The Bank of Chile's latest Annual Conference volume, Monetary Policy and Global Spillovers: Mechanisms, Effects, and Policy Measures, is now out, here. In addition to the research presented in the volume, I love the picture on its front cover. So peaceful.
Showing posts with label Policy. Show all posts
Showing posts with label Policy. Show all posts
Monday, May 14, 2018
Monday, May 7, 2018
Fourth Penn Quantitative Policy Workshop
Wednesday, February 10, 2016
More on Policy Uncertainty
Speaking of policy uncertainty (earlier blog post here), read here about the exciting ongoing project at the Becker-Friedman Institute of the University of Chicago.
Sunday, January 17, 2016
Measuring Policy Uncertainty and its Effects
Fascinating work like Baker, Bloom and Davis (2015) has for some time had me interested in defining and measuring policy uncertainty and its effects.
A plausible hypothesis is that policy uncertainty, like inflation uncertainty, reduces aggregate welfare by throwing sand in the Walrasian gears. An interesting new paper by Erzo Luttmer and Andrew Samwick, "The Welfare Cost of Policy Uncertainty: Evidence from Social Security," drills down to the micro decision-making level and shows how it reduces individual welfare by directly eroding the intended policy benefits. Nice work.
A plausible hypothesis is that policy uncertainty, like inflation uncertainty, reduces aggregate welfare by throwing sand in the Walrasian gears. An interesting new paper by Erzo Luttmer and Andrew Samwick, "The Welfare Cost of Policy Uncertainty: Evidence from Social Security," drills down to the micro decision-making level and shows how it reduces individual welfare by directly eroding the intended policy benefits. Nice work.
Thursday, September 24, 2015
Coolest Paper at 2015 Jackson Hole
The Faust-Leeper paper is wild and wonderful. The friend who emailed it said, "Be prepared, it’s very different but a great picture of real-time forecasting..." He got it right.
Actually his full email was, "Be prepared, it’s very different but a great picture of real-time forecasting, and they quote Zarnowitz." (He and I always liked and admired Victor Zarnowitz. But that's another post.)
The paper shines its light all over the place, and different people will read it differently. I did some spot checks with colleagues. My interpretation below resonated with some, while others wondered if we had read the same paper. Perhaps, as with Keynes, we'll never know exactly what Faust-Leeper really, really, really meant.
I read Faust-Leeper as speaking to factor analysis in macroeconomics and finance, arguing that dimensionality reduction via factor structure, at least as typically implemented and interpreted, is of limited value to policymakers, although the paper never uses wording like "dimensionality reduction" or "factor structure".
If Faust-Leeper are doubting factor structure itself, then I think they're way off base. It's no accident that factor structure is at the center of both modern empirical/theoretical macro and modern empirical/theoretical finance. It's really there and it really works.
Alternatively, if they're implicitly saying something like this, then I'm interested:
Small-scale factor models involving just a few variables and a single common factor (or even two factors like "real activity" and "inflation") are likely missing important things, and are therefore incomplete guides for policy analysis.
Or, closely related and more constructively:
We should cast a wide net in terms of the universe of observables from which we extract common factors, and the number of factors that we extract. Moreover we should examine and interpret not only common factors, but also allegedly "idiosyncratic" factors, which may actually be contemporaneously correlated, time dependent, or even trending, due to mis-specification.
Enough. Read it for yourself.
[General note: My use of terms like "factor modeling" throughout this post should be broadly interpreted to include not only explicit reduced-form statistical/econometric dynamic factor modeling, but also structural DSGE modeling.]
Actually his full email was, "Be prepared, it’s very different but a great picture of real-time forecasting, and they quote Zarnowitz." (He and I always liked and admired Victor Zarnowitz. But that's another post.)
The paper shines its light all over the place, and different people will read it differently. I did some spot checks with colleagues. My interpretation below resonated with some, while others wondered if we had read the same paper. Perhaps, as with Keynes, we'll never know exactly what Faust-Leeper really, really, really meant.
I read Faust-Leeper as speaking to factor analysis in macroeconomics and finance, arguing that dimensionality reduction via factor structure, at least as typically implemented and interpreted, is of limited value to policymakers, although the paper never uses wording like "dimensionality reduction" or "factor structure".
If Faust-Leeper are doubting factor structure itself, then I think they're way off base. It's no accident that factor structure is at the center of both modern empirical/theoretical macro and modern empirical/theoretical finance. It's really there and it really works.
Alternatively, if they're implicitly saying something like this, then I'm interested:
Small-scale factor models involving just a few variables and a single common factor (or even two factors like "real activity" and "inflation") are likely missing important things, and are therefore incomplete guides for policy analysis.
Or, closely related and more constructively:
We should cast a wide net in terms of the universe of observables from which we extract common factors, and the number of factors that we extract. Moreover we should examine and interpret not only common factors, but also allegedly "idiosyncratic" factors, which may actually be contemporaneously correlated, time dependent, or even trending, due to mis-specification.
Enough. Read it for yourself.
[General note: My use of terms like "factor modeling" throughout this post should be broadly interpreted to include not only explicit reduced-form statistical/econometric dynamic factor modeling, but also structural DSGE modeling.]
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