## Friday, May 31, 2013

### Research Computing / Data / Writing Environments

You asked for favorite blogs, and I obliged. You also asked for favorite computing environments etc., so here goes. I look forward to comments telling me why I'm wrong, stupid, insane, or worse.

At some level, who cares about computing etc.? If you're deep into retirement, a SAS guru writing in WordPerfect (say), is it worth updating? Almost surely not.

But if your investment horizon is longer, and if you want to be on the cutting edge, and if you want my opinion, I certainly have one. What follows is in part prescriptive, although I realize that one size surely can't fit all. In any event it's certainly descriptive; it's basically what I do, in principle if not always in practice. (I admit that I'm still rather fond of certain ancient low-level environments like Fortran, and certain high-level environments like Eviews.)

My computing epiphany of recent years centers on R, a mid-level environment.  I find that R is most often the place to be.  Check R Studio IDE, a wonderful R work environment. Check R-bloggers (I should have mentioned it as a favorite blog -- thanks to Frank DiTraglia for reminding me). And for all you parallelization freaks with GPU's, check the CRAN Task View on High-Performance and Parallel Computing with R and the R Tutorial.

For time-series data, check Quandl. Totally amazing. Just click on the link and see for yourself. (And yes, there's a seamless R interface.) Imagine having basically any time-series you could ever want, instantly available and continuously updated, for use in your R code.

For writing, obviously it's LaTeX. My favorite flavor is MiKTeX. Enough said.

Now here's the first kicker. I already mentioned that Quandl and R are interfaced. But so too are R and LaTex, via Sweave. So now data, computing and writing are all linked. Imagine writing a book (in LaTeX) whose graphics and statistical analyses (in R) are automatically updated in real time as new data arrive (in Quandl). It's not a dream.

And here's the second kicker. Everything I've emphasized is public domain, open source, free. Who says that you get only what you pay for? This is highest quality everything, cutting edge, with no license hassles, no renewal hassles, no payment hassles.

Power to the people!

## Tuesday, May 21, 2013

### No Hesitations Birthday

Wow, I can't believe that No Hesitations now has 1000 page views, and it's only a few days old, and with only one real post. Of course I understand that by the standards of the blogosphere 1000 is basically 0, but I am nevertheless humbled. And I swear that no more than 985 of the page views are mine. Only a billion more until I match Cochrane! Thanks my friends.

## Saturday, May 18, 2013

### Simon Kuznets: Penn Professor, Nobel Laureate, and Master of Measurement

A few days ago I received in the snail mail a copy of Robert Fogel's new book, Political Arithmetic: Simon Kuznets and the Empirical Tradition in Economics.  Maybe it was in my box for a while; I must admit to checking it only infrequently. (I mean, seriously, what of interest arrives anymore by U.S. mail? Someone should invent a mailbox that flushes.) I'm also not sure who sent it; maybe it was Fogel, or maybe it was the NBER or the University of Chicago Press, as the book is in the legendary NBER Series on Long-Term Factors in Economic Development, published by the U. of C. Press.

Anyway, Fogel's book is fantastic.

First, it's just a little longer than one hundred pages.  I appreciate that.

Second, I personally like it because it's related to my alma mater and employer, the University of Pennsylvania, where Kuznets taught for decades, and about measurement in economics, which I view as central. Many people associate Kuznets with Harvard, which is also correct, but Harvard appointments tend to be lagging indicators -- effectively rewards for earlier path-breaking work done elsewhere -- and in Kuznets' case the earlier path-breaking work was done at the University of Pennsylvania. Moreover, many of Penn's most-lauded subsequent contributions have also been in the Kuznets' empirical / measurement tradition, from the early macro-econometric models of Nobel laureate Larry Klein, to the ongoing Penn World Tables of Irv Kravis, Bob Summers and Al Heston, to a wide variety of more recent work by current faculty. (Hey, if Greg Mankiw can gush about Harvard in his blog, then I can gush about Penn in mine.)

Third, it's a beautifully-written and entertaining history of many fascinating and entangled aspects of economic measurement, from the rise of academic economics in the early twentieth century, to the development of the NBER's stunningly-successful tradition of empirical economics, to the interplay between measurement and theory. I found it especially valuable and informative in that, although the NBER's tradition in empirical business cycle analysis (Burns, Mitchell, Zarnowitz, Stock and Watson, etc.) is well-known and justly lauded, the parallel NBER tradition in empirical growth analysis is less well understood and appreciated (certainly by me, but I suspect much more widely).

Fourth, it's eye opening. We tend to take things like GDP data for granted, as with the national income and product accounts more generally. But before Kuznets' path-breaking work, there was nothing. Imagine that.   Seriously, try to imagine that!  Imagine trying to price an asset like foreign exchange with no idea of domestic or foreign GDP growth or inflation, or more generally, imagine trying to make any kind of economic or financial decision -- from the national level to the household level -- largely in a data vacuum.  That's how it was, less than a hundred years ago. Thanks, Simon, for shining your light.

Finally, the book, like Kuznets' work itself, testifies convincingly to the power and centrality of measurement in science. Indeed measurement is the essence of science. Yes, yes, of course, my offended theorist friends, theory is important too, but theory is little more than data reduction, and the theory mill needs grist before it can grind. And yes, I'll have more to say about measurement vs. theory in future installments.

But for now, there's only one important matter at hand -- thanking Robert Fogel for writing his beautiful and unique book. Here here!

## Friday, May 17, 2013

### Questions

Two questions loom large in my mind: (1) Am I really writing a blog?, and (2) If so, how did I get here? The answers are (1) Yes, and (2) I'm not exactly sure, but I'm the same as I ever was.

Why No Hesitations? At first I liked No Reservations, but then I realized that a certain ex-chef turned television star might take issue (read: sue me), so I settled on No Hesitations, which is actually better for several reasons. First, it conveys the same flavor of honest, no-holds-barred, observation. Second, it discards the double entendre of "no reservations," which is sensible since I don't plan to write about restaurant meals (although you never know). Third, again, I won't get sued. So it's good all around.

As it says in the "About The Blog" blurb, this blog will contain news and views, comment and criticism, rants and raves. Perhaps the best way to sketch a bit of what I plan to do is to start by sketching a bit of what I won't do. First, I promise not to torture you with boring policy drivel. Put differently, if I ever post an installment with a title of, say, On Regulatory Framework Considerations for Theoretical and Empirical Macro-Prudential Analysis of Systemic Risk with Implications for Basel XIV," please shoot me. In addition, I won't provide too much commentary on current events, as doing so would require me to know about current events.  Seriously, though, friends like Jim Hamilton and Menzie Chin at  Econbrowser, or John Cochrane at The Grumpy Economist would run circles around me -- their continuous insights and energy never cease to amaze me.

OK, what then will I do, if I don't torture you with current events and policy drivel? Basically I'll torture you with Diebold drivel. In particular, if you're interested in financial markets and associated macroeconomic fundamentals, in their relation to data, statistics and predictive modeling, you'll like the blog. Did I mention data, statistics and predictive modeling?

Let me expand on my assertion of "honest, no-holds-barred, observations." You'll find No Hesitations quirky and different, turning stones often unnoticed, let alone turned. For example, in addition to Diebold drivel, you'll find ruminations on things ranging from academic life to Led Zeppelin. And you'll find it mildly irreverent, if you haven't already. By the way, did I mention data, statistics and predictive modeling?

So much for wanton aggrandizing. But while I'm at it, let me take it to the limit, concluding as I began, with a question: Might No Hesitations emerge as the most interesting blog in the world? Stay reading my friends.