The U.S. ranks 28th in the world in achieving certain environmental goals according to the Environmental Performance Index produced by Yale and Columbia. Yesterday Mark Thoma linked to a NYTimes article which could be interpreted as implying that the U.S. should be doing better.
The analysis conducted in the reports puts the U.S. under the line. In other words, the U.S. is doing worse than expected given its income level. I wondered if this were true. Using a slightly more complicated analysis it appears that the U.S. is doing about as well as it should be doing.
First, the economic theory of achieving environmental goals considers the benefits and costs. One factor that affects the benefits of achieving environmental goals is income. Many economists believe, and have found in studies of individual and country-level demand for environmental quality, that the demand for environmental quality (i.e., benefits) increases with income. The costs of achieving environmental goals depends mostly on technology such as knowledge of the capital equipment needed to achieve environmental goals and policy instruments (e.g., marketable permits, command and control). Technology should be constant across countries.
Since one of the primary determinants of the demand for environmental quality varies across countries it is possible to estimate whether income is a determinant of how effective countries are at achieving environmental goals, measured by the EPI.
Fortunately, the EPI report includes an Excel file with all of the data necessary to estimate a simple model. I took the data and used regression analysis to estimate the effect of a country's per capita GDP (i.e., average income) on the EPI while holding constant the region of the world (i.e., Americas, European Union, etc). The EPI did not include these control variables. Here are the results:
EPI = 60.5 + .00215*(GDP/pop) - .00004*((GDP2/pop)/1000)
GDP/pop is GDP per capita and (GDP2/pop)/1000 is GDP squared divided by 1000. The regional effects are not shown but they indicate that the Americas has a higher EPI than the rest of the world. The independent variables (GDP, etc) explain about 75% of the variation in EPI, which is pretty good.
This model tells us that EPI increases with GDP but at a decreasing rate. In other words, the EPI is subject to diminishing returns. An country can improve its environmental performance with increasing gains in per capita GDP but these gains are smaller and smaller as GDP per capita increases.
One way of thinking about this model is as a production function. The input is income and the output is EPI. Plug in a country's GDP and region and the model will tell you how that country should be doing. Countries that have a positive difference between their EPI and the predicted EPI are doing better than expected. Countries that have a negative difference are doing worse than expected.
The U.S. ranks 28th in the world in EPI. The U.S. ranks 29th in the world. The U.S. EPI is 78.5 and the predicted EPI is 78.4514. The multiple regression model predicts the U.S. performance almost perfectly. The U.S. is achieving environmental goals about as well as expected given its GDP per capita.
Which countries are doing better than expected? They are all relatively poor:
Country EPI Predicted EPI 1 Gabon 73.3 57.8956 2 Lebanon 76.7 61.7754 3 Malaysia 83.3 69.4951 4 Zimbabwe 63 50.621 5 Ghana 63.1 51.4095 6 Uganda 60.8 49.8188 7 Nepal 60.2 49.3573 8 Tanzania 59 48.1737 9 Sri Lanka 64.6 54.148 10 Benin 58.4 49.2083
Which countries are doing worse than expected? Again, they are all relatively poor:
Country EPI Predicted EPI 124 Romania 56.9 66.6398 125 Turkmenistan 52.3 63.4779 126 Ethiopia 36.7 48.3823 127 Angola 39.3 51.0169 128 Mexico 64.8 77.2201 129 Mali 33.9 48.5901 130 Haiti 48.9 63.6234 131 Mauritania 32 50.4217 132 Chad 30.5 50.0206 133 Niger 25.7 48.5901
Of course, this isn't the whole story. There are a host of other variables that could potentially help explain the variation in the EPI. For example, increases in population density could limit the ability of countries to achieve environmental goals. GDP could be high (or rising rapidly) because of sustainable factors (e.g., high labor productivity) or unsustainable factors (e.g., exploitation of natural resources). Maybe I'll think about this next week.
Also, I really should read the damn report and appendices before I naively plug the numbers into the computer and make them scream! Maybe next week.
And, feel free to make unreasonable demands for additional analysis!
One more thing: why didn't the authors of the EPI report do the multiple regression analysis?
