Expansions Don't Die of Old Age

As the expansion ages, there's progressively more discussion of whether its advanced age makes it more likely to end. The answer is no. More formally, postwar U.S. expansion hazards are basically flat, in contrast to contraction hazards, which are sharply increasing. Of course the present expansion will eventually end, and it may even end soon, but its age it unrelated to its probability of ending.

All of this is very clear in Diebold, Rudebusch and Sichel (1992). See Figure 6.2 on p. 271. (Sorry for the poor photocopy quality.) The flat expansion hazard result has held up well (e.g., Rudebusch (2016)), and moreover it would only be strengthened by the current long expansion.

[I blogged on flat expansion hazards before, but the message bears repeating as the expansion continues to age.]

Exogenous vs. Endogenous Volatility Dynamics

I always thought putting exogenous volatility dynamics in macro-model shocks was a cop-out.  Somehow it seemed more satisfying for volatility to be determined endogenously, in equilibrium.  Then I came around:  We allow for shocks with exogenous conditional-mean dynamics (e.g., AR(1)), so why shouldn't we allow for shocks with exogenous conditional-volatility dynamics?  Now I might shift back, at least in part, thanks to new work by Sydney Ludvigson, Sai Ma, and Serena Ng, "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?", which attempts to sort things out. The October 2016 version is here.  It turns out that real (macro) volatility appears largely endogenous, whereas nominal (financial market) volatility appears largely exogenous. 

Econometric Analysis of Recurrent Events

Don Harding and Adrian Pagan have a fascinating new book (HP) that just arrived in the snail mail.  Partly HP has a retro feel (think: Bry-Boshan (BB)) and partly it has a futurist feel (think: taking BB to wildly new places).  Notwithstanding the assertion in the conclusion of HP's first chapter (here), I remain of the Diebold-Rudebusch view that Hamilton-style Markov switching remains the most compelling way to think about nonlinear business-cycle events like "expansions" and "recessions" and "peaks" and "troughs".  At the very least, however, HP has significantly heightened my awareness and appreciation of alternative approaches.  Definitely worth a very serious read.

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.]  

New GDP Series From BEA

BEA's "new product" (see below) -- a U.S. GDP estimate that's a simple average of expenditure- and income-side GDP estimates -- is not yet at the cutting-edge of historical GDP estimation.

On the benefits of blending the expenditure- and income-side historical GDP estimates, see ADNSS1 for a forecast-combination perspective and ADNSS2 for a Kalman-filtering signal-extraction perspective.  The ADNSS1 "combined" GDP estimate is a convex combination of expenditure- and income-side GDP estimates, but the BEA equal-weight case is very special and generally sub-optimal. Moreover, ADNSS2's Kalman-filter approach is likely superior to ADNSS1's convex-combination approach for reasons detailed by ADNSS2, and for some years now it has been implemented and published to the web by FRB Philadelphia as "GDPplus".

Neverthess, I applaud the BEA's new averaged GDP. If it's not at the cutting edge, it's nevertheless much superior to the standard approach of doing nothing -- that is, using expenditure-side GDP alone -- and it's an official acknowledgment of the wastefulness of doing so. Hence it's a significant step in the right direction. Hopefully its publication by BEA will nudge people away from uncritical and exclusive reliance on expenditure-side GDP.    







May 14, 2015
Twitter: @BEA_News
www.bea.gov

Coming in July: 
BEA to Launch New Tools for Analyzing Economic Growth

WASHINGTON – The Bureau of Economic Analysis plans to launch two new statistics that will serve as tools to help businesses, economists, policymakers and the American public better analyze the performance of the U.S. economy. These tools will be available on July 30 and emerge from an annual BEA process where improvements and revisions to GDP data are implemented. BEA created these two new tools in response to demand from our customers.

Average of Gross Domestic Product (GDP) and Gross Domestic Income (GDI)

-- BEA will launch a new series that is an average of GDP and GDI, giving users another way to track U.S. economic growth.

-- BEA will present a nominal (or current-dollar) measure of the series and an inflation-adjusted (or chained-dollar) measure of the series.

-- For current dollars, the new measure will be a simple, equally weighted average of GDP and GDI for any given quarter or year.

-- For chained dollars, the new measure will be the current-dollar value deflated by the GDP price index.

-- The new series will be available back to 1929 on an annual basis and to 1947 on a quarterly basis.

-- The new series will not only provide users with another barometer on the U.S. economy but also make available series that several independent experts have recommended using in their analysis of the nation’s economic growth.

-- The new series could help account for known measurement inconsistencies between the two statistics. Those may include timing differences, gaps in underlying source data, and survey measurement errors.

-- The new statistics will be available in BEA’s interactive database as well as in the GDP news release tables.

Interesting New Work on Yield Curve Modeling

Loved last week's PIER lectures at Penn. Good people, good times, good spring weather.  (Please join us next year in May 2016! More information in due course.) On Thursday we did yield curves, which had me thinking about what's new that I like in that area. Not surprisingly, I'm a fan of dynamic Nelson-Siegel (DNS), arbitrage-Free Nelson-Siegel (AFNS), and the many variations.  (See the Diebold-Rudebusch 2013 book.) What's more surprising is that although Nelson-Siegel is almost thirty years old, and DNS/AFNS is almost a teenager, interesting and useful new variations keep coming along.

The most important new work concerns imposition of the zero lower bound (ZLB). Fischer Black's "shadow rate" approach has influenced me most. Recently it's been taken to new heights by Glenn Rudebusch and coauthors at the Federal Reserve Bank of San Francisco (e.g., Christensen and Rudebusch 2015 -- just published in Journal of Financial Econometrics), and Leo Krippner at the Reserve Bank of New Zealand (see his wonderful 2015 book). The amazing thing is that one can stay in the DNS/AFNS framework -- the key tractable subclass of Gaussian affine models -- and still respect the ZLB by appropriately truncating simple simulations. The figure below, assembled from some of Krippner's, says it all. Also see these slides.   

I'm also partial to shadow-rate ZLB work by Cynthia Wu and coauthors at Chicago and San Diego (e.g. Wu and Xia, 2014). (Thanks to Jim Hamilton, her Ph.D. advisor, for reminding me!) See the monthly Wu-Xia shadow short rate series, produced and published to the web by FRB Atlanta.

Last and not at all least is the recent "ARG0" work of Monfort et al., which imposes the ZLB in a very different and elegant way. Again see these slides.   

Another interesting strand of recent DNS/AFNS progress concerns modeling the interaction of bond yield factors, macro fundamentals, and central bank policy.  More on that sometime soon.

Quantitative Tools for Macro Policy Analysis

Penn's First Annual PIER Workshop on Quantitative Tools for Macroeconomic Policy Analysis will take place in May 2015.  The poster appears below (and here if the one below is a bit too small), and the website is here. We are interested in contacting anyone who might benefit from attending. Research staff at central banks and related organizations are an obvious focal point, but all are welcome. Please help spread the word, and of course, please consider attending. We hope to see you there!

ADS Perspective on the First-Quarter Contraction

Following on my last post about the first-quarter GDP contraction, now look at the FRB Philadelphia's Aruoba-Diebold-Scotti (ADS) Index. 2014Q1 is the rightmost downward blip. It's due mostly to the huge drop in expenditure-side GDP (GDP_E), which is one of the indicators in the ADS index. But it's just a blip, nothing to be too worried about. [Perhaps one of these days we'll get around to working with FRB Philadelphia to replace GDP_E with GDPplus in the ADS Index, or simply to include income-side GDP (GDP_I) directly as an additional indicator in the ADS Index.]

Source: FRB Philadelphia

One might wonder why the huge drop in measured GDP_E didn't cause a bigger drop in the ADS Index. The reason is that all real activity indicators are noisy (GDP_E is just one), and by averaging across them, as in ADS, we can eliminate much of the noise, and most of the other ADS component indicators fared much better. (See the component indicator plots.)

Note well the important lesson: both the ADS Index (designed for real-time analysis of broad real activity) and GDPplus (designed mostly for historical analysis of real GDP, an important part of real activity) reduce, if not eliminate, measurement error by "averaging it out."

All told, ADS paints a clear picture: conditional on the underlying indicator data available now, real growth appears to be typical (ADS is constructed so that 0 corresponds to average growth) -- not especially strong, but simultaneously, not especially weak.

The First Quarter GDP Contraction was Less Severe than you Think

As discussed in an earlier post, my co-authors and I believe that our "GDPplus," obtained by optimally blending the noisy expenditure- and income-side GDP estimates, provides a superior U.S. GDP measure. (Check it out online; the Federal Reserve Bank of Philadelphia now calculates and reports it.) A few days ago we revised and re-posted the working paper on which it's based (Aruoba, Diebold, Nalewaik, Schorfheide, and Song, "Improving GDP Measurement: A Measurement Error Perspective," Manuscript, University of Maryland, Federal Reserve Board and University of Pennsylvania, Revised June 2014).

It's important to note that GDPplus is not simply a convex combination of the expenditure- and income-side estimates; rather, it is produced via the Kalman filter, which averages optimally over both space and time. Hence, although GDPplus is usually between the expenditure- and income-side estimates, it need not be. Presently we're in just such a situation, as shown in the graph below. 2014Q1 real growth as measured by GDPplus (in red) is well above both of the corresponding expenditure- and income-side GDP growth estimates (in black), which are almost identical. 

Source:  FRB Philadelphia

Federal Reserve Research: Wake Up Before It's Too Late

I am familiar with the U.S. Federal Reserve System. Long ago I spent the first three (wonderful) years of my working life as an economist at the Board of Governors in DC, 1986-1989. Most recently I chaired the Fed's Model Validation Council, 2012-2013. In the intervening years I've had many engagements with the System, and I've sent many of my Ph.D. students, perhaps twenty, to work there.

So believe me when I say that during the last half-century, there were few better places in the world for a research economist to work, universities included. The research staff quality and esprit de corps were unmatched. Runner-up institutions, world-wide, were miles behind. And believe me as well when I say that I'm now worried.

When I read the recent Huffington Post piece, "Federal Reserve Employees Afraid To Speak Put Financial System At Risk," I was pretty alarmed. I figured it must be strongly negatively biased, so I made some personal inquiries. No -- pretty accurate. Wow. Well, I noticed, it focuses mostly on the Board's division of Supervision and Regulation (Sup&Reg), filled with lawyers. Surely the Board's key research divisions (Research and Statistics, Monetary Affairs, International Finance), filled with economists, are as healthy as ever. So I made some more inquiries. Not yet a Sup&Reg situation, but lots of bewilderment, concern, and top talent looking, or thinking of looking, for greener pastures. Wow.

I understand that we just went through the worst recession since the Great Depression, and that enforcing the ensuing legislation requires a major effort. But I also understand that effective institutions and stellar reputations take half-centuries to build but can collapse quickly, and moreover that, at a deep level, the Fed's research prowess is largely responsible for its respect and effectiveness. So if a new Fed regulatory culture must be built, then build it, but Fed senior management needs simultaneously to preserve and promote the serious research culture that drives Fed effectiveness. Related, people who don't deeply understand and appreciate serious research should never, ever, be promoted to senior management in divisions like Research and Statistics, Monetary Affairs, and International Finance.

Fed Chair Desiderata

I'm so bored with the endless Larry and Janet show.  Finally some real wisdom, from John Cochrane. Tom Sargent has my vote!