Results for “prediction market”

326 found

1. Rapid chicken evolution.  And the invention of pad thai.

2. My 2013 post on why short-term interest rates are so persistently low these days.

3. Using prediction markets to forecast research evaluations.

4. The accent that is Australian (speculative, boozy).

5. Puffins are at risk of extinction.

6. Ending China’s one-child policy won’t matter much at this point.

1. Are millionaires more generous?

2. Facts about American trade with Mexico.

3. The founding father of Liberland.

4. Augur: blockchain-based prediction markets.

5. Lukianoff and Haidt on the coddling of the American college mind.

6. Do bad weather and ugly scenery correlate with religiosity?

7. Todd Kliman continues his intellectual ascent.

Philosopher Thomas Wells argues that future citizens need the vote today:

…future generations must accept whatever we choose to bequeath them, and they have no way of informing us of their values. In this, they are even more helpless than foreigners, on whom our political decisions about pollution, trade, war and so on are similarly imposed without consent. Disenfranchised as they are, such foreigners can at least petition their own governments to tell ours off, or engage with us directly by writing articles in our newspapers about the justice of their cause. The citizens of the future lack even this recourse.

The asymmetry between past and future is more than unfair. Our ancestors are beyond harm; they cannot know if we disappoint them. Yet the political decisions we make today will do more than just determine the burdens of citizenship for our grandchildren. They also concern existential dangers such as the likelihood of pandemics and environmental collapse. Without a presence in our political system, the plight of future citizens who might suffer or gain from our present political decisions cannot be properly weighed. We need to give them a voice.

But how can we solve this problem? Wells has some very good insights:

If current citizens can’t help but be short-sighted, perhaps we should consider introducing agents who can vote in a far-seeing and impartial way. They would need to be credibly motivated to defend the basic interests of future generations as a whole, rather than certain favoured subsets, and they would require the expertise to calculate the long-term actuarial implications of government policies.

But then his solution turns laughable:

Such voters would have to be more than human. I am thinking of civic organisations, such as charitable foundations, environmentalist advocacy groups or non-partisan think tanks.

Well’s solution (give these groups votes) is so tied to his conception of what the “enlightened” future will bring that it clearly fails the far-seeing, impartiality, credibly motivated and expertise requirements that he outlines as desirable. We need not conclude, however, that Well’s plea is disingenuous or impossible but we do need a better implementation.

Robin Hanson’s government of prediction markets (“futarchy“) is a better approach. It is know well understood that relative to other institutions prediction markets draw on expertise to produce predictions that are far seeing and impartial. What is less well understood is that through a suitable choice of what is to be traded, prediction markets can be designed to be credibly motivated by a variety of goals including the interests of future generations.

To understand futarchy note that a prediction market in future GDP would be a good predictor of future GDP. Thus, if all we cared about was future GDP, a good rule would be to pass a policy if prediction markets estimate that future GDP will be higher with the policy than without the policy. Of course, we care about more than future GDP; perhaps we also care about environmental quality, risk, inequality, liberty and so forth. What Hanson’s futarchy proposes is to incorporate all these ideas into a weighted measure of welfare. Prediction markets would then be used to predict and make policy choices based on future welfare. Incorporated within the measure of welfare could be factors like environmental quality many years into the future. 

Note, however, that even this assumes that we know what people in the future will care about. Here then is the final meta-twist. We can also incorporate into our measure of welfare predictions of how future generations will define welfare. We could, for example, choose a rule such that we will pass policies that increase future environmental quality unless a prediction market in future definitions of welfare suggests that future generations will change their welfare standards. It sounds complicated but then so is the problem.

In short, more than any other form of government, futarchy is based on far seeing, impartial, expertise driven and credibly motivated predictions of future welfare and it is flexible enough to allow for a wide definition of welfare including taking into account the interests of future generations.

Hat tip: Carl Close.

1. Meet the two artists living in a giant hamster wheel.  And decentralized Bitcoin prediction markets.

2. Do women respond more to grades than do men?  And Ph.d. candidates as fashion models.  And new and fairly comprehensive study of the economics of the sex trade.

3. Useful origami microscope for less than a dollar.

4. Winkbooks, a new book review site, I believe from Boing Boing and Wired.

5. With proper adjustments, cohabitation before marriage does not predict divorce.

6. Full transcript and video of the Edward Snowden talk.  And has Snowden improved our cyberdefense credibility?

7. The world’s longest high-speed rail line has just opened in China.

8. Company reverses drug decision.

Robert Shiller spent much of his career at Yale University.  He is a famous economist for his analysis of speculative bubbles and price overreaction to new information, first in stock markets and then later in real estate markets.  He has been a leading candidate for a Nobel Prize for some time now.

Here is Shiller’s home page.  Here is Shiller on Wikipedia.  Here are short columns by Shiller on Project Syndicate.  He also writes regularly for the Sunday New York Times, and some of his columns are here.  Here is a 2005 David Leonhardt profile of Shiller.

Shiller’s most famous piece is from 1981, “Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?”  Here Shiller developed the very important “variance bounds test” for scrutinizing the rationality of stock prices.  The intuition runs like this.  Let’s say you were trying to forecast the result of Miami Heat vs. San Antonio Spurs.  The results of the actual games would show higher variance than your forecast, which would reflect your single best guess of which team is better.  But in reality sometimes Miami will win, sometimes the Spurs will win, by a little, by a lot, etc.   That is a basic principle of forecasting rationality, in other words that actual outcomes should show higher variance than forecasts.  But now consider stocks.  According to Shiller, the “actual results” — namely the realized returns — are the dividends.  The forecasts of the dividends are stock prices.  Yet dividends hardly vary, while stock prices move around a great deal.  It would appear that stock prices violate this variance bounds test because the forecast has a higher variance than the actual outcomes.  (For some push back on this, see the papers by Allan Kleidon from the 1980s.  For non-stationary time series for instance a variance bounds test may not hold because the population variance, as opposed to the sample variance, is infinite and thus undefined.  Another point is that stock prices may move because the stock is an option on the real assets of the firm, which have changing value, whether or not dividends ever vary and of course dividends are consciously smoothed.)

Shiller also extended his variance bounds test to the term structure of interest rates, for instance in his work with John Campbell.  Think of long rates as being forecasts of future short rates.  According to a variance bounds test, the long rates should be less volatile, but in market data we generally observe the opposite.  This again raises the possibility that markets are overreacting to new information rather than estimating values rationally.

You will note that some of Shiller’s models imply systematic returns to betting against the market and expecting some long-run mean reversion.  If the market is overreacting to new information right now, over some longer time horizon it will have to return closer to fundamental values.  So if you, as an investor, have enough patience, you should (on average) bet against short-term market movements.  Of course this hypothesis has received a good deal of empirical testing and perhaps there is some (slight) long run mean reversion, although it is not clear how much those gains can be captured after transactions costs are paid.  In any case, there may be some excess returns to buying right after prices have fallen, contrary to what a strict interpretation of efficient markets theory would suggest.

Shiller’s 1984 piece, “Stock Prices and Social Dynamics,” with Ben Friedman, started laying out a “trends” and “fads” approach to stock and also housing prices.  This integration of psychology and economics might help explain why markets appear to overreact to short-term information.

One intriguing side of Shiller is his advocacy of derivatives and prediction markets to help individuals better hedge risk.  On that see Shiller’s book Finance and the Good Society.  Shiller for instance would like to see explicit futures or forward markets in gdp, and individuals could hedge with those markets to bet against bad business prospects.  One also can imagine laborers insuring their future income by transacting in indicators of economic health.  Shiller has raised the idea of using housing price indices to help hedge against home price risk, whether for future sellers or future buyers.  This aspect of Shiller’s thought has perhaps disappointed some of his fans who have wanted him to take a more critical attitude toward finance.  Shiller instead thinks that a properly reconstituted financial sector could bring the world very significant gains, typically through superior risk hedging.  It remains a general puzzle why so many of these markets continue not to exist, and when they are sometimes started up, they fail to attract sufficient liquidity.

Shiller’s greatest practical contribution is the Case-Shiller housing price index, described by Wikipedia like this:

The Standard & Poor’s Case–Shiller Home Price Indices are repeat-sales house price indices for the United States. There are multiple Case–Shiller home price indices: A national home price index, a 20-city composite index, a 10-city composite index, and twenty individual metro area indices.

This index has become a staple of real world financial analysis and discussion and it is reported in the financial press on a regular basis.

Shiller is also famous for having predicted the housing price bubble which played an important role in America’s Great Recession.  Here is one of his early pieces on that issue.  One of his research innovations was the common sense idea of simply asking home buyers what kind of future price gains they were expecting and then analyzing whether those expectations were realistic (hint: they weren’t).

Here is an on-line course with Shiller, on finance.

1. The economics of crossword puzzles.

2. More Krugman on Asimov, and Robin Hanson gets one part of his dream come true on combinatorial prediction markets.

3. Good Josh Hendrickson post on fiscal policy.

4. How many Americans view the Gaza conflict.

5. Text messages direct to your contact lens.

6. The rise of the underground restaurant.

1. Science is the key to growth.

2. Roberto Unger criticizes Keynesianism.

3. Are psychopaths physically attractive?

4. Are economists ignoring neuroeconomics?

5. How permanent is the rise in risk premia?  And a combinatorial prediction market for the election and related matters.

6. Thwarted India and China markets in everything, Siri edition.