A long-run measure of country-level subjective wellbeing

Thanks to the Maddison project, we have long-run measures of GDP that go back to 1820 for many countries, and all the way back to 1 C.E. for some countries. However, it is widely acknowledged that GDP is an imperfect measure of wellbeing - at which point, everyone quotes Robert Kennedy's speech at the University of Kansas in 1968:

The gross national product does not allow for the health of our children, the quality of their education, or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages; the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage; neither our wisdom nor our learning; neither our compassion nor our devotion to our country; it measures everything, in short, except that which makes life worthwhile.

So, what do we do if we want an alternative measure of wellbeing? Many researchers have begun making use of measures of subjective wellbeing (e.g. life satisfaction, or happiness), notwithstanding recently identified problems with these measures (e.g. see this recent post). But the problem is that these measures have only been collected across a few countries, and only since the 1970s (e.g. see the World Database of Happiness).

A recent article by Thomas Hills (University of Warwick), Eugenio Proto (University of Glasgow), Daniel Sgroi (University of Warwick), and Chanuki Illushka Seresinhe (Alan Turing Institute at the British Library), published in the journal Nature Human Behaviour (ungated earlier version here), attempts to fill this gap. They use data from around 8 million books in the Google Books corpus, published in the U.S., U.K., Germany, and Italy. They analysed the sentiment of words in these books:

We use the words published in these books to compute subjective wellbeing at a given time by using affective word norms to derive sentiment from text. Affective word norms are ratings provided by groups of individuals who examine a list of words and rate them on their valence, indicating how good or bad individual words make them feel.

They then validate their data by showing that it correlates with life satisfaction data from the Eurobarometer survey since the 1970s, and that it seems to pick up key expected trends in life satisfaction over the whole period from 1820. These includes decreases in life satisfaction in all four countries during World War I, for instance.

They then demonstrate some other results using their data, such as the following (based on a regression of life expectancy and GDP growth on their National Valence Index measure):

...one extra year of life expectancy is worth as much as 4.3% annual growth in GDP per capita.

There is a problematic issue that I can see with this data. The meaning of words changes subtly over time, and no doubt the sentiment of words also changes over time. So, measuring the sentiment over nearly two centuries, using word norms from modern times, has the potential to lead to bias. However, it is a measure we didn't have before, and all measures have their limitations. It seems to me that there is a lot of potential for using this measure in some interesting research, and the index can be downloaded from Github here.

[HT: The Economist]