Milton Friedman’s advice about climate models, & how to win the policy debate

By Larry Kummer. From the Fabius Maximus website.

Summary: The vital public policy debate over climate change is deadlocked. This is the sixth in a series about ways to restart the debate — and resolve it. This post gives Milton Friedman’s advice about using predictions as the gold standard for validation of theories. This implies that the key to policy action is testing climate models, the only means to give a majority of the public confidence in their forecasts.

“For such a model there is no need to ask the question ‘Is the model true?’. If ‘truth’ is to be the ‘whole truth’ the answer must be ‘No’. The only question of interest is ‘Is the model illuminating and useful?’”

— G.E.P. Box in “Robustness in the strategy of scientific model building” (1978). He also said “All models are wrong; some are useful.”

The debate about public policy for climate change has deadlocked. There are many factors at work, but two stand out as unnecessary problems — as “own goals” by scientists. First they didn’t provide information about data and methods to their opponents (there are always opponents to such large public proposals). Second they didn’t provide compelling proof that climate models’ predictions are reliable — often ignoring the large literature about validation of theories and models.

This series suggests that we restart the debate by better using our knowledge about the methodology of science — especially about models, the embodiment of theories. Box’s insight above applies strongly to debates about policy, where decision-makers are seldom masters of the subject — and so must rely on scientists’ insights.

Previous chapters looked at suggestions about testing models from Paul Krugman, Daniel Davies, and Karl Popper. This post examines a seminal essay by Milton Friedman about the use of theories. Like Karl Popper, he sees predictions as the gold standard for validation of theories. Theories’ value lies in their ability to make accurate predictions, not the degree of their fidelity to nature. That is, abstractions and simplifications are useful if they improve predictions; additional complexity or detail is not useful if it fails to enhance predictions.

Friedman was discussing economics, but these excerpts apply with equal force to climate science.

“The Methodology of Positive Economics“

by Milton Friedman

From Essays in Positive Economics (1966)

Excerpts. Headers and red emphasis added.

Defining Terms

In The Scope and Method of Political Economy (1891) … John Neville Keynes distinguishes among “a  positive science … a body of systematized knowledge concerning what is; a normative or regulative science…  a body of systematized knowledge discussing criteria of what ought to be … a system of rules for the attainment of a given end”; and comments that “confusion between them is common and has been the source of many mischievous errors”.

The vital role of positive science in public policy debates

… Any policy conclusion necessarily rests on a prediction about the consequences of doing one thing rather than another, a prediction that must be based – implicitly or explicitly – on positive economics.

… differences about economic policy among disinterested citizens derive predominantly from different predictions about the economic consequences of taking action – differences that in principle can be eliminated by the progress of positive economics – rather than from fundamental differences in basic values, differences about which men can ultimately only fight.

Testing theories

… The ultimate goal of a positive science is the development of a “theory” or, “hypothesis” that yields valid and meaningful (i.e., not truistic) predictions about phenomena not yet observed.

… Viewed as a body of substantive hypotheses, theory is to be judged by its predictive power for the class of phenomena which it is intended to “explain.” Only factual evidence can show whether it is “right” or “wrong” or, better, tentatively “accepted ” as valid or “rejected.” As I shall argue at greater length below, the only relevant test of the validity of a hypothesis is comparison of its predictions with experience.

The hypothesis is rejected if its predictions are contradicted (“frequently” or more often than predictions from an alternative hypothesis); it is accepted if its predictions are not contradicted; great confidence is attached to it if it has survived many opportunities for contradiction. Factual evidence can never “prove” a hypothesis; it can only fail to disprove it, which is what we generally mean when we say, somewhat inexactly, that the hypothesis has been “confirmed” by experience.

To avoid confusion, it should perhaps be noted explicitly that the “predictions” by which the validity of a hypothesis is tested need not be about phenomena that have not yet occurred, that is, need not be forecasts of future events; they may be about phenomena that have occurred but observations on which have not yet been made or are not known to the person making the prediction.

… Evidence cast up by experience is abundant and frequently as conclusive as that from contrived experiments; thus the inability to conduct experiments is not a fundamental obstacle to testing hypotheses by the success of their predictions. But such evidence is far more difficult to interpret. It is frequently complex and always indirect and incomplete. Its collection is often arduous, and its interpretation generally requires subtle analysis and involved chains of reasoning, which seldom carry real conviction. … It renders the weeding-out of unsuccessful hypotheses slow and difficult. They are seldom downed for good and are always cropping up again.

The value of theories

… the relevant question to ask about the “assumptions” of a theory is not whether they are descriptively “realistic,” for they never are, but whether they are sufficiently good approximations for the purpose in hand. And this question can be answered only by seeing whether the theory works, which means whether it yields sufficiently accurate predictions.

Conclusion

Economics as a positive science is a body of tentatively accepted generalizations about economic phenomena that can be used to predict the consequences of changes in circumstances.

—————————- End excerpt —————————-

What can we get from Friedman’s insights?

Friedman has lessons for both sides in the climate wars. Many skeptics have unrealistic expectations for models, which this essay can help reset.

More important for the policy debate is Friedman’s emphasis on validated predictions, something potentially of great power in the public policy debate — but which climate scientists have largely ignored (preferring hindcasts and appeals to authority).

Friedman specifically refutes the common rebuttal by climate scientists — that they cannot test climate models’ forecasts vs. future data. He says that forecasts can be validated by “observations … not known to the person making the prediction“. Climate scientists can test the models used in the past IPCC Assessment Reports by running them with current data — not vs. scenarios, as originally done, but vs. observations made after their publication.

About Milton Friedman

Milton Friedman (1912 – 2006) was an American economist. He received the 1976 Nobel Memorial Prize in Economic Sciences. See his Wikipedia entry for more information about his work.

Friedman was an advisor to Republican U.S. President Ronald Reagan and Prime Minister Margaret Thatcher, advocating for policy emphasis on free markets with minimal intervention. He considered his role in eliminating conscription in America as his proudest achievement. In Capitalism and Freedom (1962) he recommended adoption of a volunteer military, floating exchange rates, abolition of medical licenses, a negative income tax, and school vouchers (he founded the Friedman Foundation for Educational Choice) — far he’s 2 for 5.

For another perspective on Friedman’s essay see Julian Reiss’ excellent review. See a preview of Capitalism and Freedom here.

Other posts about the climate policy debate

Criticism of alarmists is not enough: positive proposals are needed to resolve this debate so we can more on (at least to prepare for the almost inevitable return of past extreme weather).

1. How we broke the climate change debates. Lessons learned for the future.
2. Climate scientists can restart the climate change debate – & win.
3. Thomas Kuhn tells us what we need to know about climate science.
4. Daniel Davies’ insights about predictions can unlock the climate change debate.
5. Karl Popper explains how to open the deadlocked climate policy debate.
6. Milton Friedman’s advice about restarting the climate policy debate
7. Coming: Gavin Schmidt and Steven Sherword explain the policy gridlock.
8. Coming: Why the policy debate is deadlocked. How we can restart it.