I really don’t understand the results of point 1. I guess I miss something.
Easterlin’s estimates include many countries, including a significant number of economically strong countries, right? And cash transfers are directed to the very poor, aren’t they? If so, I really don’t understand how the increase in happiness due to cash transfers is not much higher than that of Easterlin’s estimates (or at least significantly higher if only a small fraction of the countries included are rich). Isn’t it well established that the effect of wealth in happiness is much stronger for poorer people? What am I missing?
There are two different things you could mean by “effect of wealth in happiness is much stronger for poorer people”:
Giving $1000 to a family in Kenya brings them much more life satisfaction than giving $1000 to a family in the United States:
This is uncontroversial. Since Easterlin and O’Connor’s regressions look at the impact of percent change in GDP, they are assuming a logarithmic utility function. Therefore, a $1000 increase would represent something like a 100% GDP increase, while it would only represent something like 1.5% in the US. So the impact on happiness in Kenya would be much higher to be consistent with the regression.
Utility functions aren’t actually logarithmic. A 1% increase in income should bring a lot of happiness in Kenya, but almost none in the United States, because the United States has maxed out:
I think Easterlin, O’Connor and some other economists believe this. Others don’t. I ran a quick regression of my own on Easterlin’s data, and it suggests that a 1% increase in income for developed countries actually increases happiness more than a 1% increase in LMICs. So that would lead us to expect that the impact from cash transfers might actually be a bit smaller than the results of Easterlin-style regression.
Thanks for the answer. I was referring to 2. I thought it was something we’ll established. But I think I was so convinced of it because I did not think much about and I probably conflated it with 1 as well.
I really don’t understand the results of point 1. I guess I miss something.
Easterlin’s estimates include many countries, including a significant number of economically strong countries, right? And cash transfers are directed to the very poor, aren’t they? If so, I really don’t understand how the increase in happiness due to cash transfers is not much higher than that of Easterlin’s estimates (or at least significantly higher if only a small fraction of the countries included are rich). Isn’t it well established that the effect of wealth in happiness is much stronger for poorer people? What am I missing?
There are two different things you could mean by “effect of wealth in happiness is much stronger for poorer people”:
Giving $1000 to a family in Kenya brings them much more life satisfaction than giving $1000 to a family in the United States: This is uncontroversial. Since Easterlin and O’Connor’s regressions look at the impact of percent change in GDP, they are assuming a logarithmic utility function. Therefore, a $1000 increase would represent something like a 100% GDP increase, while it would only represent something like 1.5% in the US. So the impact on happiness in Kenya would be much higher to be consistent with the regression.
Utility functions aren’t actually logarithmic. A 1% increase in income should bring a lot of happiness in Kenya, but almost none in the United States, because the United States has maxed out: I think Easterlin, O’Connor and some other economists believe this. Others don’t. I ran a quick regression of my own on Easterlin’s data, and it suggests that a 1% increase in income for developed countries actually increases happiness more than a 1% increase in LMICs. So that would lead us to expect that the impact from cash transfers might actually be a bit smaller than the results of Easterlin-style regression.
Thanks for the answer. I was referring to 2. I thought it was something we’ll established. But I think I was so convinced of it because I did not think much about and I probably conflated it with 1 as well.