Netflix has a new documentary on Blue Zones, regions in the world such as Okinawa Prefecture, Japan; Nuoro Province, Sardinia, Italy; the Nicoya Peninsula, Costa Rica; Icaria, Greece; and Loma Linda, California, where people appear to live “extraordinarily long and vibrant lives.” What are the secrets of such blue zones and how can you live to be 100?

These blue zones first started to be discussed in the 2000s which means that people aged 100 or older were born sometime around 1900. What do we know about that period of history? It was before vital records were uniformly established. And what happens when state-wide certification goes into effect? Saul Justin Newman shows that the number of supercentarians [100+] drops sharply a hundred or so years later!

…the introduction of state-wide birth certification coincides with a sharp reduction in the number of supercentenarians born in each state. In total, 82% of the GRG supercentenarian records from the USA predate state-wide birth certification. Forty-two states achieved complete birth certificate coverage during the survey period. When these states transition to state-wide birth registration, the number of supercentenarians falls by 80% per year overall and 69% per capita when adjusted relative to c.1900 state population sizes.

The author goes on to show that in many countries the number of of extremely old people is positively correlated with poverty, shorter average life spans and illiteracy. All factors which are difficult to explain if we think these factors are causally related to health but which make sense if we think that the explanation is unreliable birth and death records. Supercentenarian birthdates also exhibit patterns such as age-heaping that are “strongly indicative of manufactured birth data.”

In addition, cross-country comparisons don’t make much sense if we focus on health:

In 1900 the UK had eight million more inhabitants than Italy, a 1.22-fold larger population. Citizens of the UK also enjoyed 2.5 times the GDP per capita, earned 3.5 times higher wages in real terms, had 1.25 times lower income inequality, received 2.2 times the average education (with just 5.3 years of schooling), were four times less likely to be murdered, were 3.8cm taller, and lived 5.3 years longer on average than people in Italy. Given these indicators and the long history of birth records in both countries, it is difficult to reconcile why the healthier, wealthier, better-educated, taller, and longer-lived population of the UK produced roughly a quarter as many SSCs per capita. One explanation is that remarkable age records result, not from better health or greater longevity, but from the historical accumulation of illiteracy-driven errors and the modern dynamics of poverty-driven fraud.

Thus, in Blue Zones, people aren’t necessarily living longer lives; they’re just experiencing a ‘senior moment’ with their date of birth.

Hat tip: The always skeptical, Paul Kedrosky.

In Unity in Diversity? How Intergroup Contact Can Foster Nation Building, Bazzi, Gaduh, Rothenberg, and Wong use a nation-wide natural experiment to test when diversity leads to unity and strength and when it leads to disunity and weakness.

Indonesia consists of 17,000 islands with thousands of distinct ethnic groups and hundreds of languages. The post-Colonial leaders understood the difficulty of creating a nation from such diversity and to try to birth a nation they implemented several bold policies. One such policy was creating a national language that was not the language of the majority or any large plurality. Indeed, the Indonesian national language was spoken as a mother tongue by only 5% of the native citizens but its use is required in schools and official communications. The second bold policy was the transmigration experiment. The transmigration experiment moved millions of people from the more densely populated islands to the less densely populated islands. The policy was big, between 1979 and 1984, for example, 2.5 million people were moved.

One goal of the program was to relieve population pressures and give more Indonesians their own plot of land but another goal was the creation of a unified nation.

[T]he Minister of Transmigration stated “By way of transmigration, we will try to . . . integrate all the ethnic groups into one nation, the Indonesian nation. The different ethnic groups will in the long run disappear because of integration and there will be one kind of man, Indonesian” (Hoey, 2003).

The program was voluntary. Migrants received plots of lands assigned by lottery in new villages. The way the program worked was that people of many different ethnicities and languages volunteered and (more or less, see the paper for details) lined up haphazardly to be assigned to a new village on a new island. The migrants could not choose their new village. Thus, the new villages varied in diversity: some of them were highly fractionalized (a high probability of two randomly chosen people in the village having different mother tongues) but due to bunching in the entry line, some of the villages had less diversity.

The authors show that people who for random reasons ended up in villages with a high fractionalizatin adoped more “national” or “unifying” behaviours. For example, people in high fractionalization villages were more likely to adopt the national language as the language spoken in their home (as opposed to speaking their mother tongue at home). In addition, the people in high fractionalization villages were more likely to intermarry and to give their children less ethnic names. Measures of social capital such as trust, tolerance and public goods provision were also higher in high fractionalization villages.

A simple way of summarizing these results is that people in high fractionalization villages adopted behaviours similar to those of people in cities.

Now, you might think; of course people in fractionalized villages adopt the national language because that was the only common language! There is something to that although it doesn’t explain why people adopt the national language as their home language. More importantly, the authors make a distinction between fractionalized and polarized villages. Polarized villages also have significant diversity but instead of many small groups there are a few large groups. People in polarized villages are less likely to adopt the national language as the language spoken in their home, are less likely to intermarry, less likely to give their children less ethnic names and measures of social capital such as trust, tolerance and public goods provision tend to be lower in high polarization villages.

My interpretation, which goes beyond what the authors say, is that diversity is good when it promotes individualism. A highly diverse society lets people break free from traditional constraints and develop as unique individuals. City air sets you free was a principle of law but also a recognition that in a city with many groups none could impose their will on all and thus social freedom blossomed. As Milton Friedman once said freedom promotes diversity and diversity protects freedom.

In contrast, diversity in the form of polarization, two or three big groups, makes tribalism even worse because the presence of multiple large groups increases the salience of group identity and makes people conform more and enforce conformity to their own group more, both as a kind of reactive self-defense.

One surprise is that the authors argue that ethnic segregation in high fractionalization villages tends to reduce the good effects of diversity but segregation in high polarization villages tends to ameliorate the costs of diversity; in other words, segregation significantly dampens the effects of both fractionalization and polarization. That’s surprising because other work argues that geographic segregation increases the salience of groups and group differences–if blacks and whites live in different parts of town or different castes live in different parts of town, for example, that increases the salience of racial or caste differences which might diminish if races and castes were more evenly distributed, even absent other changes.

In any case, this is a great paper taking advantage of a novel experiment in social engineering that, unusually, may have worked.