The best books on Learning Economics

Following the release of Economics in Two Lessons, Sophie Roell of Five Books invited me to do an interview. The Five Books format is that the interviewee (usually an author) nominates the best five books (not including their own) on a given topic. My topic was the Best Books on Learning Economics, with the explanation

these are not textbooks for students studying economics. They’re books for the intelligent, general reader to learn what economics is about—and what the important issues are—without doing any actual [technical] economics.

I’ve picked books by Milton Friedman, Paul Ormerod, Tony Atkinson, Thomas Piketty, and Abhijit Banerjee & Esther Duflo. The interview is here.

The worst case is happening

A couple of years ago, I published an article on why “extremely unlikely” climate events matter. The central point was that climate outcomes with a probability of 5 per cent or less (“extremely unlikely” in IPCC terminology) were still much more likely than risks we take seriously in our daily life, like dying in a car crash). As an illustration, at the time the piece was written, it seemed less than 5 per cent probable that, within two years, many countries in the world (including Australia) would see catastrophic fires on the scale of those that have actually happened.

I made this point in an interview for an ABC story on economists’ views of the likely costs of 3 to 4 degrees of climate change. Most of those interviewed agreed with me that the costs were likely to be much higher than suggested by economics Nobelist William Nordhaus (with whom John Horowitz and I had a debate in the American Economic Review quite a while ago). We pointed out, among other problems, that a paper he had co-authored implied an optimal July temperature of -146 degrees Fahrenheit.

Nordhaus declined an interview, but his viewpoint was represented by Richard Tol. Longstanding readers will remember Tol as a commenter here who eventually wore out his welcome.

The other point I made in the interview was that the abstruse debate about discount rates central to much of the debate between Nordhaus and Nicholas Stern has turned out to be largely irrelevant. The premise of that debate was that the costs of unmitigated climate change would be felt decades into the future while the costs of mitigation would be immediate.

As it’s turned out, the costs of climate change have arrived much sooner than we expected. And the only mitigation options adopted so far have been low cost or even negative cost choices like energy efficiency and abandoning coal (more than justified by the health costs of particulate pollution).

That doesn’t mean discount rates are completely irrelevant. If we manage to decarbonize the global economy by 2050, benefits will keep accruing well after that. But even if we stopped the analysis at 2050, we would still have a substantial net benefit. The likely cost of near-complete decarbonization now looks to be less than a two per cent reduction in national income. Reducing the frequency and severity of disasters like the bushfires will more than offset that.

The statistical significance of focus groups

I’ve generally taken a pretty dim view of focus groups, which seem to be used mostly to detect and amplify unthinking prejudices. But, I have to admit, that probably is due at least in part to the fact that my prejudices aren’t very close to those of the median focus group participant. So, it wasn’t until I saw focus group results matching my own thoughts that I paid any attention to the question of whether the results actually meant anything.

According to the SMH report, participants in two Ipsos focus groups almost uniformly saw Morrison’s response to the bushfires as “pathetic” and “lacking empathy”. In each case, eight of nine respondents gave such negative views. Ipsos also concluded there was “little confidence” Labor leader Anthony Albanese would have provided better leadership, with descriptions like “weak” and “bland” being offered. Regular readers won’t be surprised to learn that I agree with both judgements.

But how much can we learn from an exercise involving only eighteen participants? Surprisingly, the answer is, quite a lot. Use q to denote the proportion of the population who approve of Morrison

If the population from which the group was drawn was evenly divided between approvers and disapprovers, the chance of getting results like this would be tiny. This table (look at N=18, x = 16, p 0.5) gives it at 0.000584. A classical hypothesis test would reject the null hypothesis (or, in the usual jargon, find a statistically significant effect) for any chance below 0.05. Using a more sensible, Bayesian approach, with just about any prior distribution, the updated estimate of for the distribution of q would lie entirely below 0.25 (25 per cent approval). We could do something similar for Albanese, but the exact numbers aren’t given.

These numbers are substantially worse than the approval/disapproval numbers given by Newspoll. So what is going on?

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