[FRIAM] runaway happiness _and_ Hail Satan

[Marcus Daniels]

The Bay Area is interesting in that there are some clear tiers.   There are areas with retired NIMBYs that can continue their way of living indefinitely thanks to Proposition 13 which limits the rate of growth of property taxes.   They own their homes where real estate is very valuable.  The main task for them is to keep outsiders away.  As they get older, they can move out of state or into assisted living and probably be ok.   Increasingly tech people are buying these properties and moving to much higher property tax burdens as the assessments go up.   Even though they have much higher salaries than the previous generation their costs are much higher too.   Meanwhile there are poorer people in cities farther out that commute in, sometimes long distances.   They somehow absorb the escalation in the price of everything.   Here I think less money means more misery, and more money means securing the nicest, safest places to live.   The very high salaried may find they have pushed to hard into work they really care nothing about, or work they deep down know causes harm.   That could also lead to burnout.  

-----Original Message-----
From: Friam <friam-bounces at redfish.com> On Behalf Of glen
Sent: Thursday, April 20, 2023 7:38 AM
To: friam at redfish.com
Subject: [FRIAM] runaway happiness _and_ Hail Satan

Income and emotional well-being: A conflict resolved
https://www.pnas.org/doi/10.1073/pnas.2208661120

> Do larger incomes make people happier? Two authors of the present paper have published contradictory answers. Using dichotomous questions about the preceding day, [Kahneman and Deaton, Proc. Natl. Acad. Sci. U.S.A. 107, 16489–16493 (2010)] reported a flattening pattern: happiness increased steadily with log(income) up to a threshold and then plateaued. Using experience sampling with a continuous scale, [Killingsworth, Proc. Natl. Acad. Sci. U.S.A. 118, e2016976118 (2021)] reported a linear-log pattern in which average happiness rose consistently with log(income). We engaged in an adversarial collaboration to search for a coherent interpretation of both studies. A reanalysis of Killingsworth’s experienced sampling data confirmed the flattening pattern only for the least happy people. Happiness increases steadily with log(income) among happier people, and even accelerates in the happiest group. Complementary nonlinearities contribute to the overall linear-log relationship. We then explain why Kahneman and Deaton overstated the flattening pattern and why Killingsworth failed to find it. We suggest that Kahneman and Deaton might have reached the correct conclusion if they had described their results in terms of unhappiness rather than happiness; their measures could not discriminate among degrees of happiness because of a ceiling effect. The authors of both studies failed to anticipate that increased income is associated with systematic changes in the shape of the happiness distribution. The mislabeling of the dependent variable and the incorrect assumption of homogeneity were consequences of practices that are standard in social science but should be questioned more often. We flag the benefits of adversarial collaboration.


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