That current measures of GDP do not reflect important subjective and qualitative parameters that define the state of the society and its citizens, is well acknowledged. The US Bureau of Labor Statistics (BLS) has been collecting National Time Accounting data through its American Time Use Survey (ATUS) for some time, and there have been numerous studies indicating how these measures give a different perspective on debates about economic growth.
Robert H Frank summarizes this debate in his NYT Economic View column. He sums up the views of both the opponents and supporters of the traditional model of calculating GDP based economic growth. This post examined some of the problems associated with simple "happiness" or "life satisfaction" surveys.
Alan Krueger, Daniel Kahneman et al have come up with what they called the Princeton Affect and Time Survey (PATS), designed to produce a “U-index” to measure the proportion of time individuals spend in an “unpleasant” or “undesirable” or “unhappy” state, which they tried out with a telephone survey of 4,000 persons. The U-index measures the proportion of time an individual spends in an unpleasant state and is an ordinal measure at the level of feelings.
They have co-authored an NBER working paper in which they describe National Time Accounting as the "currency of life". They define National Time Accounting (NTA) as "a set of methods for measuring, comparing and analyzing how people spend and experience their time - across countries, over historical time, or between groups of people within a country at a given time." The NTA provides a method for tracking time allocation and assessing whether people are experiencing their daily lives in more or less enjoyable ways.
Their approach is based on "evaluated time use, or the flow of emotional experience during daily activities", and seeks to measure "individuals’ emotional experiences and time use". They write, "We illustrate NTA with: (1) a new cross-sectional survey on time use and emotional experience for a representative sample of 4,000 Americans; (2) historical data on the amount of time devoted to various activities in the United States since 1965; and (3) a comparison of time use and well-being in the United States and France. In our applications, we focus mainly on the U-index, a measure of the percentage of time that people spend in an unpleasant state, defined as an instance in which the most intense emotion is a negative one. (A "Misery Index") The U-index helps to overcome some of the limitations of interpersonal comparisons of subjective well-being."
Some of the activities monitored to collect time use data in the study include
1. Commuting to work
2. Working in your main job
3. Having lunch on a workday
4. Socializing at work
5. Commuting to home from work
6. Socializing with friends
7. Talking on the phone at home
8. Taking care of your children
9. Doing housework
10. Cooking/preparing food
11. Having dinner on a workday
12. Relaxing at home
13. Watching TV
The psychological responses each of these activities evoke in individuals are mapped in an ordinal ranking in the range of extreme displeasure to extreme pleasure, and added up after assigning appropriate weights to measure the U-index.
Angus Deaton captures the happiness-GDP comparison for different countries in this plot using Gallup world poll data.
In the graph, each circle is a country, with diameter proportional to population. The horizontal axis is national per-capita GDP in 2003 (the nearest year for which there is complete data) measured in purchasing power parity (PPP) dollars at 2000 prices, while the vertical axis is a country's average life-satisfaction rating. Most of the countries of sub-Saharan Africa are on the bottom left, India and China are the two large circles near the left, the western European countries appear near the upper right, and the United States is the large country on the top right.
Deaton writes, "As the graph indicates, life satisfaction is higher in countries with higher GDP per head. The slope is steepest among the poorest countries, where income gains are associated with the largest increases in life satisfaction, but it remains positive and substantial even among the rich countries; it is not true that there is some critical level of GDP per capita above which income has no further effect on life satisfaction. Instead, each doubling of income adds about the same amount to life satisfaction, across poor and rich countries alike."
Deaton also calls attention to the recent study of Andrew Clark, Paul Frijters, and Michael Shields, which found that life satisfaction is sensitive to respondents' income relative to those with whom they most closely associate, which implies that there should be no relation between average national life satisfaction and national income, unless there is some other aspect of national income that raises everyone's life satisfaction together. This, Deaton concludes, will make the Danes to continue to maintain an average rating of 8 as national income rises, provided they stay in the same position in the global income rankings.