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The Relationship Between Money and Happiness

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Charting the Relationship Between Money and Happiness

Charting the Relationship Between Money and Happiness

Today’s chart is best viewed full-screen. Explore the high resolution version by clicking here.

Can money buy you happiness?

It’s a longstanding question that has many different answers, depending on who you ask.

Today’s chart approaches this fundamental question from a data-driven perspective, and it provides one potential solution: money does buy some happiness, but only to a limited extent.

Money and Happiness

First, a thinking exercise.

Let’s say you have two hypothetical people: one of them is named Beff Jezos and he’s a billionaire, and the other is named Jill Smith and she has a more average net worth. Who do you think would be happiest if their wealth was instantly doubled?

Beff might be happy that he’s got more in the bank, but materially his life is unlikely to change much – after all, he’s a billionaire. On the flipside, Jill also has more in the bank and is likely able to use those additional resources to provide better opportunities for her family, get out of debt, or improve her work-life balance.

These resources translate to real changes for Jill, potentially increasing her level of satisfaction with life.

Just like these hypotheticals, the data tells a similar story when we look at countries.

The Data-Driven Approach

Today’s chart looks at the relationship between GDP per capita (PPP) and the self-reported levels of happiness of each country. Sources for data are the World Bank and the World Happiness Report 2017.

According to the numbers, the relationship between money and happiness is strong early on for countries. Then later, when material elements of Maslow’s hierarchy are met, the relationship gets harder to predict.

In general, this means that as a country’s wealth increases from $10k to $20k per person, it will likely slide up the happiness scale as well. For a double from $30k to $60k, the relationship still holds – but it tends to have far more variance. This variance is where things get interesting.

Outlier Regions

Some of the most obvious outliers can be found in Latin America and the Middle East:

Latin America vs. Middle East

In Latin America, people self-report that they are more satisfied than the trend between money and happiness would predict.

Costa Rica stands out in particular here, with a GDP per capita of $15,400 and a 7.14 rating on the Cantril Ladder (which is a measure of happiness). Whether it’s the country’s rugged coastlines or the local culture that does the trick, Costa Rica has higher happiness ratings than the U.S., Belgium, or Germany – all countries with far higher levels of wealth.

In the Middle East, the situation is mostly reversed. Countries like Saudi Arabia, Qatar, Iran, Iraq, Yemen, Turkey, and the U.A.E. are all on the other side of the trend line.

Outlier Countries

Within regions, there is even plenty of variance.

We just mentioned the Middle East as a place where the wealth-happiness continuum doesn’t seem to hold up as well as it does in other places in the world.

Interestingly, in Qatar, which is actually the wealthiest country in the world on a per capita basis ($127k), things are even more out of whack. Qatar only scores a 6.37 on the Cantril Ladder, making it a big exception even within the context of the already-outlying Middle East.

Nearby Saudi Arabia, U.A.E., and Oman are all poorer than Qatar per capita, yet they are happier places. Oman rates a 6.85 on the satisfaction scale, with less than one-third the wealth per capita of Qatar.

There are other outlier jurisdictions on the list as well: Thailand, Uzbekistan, and Pakistan are all significantly happier than the trend line (or their regional location) would project. Meanwhile, places like Hong Kong, Ireland, Singapore, and Luxembourg are less happy than wealth would predict.

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Chart of the Week

At Risk: The Geography of America’s Senior Population

The U.S. senior population is much more vulnerable to COVID-19. Which states and cities have the most people in this at-risk age group?

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U.S. Senior Population

At Risk: The U.S. Senior Population

The U.S. now has the largest number of confirmed COVID-19 cases globally, and modelling predicts that the country could see about 100,000 to 200,000 total deaths. Unfortunately, adults aged 65 or older—about 16% of the U.S. population—are at much higher risk of both severe illness and death.

Today’s chart uses U.S. Census Bureau data to map the percentage of the population that is 65 years or older by state. It also outlines the urban areas that are most heavily skewed towards this older age group.

Proportion of Seniors by State

Below is the full breakdown of the U.S. senior population by state, using the latest available data from 2018.

Maine tops the list with 20.6% of its population comprising adults age 65 or older. At the other end of the scale, Utah’s seniors make up only 11.1% of its population.

RankState65+, % of Population65+, Total Population
1Maine20.6%276,069
2Florida20.5%4,358,784
3West Virginia20.0%361,216
4Vermont19.8%123,875
5Montana18.8%200,239
6Delaware18.7%180,756
7Hawaii18.4%261,467
8Pensylvannia18.2%2,332,369
9New Hampshire18.1%245,156
10South Carolina17.7%899,754
11Oregon17.6%739,611
12Arizona17.6%1,259,103
13New Mexico17.6%368,480
14Rhode Island17.3%182,645
15Conneticut17.2%613,147
16Michigan17.2%1,720,453
17Ohio17.1%1,996,163
18Iowa17.0%537,818
19Wisconsin17.0%986,483
20Alabama17.0%829,663
21Missouri16.9%1,035,074
22Arkansas16.8%507,676
23Wyoming16.7%96,557
24South Dakota16.6%146,358
25Massachusetts16.5%1,137,541
26Kentucky16.4%731,392
27New York16.4%3,212,065
28Tennesse16.3%1,104,797
29North Carolina16.3%1,688,574
30New Jersey16.1%1,438,289
31Idaho15.9%279,441
32Kansas15.9%462,191
34Mississipi15.9%474,423
33Minnesota15.8%888,634
36Nebraska15.8%303,998
35Indiana15.7%1,051,146
37Nevada15.7%475,120
38Oklahoma15.7%619,601
39Illinois15.6%1,990,548
40Louisiana15.5%720,610
42Virginia15.5%1,318,225
41Maryland15.4%931,041
43Washington15.4%1,163,987
44North Dakota15.3%116,433
45California14.3%5,667,337
46Colorado14.2%807,855
47Georgia13.8%1,456,428
48Texas12.5%3,599,599
49Alaska11.9%88,000
50Utah11.1%351,297

Notably, Florida has the second highest percentage and number of seniors nationwide. Its governor just announced the state’s stay-at-home order on April 1st, after taking criticism for refusing to do so earlier.

New York, the current global hot spot of COVID-19, is close to the national average with 16.4% of its population aged 65 or older. However, with over 3.2 million seniors, the sheer volume of individuals needing hospitalization has already put a strain on the state’s healthcare system. Governor Andrew Cuomo says the state will run out of its current supply of ventilators in less than a week.

The Most Vulnerable Urban Areas

On a local level, which places have the highest proportion of seniors? Based on all urban areas* with a population of 250,000 or more, here’s how the top 50 looks:

RankUrban Area65+, % of Population65+, Total Population
1Bonita Springs, FL38.2%135,286
2Sarasota–Bradenton, FL33.2%242,613
3Barnstable Town, MA29.4%74,614
4Palm Coast–Daytona Beach–Port Orange, FL28.3%110,355
5Myrtle Beach–Socastee, SC–NC27.3%74,783
6Cape Coral, FL27.0%175,483
7Indio–Cathedral City, CA26.0%95,054
8Port St. Lucie, FL25.6%110,883
9Palm Bay–Melbourne, FL22.9%114,347
10Youngstown, OH–PA21.0%78,739
11Asheville, NC20.9%65,540
12Pittsburgh, PA19.6%335,546
13Canton, OH19.6%54,214
14Scranton, PA19.1%71,876
15Mission Viejo–Lake Forest–San Clemente, CA19.0%115,891
16Tampa–St. Petersburg, FL18.9%516,269
17Tucson, AZ18.8%165,399
18Lancaster, PA18.5%77,538
19Cleveland, OH18.4%324,707
20Miami, FL18.3%1,117,926
21Buffalo, NY18.1%168,121
22Dayton, OH18.0%130,722
23Harrisburg, PA18.0%83,201
24Wilmington, NC17.8%45,457
25Urban Honolulu, HI17.7%148,045
26Akron, OH17.6%99,010
27New Haven, CT17.6%97,888
28Rochester, NY17.5%125,516
29Peoria, IL17.5%44,722
30Allentown, PA–NJ17.4%119,508
31Concord, CA17.4%115,460
32Chattanooga, TN–GA17.4%69,098
33Flint, MI17.2%59,525
34Santa Rosa, CA17.1%55,094
35Lakeland, FL17.1%51,107
36Davenport, IA–IL17.1%48,387
37Providence, RI–MA17.0%204,148
38Rockford, IL16.9%48,370
39Springfield, MA–CT16.8%105,694
40Knoxville, TN16.8%101,332
41Albany–Schenectady, NY16.8%100,756
42Albuquerque, NM16.7%126,081
43Hartford, CT16.6%153,367
44Toledo, OH–MI16.6%82,480
45Pensacola, FL–AL16.6%62,216
46Bridgeport–Stamford, CT–NY16.5%156,035
47Syracuse, NY16.4%66,818
48Detroit, MI16.2%608,427
49St. Louis, MO–IL16.2%347,537
50Trenton, NJ16.2%47,803

*Urban areas consist of a downtown core and adjacent territories

With 6 areas in the top 10, Florida is quite vulnerable at the local level as well. Other states with multiple areas on the list include Ohio, Pennsylvania, and New York.

The Senior Population of Current U.S. Hotspots

To determine the vulnerability of current COVID-19 hotspots, we compared U.S. counties with a high number of cases per capita against their percentage of seniors.

Counties at the bottom left have low readings on both metrics. Conversely, counties in the top right have a dangerous combination: a high concentration of cases and vulnerable seniors.

senior population vs covid-19 outbreak

Multiple counties in New York occupy the top right quadrant, with Yonkers being the worst off. Los Angeles county, which has a similar population to all counties in New York City, has fewer cases and a smaller proportion of seniors.

To date, outbreaks have been mostly focused in urban areas where populations tend to be younger. However, as COVID-19 begins infiltrating rural areas, healthcare systems will need to contend with both older age groups and fewer resources.

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Chart of the Week

Global Shutdown: Visualizing Commuter Activity in the World’s Cities

Amid the COVID-19 crisis, cities are dramatically slowing down. Today’s chart demonstrates the impact of lockdowns on commuter activity worldwide.

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Staying Put: The COVID-19 Commuter Decline

Every day, millions of people worldwide rely on public transport networks to get around. But in times of crisis, bustling cities with high volumes of commuter traffic can come to a dramatic halt.

Today’s chart breaks down daily data from Citymapper’s Mobility Index, according to trips planned on the transport app across 41 select cities.

The results paint a unique picture of how social distancing and lockdown measures are impacting commuter and economic activity in major urban hubs.

Cities With the Biggest Drops in Activity

As the government response to the COVID-19 pandemic intensifies and people are urged to stay home, transit activity is dropping everywhere.

However, some areas are seeing more of a reduction in activity than others. Where has activity declined the most over the month?

RankCityCountry04-Mar11-Mar18-Mar25-MarTotal Change (%)
#1Vienna🇦🇹 Austria128%92%9%6%-122%
#2Lisbon🇵🇹 Portugal128%108%24%12%-116%
#3Istanbul🇹🇷 Turkey117%103%20%10%-107%
#4Barcelona🇪🇸 Spain105%86%6%4%-101%
#5Brussels🇧🇪 Belgium107%96%15%7%-100%
#6São Paolo🇧🇷 Brazil112%113%33%12%-100%
#7New York City🇺🇸 USA104%85%17%7%-97%
#8Madrid🇪🇸 Spain100%65%5%4%-96%
#9Los Angeles🇺🇸 USA108%81%23%13%-95%
#10Melbourne🇦🇺 Australia113%110%53%20%-93%

*Note: Data measures the % of city moving compared to 100% baseline.

Overall, Vienna and Lisbon are the cities with the biggest average drop in commuter activity over the past few weeks. This decline in mobility is correlated with a spike in the proportion of COVID-19 cases in the population:

  • Austria
    March 4: 2.6 per million
    March 25: 586 per million
  • Portugal
    March 4: 0.4 per million
    March 25: 232 per million

That said, not every city is seeing a precipitous decline in activity — let’s look at those next.

Standing Still, or On Guard

Cities that saw lower decreases in commuter activity over recent weeks can generally be slotted into three categories:

  1. Cities that were already on or near shutdown (Seoul, Milan)
  2. Cities that have so far avoided major impacts from the virus (St. Petersburg)
  3. Cities that successfully mitigated spread (Singapore)

Here are the 10 cities on the list that saw the lowest changes in activity:

RankCityCountry04-Mar11-Mar18-Mar25-MarTotal Change (%)
#1Seoul 🇰🇷 South Korea48%43%41%37%-11%
#2Hong Kong🇭🇰 China (SAR)50%52%48%37%-13%
#3Singapore🇸🇬 Singapore90%88%79%62%-28%
#4Milan🇮🇹 Italy43%10%5%3%-40%
#5Tokyo🇯🇵 Japan63%54%42%21%-42%
#6St Petersburg🇷🇺 Russia114%114%85%69%-45%
#7Moscow🇷🇺 Russia112%113%75%54%-58%
#8Rhine-Ruhr🇩🇪 Germany75%72%28%15%-60%
#9Stockholm🇸🇪 Sweden97%83%34%32%-65%
#10Lyon🇫🇷 France75%97%6%4%-71%

*Note: Data measures the % of city moving compared to 100% baseline.

St. Petersburg is still seeing commuter activity at 69% of normal levels as of March 25th, as the proportion of confirmed COVID-19 cases in Russia remains low, at roughly 3.4 per million.

Milan has the lowest activity of any city at 3%, and has been in shutdown for most of the month.

Although Singapore’s total COVID-19 cases grew from 18.8 to 95.4 per million, it still has 62% commuter activity. Interestingly, Singapore is one of the few countries that has been able to properly control and manage its COVID-19 outbreak.

Biggest Weekly Declines

As the month progressed, various cities showed stark one-week declines in commuter activity based on official healthcare recommendations and growing case numbers.

After a government lockdown announced on March 9, Rome experienced the sharpest decline of -75% commuter activity in the week from March 4 to March 11. Currently, there is only 5% activity compared to usual, similar to Milan.

In the second week of March, COVID-19 cases in France jumped fourfold, from 27.3 per million to 118.4 per million people. As a result, Lyon saw a whopping -91% drop in commuter activity—going from 97% on March 11 to 6% on March 18.

Over the past week, as cases in Australia reached 95 per million, Sydney and Melbourne exhibited the highest average declines at -36% and -33% in commuter activity respectively.

Full List of 41 Cities

Here’s the full list of cities, courtesy of Citymapper.

City, CountryMarch 4March 11March 18March 25Total Change (%)
Vienna, Austria128%92%9%6%-122%
Lisbon, Portugal128%108%24%12%-116%
Istanbul, Turkey117%103%20%10%-107%
Barcelona, Spain105%86%6%4%-101%
Brussels, Belgium107%96%15%7%-100%
São Paulo, Brazil112%113%33%12%-100%
New York City, U.S.104%85%17%7%-97%
Madrid, Spain100%65%5%4%-96%
Los Angeles, U.S.108%81%23%13%-95%
Melbourne, Australia113%110%53%20%-93%
Amsterdam, Netherlands98%86%13%6%-92%
Washington DC, U.S.97%82%15%6%-91%
San Francisco, U.S.96%65%9%6%-90%
Boston, U.S.97%77%16%7%-90%
Chicago, U.S.97%92%16%7%-90%
Montréal, Canada103%104%31%14%-89%
Paris, France95%89%8%6%-89%
London, UK100%91%36%12%-88%
Manchester, UK100%91%42%13%-87%
Sydney, Australia106%99%56%20%-86%
Mexico City, Mexico109%110%53%23%-86%
Rome, Italy91%16%6%5%-86%
Copenhagen, Denmark97%80%11%11%-86%
Berlin, Germany93%86%26%12%-81%
Birmingham, UK99%91%45%18%-81%
Toronto, Canada97%91%32%19%-78%
Vancouver, Canada94%89%38%16%-78%
Philadelphia, U.S.89%85%22%13%-76%
Monaco, Monaco81%50%12%7%-74%
Hamburg, Germany85%72%20%12%-73%
Seattle, U.S.80%51%19%8%-72%
Lyon, France75%97%6%4%-71%
Stockholm, Sweden97%83%34%32%-65%
Rhine-Ruhr, Germany75%72%28%15%-60%
Moscow, Russia112%113%75%54%-58%
St Petersburg, Russia114%114%85%69%-45%
Tokyo, Japan63%54%42%21%-42%
Milan, Italy43%10%5%3%-40%
Singapore, Singapore90%88%79%62%-28%
Hong Kong, Hong Kong50%52%48%37%-13%
Seoul, South Korea48%43%41%37%-11%

*Note: Data measures the % of city moving compared to 100% baseline.

The COVID-19 pandemic is affecting everything from the stock market to the environment. With cities actively working to keep populations in isolation and healthy during this time, it may take a while before commuter activity returns to normal.

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