We really are struggling to find a decent measure of poverty for our study. It’s an age old problem. The World Bank, IMF, United Nations and other such organisations base many of their country indicators on factors such as infrastructure, access to education, health and measures of income. Government departments can fairly easily provide these numbers, and so we have loads of info out there at the national and sub-national scale on these types of capital. However, we’ve discovered a strong allergy to such indicators in our region, and if we really want to understand how ecosystem services are related to poverty and poverty alleviation, we’ve been encouraged to take on a definition of poverty that embraces calidad de vida (quality of life). Nice in theory, but in practice pretty difficult to quantify.
But there is at least a glimmer of hope thanks to a new paper I stumbled upon that develops a worldwide life satisfaction index. The authors generate a score for each country of the world based on actual life satisfaction surveys, or in their absence and of most interest to us, regression techniques for approximating life satisfaction from human, natural and socio-political capital indicators (of the kind that are widely available). This might just be a way of moving towards quality of life indicators without having to do endless surveys in the region. In the modelled life satisfaction, Nordic countries came out best, and eastern European countries like Moldova, Ukraine and Belarus came out worst, alongside Zimbabwe for fairly obvious reasons. For our region, we had Brazil (7.09), Colombia (6.80), Venezuela (6.76), Ecuador (6.75), Bolivia (6.40) and Peru (6.31). The trick now is reducing the scale to the sub-national to really get to grips with how the state of ecosystem services relate to life satisfaction.
On a side note, quite astonishing to me was the fact that there have been 4,300 articles published that discuss “life satisfaction” or “subjective well-being”, and many of these are in the fantastically titled Journal of Happiness Studies. No sign of a Journal of Sadness studies fortunately.
And finally, it is worth a mention on how they actually calculate life satisfaction. Well, there is a reason that it is also known as subjective well-being. In a random survey, people are asked:
In general, would you say that you are satisfied with your life?
Given that, I cannot for the life of me understand how the Brits got a score of 7.40. They must have held the survey down the pub at 10pm.
Yes, a very interesting paper. The “small area estimation” technique could be one way to reduce the scale to sub-national. If we had a sufficient number of the life satisfaction surveys, we could find the statistical relationship with variables in a census. Then estimate the life satisfaction score for small areas (canton, municipio, etc). In theory this could work, but in practice you need a good survey.
Here is a paper on another measure of poverty that shows some promise (although perhaps not much):
Krishna, Anirudh. 2007. For Reducing Poverty Faster: Target Reasons Before People. World Development. 35(11):1947-1969.
The “stages-of-progress” methodology for measuring poverty is a promising framework (Krishna, 2007). Instead of assessing the income, consumption and assets of people, the method focuses on the reasons people either fall into poverty or escape it. There could be substantial changes in who is becoming poor or who is escaping poverty, even when the poverty rate remains unchanged. But the main advantage of the method is that it suggests possible interventions. By targeting the reasons people become more or less poor, not people’s income or consumption level, this method suggests the actions and policies needed for alleviating poverty.
One potential exit path could be payment for environmental services.
The problem is how you would collect data on this. The method can be applied in household surveys. But there is no standard survey that includes the data you would need. Crowd-sourcing? Difficult to see how that would work.