Monday, August 18, 2014

Models Didn't Cause the Crisis

Some of the comments engendered by the Black Swan post remind me of something I've wanted to say for a while: In sharp contrast to much popular perception, the financial crisis wasn't caused by models or modelers.

Rather, the crisis was caused by huge numbers of smart, self-interested people involved with the financial services industry -- buy-side industry, sell-side industry, institutional and retail customers, regulators, everyone -- responding rationally to the distorted incentives created by too-big-to-fail (TBTF), sometimes consciously, often unconsciously. Of course modelers were part of the crowd looking the other way, but that misses the point: TBTF coaxed everyone into looking the other way. So the key to financial crisis management isn't as simple as executing the modelers, who perform invaluable and ongoing tasks. Instead it's credibly committing to end TBTF, but no one has found a way. Ironically, Dodd-Frank steps backward, institutionalizing TBTF, potentially making the financial system riskier now than ever. Need it really be so hard to end TBTF? As Nick Kiefer once wisely said (as the cognoscenti rolled their eyes), "If they're too big to fail, then break them up."

[For more, see my earlier financial regulation posts:  part 1part 2 and part 3.]

Monday, August 11, 2014

You Can Now Browse by Topic

You can now browse No Hesitations by topic.  Check it out -- just look in the right column, scrolling down a bit. I hope it's useful.

On Rude and Risky "Calls for Papers"

You have likely seen calls for papers that include this script, or something similar: 
You will not hear from the organizers unless they decide to use your paper.
It started with one leading group's calls, which go so even farther:
You will not hear from the organizers unless they decide to use your paper.  They are not journal editors or program committee chairmen for a society. 
Now it's spreading.

Bad form, folks.

(1) It's rude. Submissions are not spam to be acted upon by the organizers if interesting, and deleted otherwise. On the contrary, they're solicited, so the least the organizer can do is acknowledge receipt and outcome with costless "thanks for your submission" and "sorry but we couldn't use your paper" emails (which, by the way, are automatically sent in leading software like Conference Maker). As for gratuitous additions like "They are not journal editors or program committee chairmen...," well, I'll hold my tongue.

(2) It's risky. Consider an author whose fine submission somehow fails to reach the organizer, which happens surprisingly often. The lost opportunity hurts everyone -- the author whose career would have been enhanced, the organizer whose reputation would have been enhanced, and the conference participants whose knowledge would have been enhanced, not to mention the general advancement of science -- and no one is the wiser. That doesn't happen when the announced procedure includes acknowledgement of submissions, in which case the above author would simply email the organizer saying, "Hey, where's my acknowledgement? Didn't you receive my submission?"

(Note the interplay between (1) and (2). Social norms like "courtesy" arise in part to promote efficiency.)

Monday, August 4, 2014

The Black Swan Spectrum

Speaking of the newly-updated draft of Econometrics, now for some fun. Here's a question from the Chapter 6 EPC (exercises, problems and complements). Where does your reaction fall on the A-B spectrum below?
Nassim Taleb is a financial markets trader (and Wharton graduate) turned pop author. His book, The Black Swan, deals with many of the issues raised in this chapter. "Black swans"' are seemingly impossible or very low-probability events -- after all, swans are supposed to be white -- that occur with annoying regularity in reality. Read his book. Where does your reaction fall on the A-B spectrum below? 
A. Taleb offers crucial lessons for econometricians, heightening awareness in ways otherwise difficult to achieve. After reading Taleb, it's hard to stop worrying about non-normality, model misspecification, and so on.
B. Taleb belabors the obvious for hundreds of pages, arrogantly "informing"' us that non-normality is prevalent, that all models are misspecified, and so on. Moreover, it takes a model to beat a model, and Taleb offers nothing new.
The book is worth reading, regardless of where your reaction falls on the A-B spectrum.

Thursday, July 31, 2014

Open Econometrics Text Updated for Fall Use

I have just posted an update of my introductory undergraduate Econometrics (book, slides, R code, EViews code, data, etc.). Warning: although it is significantly improved, it nevertheless remains highly (alas, woefullypreliminary and incomplete.

I intend to keep everything permanently "open," freely available on the web, continuously evolving and improving.

If you use the materials in your teaching this fall (and even if you don't), I would be grateful for feedback.

Monday, July 28, 2014

A Second NBER Econometrics Group?

The NBER is a massive consumer of econometrics, so it needs at least a group or two devoted to producing econometrics. Hence I'm thrilled that the "Forecasting and Empirical Methods in Macroeconomics and Finance" group, now led by Allan Timmermann and Jonathan Wright, continues to thrive. Timmermann-Wright is strongly and appropriately time-series in flavor, focusing on developing econometric methods for macroeconomics, financial economics, and other areas that feature time series prominently.

In my view, there's a strong and obvious argument favoring creation of a second NBER working group in econometrics, focusing on micro-econometrics. Quite simply, econometiric methods are central to the NBER's mission, which has both macro/finance and micro components. Timmermann-Wright addresses the former, but there's still no explicit group addressing the latter. (The Bureau's wonderful and recently-instituted Econometrics Methods Lectures include micro, but the Methods Lectures are surveys/tutorials and hence fill a very different void.) An ongoing working group led by Chernozhukov-Imbens-Wooldridge (for example -- I'm just making this up) would be a fine addition and would nicely complement Timmermann-Wright.

Tuesday, July 22, 2014

Chinese Diebold-Rudebusch Yield Curve Modeling and Forecasting

A Chinese edition of Diebold-Rudebusch, Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach, just arrived. (I'm traveling -- actually at IMF talking about Diebold-Rudebusch among other things -- but Glenn informed me that he received it in San Francisco.) I'm not even sure that I knew it was in the works. Anyway, totally cool. I love the "DNS" ("Dynamic Nelson-Siegel") in the Chinese subtitle. Not sure how/where to buy it. In any event, the English first chapter is available free from Princeton University Press, and the English complete book is available almost for free (USD 39.50 -- as they used to say in MAD Magazine: Cheap!).

Sunday, July 20, 2014

Some History of NBER Econometrics

My last post led me to reminisce. So, for history buffs, here's a bit on the origins and development of the NBER working group on Forecasting and Empirical Methods in Macro and Finance. (No promises of complete accuracy -- some of my memory may be fuzzy.)

In the early 1990's Steve Durlauf had an idea for an "Empirical Methods in Macro" NBER group, and he asked me to join him in leading it. Bob Hall kindly supported the idea, so we launched. Some years later Steve stepped down, Ken West joined, and we decided to add "Finance." I was also leading a "Forecasting" group with highly-related interests, so we merged the two, and Diebold-Durlauf "Empirical Methods in Macro" then became Diebold-West, "Forecasting and Empirical Methods in Macro and Finance." Quite a mouthful, but it worked!

We met at least once per year at the NBER Summer Institute, sometimes more. Papers drawn from the meetings sometimes appeared as journal symposia. I'm particularly fond of those in International Economic Review (1998, 811-1144), which contains Andersen-Bollerslev on realized volatility from underlying diffusions, Rudebusch on measuring monetary policy in VAR's (with discussion by Sims and a feisty rejoinder by Rudebusch), Christoffersen on interval forecast calibration, Diebold-Gunther-Tay on density forecast calibration, among others, and Review of Economics and Statistics (1999, 553-673), which contains Baxter-King on bandpass filters for business-cycle measurement, Kim-Nelson on measuring changes in business-cycle stability using Bayesian dynamic-factor Markov-switching models, and Gallant-Hsu-Tauchen on range-based asset return volatility estimation, among others.

I eventually stepped down around 2005, and Mark Watson joined. (Mark and I had earlier edited another group symposium in Journal of Applied Econometrics (1996, 453-593).) So Diebold-West became Watson-West, and the group continued to thrive. In 2013, Mark and Ken passed their batons to Allan Timmermann and Jonathan Wright, who are off and running. This summer's program was one of the best ever, and the meeting was heavily over-subscribed.

Tuesday, July 15, 2014

Time to Re-Think NBER Programs?

Check out John Cochrane's recent NBER post if you didn't already. It ends with:
A last thought. Economic Fluctuations [an NBER program] merged with Growth [another NBER program] in the mid 1990s. At the time there was a great confluence of method as well as interest. Growth theorists were studying growth with Bellman equations, dynamic general equilibrium models of innovation and transmission of ideas, thinking about where productivity shocks came from. Macroeconomists were using Bellman equations and studying dynamic general equilibrium models with stochastic technology, along with various frictions and other propagation mechanisms. 
That confluence has now diverged. ...  ...when Daron Acemoglu, who seems to know everything about everything, has to preface his comments on macro papers with repeated disclaimers of lack of expertise, it's clear that the two fields [fluctuations and growth] really have gone their separate ways. Perhaps it's time to merge fluctuations with finance, where we seem to be talking about the same issues and using the same methods, and to merge growth with institutions and political or social economics.

[Material in square brackets and bold added by me.]
I agree. Fluctuations and finance belong together. (I'm talking about asset pricing broadly defined, not corporate finance.) Yes, the methods are basically the same, and moreover, the substance is inextricably linked. Aspects of fluctuations are effectively the fundamentals priced in financial markets, and conversely, financial markets can most definitely impact fluctuations. (Remember that little recession a few years back?)

The NBER Summer Institute group in which I most actively participate, Forecasting and Empirical Methods in Macroeconomics and Finance (one of several so-called working groups under the umbrella of the NBER's program in Economic Fluctuations and Growth), has been blending fluctuations and finance for decades. But we're intentionally narrowly focused on applied econometric aspects. It would be wonderful and appropriate to see broader fluctuations-finance links formalized at the NBER, not just at the working group level, but also at the program level.

Sunday, June 29, 2014

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.]

Plot of ADS Business Conditions Index in 2007

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.