How is the U.S. really doing on the 2006 Environmental Performance Index?

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?

Comments

[joshua corning]

I wondered if this were true. Using a simple analysis it appears that the U.S. is doing about as well as it should be doing.

and john is not going to tell us what that analysis is becouse it is a secret.

Either that or he just had massive heart attack and all he could do was hit the post button before he died doing what he loves the most...blog economics.

[John Whitehead]

Ooops! Premature post! I'm still writing ...

[joshua corning]

Ooops! Premature post! I'm still writing ...

damn i was hoping you had died. Not that i want you dead or anything just that i wanted proof that my future telling powers went farther then prdicting which NFL team went to the superbowl.

Oh wait i almost forgot why i was really going to post.

Just went through the report with a glance and saw the graph on page 36.

Now just not robert an i can hate this report but the other side as well. Apparently there is very very strong corilation with high per capita gdp and high ranking on the index.

Perhaps Lomborg is right. We should give up on CO2 quotas and instead work on developing markets in the third world.

[John Whitehead]

Yep, just what I found. The graph on page 36 is a "bivariate" regression. It helps to add other variables. This puts the U.S. on the regression line and gets rid of the underperformance label. I need to add this to the post ...

[Tim Haab]

John,

Nice post.

Tim

[matthew e. kahn]

John, very nice regression work. One follow up point. The sustainability index (ESI) is built from 5 subindices.

ESI SYSTEM STRESS VULNER CAP GLOBAL

United States 53.0 60.3 27.3 73.5 78.1 38.3

Uruguay 71.8 70.5 67.3 78.0 73.6 73.6

Here I give you the data for the U.S and Uruguay. The U.S is scoring low on "STRESS" and "GLOBAL"

Looking at the table notes to the excel spreadsheet, the U.S relatively low ranking is being generated by the ecological footprint.

Anthropogenic NOx emissions per populated land area STRESS
Anthropogenic SO2 emissions per populated land area STRESS
Anthropogenic VOC emissions per populated land area STRESS
Coal consumption per populated land area STRESS
Vehicles in use per populated land area STRESS
Annual average forest cover change rate from 1990 to 2000 STRESS
Acidification exceedance from anthropogenic sulfur deposition STRESS
Percentage change in projected population 2004-2050 STRESS
Total Fertility Rate STRESS
Ecological Footprint per capita STRESS
Waste recycling rates STRESS
Generation of hazardous waste STRESS
Industrial organic water pollutant (BOD) emissions per available freshwater STRESS
Fertilizer consumption per hectare of arable land STRESS
Pesticide consumption per hectare of arable land STRESS
Percentage of country under severe water stress STRESS
Productivity overfishing STRESS
Salinized area due to irrigation as percentage of total arable land STRESS
Percentage of total forest area that is certified for sustainable management STRESS
World Economic Forum Survey on subsidies STRESS
Agricultural subsidies STRESS

Number of memberships in environmental intergovernmental organizations GLOBAL
Contribution to international and bilateral funding of environmental projects and development aid GLOBAL
Participation in international environmental agreements GLOBAL
Carbon emissions per million US dollars GDP GLOBAL
Carbon emissions per capita GLOBAL
SO2 Exports GLOBAL
Import of polluting goods and raw materials as percentage of total imports of goods and services GLOBAL

[John Whitehead]

Matthew,

I agree with your comment above and your post at Env and Urb Econ that more informative rankings are disaggregated. As you suggest, we might be doing pretty well if we exclude CO2 per capita!

John

[John Whitehead]

Joshua,

I'm trying to ignore your death wish and subtle slam on the Panthers (grrrrrrr).

John

[Dano]

I think the comments, additional analysis, and Matt's blog help inform additional thoughts. Good comment thread, and thanx John for the additional work.

The diminishing returns point is a good one; combine the 'footprint' finding with diminishing returns and it helps us consider that there is not just one solution to reducing externalities. Ecosystem managers know this. Getting decision-makers to that point is a long, tough road.

In addition, I would encourage folk to look at the indicators. It is very difficult to manage resources without knowledge and the difficulty of assessing, say, whether there is enough water has to be encapsulated in one or two metrics - (OVRSUB) here captures sub-metrics that determine whether the ecosystem gets enough water after human use.

Decision-makers at local levels can use these metrics - I'm thinking Klamath Basin and Great Central Valley irrigators in CA.

Best,

D

P.S., Carolina had too many injuries to compete.

[Robert Schwartz]

"One more thing: why didn't the authors of the EPI report do the multiple regression analysis?"

Because all they really cared about was bashing the US.

The real question is why should I care. To me it was just an arbitrary assemblage of numbers that reached a predetermined conclusion.

The first task in assessing this thing is to figure out why these numbers represent real world phenomena that measure something we ought to care about.

Basically this is an exercise in adding apples and oranges to come up with fruit salad. We still don't know if it is tasty or nutritious.

[joshua corning]

Just thought of something.

The diminishing returns could just be an artifact of lower GDP countries leap froging in technological gains.

ie as GDP rises technology becomes more available that benifits the enviornment but the higher GDP nations can only gain by inventing new stuff which is slower then the adaption of technology already developed. This would bunch up the curve at the top making it look like a diminishing return...my guess would be that the liniar slope at the top represents the true relationship of gnp and enviornmental improvement.

[Dano]

The real question is why should I care. To me it was just an arbitrary assemblage of numbers that reached a predetermined conclusion.

IMHO, the real question is should EPIs play to people who don't care about the environment. Of course not. That's why you're grumpy.

The first task in assessing this thing is to figure out why these numbers represent real world phenomena that measure something we ought to care about.

Well, that's not your task. And they do. These are decent indicators. One can quibble ad infinitum about quibbling bits, but you still have to manage.

The first task is to assemble indicators for which you have data, because that indicates caring.

HTH,

D