Wednesday, September 29, 2010

Beyond GDP Part II

Back in July, I highlighted an article that argued for a more holistic approach to measuring changes in human welfare that goes beyond simple income/output based measures such as GDP. Now along comes this new paper by Charles Jones and Peter Klenow of Stanford University that takes the idea a step further (abstract):

Beyond GDP? Welfare across Countries and Time

We propose a simple summary statistic for a nation's flow of welfare, measured as a consumption equivalent, and compute its level and growth rate for a broad set of countries. This welfare metric combines data on consumption, leisure, inequality, and mortality. Although it is highly correlated with per capita GDP, deviations are often economically significant: Western Europe looks considerably closer to U.S. living standards, emerging Asia has not caught up as much, and many African and Latin American countries are farther behind due to lower levels of life expectancy and higher levels of inequality. In recent decades, rising life expectancy boosts annual growth in welfare by more than a full percentage point throughout much of the world. The notable exception is sub-Saharan Africa, where life expectancy actually declines.

The authors use a consumption-equivalent utility function to compare welfare across countries and through time, incorporating not just consumption but life expectancy, leisure time, and income inequality. The results are fascinating (quoting from the paper):

  1. Key Point 1: GDP per person is an excellent indicator of welfare across the broad range of countries: the two measures have a correlation of 0.95. Nevertheless, for any given country, the difference between the two measures can be important. Averaged across 134 countries, the typical deviation is about 46%.
  2. Key Point 2: Average Western European living standards appear much closer to those in the United States when we take into account Europe’s longer life expectancy, additional leisure time, and lower levels of inequality.
  3. Key Point 3: Many developing countries — including much of sub-Saharan Africa, Latin America, southern Asia, and China—are poorer than incomes suggest because of a combination of shorter lives and extreme inequality.
  4. Key Point 4: Welfare growth averages 2.54%between 1980 and 2000, versus income growth of 1.80%. A large boost from growth in life expectancy, of over one percentage point per year, is partially offset by declining consumption shares and rising inequality.
  5. Key Point 5: The mean absolute deviation between welfare growth and income growth is 0.99 percentage points.

Some examples illustrate the points that the authors are making:

  1. France has a GDP per capita about 70% of the United States, but welfare is approximately the same because the French have longer life expectancy and greater leisure hours.
  2. Singapore has a GDP per capita about 82.9% of the United States but has a welfare level less than half of that, due to lower levels of consumption and much higher working hours.

The full results can be obtained through this link (excel spreadsheet).

How does Malaysia rate? Badly – the authors’ welfare measure suggests a welfare level about a sixth of the US, compared to per capita GDP which is higher at about a third. In Malaysia’s case (as in Singapore’s) this has a lot to do with high investment rates relative to consumption, but Malaysia also has a lower life expectancy (72.6 versus 77 in the US and 78.1 in Singapore) while also having worse income inequality and long working hours (1313 hours per annum versus 1186 for the US and 1375 for Singapore). Looking at growth over time, Malaysian GDP per capita and welfare have risen more or less in tandem, though welfare lags slightly.

Worth a full read, even if you don’t quite follow the mathematics of it.

Technical Notes:

Jones, Charles I., & Peter J. Klenow, "Beyond GDP? Welfare across Countries and Time", NBER Working Paper No. 16352, September 2010

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