Politics and Policy

Christie Todd-Whitman resigned last week from her position as Administrator of the Environmental Protection Agency. I was surprised she didn't resign the first time that the rug was pulled out from under her in the first weeks of her tenure. She was in the middle of a lot of scraps, but I always felt that she worked to advance her agencies missions by constructing the best policies possible based on what we know about interactions between humans and the environment. This often means moving away from a problem rather than solving it outright. She did some things I didn't agree with, but given the current administrations complete lack of understanding of the value of a healthy environment, I think she as good a job as possibly could have been done. I admire the fact that she didn't throw in the towel on many of the occasions when she was blind sided.

This is in the context of a distinction between means and ends. Whitman kept the common good that her agency was charged with in mind as she worked the politics of advancing her agency's mission. I thinks this sets her apart from much of the maneuvering that goes on in our government today. It is not clear that politics has not become the ends rather than the means.

Begin Aside
A lot of the following comes from conversations I have been having with David Gilbert-Keith.
End Aside

I read a more recent article by Lindblom this week. He continues to think that incrementalism is basically a good idea, but he is a bit more concerned about how common good is protected in the policy process. He sketches a scenario of tension among competing groups as a means to seek common ground and as a platform for developing policy. The problem comes when one group gains an overwhelming majority (the tyranny of the majority). I read an article in The New Yorker that follows this theme in the context of a discussion of Karl Rove; it seems that some of The Federalist Papers were also concerned with balancing the influence of "interests."

My question / concern is "How do we design policy processes that avoid tyrannies of interests?" As a member of an elite, it is not hard for me to entertain the value of a technocracy. As a liberal intellectual, I wonder how my far my ideas of societal good should be pressed in a highly heterogeneous society. We can no longer solve problems of difference by moving the frontier a little further west. We have reached the edges and are now filling in.

If we are going to be successful at managing Earth systems, then we will have to find ways to make trade-offs among competing interests. In building the necessary processes we will need to be careful the ends remain a healthy planet and that they don't contract to focus on strengthening the political power of "interests."

Initial Conditions

Well the little go-round I just had with html and my browser is as good a place to start as any. Bear with me as I go into a bit of detail about how my browser (Internet Explorer, you might use Netscape or any one of a number of other options but I think they all do the same basic thing). The browser does a number of things to make pages load faster. One of the things it does is that the first time it downloads a picture, it makes a temporary copy of that picture and stores it deep in your hard drive. Everytime you look at a picture on a web page, your browser looks to see if it already has a copy of that picture. If it does then it uses the copy on your hard drive rather than downloading it again - this makes pages load faster. It keeps track of pictures by their names.

Now my problem is that I often diddle with pictures as I go along but leave their names the same. Many times I have beaten my head against the wall trying to figure out why the changes I have made in the picture don't show up on my web pages. The reason is that I change the original and I change the web page version, but I forget to tell my browser to update its copy so it continues to use the copy of the initial version that it has stored on my hard drive.

The point here is that the browser initializes itself and then proceeds happily and I forget that the browser has this initial condition and beat my head against the wall.

Initial conditions are just that - they are the place that a system or a process starts from. They are the parameters of a model at the point that the model begins to run. In a baseball game, the initial conditions include the number and skills of the players available to play each position, the starting pitcher, the batting order, the umpiring staff, the size of the crowd, the weather and the score. As the game progresses each of these parameters can change and the details of how the game develops will be influenced by those changes. Changes in some parameters are more influential than others (pitcher vs crowd size).

Initial conditions have to do with time and answer the question "What is the state of the system of interest at the beginning of the time period of interest?" In the baseball example above, the period of interest was implicitly a single game. If I were interested in the history of a team or league, the parameters I choose to follow and specify as a starting point would likely be different. They would certainly include the management, the home town, and the ball park.

Begin Aside
Exercise for the reader: In the context of a single game, is the ball park an initial condition?
End Aside

Thus one person's initial conditions are another's intermediate state. In the context of weather, today's weather is an intermediate value in yesterdays 5-day forecast, but is the initial condition for today's 5-day forecast. Similarly the political state of an institution or nation provides initial conditions for the development of policy solutions.

Consider the activities of the EPA. Christie Todd-Whitman's initial conditions included US participation in the Kyoto protocol and she advanced from that condition. Unfortunately rate of change of that parameter was very high and negative. Her initial conditions also included much stronger political pressure to roll back environmental regulations that she had championed as Governor of New Jersey. Todd-Whitman's resignation changes the state of the EPA and will be part of the initial conditions that her successor inherits.

Policy Process - slight return

The figure from yesterday is kind of a joke. The joke has to do with the reduction of policy to a single instruction - "weigh all factors". Compare the following figures from Morgan and Henrion (1990):


Less Real

More Real

Morgan, M.G., M. Henrion, and M. Small, Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis, 332 pp., Cambridge University Press, New York, 1990.

Muddling Through

In 1959 Charles Lindblom published The science of "muddling through". It was destined to become a classic and muddling through is now a term of art in much of the public policy world. Lindblom's paper starts out with a sketch of what a rational process of policy making would look like. Part of the first step is to "list all related values in order of importance." This step is followed by a comprehensive analysis of all possible policy outcomes. With this thorough analysis in hand, the policy maker makes a choice that maximizes her values. Something like the following diagram (note especially the policy box toward the bottom of the diagram).

Policy Flow Diagram

This process of policy making requires assembling and integrating tremendous volumes of data and knowledge Beyond the simplest, and not very interesting, policy problems Lindblom argues that this commonly articulated approach to policy making is not even possible. Herbert Simon's bounded rationality and his work with James March on the work of organizations point out that what in fact happens is that people use a limited amount of the information that they have available at any given time to actually make decisions.

In Muddling Through, Lindblom contrasts the fully rational approach with one in which the policy maker chooses one objective that is of primary importance and then, making choices from a small portfolio of policy approaches that she has experience, designs a next step in the evolution of the policy history of her agency. Lindblom argues that in making these choices the policy maker is choosing from differences at the margin. In this incremental approach to policy making, value tradeoffs and policy tradeoffs are intertwined.

Among the advantages of this approach is the fact that values do not have to be agreed upon among policy makers. "Agreement on policy thus becomes the only practicable test of the policy's correctness." The failure of a given analyst to consider all possible values is addressed by the fact that there is a portfolio of policy making agencies, each with its own primary values; interactions at the margins works to protect undue impacts of one policy on values that are not within its immediate scope. Muddling through recognizes that policy problems will never be solved comprehensively and thus policy solutions will advance toward better states by an ongoing process of iteration.

There is a notion of democratic principles in Lindblom's model. In particular by ensuring that values are advanced and prioritized through interactions among agencies with differing sets of priorities, he seems to assume that the portfolio of agencies in some ways reflects the societal parsing of problems and priorities.

The ideas of muddling through have been expanded upon by a school of environmental management called adaptive management. The primary difference is that in adaptive management, policies goals are made explicit and policies are treated as experiments. The experiment is successful if progress is made toward the goal; thus another explicit element of adaptive management is the inclusion of a measurement program in all policy regimes. It is this measurement program that allows statement to be made about whether a policy is successful or not.

Begin Aside
Of course it is a management axiom that "if you can't measure it, you can't manage it"
End Aside

So Lindblom sketches a policy landscape that moves incrementally and recursively from its current state to a new one according to a limited set of rules. Policy agents interact in a loosely couple ways that ensure that a wide range of values are represented and advanced in aggregate. In some ways this looks alot like the cellular automata models I was constructing of earthquake processes.

Weather vs. Climate

The difference between weather and climate is summed up in the following:

Climate is what you expect, Weather is what you get
or
If you don't like the weather, wait a few days; if you don't like the climate, move

So let's deconstruct...

Expect vs Get
The statistical part of weather vs. climate is captured in this one. Simply put climate is the average weather over some period of time. I spent a string of summers at the far end of the Alaskan peninsula on a set of islands sticking out into the Pacific Ocean. There was a map of Alaskan weather that turned up on post cards and T-shirts; the weather in the Shumagins was characterized as Always Shitty (as opposed to Mostly Shitty, Occasionally Shitty etc in other parts of that great state). You get the picture. In the Shumagins we would watch the Weather Channel precursor called "Alaska Weather" it was a brilliant 1/2 hour weather forecast for the region and you could often see the low pressure systems lining up to the west along the Aleutians. The Lows would bring the weather, the lining up is the climate.

Wait vs. Move
This one captures another piece of the story. Different places have different climates, Everywhere has weather. Weather is variable on the time scale of days or weeks. At best climate is variable on time scales of years or decades. So if you don't like "Shitty" weather, it is best not to live in Alaska (if on the other hand a really good storm on a regular basis through out the summer is your cup of tea, then the Shumagins are just the place (I spent my summers there because my adviser was an Englishman (Welsh really) who like the northern bits of the UK and the Shumagins were a good subsitute and had more active tectonics (or so we thought...))). If you like a really good down-pour 'long about mid-afternoon everyday through out the summer and fall followed by a really steamy evening, then South Florida is just the place for you. Sometimes you get hurricanes in South Florida, sometimes you get thunderstorms in Alaska, but the expectation is different.

Begin Aside
So then what is all the fuss about "climate variability" that we have been making in the National Assessment of Climate Variability and Change. Well here is the rub, sometimes you don't get what you expect. We have warm winters, wet springs, dry summers, and cool falls. It all comes down to the base line. One major factor in the variability of climate is El Nino. Another may be that human activity is changing some of the fundamental dynamics that we have come to take as normal (At the 100,000yr time frame, you get climate variability on the scale of glaciers vs no glaciers). (If your mind is starting to bend that is ok) But as I love to say that is a future topic...
End Aside

This Weekend's Weather

Soccer this spring has hammered by the weather. It seems that at times in the year, spring being one of them, the weather can run in roughly 7 day cycles and this year the 1 or 2 days of that cycle that were rainy and raw tended to fall on Saturday. This weekend it looked to be another rain-out. The Weather Channel multi-day forecast called for rain on Friday tapering off into showers Saturday morning. This is a recipe for canceled games, because the fields don't drain so even if things are off by 1/2 of a day, the fields can still be rendered unusable.

But the rain never developed. In fact as the Friday got closer, the forecast changed from rain to showers, but continued to call for precipitation over the crucial field-soaking period. So Friday dawned, and sure enough the clouds came in, but noontime came and went without any rain, and then so did mid-afternoon. I went to bed with dry streets, peaked out the window at 3a (says something about my sleeping these days) and saw dry sidewalks. The sun rose behind a pretty raw overcast on Saturday, but everything was dry; so the Rockets got hammered in a 0-4 blowout (better game actually than the score).

The rain we were supposed to get was from a low that was to head northeast up the coast from the Carolinas. In this case there was also a high over New England that was to steer it out to sea. Based on watching my barometer, it looks like the high won and held the low further south than the forecasters expected. We have had seasonally pretty high pressure for the last few days.

Weather forecasting these days, at least in New York, is pretty good. The five day is not bad and by the time you get within 3 days it is pretty reliable in its main features (e.g rain vs no rain, warm vs cold). This is actually why the lack of rain this weekend impressed me. The forecast continued to call for showers long after they had failed to materialize as expected midday on Friday. The best I can do to explain it is the pressure story above and the observation that on the maps, New York was always on the northern edge of the region with predicted precipitation, so small changes in what actually happened could make a difference between getting rain and getting hammered.

In talking about the lack of rain with another soccer parent who spends a lot of time in England, she noted that in England nobody pays any attention to the weather forecast. Thus it would seem that the weather is more predictable on the East Coast of the US than it is in England (it is not that we are better at it, because the UK has one of the world's best Met Services). This is probably because the weather on the East Coast pretty much is all leftover from what was in Minnesota 24-36 hours earlier. Basically we can see it coming. England on the other hand is basically an island at the intersection of two or three serious oceans and its weather comes at it from all directions. (The geography of our weather also accounts for the pretty stable spring time period of 5-7 days.)

That said weather forecasting has still gotten pretty good. At least part of this skill is attributed to the fact that weather forecasters make literally thousands of predictions every year and with the success or failure of those predictions they learn a little bit more about how to make predictions. There are theoretical reasons why weather forecasting is not likely to go much further into the future than the 5-7 days that they now attempt. These reasons have to do with the complexity of weather systems and their sensitive dependence on initial conditions.

In fact, one of the founding scientists of the field of chaotic systems, Ed Lorenz, discovered sensitive dependence on initial conditions as he was developing the first very simple computer models of atmospheric dynamics. He was puzzled by the fact that if he restarted the model using output values of the model's parameters at some time, then the second run of the model would rapidly diverge from the first run. It turns out that in writing out the computer model's parameters, he was rounding them off and the round off mattered.

So weather predicting is probably at its limit as far as how far out it can go. Inside of the theoretical limits I expect we will get better at predicting the details of when the rain will start and stop and how much we will get etc. Next weekend looks like a soaker, but it is Memorial Day weekend so no soccer game. What the following weekend holds with respect to the weather is anyone's guess, but the twins have another commitment so the Rockets will be weakened up front and in the mid-field.