As I indicated here I am reading Probability, Econometrics, and Truth. A nice outline of things, I’m enjoying it at present (I was 20% of the way through when I wrote this post over five weeks ago).
Two quotes I’d like to note down here: Read more
I am currently reading “Inequality Reexamined” by Amartya Sen, as I’ve never read his books – only his papers. This suits my current binge reading of inequality, income distribution, and methodology of economics and econometrics books I’m trying to read (albeit too slowly for my own liking).
Anyway, the prologue immediately neatly summarises a point worth noting. I was reading a little way into the book, and decided that the stuff in the prologue served as a neat “taster” and that I wanted to share it. So here we go!
The central question in the analysis and assessment of inequality is, I argue here, ‘equality of what?’
…
Not only do income-egalitarians (if I may call them that) demand equal incomes, and welfare-egalitarians ask for equal welfare levels, but also classic utilitarians insist on equal weights on the utilities of all, and pure libertarians demand equality with respect to an entire class of rights and liberties. They are all ‘egalitarians’ in some essential way.
Via Twitter:
When I told Tyler I was confused in PhD Macro I, he said, “Good, that means you understand.”
Ahhh macro. I think we can all take a lesson from this and recognise the limits of our knowledge – if the specialists that spend their entire lives and focus on hefty amounts of data appreciate their knowledge is limited, I don’t think the rest of us can just magically “intuit” certain knowledge through our “common sense”. This holds to a lesser degree in all of economics – macro is just especially funktastic.
What does this mean for policy? It doesn’t mean there is no role for government – we can still view government as a form of social insurance between us all, helping us deal with an uncertain world. But, it does imply that government micromanagement and fine tuning have to pass a pretty massive burden of proof. A burden that is hard to pass given that our knowledge is both uncertain and massively conditional. I’ve heard this points before a few time (here, here, here) … 😉
This quote is golden, and since I’ve removed it from my paper at NZAE I have to put it somewhere … lest I lose it from my memory!
Observed facts are necessarily finite in number; possible hypotheses, infinite. If there is one hypothesis that is consistent with the available evidence, there are always an infinite number that are.
Via this excellent review by John Cochrane, I decided to read “the banker’s new clothes“. I’m only a small way in, but it already seem like a pretty good book, written for a non-technical type of audience. Excellent.
My view has been that there is potentially some type of externality from bank’s actions (systemic risk stemming from asymmetric information and potentially linkages), and that there has been a implicit subsidy to deal with this – and so the clearest solution would be to treat the lender of last resort function as enforced insurance … and make banks pay an insurance premium (*,*).
The book is taking a very similarish line, although it is focusing on capital ratios. Essentially, banks become highly leveraged because debt is lower risk than capital funding when they go to borrow (as bondholders will get bailed out, but equity holders won’t) – so they appear to be pushing towards (as Cochrane is) much higher minimum capital ratios. I would note that this is where the NZ Reserve Bank has been pushing regulation since prior to the crisis (to prove this I was looking for a paper I saw from 1999 … and ran into this bulletin from 1996!), and a number of measures have been introduced or are close. By default I prefer price to quantity mechanisms, but I’m leaving myself open to be persuaded by the book.
In any case, the quote. Here:
Subsidizing banks to borrow excessively and take on so much risk that the entire banking system is threatened is like subsidizing and encouraging companies to pollute when they have clean alternatives
On thing missing in the quote is the cost – we haven’t pinned down the true relative price for clean vs non-clean. But adding a subsidy in the face of an externality is peverse, and is a good motivator for looking at the issue.
Writing in the FT he says:
I think forecasting in a complex world is a poor test of expertise because luck is the overwhelming success factor. … The wonderful thing about a forecast is that both the forecaster and his audience feel that something profound has been expressed. And nobody will remember the forecast anyway.
I’m not sure that’s wholly true: forecasters seem to spend a lot of time disavowing their predictions and claiming that the narrative is the important thing. Of course, they still publish headline figures and institutions such as the Bank of England, who only publish a range, get regularly criticised for being too vague. Even if you don’t believe Harford’s explanation, those facts need to be reconciled somehow.