Category: Policy

Vi Hart on positive feedback driving polarization

Vi Hart’s interesting comments on the dynamics of political polarization, following the release of an innocuous video:

I wonder what made those commenters think we have opposite views; surely it couldn’t just be that I suggest people consider the consequences of their words and actions. My working theory is that other markers have placed me on the opposite side of a cultural divide that they feel exists, and they are in the habit of demonizing the people they’ve put on this side of their imaginary divide with whatever moral outrage sounds irreproachable to them. It’s a rather common tool in the rhetorical toolset, because it’s easy to make the perceived good outweigh the perceived harm if you add fear to the equation.

Many groups have grown their numbers through this feedback loop: have a charismatic leader convince people there’s a big risk that group x will do y, therefore it seems worth the cost of being divisive with those who think that risk is not worth acting on, and that divisiveness cuts out those who think that risk is lower, which then increases the perceived risk, which lowers the cost of being increasingly divisive, and so on.

The above feedback loop works great when the divide cuts off a trust of the institutions of science, or glorifies a distrust of data. It breaks the feedback loop if you act on science’s best knowledge of the risk, which trends towards staying constant, rather than perceived risk, which can easily grow exponentially, especially when someone is stoking your fear and distrust.

If a group believes that there’s too much risk in trusting outsiders about where the real risk and harm are, then, well, of course I’ll get distrustful people afraid that my mathematical views on risk/benefit are in danger of creating a fascist state. The risk/benefit calculation demands it be so.

A conversation about infrastructure

A conversation about infrastructure, with Carter Williams of iSelect and me:

The $3 Trillion Problem: Solving America’s Infrastructure Crisis

I can’t believe I forgot to mention one of the most obvious System Dynamics insights about infrastructure:

There are two ways to fill a leaky bucket – increase the inflow, or plug the outflows. There’s always lots of enthusiasm for increasing the inflow by building new stuff. But there’s little sense in adding to the infrastructure stock if you can’t maintain what you have. So, plug the leaks first, and get into a proactive maintenance mode. Then you can have fun building new things – if you can afford it.

Dynamics of Term Limits

I am a little encouraged to see that the very top item on Trump’s first 100 day todo list is term limits:

* FIRST, propose a Constitutional Amendment to impose term limits on all members of Congress;

Certainly the defects in our electoral and campaign finance system are among the most urgent issues we face.

Assuming other Republicans could be brought on board (which sounds unlikely), would term limits help? I didn’t have a good feel for the implications, so I built a model to clarify my thinking.

I used our new tool, Ventity, because I thought I might want to extend this to multiple voting districts, and because it makes it easy to run several scenarios with one click.

Here’s the setup:

structure

The model runs over a long series of 4000 election cycles. I could just as easily run 40 experiments of 100 cycles or some other combination that yielded a similar sample size, because the behavior is ergodic on any time scale that’s substantially longer than the maximum number of terms typically served.

Each election pits two politicians against one another. Normally, an incumbent faces a challenger. But if the incumbent is term-limited, two challengers face each other.

The electorate assesses the opponents and picks a winner. For challengers, there are two components to voters’ assessment of attractiveness:

  • Intrinsic performance: how well the politician will actually represent voter interests. (This is a tricky concept, because voters may want things that aren’t really in their own best interest.) The model generates challengers with random intrinsic attractiveness, with a standard deviation of 10%.
  • Noise: random disturbances that confuse voter perceptions of true performance, also with a standard deviation of 10% (i.e. it’s hard to tell who’s really good).

Once elected, incumbents have some additional features:

  • The assessment of attractiveness is influenced by an additional term, representing incumbents’ advantages in electability that arise from things that have no intrinsic benefit to voters. For example, incumbents can more easily attract funding and press.
  • Incumbent intrinsic attractiveness can drift. The drift has a random component (i.e. a random walk), with a standard deviation of 5% per term, reflecting changing demographics, technology, etc. There’s also a deterministic drift, which can either be positive (politicians learn to perform better with experience) or negative (power corrupts, or politicians lose touch with voters), defaulting to zero.
  • The random variation influencing voter perceptions is smaller (5%) because it’s easier to observe what incumbents actually do.

There’s always a term limit of some duration active, reflecting life expectancy, but the term limit can be made much shorter.

Here’s how it behaves with a 5-term limit:

terms

Politicians frequently serve out their 5-term limit, but occasionally are ousted early. Over that period, their intrinsic performance varies a lot:

attractiveness

Since the mean challenger has 0 intrinsic attractiveness, politicians outperform the average frequently, but far from universally. Underperforming politicians are often reelected.

Over a long time horizon (or similarly, many districts), you can see how average performance varies with term limits:

long

With no learning, as above, term limits degrade performance a lot (top panel). With a 2-term limit, the margin above random selection is about 6%, whereas it’s twice as great (>12%) with a 10-term limit. This is interesting, because it means that the retention of high-performing politicians improves performance a lot, even if politicians learn nothing from experience.

This advantage holds (but shrinks) even if you double the perception noise in the selection process. So, what does it take to justify term limits? In my experiments so far, politician performance has to degrade with experience (negative learning, corruption or losing touch). Breakeven (2-term limits perform the same as 10-term limits) occurs at -3% to -4% performance change per term.

But in such cases, it’s not really the term limits that are doing the work. When politician performance degrades rapidly with time, voters throw them out. Noise may delay the inevitable, but in my scenario, the average politician serves only 3 terms out of a limit of 10. Reducing the term limit to 1 or 2 does relatively little to change performance.

Upon reflection, I think the model is missing a key feature: winner-takes-all, redistricting and party rules that create safe havens for incompetent incumbents. In a district that’s split 50-50 between brown and yellow, an incompetent brown is easily displaced by a yellow challenger (or vice versa). But if the split is lopsided, it would be rare for a competent yellow challenger to emerge to replace the incompetent yellow incumbent. In such cases, term limits would help somewhat.

I can simulate this by making the advantage of incumbency bigger (raising the saturation advantage parameter):

attractiveness2

However, long terms are a symptom of the problem, not the root cause. Therefore it probably necessary in addition to address redistricting, campaign finance, voter participation and education, and other aspects of the electoral process that give rise to the problem in the first place. I’d argue that this is the single greatest contribution Trump could make.

You can play with the model yourself using the Ventity beta/trial and this model archive:

termlimits4.zip

Tax cuts visualized

Much has been made of the fact that Trump’s revised tax plan cuts its implications for deficits in half (from ten to five trillion). Oddly, there’s less attention to the equity implications, which border on the obscene. Trump’s plan gives the top bracket a tax cut ten times bigger (as percentage of income) than that given to the bottom three fifths of the income distribution.

That makes the difference in absolute $ tax cuts between the richest and poorest pretty spectacular – a factor of 5000 to 10,000:

trumptax

Trump tax cut distribution, by income quantile.

To see one pixel of the bottom quintile’s tax cut on this chart, it would have to be over 5000 pixels tall!

For comparison, here are the Trump & Clinton proposals. The Clinton plan proposes negligible increases on lower earners (e.g., $4 on the bottom fifth) and a moderate increase (5%) on top earners:

trumpclinton

Trump & Clinton tax cut distributions, by income quantile.

Sources:

http://www.taxpolicycenter.org/publications/analysis-donald-trumps-tax-plan/full

http://taxfoundation.org/article/details-and-analysis-donald-trump-tax-reform-plan-september-2016

http://www.taxpolicycenter.org/publications/analysis-hillary-clintons-tax-proposals/full

Structure First!

One of the central tenets of system dynamics and systems thinking is that structure causes behavior. This is often described as an iceberg, with events at as the visible tip, and structure as greater submerged bulk. Patterns of behavior, in the middle, are sequences of events that may signal the existence of the underlying structure.

The header of the current Wikipedia article on the California electricity crisis is a nice illustration of the difference between event and structural descriptions of a problem.

The California electricity crisis, also known as the Western U.S. Energy Crisis of 2000 and 2001, was a situation in which the United States state of California had a shortage of electricity supply caused by market manipulations, illegal[5] shutdowns of pipelines by the Texas energy consortium Enron, and capped retail electricity prices.[6] The state suffered from multiple large-scale blackouts, one of the state’s largest energy companies collapsed, and the economic fall-out greatly harmed GovernorGray Davis’ standing.

Drought, delays in approval of new power plants,[6]:109 and market manipulation decreased supply.[citation needed] This caused an 800% increase in wholesale prices from April 2000 to December 2000.[7]:1 In addition, rolling blackouts adversely affected many businesses dependent upon a reliable supply of electricity, and inconvenienced a large number of retail consumers.

California had an installed generating capacity of 45GW. At the time of the blackouts, demand was 28GW. A demand supply gap was created by energy companies, mainly Enron, to create an artificial shortage. Energy traders took power plants offline for maintenance in days of peak demand to increase the price.[8][9] Traders were thus able to sell power at premium prices, sometimes up to a factor of 20 times its normal value. Because the state government had a cap on retail electricity charges, this market manipulation squeezed the industry’s revenue margins, causing the bankruptcy of Pacific Gas and Electric Company (PG&E) and near bankruptcy of Southern California Edison in early 2001.[7]:2-3

The financial crisis was possible because of partial deregulation legislation instituted in 1996 by the California Legislature (AB 1890) and Governor Pete Wilson. Enron took advantage of this deregulation and was involved in economic withholding and inflated price bidding in California’s spot markets.[10]

The crisis cost between $40 to $45 billion.[7]:3-4

This is mostly a dead buffalo description of the event:

ca_elec_dead_buffalo

It offers only a few hints about the structure that enabled these events to unfold. It would be nice if the article provided a more operational description of the problem up front. (It does eventually get there.) Here’s a stab at it:

ca_elec_structure

A normal market manages supply and demand through four balancing loops. On the demand side, in the short run utilization of electricity-consuming devices falls with increasing price (B1). In the long run, higher prices also suppress installation of new devices (B2). In parallel on the supply side, higher prices increase utilization in the short run (B4) and provide an incentive for capacity investment in the long run (B3).

The California crisis happened because these market-clearing mechanisms were not functioning. Retail pricing is subject to long regulatory approval lags, so there was effectively no demand price elasticity response in the short run, i.e. B1 and B2 were ineffective. The system might still function if it had surplus capacity, but evidently long approval delays prevented B3 from creating that. Even worse, the normal operation of B4 was inverted when Enron amassed sufficient market power. That inverted the normal competitive market incentive to increase capacity utilization when prices are high. Instead, Enron could deliberately lower utilization to extract monopoly prices. If any of B1-B3 had been functioning, Enron’s ability to exploit B4 would have been greatly diminished, and the crisis might not have occurred.

I find it astonishing that deregulation created such a dysfunctional market. The framework for electricity markets was laid out by Caramanis, Schweppe, Tabor & Bohn – they literally wrote the book on Spot Pricing of Electricity. Right in the introduction, page 5, it cautions:

Five ingredients for a successful marketplace are

  1. A supply side with varying supply costs that increase with demand
  2. A demand side with varying demands which can adapt to price changes
  3. A market mechanism for buying and selling
  4. No monopsonistic behavior on the demand side
  5. No monopolistic behavior on the supply side

I guess the market designers thought these were optional?

An unwinnable arms race

It seems that we Americans are engaged in an arms race with our own government. Bozeman is the latest to join in, with its recent acquisition of an armored vehicle:

armoredArms races are an instance of the escalation archetype, where generally the only winning strategy is not to play, but it’s particularly foolish to run an arms race against ourselves.

Here’s how it works:
WeaponEscalation
The police (left) and citizens (right) each have stocks of weapons and associated skills and attitudes. Each “side” adjusts those stocks toward a desired level, which is set by various signals.

Citizens, for example, see media coverage of school shootings and less spectacular events, and arm themselves against their fellow citizens and against the eventuality of totalitarian government. A side effect of this is that, as the general availability of weapons increases, the frequency and scale of violent conflict increases, all else equal. This in itself reinforces the citizen perception of the need to arm.

The government (i.e. the police) respond to the escalation of violent conflict in their own locally rational way as well. They acquire heavy weapons and train tactical teams. But this has a number of side effects that further escalate conflict. Spending and training on paramilitary approaches necessarily comes at the expense of non-violent policing methods.

… Lester said he’s concerned about the potential overuse of such commanding vehicles among some police departments, a common criticism in the wake of the Ferguson protests.“When you bring that to the scene,” he said, “you bring an attitude that’s not necessarily needed.”

Accidents happen, and the mere availability of heavy armor encourages overkill, as we saw in Ferguson. And police departments are not immune to keeping up with the Joneses:

“For a community our size, we’re one of the last communities that does not have an armored rescue vehicle,” he said.

This structure is a nest of reinforcing feedback loops – I haven’t labeled them, because every loop above is positive, except the two inner loops in the acquisition/militarization stock control processes.

Strangely, this is happening at a time in which violent crime rates are trending down. This means that the driver of escalation must be more about perceptions and fear of potential harm than about actual shooting incidents.

Carrying the escalation to its conclusion, one of two things has to happen. The police win, and we have a totalitarian state. Or, the citizens win, and we have stateless anarchy. Neither outcome is really a “win.”

The alternative is to reverse the escalation, and make the reinforcing loops virtuous rather than vicious cycles. This is harder than it should be, because there’s a third party involved, that profits from escalation (red):
EscalationLobbying
Arms makers generate revenue from weapon sales and service, and reinvest that in marketing, to increase both parties desired weapons, and in lobbying to preserve the legality of assault weapons and fund the grant programs that enable small towns to have free armor.
EscalationEngagement
Fortunately, there is a remedy. Voters can (at least indirectly) fire the Bozeman officials who “forgot” to run the armored vehicle acquisition through any public process, and defund the Homeland (In)Security programs that bring heavy weapons to our doorsteps.

The difficult pill to swallow is that, for this to work, citizens have to de-escalate too. Reinstating the assault weapons ban is messy, and perhaps ineffective given the large stock of weapons now widely distributed. Maybe the first change should be cultural: recognizing that arming oneself to the teeth is a fear-driven antisocial response to our situation, and that ballots are a better solution than bullets.

GDP's … something?

While the government is shut down, it seems like a good time for a rousing round of Alan Atkisson‘s GDP Song:

The shutdown means GDP measurements are on ice, which is not all bad, though we can expect a 15 basis point drag on GDP per week to include some real harm.

Shutting down our measurement systems strikes me as alarmingly close to turning off the instruments on the flight deck of a plane, due to a route dispute between the pilot and copilot.

Tax time

It’s time* for environmentalists (and everyone else) to give up on a myriad of second-best regulatory policies and push for a simple emissions price (i.e. a carbon tax). The latest reason: green subsidies are unraveling under adverse energy market conditions. There are many others:

All of the above have some role to play, but without prices as a keystone economic signal, they’re fighting the tide. Moreover, together they have a large cost in administrative complexity, which gives opponents a legitimate reason to whine about bureaucracy and promotes regulatory capture.

If all the effort that’s now expended in fragmented venues to create these policies were focused on one measure, would it be enough to pass a significant emissions price with fair revenue recycling and a border adjustment? I don’t know for sure, but I’d like to see us try.

* Actually, I think it was time for a carbon tax at least 20 years ago.

EU ETS on the ropes

The EU declined backloading, a deferral of permit auctions that would have supported prices in the Emissions Trading System (ETS).

This is described imminent collapse to the system, threatening the achievement of emissions targets. Perhaps a political collapse is imminent – not my department – but the idea that low emissions prices threaten the system is a bit odd. The ETS price is a feedback mechanism. Low prices are a symptom, indicating that the marginal cost of meeting targets is extremely low. That should be a cause for celebration (except for traders).

For the umpteenth time, this shows the difficulty of running a system that invites wrangling over allocation and propagates noise from the economy into a market.

Meanwhile, carbon taxes grind away at their job.

Greek oil taxes – the real story

A guest post from Ventana colleague Marios Kagarlis, who writes about the NYT article on Greek heating oil taxes:

The problems in Greece are interdependent and all have their roots at the fact that the model of government that has been the status quo in Greece since WWII isn’t working and needs radical change, but the people who run the system know no other way, so the problems keep compounding with no solution in sight.There used to be two tiers of taxation for oil: one was for heating oil, which was relatively low, and the other was for oil used for all other purposes (e.g. for diesel cars etc) which was taxed at about 100% over the fuel cost.

Because of the inability of the government institutions to enforce the laws in Greece (which on paper are tough but in practice are not enforced because the system is incompetent), there has been widespread abuse of this: from refineries to gas stations, many oil merchants have been branding diesel as heating oil to evade the tax, and then selling at as non-heating oil, doubling their profit and ripping off both the consumers and the government.

The government has for years been attempting (supposedly) to crack down on this, with pitiable results. The international lenders have demanded from the Greek government, as a precondition for the continuation of the bailout installments paid every now and then (essentially going in their entirety toward servicing past debt, as opposed to relieving the economy), to crack down on tax evasion via illegal diesel sales of ‘heating oil’ as non-heating diesel. Because the tax collection system is broken and cannot control the diesel market or collect the taxes due, the Greek government had to do something quickly to meet the lenders’ demands. And this was the best they could come up with…

So they finally decided to do away with the two separate tiers of taxation and tax all oil as non-heating oil. To make up for the huge rise in cost to the end consumer they established obscure and bureaucratic criteria for lower income families to submit applications to the government for partial reimbursement of the extra tax, the idea being that this would deprive the sellers from a means to cheat and would still enable end consumers in need to get reasonably priced heating oil after reimbursements. However this didn’t work and instead people just massively stopped using oil for heating, which is by far prevalent in Greece (another government failure, for a country with no oil resources and lots of sun and wind). There are entire older building blocs in cities that were built without fireplaces (which up until recently in modern city apartments were more of a symbol of affluence than of any practical use – people essentially never using them) that have just turned off heating altogether, and fights amongst tenants are commonplace for disagreements over whether to turn on heating or not (which in older buildings is collective so it’s heating for all or for none). Those who cannot afford it just don’t pay so sooner or later most buildings in working class neighborhoods are forced to abandon central heating and sustain the cold or improvise.

Because the government again hadn’t foreseen any of this, and wood burning was never particularly widespread in Greece, there had not been standards for wood or pellet burning stoves. So the market is flooded with low quality wood-burning stoves which are totally inefficient and polluting. So suddenly from December the larger cities in Greece are filled with smog and particulates for the first time from inefficient wood-burning stoves, and from burning inappropriate wood (e.g. people burn disused lacquered furniture at their fireplaces, which is very polluting). Cases of asthma and respiratory illnesses in the larger cities since December have skyrocketed. In the meantime forests and even city parks are raided daily by desperate unemployed people who cannot afford heating (especially in northern Greece), who cut down any trees they can get their hands on.

It’s hard to see that there can be any short term solution to this, in the middle of the worst economic crisis Greece has faced since WWII.

Marios lives in Athens.