuania(6.255) 39. Cyprus(6.223) 40. Estonia(6.189) *41. Panama(6.180) *42. Uzbekistan(6.179) 43. Chile(6.172) 44. Poland(6.166) 45. Kazakhstan(6.152) *46. Romania(6.140) *47. Kuwait(6.106) 48. Serbia(6.078) 49. El Salvador(6.061) 50. Mauritius(6.049) 51. Latvia(6.032) 52. Colombia(6.012) 53. Hungary(5.992)

0 1 2 3 4 5 6 7 8

Dystopia (happiness=2.43) Dystopia + residual Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption 95% confidence interval

21 Figure 8: Ranking of Happiness: 2018-2020 (Part 2); those with a * before ranking do not have 2020 information

54. Thailand(5.985) *55. Nicaragua(5.972) 56. Japan(5.940) 57. Argentina(5.929) 58. Portugal(5.929) *59. Honduras(5.919) 60. Croatia(5.882) 61. Philippines(5.880) 62. South Korea(5.845) *63. Peru(5.840) 64. Bosnia and Herzegovina(5.813) 65. Moldova(5.766) 66. Ecuador(5.764) 67. Kyrgyzstan(5.744) 68. Greece(5.723) 69. Bolivia(5.716) 70. Mongolia(5.677) *71. Paraguay(5.653) 72. Montenegro(5.581) 73. Dominican Republic(5.545) *74. North Cyprus(5.536) *75. Belarus(5.534) 76. Russia(5.477) 77. Hong Kong S.A.R. of China(5.477) 78. Tajikistan(5.466) *79. Vietnam(5.411) *80. Libya(5.410) *81. Malaysia(5.384) *82. Indonesia(5.345) *83. Congo (Brazzaville)(5.342) 84. China(5.339) 85. Ivory Coast(5.306) *86. Armenia(5.283) *87. Nepal(5.269) 88. Bulgaria(5.266) *89. Maldives(5.198) *90. Azerbaijan(5.171) 91. Cameroon(5.142) *92. Senegal(5.132) 93. Albania(5.117) 94. North Macedonia(5.101) 95. Ghana(5.088) *96. Niger(5.074) *97. Turkmenistan(5.066) *98. Gambia(5.051) 99. Benin(5.045) 100. Laos(5.030) 101. Bangladesh(5.025) *102. Guinea(4.984) 103. South Africa(4.956) 104. Turkey(4.948) *105. Pakistan(4.934) 106. Morocco(4.918)

0 1 2 3 4 5 6 7 8

Dystopia (happiness=2.43) Dystopia + residual Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption 95% confidence interval

22 Figure 9: Ranking of Happiness: 2018-2020 (Part 3); those with a * before ranking do not have 2020 information

107. Venezuela(4.892) 108. Georgia(4.891) *109. Algeria(4.887) 110. Ukraine(4.875) 111. Iraq(4.854) *112. Gabon(4.852) *113. Burkina Faso(4.834) 114. Cambodia(4.830) *115. Mozambique(4.794) 116. Nigeria(4.759) *117. Mali(4.723) 118. Iran(4.721) 119. Uganda(4.636) *120. Liberia(4.625) 121. Kenya(4.607) 122. Tunisia(4.596) *123. Lebanon(4.584) 124. Namibia(4.574) *125. Palestinian Territories(4.517) 126. Myanmar(4.426) 127. Jordan(4.395) *128. Chad(4.355) *129. Sri Lanka(4.325) *130. Swaziland(4.308) *131. Comoros(4.289) 132. Egypt(4.283) 133. Ethiopia(4.275) *134. Mauritania(4.227) *135. Madagascar(4.208) *136. Togo(4.107) 137. Zambia(4.073) *138. Sierra Leone(3.849) 139. India(3.819) *140. Burundi(3.775) *141. Yemen(3.658) 142. Tanzania(3.623) *143. Haiti(3.615) *144. Malawi(3.600) *145. Lesotho(3.512) *146. Botswana(3.467) *147. Rwanda(3.415) 148. Zimbabwe(3.145) *149. Afghanistan(2.523)

0 1 2 3 4 5 6 7 8

Dystopia (happiness=2.43) Dystopia + residual Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption 95% confidence interval

23 Figure 10: Ranking of Happiness: 2018-2020 (Part 1); those with a * before ranking do not have 2020 information

1. Finland(7.842) 2. Denmark(7.620) 3. Switzerland(7.571) 4. Iceland(7.554) 5. Netherlands(7.464) 6. Norway(7.392) 7. Sweden(7.363) *8. Luxembourg(7.324) 9. New Zealand(7.277) 10. Austria(7.268) 11. Australia(7.183) 12. Israel(7.157) 13. Germany(7.155) 14. Canada(7.103) 15. Ireland(7.085) *16. Costa Rica(7.069) 17. United Kingdom(7.064) 18. Czech Republic(6.965) 19. United States(6.951) 20. Belgium(6.834) 21. France(6.690) 22. Bahrain(6.647) 23. Malta(6.602) 24. Taiwan Province of China(6.584) 25. United Arab Emirates(6.561) 26. Saudi Arabia(6.494) 27. Spain(6.491) 28. Italy(6.483) 29. Slovenia(6.461) *30. Guatemala(6.435) 31. Uruguay(6.431) *32. Singapore(6.377) 33. Kosovo(6.372) 34. Slovakia(6.331) 35. Brazil(6.330) 36. Mexico(6.317) *37. Jamaica(6.309) 38. Lithuania(6.255) 39. Cyprus(6.223) 40. Estonia(6.189) *41. Panama(6.180) *42. Uzbekistan(6.179) 43. Chile(6.172) 44. Poland(6.166) 45. Kazakhstan(6.152) *46. Romania(6.140) *47. Kuwait(6.106) 48. Serbia(6.078) 49. El Salvador(6.061) 50. Mauritius(6.049) 51. Latvia(6.032) 52. Colombia(6.012) 53. Hungary(5.992)

0 1 2 3 4 5 6 7 8

Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption Dystopia (2.43) + residual 95% confidence interval

24 Figure 11: Ranking of Happiness: 2018-2020 (Part 2); those with a * before ranking do not have 2020 information

54. Thailand(5.985) *55. Nicaragua(5.972) 56. Japan(5.940) 57. Argentina(5.929) 58. Portugal(5.929) *59. Honduras(5.919) 60. Croatia(5.882) 61. Philippines(5.880) 62. South Korea(5.845) *63. Peru(5.840) 64. Bosnia and Herzegovina(5.813) 65. Moldova(5.766) 66. Ecuador(5.764) 67. Kyrgyzstan(5.744) 68. Greece(5.723) 69. Bolivia(5.716) 70. Mongolia(5.677) *71. Paraguay(5.653) 72. Montenegro(5.581) 73. Dominican Republic(5.545) *74. North Cyprus(5.536) *75. Belarus(5.534) 76. Russia(5.477) 77. Hong Kong S.A.R. of China(5.477) 78. Tajikistan(5.466) *79. Vietnam(5.411) *80. Libya(5.410) *81. Malaysia(5.384) *82. Indonesia(5.345) *83. Congo (Brazzaville)(5.342) 84. China(5.339) 85. Ivory Coast(5.306) *86. Armenia(5.283) *87. Nepal(5.269) 88. Bulgaria(5.266) *89. Maldives(5.198) *90. Azerbaijan(5.171) 91. Cameroon(5.142) *92. Senegal(5.132) 93. Albania(5.117) 94. North Macedonia(5.101) 95. Ghana(5.088) *96. Niger(5.074) *97. Turkmenistan(5.066) *98. Gambia(5.051) 99. Benin(5.045) 100. Laos(5.030) 101. Bangladesh(5.025) *102. Guinea(4.984) 103. South Africa(4.956) 104. Turkey(4.948) *105. Pakistan(4.934) 106. Morocco(4.918)

0 1 2 3 4 5 6 7 8

Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption Dystopia (2.43) + residual 95% confidence interval

25 Figure 12: Ranking of Happiness: 2018-2020 (Part 3); those with a * before ranking do not have 2020 information

107. Venezuela(4.892) 108. Georgia(4.891) *109. Algeria(4.887) 110. Ukraine(4.875) 111. Iraq(4.854) *112. Gabon(4.852) *113. Burkina Faso(4.834) 114. Cambodia(4.830) *115. Mozambique(4.794) 116. Nigeria(4.759) *117. Mali(4.723) 118. Iran(4.721) 119. Uganda(4.636) *120. Liberia(4.625) 121. Kenya(4.607) 122. Tunisia(4.596) *123. Lebanon(4.584) 124. Namibia(4.574) *125. Palestinian Territories(4.517) 126. Myanmar(4.426) 127. Jordan(4.395) *128. Chad(4.355) *129. Sri Lanka(4.325) *130. Swaziland(4.308) *131. Comoros(4.289) 132. Egypt(4.283) 133. Ethiopia(4.275) *134. Mauritania(4.227) *135. Madagascar(4.208) *136. Togo(4.107) 137. Zambia(4.073) *138. Sierra Leone(3.849) 139. India(3.819) *140. Burundi(3.775) *141. Yemen(3.658) 142. Tanzania(3.623) *143. Haiti(3.615) *144. Malawi(3.600) *145. Lesotho(3.512) *146. Botswana(3.467) *147. Rwanda(3.415) 148. Zimbabwe(3.145) *149. Afghanistan(2.523)

0 1 2 3 4 5 6 7 8

Explained by: GDP per capita Explained by: social support Explained by: healthy life expectancy Explained by: freedom to make life choices Explained by: generosity Explained by: perceptions of corruption Dystopia (2.43) + residual 95% confidence interval

26 Table 13: Countries that used imputed corrupt based on WGI control of corruption indicators Country name Imputation indicator: corrupt is imputed based on WGI’s control of corruption in

Egypt 1 Saudi Arabia 1 Jordan 1 China 1 Bahrain 1 Kuwait 1 Maldives 1 Turkmenistan 1 United Arab Emirates 1

Ranking of the Six Factors Used to Explain Happiness Scores The next set of figures are rankings of countries by the six underlying factors used to explain international differences in happiness scores, namely GDP per person, healthy life expectancy, social support, perceived freedom to make life choice, generosity and perception of corruption. The rankings are based on national averages over the period from 2018 to 2020. The ranking figures do not show imputed data. As we explain when describing our imputation algorithm, we do not use the imputed values in any of our headline results including the happiness rankings. The only place where we use them is when we try to decompose a country’s average happiness score into com- ponents explained by the six factors. The imputation involves only a small number of countries. Here, we avoid relying on the imputation to generate the rankings. If a country is missing the information about corruption perceptions, for example, they won’t show up in the corruption ranking, thus the ranking for corruption will cover a smaller number of countries than the ranking of overall happiness.

27 Figure 13: Ranking of Natural Log of Per-Capita GDP: 2018-2020; bars show natural logs, dollar values are shown on the Y axis after country names (Part 1)

1. Luxembourg(114,298) 2. Singapore( 97,539) 3. Ireland( 84,313) 4. Switzerland( 67,330) 5. United Arab Emirates( 65,179) 6. Norway( 63,141) 7. United States( 61,276) 8. Hong Kong S.A.R. of China( 59,893) 9. Denmark( 56,004) 10. Netherlands( 55,928) 11. Austria( 54,520) 12. Iceland( 52,985) 13. Germany( 52,709) 14. Sweden( 52,417) 15. Belgium( 50,165) 16. Kuwait( 49,846) 17. Australia( 48,806) 18. Canada( 47,864) 19. Finland( 47,820) 20. Saudi Arabia( 46,282) 21. United Kingdom( 44,674) 22. France( 44,529) 23. Malta( 43,203) 24. Bahrain( 42,985) 25. South Korea( 42,223) 26. New Zealand( 41,886) 27. Italy( 41,064) 28. Japan( 40,596) 29. Cyprus( 39,184) 30. Israel( 39,134) 31. Spain( 38,982) 32. Czech Republic( 38,413) 33. Slovenia( 37,398) 34. Lithuania( 36,269) 35. Estonia( 35,638) 36. Portugal( 33,564) 37. Poland( 32,273) 38. Slovakia( 31,855) 39. Hungary( 31,515) 40. Panama( 31,262) 41. Latvia( 30,175) 42. Romania( 29,253) 43. Greece( 29,109) 44. Turkey( 28,014) 45. Malaysia( 27,950) 46. Croatia( 27,370) 47. Russia( 26,602) 48. Kazakhstan( 25,713) 49. Chile( 23,649) 50. Bulgaria( 22,372) 51. Mauritius( 22,206) 52. Uruguay( 21,281) 53. Argentina( 21,197)

5 6 7 8 9 10 11 12 Natural log of GDP per capita

28 Figure 14: Ranking of Natural Log of Per-Capita GDP: 2018-2020; bars show natural logs, dollar values are shown on the Y axis after country names (Part 2)

54. Montenegro( 20,743) 55. Costa Rica( 19,534) 56. Mexico( 19,128) 57. Belarus( 19,020) 58. Maldives( 18,509) 59. Thailand( 18,118) 60. Dominican Republic( 18,076) 61. Serbia( 17,794) 62. Botswana( 17,704) 63. North Macedonia( 16,207) 64. China( 15,886) 65. Turkmenistan( 15,204) 66. Lebanon( 15,149) 67. Libya( 15,098) 68. Gabon( 14,809) 69. Bosnia and Herzegovina( 14,618) 70. Georgia( 14,539) 71. Brazil( 14,433) 72. Azerbaijan( 14,310) 73. Colombia( 14,143) 74. Albania( 13,636) 75. Armenia( 13,192) 76. Sri Lanka( 12,970) 77. Peru( 12,815) 78. Moldova( 12,758) 79. Paraguay( 12,685) 80. Ukraine( 12,532) 81. South Africa( 12,120) 82. Mongolia( 12,091) 83. Egypt( 11,692) 84. Indonesia( 11,670) 85. Algeria( 11,411) 86. Kosovo( 11,139) 87. Ecuador( 11,080) 88. Tunisia( 10,570) 89. Iraq( 10,302) 90. Jamaica( 9,761) 91. Jordan( 9,722) 92. Namibia( 9,514) 93. Philippines( 8,739) 94. Swaziland( 8,649) 95. El Salvador( 8,551) 96. Guatemala( 8,548) 97. Bolivia( 8,482) 98. Vietnam( 7,888) 99. Laos( 7,688) 100. Morocco( 7,352) 101. Uzbekistan( 6,880) 102. India( 6,343) 103. Honduras( 5,700) 104. Nicaragua( 5,543) 105. Ghana( 5,325) 106. Ivory Coast( 5,172)

5 6 7 8 9 10 11 12 Natural log of GDP per capita

29 Figure 15: Ranking of Natural Log of Per-Capita GDP: 2018-2020; bars show natural logs, dollar values are shown on the Y axis after country names (Part 3)

107. Mauritania( 5,125) 108. Myanmar( 5,120) 109. Kyrgyzstan( 5,108) 110. Nigeria( 5,078) 111. Pakistan( 4,714) 112. Bangladesh( 4,695) 113. Kenya( 4,276) 114. Cambodia( 4,274) 115. Cameroon( 3,601) 116. Zambia( 3,448) 117. Nepal( 3,361) 118. Senegal( 3,355) 119. Congo (Brazzaville)( 3,352) 120. Tajikistan( 3,264) 121. Benin( 3,252) 122. Comoros( 3,074) 123. Zimbabwe( 2,815) 124. Lesotho( 2,768) 125. Tanzania( 2,632) 126. Guinea( 2,534) 127. Mali( 2,307) 128. Afghanistan( 2,197) 129. Ethiopia( 2,194) 130. Gambia( 2,177) 131. Burkina Faso( 2,160) 132. Uganda( 2,159) 133. Rwanda( 2,156) 134. Haiti( 1,767) 135. Sierra Leone( 1,692) 136. Madagascar( 1,630) 137. Chad( 1,578) 138. Togo( 1,576) 139. Liberia( 1,462) 140. Mozambique( 1,285) 141. Niger( 1,209) 142. Malawi( 1,051) 143. Burundi( 762)

5 6 7 8 9 10 11 12 Natural log of GDP per capita

30 Figure 16: Ranking of Social Support: 2018-2020 (Part 1)

1. Iceland(0.983) 2. Turkmenistan(0.983) 3. Norway(0.954) 4. Denmark(0.954) 5. Finland(0.954) 6. Kazakhstan(0.952) 7. New Zealand(0.948) 8. Slovenia(0.948) 9. Ireland(0.947) 10. Czech Republic(0.947) 11. Hungary(0.943) 12. France(0.942) 13. Switzerland(0.942) 14. Netherlands(0.942) 15. Estonia(0.941) 16. Australia(0.940) 17. Israel(0.939) 18. Slovakia(0.936) 19. Lithuania(0.935) 20. Mongolia(0.935) 21. Austria(0.934) 22. United Kingdom(0.934) 23. Sweden(0.934) 24. Spain(0.932) 25. Malta(0.931) 26. Bulgaria(0.931) 27. Latvia(0.927) 28. Canada(0.926) 29. Uruguay(0.925) 30. Croatia(0.924) 31. United States(0.920) 32. Uzbekistan(0.918) 33. Singapore(0.915) 34. Maldives(0.913) 35. Belarus(0.910) 36. Luxembourg(0.908) 37. Belgium(0.906) 38. Mauritius(0.905) 39. Germany(0.903) 40. Russia(0.903) 41. Poland(0.898) 42. Taiwan Province of China(0.898) 43. Argentina(0.898) 44. Panama(0.896) 45. Kyrgyzstan(0.893) 46. Paraguay(0.893) 47. Costa Rica(0.891) 48. Saudi Arabia(0.891) 49. Ukraine(0.888) 50. Thailand(0.888) 51. Japan(0.884) 52. Chile(0.882) 53. Brazil(0.882)

0 1

Social support 95% confidence interval

31 Figure 17: Ranking of Social Support: 2018-2020 (Part 2)

54. Italy(0.880) 55. Portugal(0.879) 56. Jamaica(0.877) 57. Serbia(0.873) 58. Bosnia and Herzegovina(0.870) 59. Nicaragua(0.864) 60. Bahrain(0.862) 61. Venezuela(0.861) 62. Tajikistan(0.860) 63. South Africa(0.860) 64. Montenegro(0.858) 65. Moldova(0.857) 66. Dominican Republic(0.853) 67. Vietnam(0.850) 68. Lebanon(0.848) 69. Colombia(0.847) 70. United Arab Emirates(0.844) 71. Kuwait(0.843) 72. Azerbaijan(0.836) 73. Hong Kong S.A.R. of China(0.836) 74. Peru(0.832) 75. Romania(0.832) 76. Yemen(0.832) 77. Mexico(0.831) 78. Philippines(0.830) 79. Libya(0.827) 80. Sri Lanka(0.827) 81. Palestinian Territories(0.826) 82. Greece(0.823) 83. Turkey(0.822) 84. Kosovo(0.821) 85. Ecuador(0.821) 86. North Cyprus(0.820) 87. Namibia(0.818) 88. Malaysia(0.817) 89. Guatemala(0.813) 90. Honduras(0.812) 91. Indonesia(0.811) 92. China(0.811) 93. Bolivia(0.810) 94. North Macedonia(0.805) 95. Cyprus(0.802) 96. Algeria(0.802) 97. South Korea(0.799) 98. Armenia(0.799) 99. Mauritania(0.795) 100. Lesotho(0.787) 101. Botswana(0.784) 102. Uganda(0.781) 103. Myanmar(0.779) 104. Gabon(0.776) 105. Nepal(0.774) 106. Swaziland(0.770)

0 1

Social support 95% confidence interval

32 Figure 18: Ranking of Social Support: 2018-2020 (Part 3)

107. Jordan(0.767) 108. Cambodia(0.765) 109. Ethiopia(0.764) 110. El Salvador(0.762) 111. Zimbabwe(0.750) 112. Egypt(0.750) 113. Iraq(0.746) 114. Mozambique(0.744) 115. Nigeria(0.740) 116. Laos(0.728) 117. Ghana(0.727) 118. Mali(0.724) 119. Liberia(0.720) 120. Senegal(0.710) 121. Iran(0.710) 122. Cameroon(0.710) 123. Zambia(0.708) 124. Tanzania(0.702) 125. Albania(0.697) 126. Bangladesh(0.693) 127. Tunisia(0.691) 128. Gambia(0.690) 129. Kenya(0.688) 130. Madagascar(0.686) 131. Burkina Faso(0.672) 132. Georgia(0.671) 133. Pakistan(0.651) 134. Ivory Coast(0.644) 135. Niger(0.641) 136. Guinea(0.639) 137. Congo (Brazzaville)(0.636) 138. Sierra Leone(0.630) 139. Comoros(0.626) 140. Chad(0.619) 141. India(0.603) 142. Togo(0.569) 143. Morocco(0.560) 144. Rwanda(0.552) 145. Haiti(0.540) 146. Malawi(0.537) 147. Burundi(0.490) 148. Benin(0.489) 149. Afghanistan(0.463)

0 1

Social support 95% confidence interval

33 Figure 19: Ranking of Healthy Life Expectancy: 2018-2020 (Part 1)

1. Singapore(76.953) 2. Japan(75.100) 3. Spain(74.700) 4. Switzerland(74.400) 5. France(74.000) 6. Australia(73.900) 7. South Korea(73.900) 8. Cyprus(73.898) 9. Italy(73.800) 10. Canada(73.800) 11. Israel(73.503) 12. New Zealand(73.400) 13. Norway(73.300) 14. Austria(73.300) 15. Iceland(73.000) 16. Sweden(72.700) 17. Denmark(72.700) 18. Greece(72.600) 19. Luxembourg(72.600) 20. Portugal(72.600) 21. Germany(72.500) 22. United Kingdom(72.500) 23. Netherlands(72.400) 24. Ireland(72.400) 25. Malta(72.200) 26. Belgium(72.199) 27. Finland(72.000) 28. Costa Rica(71.400) 29. Slovenia(71.400) 30. Czech Republic(70.807) 31. Croatia(70.799) 32. Maldives(70.600) 33. Chile(70.000) 34. Poland(69.702) 35. Panama(69.652) 36. China(69.593) 37. Bahrain(69.495) 38. Slovakia(69.201) 39. Uruguay(69.100) 40. Argentina(69.000) 41. Albania(68.999) 42. Ecuador(68.800) 43. Estonia(68.800) 44. Montenegro(68.699) 45. Serbia(68.600) 46. Mexico(68.597) 47. Peru(68.250) 48. United States(68.200) 49. Bosnia and Herzegovina(68.098) 50. Vietnam(68.034) 51. Colombia(68.001) 52. Hungary(68.000) 53. Lithuania(67.906)

0 10 20 30 40 50 60 70 80 90 100 Healthy Life Expectancy

34 Figure 20: Ranking of Healthy Life Expectancy: 2018-2020 (Part 2)

54. Nicaragua(67.657) 55. Jamaica(67.500) 56. Thailand(67.401) 57. Lebanon(67.355) 58. Romania(67.355) 59. United Arab Emirates(67.333) 60. Honduras(67.300) 61. Sri Lanka(67.299) 62. Tunisia(67.201) 63. Turkey(67.199) 64. Malaysia(67.102) 65. Latvia(67.100) 66. Armenia(67.055) 67. Jordan(67.000) 68. Bulgaria(67.000) 69. Kuwait(66.900) 70. Mauritius(66.701) 71. Venezuela(66.700) 72. Saudi Arabia(66.603) 73. Brazil(66.601) 74. El Salvador(66.402) 75. Iran(66.300) 76. Belarus(66.253) 77. Morocco(66.208) 78. Dominican Republic(66.102) 79. Algeria(66.005) 80. Paraguay(65.900) 81. Moldova(65.699) 82. Azerbaijan(65.656) 83. North Macedonia(65.474) 84. Uzbekistan(65.255) 85. Kazakhstan(65.200) 86. Guatemala(64.958) 87. Ukraine(64.902) 88. Bangladesh(64.800) 89. Russia(64.703) 90. Kyrgyzstan(64.401) 91. Georgia(64.300) 92. Tajikistan(64.281) 93. Nepal(64.233) 94. Bolivia(63.901) 95. Mongolia(62.500) 96. Turkmenistan(62.409) 97. Libya(62.300) 98. Indonesia(62.236) 99. Cambodia(62.000) 100. Philippines(62.000) 101. Egypt(61.998) 102. Rwanda(61.400) 103. Kenya(60.704) 104. India(60.633) 105. Iraq(60.583) 106. Gabon(59.962)

0 10 20 30 40 50 60 70 80 90 100 Healthy Life Expectancy

35 Figure 21: Ranking of Healthy Life Expectancy: 2018-2020 (Part 3)

107. Senegal(59.802) 108. Madagascar(59.305) 109. Myanmar(59.302) 110. Botswana(59.269) 111. Ethiopia(59.000) 112. Laos(58.968) 113. Pakistan(58.709) 114. Congo (Brazzaville)(58.221) 115. Tanzania(57.999) 116. Malawi(57.948) 117. Ghana(57.586) 118. Comoros(57.349) 119. Mauritania(57.161) 120. Yemen(57.122) 121. South Africa(56.904) 122. Namibia(56.799) 123. Liberia(56.498) 124. Zimbabwe(56.201) 125. Uganda(56.101) 126. Zambia(55.809) 127. Haiti(55.700) 128. Gambia(55.160) 129. Guinea(55.008) 130. Togo(54.914) 131. Benin(54.713) 132. Mozambique(54.706) 133. Burkina Faso(54.151) 134. Niger(53.780) 135. Cameroon(53.515) 136. Burundi(53.400) 137. Afghanistan(52.493) 138. Mali(51.969) 139. Sierra Leone(51.651) 140. Swaziland(50.833) 141. Ivory Coast(50.114) 142. Nigeria(50.102) 143. Lesotho(48.700) 144. Chad(48.478)

0 10 20 30 40 50 60 70 80 90 100 Healthy Life Expectancy

36 Figure 22: Ranking of Freedom to Make Life Choices: 2018-2020 (Part 1)

1. Uzbekistan(0.970) 2. Norway(0.960) 3. Cambodia(0.959) 4. Iceland(0.955) 5. Finland(0.949) 6. Slovenia(0.949) 7. Denmark(0.946) 8. Sweden(0.945) 9. Vietnam(0.940) 10. Kyrgyzstan(0.935) 11. Costa Rica(0.934) 12. United Arab Emirates(0.932) 13. New Zealand(0.929) 14. Malta(0.927) 15. Singapore(0.927) 16. Bahrain(0.925) 17. Switzerland(0.919) 18. Philippines(0.917) 19. Canada(0.915) 20. Australia(0.914) 21. Netherlands(0.913) 22. Laos(0.910) 23. Estonia(0.909) 24. Austria(0.908) 25. Luxembourg(0.907) 26. Guatemala(0.906) 27. China(0.904) 28. Rwanda(0.897) 29. Uruguay(0.896) 30. Malaysia(0.895) 31. India(0.893) 32. Portugal(0.892) 33. Jamaica(0.890) 34. El Salvador(0.888) 35. Thailand(0.884) 36. Mozambique(0.882) 37. Ireland(0.879) 38. Saudi Arabia(0.877) 39. Bangladesh(0.877) 40. Turkmenistan(0.877) 41. Paraguay(0.876) 42. Myanmar(0.876) 43. Germany(0.875) 44. Bolivia(0.875) 45. Indonesia(0.873) 46. Panama(0.872) 47. Kosovo(0.869) 48. Kuwait(0.867) 49. Mauritius(0.867) 50. Mexico(0.862) 51. Dominican Republic(0.860) 52. United Kingdom(0.859) 53. Czech Republic(0.858)

0 1

Freedom to make life choices 95% confidence interval

37 Figure 23: Ranking of Freedom to Make Life Choices: 2018-2020 (Part 2)

54. Honduras(0.857) 55. Maldives(0.854) 56. Kazakhstan(0.853) 57. Romania(0.845) 58. Ecuador(0.842) 59. Sri Lanka(0.841) 60. Poland(0.841) 61. Colombia(0.837) 62. United States(0.837) 63. Nicaragua(0.836) 64. Tanzania(0.833) 65. Argentina(0.828) 66. Armenia(0.825) 67. Botswana(0.824) 68. Moldova(0.822) 69. Peru(0.822) 70. France(0.822) 71. Azerbaijan(0.814) 72. Ghana(0.807) 73. Niger(0.806) 74. Brazil(0.804) 75. Israel(0.800) 76. Japan(0.796) 77. North Cyprus(0.795) 78. Bulgaria(0.788) 79. Albania(0.785) 80. Taiwan Province of China(0.784) 81. Belgium(0.783) 82. Georgia(0.783) 83. Nepal(0.782) 84. Zambia(0.782) 85. Malawi(0.780) 86. Kenya(0.779) 87. Serbia(0.778) 88. Morocco(0.774) 89. Lithuania(0.773) 90. Libya(0.771) 91. Slovakia(0.766) 92. Cyprus(0.763) 93. Spain(0.761) 94. Benin(0.757) 95. Jordan(0.755) 96. Hungary(0.755) 97. Croatia(0.754) 98. Ethiopia(0.752) 99. North Macedonia(0.751) 100. South Africa(0.749) 101. Egypt(0.749) 102. Chile(0.742) 103. Ivory Coast(0.741) 104. Nigeria(0.737) 105. Liberia(0.735) 106. Cameroon(0.731)

0 1

Freedom to make life choices 95% confidence interval

38 Figure 24: Ranking of Freedom to Make Life Choices: 2018-2020 (Part 3)

107. Gabon(0.731) 108. Pakistan(0.726) 109. Ukraine(0.724) 110. Namibia(0.719) 111. Russia(0.718) 112. Sierra Leone(0.717) 113. Hong Kong S.A.R. of China(0.717) 114. Lesotho(0.715) 115. Latvia(0.715) 116. Uganda(0.709) 117. Montenegro(0.708) 118. Mongolia(0.708) 119. Bosnia and Herzegovina(0.706) 120. Mali(0.697) 121. Guinea(0.697) 122. Gambia(0.697) 123. Senegal(0.695) 124. Congo (Brazzaville)(0.695) 125. Burkina Faso(0.695) 126. Italy(0.693) 127. Zimbabwe(0.677) 128. South Korea(0.672) 129. Tunisia(0.656) 130. Palestinian Territories(0.653) 131. Belarus(0.650) 132. Swaziland(0.647) 133. Iraq(0.630) 134. Burundi(0.626) 135. Togo(0.619) 136. Venezuela(0.615) 137. Iran(0.608) 138. Yemen(0.602) 139. Haiti(0.593) 140. Greece(0.582) 141. Chad(0.579) 142. Turkey(0.576) 143. Mauritania(0.561) 144. Madagascar(0.552) 145. Comoros(0.548) 146. Lebanon(0.525) 147. Algeria(0.480) 148. Afghanistan(0.382)

0 1

Freedom to make life choices 95% confidence interval

39 Figure 25: Ranking of Generosity – % Who Donated to Charity in the Past Month – Without Adjusting for Per-Capita Income: 2018-2020 (Part 1)

1. Indonesia(0.840) 2. Myanmar(0.748) 3. United Kingdom(0.626) 4. Thailand(0.616) 5. Gambia(0.603) 6. Turkmenistan(0.589) 7. Netherlands(0.584) 8. Haiti(0.574) 9. Uzbekistan(0.569) 10. Kosovo(0.566) 11. Iceland(0.559) 12. Australia(0.558) 13. New Zealand(0.523) 14. Ireland(0.516) 15. United States(0.513) 16. Norway(0.511) 17. Kenya(0.510) 18. United Arab Emirates(0.494) 19. Sweden(0.490) 20. Canada(0.487) 21. Malaysia(0.485) 22. Bahrain(0.481) 23. Malta(0.478) 24. Austria(0.449) 25. Switzerland(0.446) 26. Denmark(0.439) 27. Singapore(0.430) 28. Iran(0.427) 29. Bosnia and Herzegovina(0.426) 30. Luxembourg(0.426) 31. Mongolia(0.416) 32. Germany(0.415) 33. Israel(0.415) 34. Hong Kong S.A.R. of China(0.411) 35. Laos(0.405) 36. Sri Lanka(0.387) 37. Tanzania(0.376) 38. Nepal(0.360) 39. Kyrgyzstan(0.359) 40. North Macedonia(0.358) 41. Ghana(0.357) 42. Maldives(0.353) 43. North Cyprus(0.347) 44. India(0.345) 45. Cyprus(0.345) 46. Paraguay(0.333) 47. Serbia(0.332) 48. Honduras(0.330) 49. Pakistan(0.329) 50. South Korea(0.307) 51. Montenegro(0.304) 52. Chile(0.303) 53. Italy(0.302)

0 1

Generosity, not adjusted 95% confidence interval

40 Figure 26: Ranking of Generosity – % Who Donated to Charity in the Past Month – Without Adjusting for Per-Capita Income: 2018-2020 (Part 2)

54. Spain(0.302) 55. Finland(0.300) 56. Uganda(0.298) 57. Kuwait(0.296) 58. Ukraine(0.293) 59. Mauritius(0.286) 60. Guinea(0.286) 61. Kazakhstan(0.285) 62. Comoros(0.284) 63. Taiwan Province of China(0.283) 64. Slovenia(0.279) 65. Albania(0.279) 66. Nigeria(0.275) 67. Zambia(0.273) 68. Estonia(0.271) 69. Cambodia(0.264) 70. Nicaragua(0.263) 71. Ethiopia(0.260) 72. Bulgaria(0.250) 73. Belgium(0.248) 74. Uruguay(0.248) 75. France(0.246) 76. Saudi Arabia(0.246) 77. Slovakia(0.245) 78. Sierra Leone(0.244) 79. Russia(0.244) 80. Lebanon(0.242) 81. Brazil(0.241) 82. Croatia(0.240) 83. Guatemala(0.240) 84. Rwanda(0.239) 85. Cameroon(0.238) 86. Iraq(0.234) 87. South Africa(0.231) 88. Algeria(0.229) 89. Libya(0.226) 90. Moldova(0.223) 91. Turkey(0.222) 92. Ivory Coast(0.221) 93. Costa Rica(0.208) 94. Poland(0.205) 95. Latvia(0.204) 96. Mozambique(0.202) 97. Liberia(0.201) 98. Chad(0.200) 99. Panama(0.200) 100. Dominican Republic(0.196) 101. Bolivia(0.196) 102. Bangladesh(0.192) 103. Togo(0.189) 104. Mexico(0.185) 105. Hungary(0.181) 106. Lithuania(0.181)

0 1

Generosity, not adjusted 95% confidence interval

41 Figure 27: Ranking of Generosity – % Who Donated to Charity in the Past Month – Without Adjusting for Per-Capita Income: 2018-2020 (Part 3)

107. Philippines(0.179) 108. Colombia(0.176) 109. Benin(0.176) 110. China(0.175) 111. Czech Republic(0.175) 112. Vietnam(0.173) 113. Burkina Faso(0.169) 114. Ecuador(0.168) 115. Malawi(0.162) 116. El Salvador(0.162) 117. Senegal(0.162) 118. Argentina(0.157) 119. Niger(0.157) 120. Belarus(0.152) 121. Madagascar(0.152) 122. Tajikistan(0.151) 123. Peru(0.150) 124. Jamaica(0.149) 125. Zimbabwe(0.148) 126. Romania(0.143) 127. Congo (Brazzaville)(0.143) 128. Mali(0.139) 129. Armenia(0.138) 130. Venezuela(0.136) 131. Namibia(0.135) 132. Mauritania(0.133) 133. Portugal(0.129) 134. Japan(0.128) 135. Jordan(0.117) 136. Egypt(0.114) 137. Gabon(0.111) 138. Palestinian Territories(0.108) 139. Swaziland(0.091) 140. Azerbaijan(0.089) 141. Tunisia(0.089) 142. Burundi(0.083) 143. Botswana(0.082) 144. Afghanistan(0.075) 145. Georgia(0.074) 146. Greece(0.074) 147. Lesotho(0.062) 148. Yemen(0.047) 149. Morocco(0.028)

0 1

Generosity, not adjusted 95% confidence interval

42 Figure 28: Ranking of Perceptions of Corruption: 2018-2020 (Part 1)

1. Croatia(0.939) 2. Romania(0.938) 3. Bulgaria(0.932) 4. Bosnia and Herzegovina(0.931) 5. Afghanistan(0.924) 6. Ukraine(0.924) 7. Moldova(0.918) 8. Kosovo(0.917) 9. Lesotho(0.915) 10. Slovakia(0.911) 11. Kyrgyzstan(0.908) 12. North Macedonia(0.905) 13. Albania(0.901) 14. Lebanon(0.898) 15. Thailand(0.895) 16. Peru(0.891) 17. Portugal(0.887) 18. Jamaica(0.884) 19. Paraguay(0.882) 20. Nigeria(0.878) 21. Hungary(0.876) 22. Iraq(0.875) 23. Tunisia(0.870) 24. Czech Republic(0.868) 25. Indonesia(0.867) 26. Sierra Leone(0.866) 27. Italy(0.866) 28. Sri Lanka(0.863) 29. South Africa(0.860) 30. Mongolia(0.856) 31. Panama(0.856) 32. Uganda(0.855) 33. Liberia(0.850) 34. Ghana(0.848) 35. Cameroon(0.848) 36. Namibia(0.847) 37. Russia(0.845) 38. Cyprus(0.844) 39. Cambodia(0.843) 40. Ecuador(0.843) 41. Colombia(0.841) 42. Gabon(0.840) 43. Malaysia(0.839) 44. Bolivia(0.839) 45. Serbia(0.835) 46. Argentina(0.834) 47. Chile(0.830) 48. Mali(0.827) 49. Venezuela(0.827) 50. Lithuania(0.826) 51. Kenya(0.825) 52. Zambia(0.823) 53. Greece(0.823)

0 1

Perceptions of corruption 95% confidence interval

43 Figure 29: Ranking of Perceptions of Corruption: 2018-2020 (Part 2)

54. Palestinian Territories(0.821) 55. Zimbabwe(0.821) 56. Montenegro(0.812) 57. Honduras(0.809) 58. Costa Rica(0.809) 59. Chad(0.807) 60. Slovenia(0.806) 61. Madagascar(0.803) 62. Morocco(0.801) 63. Senegal(0.801) 64. Botswana(0.801) 65. Yemen(0.800) 66. Latvia(0.800) 67. Mexico(0.799) 68. Vietnam(0.796) 69. Ivory Coast(0.794) 70. Mauritius(0.789) 71. Pakistan(0.787) 72. Comoros(0.781) 73. Turkey(0.776) 74. Guatemala(0.775) 75. India(0.774) 76. Togo(0.772) 77. Guinea(0.766) 78. Ethiopia(0.761) 79. Brazil(0.756) 80. Israel(0.753) 81. Algeria(0.752) 82. Burkina Faso(0.748) 83. Gambia(0.746) 84. Spain(0.745) 85. Congo (Brazzaville)(0.745) 86. Philippines(0.742) 87. Poland(0.735) 88. Kazakhstan(0.733) 89. Mauritania(0.731) 90. Malawi(0.729) 91. Nepal(0.727) 92. South Korea(0.727) 93. Taiwan Province of China(0.721) 94. Haiti(0.721) 95. Iran(0.714) 96. Dominican Republic(0.714) 97. Swaziland(0.708) 98. United States(0.698) 99. Niger(0.693) 100. El Salvador(0.688) 101. Mozambique(0.684) 102. Bangladesh(0.682) 103. Iceland(0.673) 104. Libya(0.667) 105. Nicaragua(0.664) 106. Benin(0.661)

0 1

Perceptions of corruption 95% confidence interval

44 Figure 30: Ranking of Perceptions of Corruption: 2018-2020 (Part 3)

107. Myanmar(0.660) 108. Laos(0.658) 109. Georgia(0.655) 110. Malta(0.653) 111. Belgium(0.646) 112. Japan(0.638) 113. Armenia(0.629) 114. Belarus(0.627) 115. North Cyprus(0.626) 116. Burundi(0.607) 117. Uruguay(0.590) 118. Tanzania(0.577) 119. France(0.571) 120. Tajikistan(0.553) 121. Estonia(0.527) 122. Uzbekistan(0.515) 123. Azerbaijan(0.506) 124. Austria(0.481) 125. Germany(0.460) 126. United Kingdom(0.459) 127. Australia(0.442) 128. Canada(0.415) 129. Hong Kong S.A.R. of China(0.403) 130. Luxembourg(0.386) 131. Ireland(0.363) 132. Netherlands(0.338) 133. Switzerland(0.292) 134. Norway(0.270) 135. New Zealand(0.242) 136. Sweden(0.237) 137. Finland(0.186) 138. Denmark(0.179) 139. Rwanda(0.167) 140. Singapore(0.082)

0 1

Perceptions of corruption 95% confidence interval

45 Figure 31: Ranking of Positive Affect: 2018-2020 (Part 1)

1. Panama(0.883) 2. Indonesia(0.876) 3. Guatemala(0.873) 4. Laos(0.870) 5. Honduras(0.862) 6. Costa Rica(0.859) 7. Uruguay(0.859) 8. Paraguay(0.859) 9. El Salvador(0.858) 10. Cambodia(0.858) 11. Mexico(0.854) 12. Iceland(0.851) 13. Taiwan Province of China(0.851) 14. China(0.849) 15. New Zealand(0.837) 16. Uzbekistan(0.836) 17. Denmark(0.834) 18. Thailand(0.832) 19. Malaysia(0.830) 20. Netherlands(0.828) 21. Sri Lanka(0.828) 22. Ecuador(0.827) 23. Norway(0.825) 24. Peru(0.820) 25. Chile(0.819) 26. Canada(0.814) 27. Colombia(0.814) 28. Nicaragua(0.814) 29. South Africa(0.810) 30. United States(0.806) 31. Sweden(0.805) 32. Ireland(0.805) 33. Argentina(0.804) 34. Swaziland(0.803) 35. Estonia(0.802) 36. Niger(0.794) 37. Gambia(0.787) 38. Switzerland(0.787) 39. Philippines(0.785) 40. Mauritius(0.782) 41. United Arab Emirates(0.781) 42. Myanmar(0.780) 43. Kyrgyzstan(0.779) 44. Bahrain(0.776) 45. Czech Republic(0.773) 46. United Kingdom(0.772) 47. Luxembourg(0.769) 48. Rwanda(0.766) 49. Australia(0.766) 50. Austria(0.766) 51. Bolivia(0.763) 52. Germany(0.763) 53. Finland(0.760)

0 1

Positive affect 95% confidence interval

46 Figure 32: Ranking of Positive Affect: 2018-2020 (Part 2)

54. Cyprus(0.758) 55. Dominican Republic(0.757) 56. Slovakia(0.755) 57. Singapore(0.754) 58. Senegal(0.753) 59. Jamaica(0.752) 60. Kosovo(0.752) 61. Saudi Arabia(0.750) 62. Venezuela(0.749) 63. Brazil(0.747) 64. Kenya(0.747) 65. Comoros(0.746) 66. France(0.746) 67. Poland(0.744) 68. Nigeria(0.744) 69. Mali(0.741) 70. Lesotho(0.739) 71. Vietnam(0.738) 72. Madagascar(0.737) 73. Japan(0.730) 74. Tanzania(0.725) 75. Kazakhstan(0.725) 76. Botswana(0.724) 77. Hungary(0.719) 78. Romania(0.717) 79. Tajikistan(0.713) 80. Zambia(0.712) 81. Belgium(0.711) 82. Zimbabwe(0.710) 83. Ghana(0.708) 84. Libya(0.707) 85. Guinea(0.706) 86. Kuwait(0.695) 87. Uganda(0.693) 88. Albania(0.692) 89. Burkina Faso(0.692) 90. Namibia(0.688) 91. Ivory Coast(0.685) 92. Portugal(0.679) 93. Mauritania(0.679) 94. Malta(0.677) 95. Russia(0.673) 96. Greece(0.672) 97. Spain(0.670) 98. Bulgaria(0.669) 99. Gabon(0.667) 100. Mongolia(0.667) 101. Burundi(0.666) 102. India(0.666) 103. South Korea(0.664) 104. Italy(0.650) 105. Liberia(0.650) 106. Ukraine(0.647)

0 1

Positive affect 95% confidence interval

47 Figure 33: Ranking of Positive Affect: 2018-2020 (Part 3)

107. Ethiopia(0.647) 108. Moldova(0.645) 109. Slovenia(0.645) 110. Bosnia and Herzegovina(0.641) 111. Israel(0.639) 112. Benin(0.637) 113. Cameroon(0.636) 114. Congo (Brazzaville)(0.626) 115. Latvia(0.626) 116. Croatia(0.624) 117. Azerbaijan(0.619) 118. Palestinian Territories(0.618) 119. Iraq(0.617) 120. Mozambique(0.613) 121. Morocco(0.607) 122. Hong Kong S.A.R. of China(0.605) 123. Togo(0.603) 124. Georgia(0.598) 125. Montenegro(0.597) 126. Lithuania(0.594) 127. Armenia(0.591) 128. North Macedonia(0.591) 129. Algeria(0.589) 130. Iran(0.580) 131. Haiti(0.580) 132. Pakistan(0.575) 133. Chad(0.575) 134. Tunisia(0.573) 135. Malawi(0.565) 136. Serbia(0.556) 137. Turkmenistan(0.556) 138. Bangladesh(0.548) 139. Nepal(0.543) 140. Egypt(0.530) 141. Sierra Leone(0.527) 142. Belarus(0.523) 143. Yemen(0.506) 144. North Cyprus(0.487) 145. Turkey(0.418) 146. Lebanon(0.391) 147. Afghanistan(0.381)

0 1

Positive affect 95% confidence interval

48 Figure 34: Ranking of Negative Affect: 2018-2020 (Part 1)

1. Iraq(0.496) 2. Chad(0.495) 3. Iran(0.470) 4. Afghanistan(0.459) 5. Guinea(0.457) 6. Sierra Leone(0.453) 7. Togo(0.443) 8. Armenia(0.442) 9. Congo (Brazzaville)(0.426) 10. Gabon(0.418) 11. Liberia(0.413) 12. Tunisia(0.410) 13. Palestinian Territories(0.409) 14. India(0.406) 15. Pakistan(0.401) 16. Libya(0.400) 17. Uganda(0.400) 18. Benin(0.399) 19. Cambodia(0.396) 20. Bolivia(0.394) 21. Mozambique(0.393) 22. Gambia(0.392) 23. Lebanon(0.385) 24. Ivory Coast(0.384) 25. Niger(0.381) 26. Turkey(0.381) 27. Montenegro(0.376) 28. Venezuela(0.372) 29. Ecuador(0.372) 30. Peru(0.371) 31. Nicaragua(0.368) 32. Nepal(0.365) 33. Burundi(0.365) 34. Rwanda(0.363) 35. Zambia(0.363) 36. Haiti(0.363) 37. Mali(0.362) 38. Burkina Faso(0.360) 39. Bangladesh(0.360) 40. Cameroon(0.358) 41. Malta(0.354) 42. Malawi(0.352) 43. Philippines(0.350) 44. Brazil(0.350) 45. Morocco(0.349) 46. Italy(0.347) 47. Comoros(0.339) 48. Egypt(0.336) 49. Portugal(0.333) 50. Laos(0.331) 51. Madagascar(0.331) 52. Spain(0.330) 53. Argentina(0.327)

0 1

Negative affect 95% confidence interval

49 Figure 35: Ranking of Negative Affect: 2018-2020 (Part 2)

54. North Macedonia(0.322) 55. Colombia(0.320) 56. Chile(0.317) 57. Costa Rica(0.315) 58. Bahrain(0.308) 59. Sri Lanka(0.307) 60. Kuwait(0.303) 61. Indonesia(0.297) 62. Serbia(0.296) 63. United Arab Emirates(0.295) 64. Myanmar(0.293) 65. Cyprus(0.291) 66. Dominican Republic(0.289) 67. El Salvador(0.289) 68. Senegal(0.288) 69. Albania(0.284) 70. Canada(0.284) 71. Honduras(0.283) 72. Hong Kong S.A.R. of China(0.283) 73. Croatia(0.283) 74. South Africa(0.282) 75. Guatemala(0.282) 76. North Cyprus(0.280) 77. Bosnia and Herzegovina(0.279) 78. United States(0.277) 79. Paraguay(0.275) 80. Ethiopia(0.274) 81. Slovenia(0.271) 82. Greece(0.270) 83. Botswana(0.269) 84. Lesotho(0.269) 85. Romania(0.267) 86. Mauritania(0.267) 87. Moldova(0.266) 88. Nigeria(0.265) 89. Swaziland(0.264) 90. Israel(0.264) 91. Zimbabwe(0.264) 92. Kenya(0.262) 93. Georgia(0.261) 94. Ghana(0.260) 95. Yemen(0.259) 96. Slovakia(0.259) 97. Saudi Arabia(0.259) 98. France(0.254) 99. Uruguay(0.253) 100. Algeria(0.252) 101. Mexico(0.251) 102. Belgium(0.251) 103. Namibia(0.250) 104. Tanzania(0.247) 105. Tajikistan(0.236) 106. Thailand(0.235)

0 1

Negative affect 95% confidence interval

50 Figure 36: Ranking of Negative Affect: 2018-2020 (Part 3)

107. United Kingdom(0.235) 108. Ukraine(0.234) 109. Panama(0.233) 110. South Korea(0.233) 111. Czech Republic(0.232) 112. Lithuania(0.231) 113. Ireland(0.227) 114. Netherlands(0.227) 115. Germany(0.225) 116. Poland(0.223) 117. Kyrgyzstan(0.222) 118. Uzbekistan(0.214) 119. Belarus(0.212) 120. Austria(0.212) 121. Norway(0.207) 122. Luxembourg(0.207) 123. Hungary(0.207) 124. Mongolia(0.206) 125. Bulgaria(0.205) 126. Denmark(0.204) 127. Latvia(0.201) 128. Australia(0.198) 129. Jamaica(0.197) 130. Russia(0.196) 131. Sweden(0.195) 132. China(0.191) 133. Japan(0.188) 134. New Zealand(0.188) 135. Malaysia(0.187) 136. Vietnam(0.187) 137. Turkmenistan(0.186) 138. Switzerland(0.185) 139. Finland(0.185) 140. Azerbaijan(0.177) 141. Iceland(0.175) 142. Kosovo(0.169) 143. Estonia(0.169) 144. Kazakhstan(0.151) 145. Mauritius(0.150) 146. Singapore(0.123) 147. Taiwan Province of China(0.090)

0 1

Negative affect 95% confidence interval

51