Must-Read: Noah Smith: Economics Has a Major Blind Spot

Must-Read: Noah Smith: Economics Has a Major Blind Spot:

Economists often don’t take politics into account. As a result, econ models leave out important pieces, and the advice of economists often falls on deaf ears or is seen as impractical…

Most economists would probably agree that fiscal and monetary policy both have an effect on aggregate demand and economic growth. But models of monetary policy often don’t consider the way that Congress’ tax and spending decisions react to changes in interest rates. And models of fiscal policy often assume that the central bank will follow some fixed rule no matter what happens to taxes and spending…. This interaction is so important that with certain assumptions about fiscal policy, it’s possible to completely reverse a model’s predictions about the effects of monetary policy.

Incomplete models aren’t the only way that econ fails…. Economists rarely think about the political feasibility of their proposals… intricate, complex models of optimal tax policy…. If academics spend their time on complex models that might only be used by some hyperadvanced future civilization, that’s not really a problem. The danger is that any attempt to change tax policy in the direction of an optimal solution might actually make things worse….

Not all economists need to take politics into account, but the ones who give policy advice definitely do…. Economists and their models are now in the thick of the political arena. If only more were aware of it.

Must-Read: Thomas Baekdal: What Killed The Newspapers? Google Or Facebook? Or…?

Must-Read: Thomas Baekdal: What Killed The Newspapers? Google Or Facebook? Or…?:

Google didn’t actually kill the newspaper advertising market…

What Killed The Newspapers Google Or Facebook Or by baekdal blog

Google replaced it with an entirely different market. It’s the same money, but Google isn’t in the same market as the newspapers. It instead created its own market and brands decided that was a better place to be…. Advertising in newspapers, they are almost always based on creating random exposure for people with no specific intent…. In the past, this was pretty much how all advertising was done…. Google Search is instead based on advertising to people when they are specifically looking for something…. It’s based on high-intent exposure. This is an incredibly important distinction to understand. Google isn’t winning because it’s big or that it has so much more scale. It’s winning because it created a way for people to have high-intent moments, which brands can reach with their ads.

We have shifted from having a single advertising market (all based on low-intent exposure), to having two different advertising markets… and the media only fits into one of them. Brands will always prefer to have a high-intent moment than low-intent moment (at least the brands who know what they are doing). And it’s because of this that newspapers are losing the market. You are not losing to Google. You are losing to people’s ‘intent’. This is the reality today…

The Stakes of the Helicopter Money Debate: A Primer

The swelling wave of argument and discussion around “helicopter money” has two origins:

First, as Harvard’s Robert Barro says: there has been no recovery since 2010.

The unemployment rate here in the U.S. has come down, yes. But the unemployment rate has come down primarily because people who were unemployed have given up and dropped out of the labor force. Shrinkage in the share of people unemployed has been a distinctly secondary factor. Moreover, the small increase in the share of people with jobs has been neutralized, as far as its effects on how prosperous we are, by much slower productivity growth since 2010 than America had previously seen, had good reason to anticipate, and deserves.

The only bright spot is a relative one: things in other rich countries are even worse.

The wave’s second origin comes in an institutional change that took place in rich countries around the year 1980, back in the era in which Paul Volcker took control of the Federal Reserve. Back then we changed our economic policy institutions. The stagflation of the 1970s convinced many that the political branches of government were incompetent at managing the business cycle. The business cycle disturbed inflation, unemployment, and short run growth. The political branches had tried to use the tools they controlled to manage the business cycle. The stagflation of the 1970s convinced many that they had failed and could not but fail. And the stagflation of the 1970s also convinced the political branches that they did not want responsibility for managing the business cycle—that to assume responsibility was to accept blame, because it would go badly.

Thus back in 1980 Paul Volcker grabbed for the Federal Reserve the power they released. Henceforth the Federal Reserve—and its kith and kin central banks elsewhere in the world—were to be “independent”: They were to be effectively freed from meddling by vote seeking politicians with or seeking soundbites. They were tasked be good technocrats finding a way for the economy between the Skylla of inflation and the Kharybdis of unemployment. And thus they were to manage the economy generate stable, satisfactory, and equitable growth.

But could the Federal Reserve and its kith and kin elsewhere do the job? Did they have the tools? Volcker’s view, and the consensus view of mainstream economists, was that they did have the tools: Milton Friedman had demonstrated, to the satisfaction of a rough consensus of mainstream economists, that central banks’ powers to create money with which to conduct financial open market operations and to both supervise and rescue the banking system were more than powerful enough to do the job.

Now note that back in 1936 [John Maynard Keynes had disagreed][]:

The State will have to exercise a guiding influence… partly by fixing the rate of interest, and partly, perhaps, in other ways…. It seems unlikely that the influence of banking policy on the rate of interest will be sufficient by itself…. I conceive, therefore, that a somewhat comprehensive socialisation of investment will prove the only means of securing an approximation to full employment; though this need not exclude all manner of compromises and of devices by which public authority will co-operate with private initiative…

By the 1980s, however, for Keynes himself the long run had come, and he was dead. The Great Moderation of the business cycle from 1984-2007 was a rich enough pudding to be proof, for the rough consensus of mainstream economists at least, that Keynes had been wrong and Friedman had been right.

But in the aftermath of 2007 it became very clear that they—or, rather, we, for I am certainly one of the mainstream economists in the roughly consensus—were very, tragically, dismally and grossly wrong.

Now we face a choice:

  1. Do we accept economic performance that all of our predecessors would have characterized as grossly subpar—having assigned the Federal Reserve and other independent central banks a mission and then kept from them the policy tools they need to successfully accomplish it?

  2. Do we return the task of managing the business cycle to the political branches of government—so that they don’t just occasionally joggle the elbows of the technocratic professionals but actually take on a co-leading or a leading role?

  3. Or do we extend the Federal Reserve’s toolkit in a structured way to give it the tools it needs?

Helicopter money is an attempt to choose door number (3). Our intellectual adversaries mostly seek to choose door number (1)—and then to tell us that the “cold douche”, as Schumpeter put it, of unemployment will in the long run turn out to be good medicine, for some reason or other. And our intellectual adversaries mostly seek to argue that in reality there is no door number (3)—that attempts to go through it will rob central banks of their independence and wind up with us going through door number (2), which we know ends badly…

[John Maynard Keynes had disagreed]: https://www.marxists.org/reference/subject/economics/keynes/general-theory/ch24.htm (John Maynard Keynes (1936): The General Theory of Employment, Interest and Money (London: Macmillan).

Musings on the Science of “Scaling”: Blum Center U.C. Berkeley

No subject brad delong gmail com Gmail

This is not at all the so-called “replication crisis”.

The devices built work as assessed by all engineering yardsticks: cheap, easy to maintain, rugged, and simple to operate. The interventions conducted work as assessed by all social science standards: they pass gold-standard RCT tests with effects that are statistically and substantively significant.

And yet…

“Scaling” is very hard…

My largely uninformed and probably wrong view is that it has everything to do with organizational and systematic robustness. In the engineering lab and in the social science RCT 98% of things go right. But out in the real world societal capabilities vary: while Toyota can hit six nines–99.9999%–at times I think U.C. Berkeley is lucky to hit nine sixes, and Berkeley is, in global context, a relatively functional organization. So: engineering and societal organization institutions designed for robustness, to degrade gracefully when you cannot attain the degree of organizational tautness of a Toyota. How do we do that? That, I think, is the BIG QUESTION here.

(And, of course, if we can attain the degree of organizational tautness of a Toyota, we no longer have a problem of economic development in any sense, do we?)

Blum Center: The Science of Scaling: Building Evidence to Advance Anti-Poverty Innovations:

September 26 @ 8:00 am – 5:00 pm
100 Blum Hall, Haviland Road
U.C. Berkeley
Berkeley, CA 94720 United States

The Development Impact Lab (DIL), headquartered at UC Berkeley and funded by USAID…

…has developed a “Development Engineering (Dev Eng)”… interdisciplinary framework for designing and testing new povertyalleviation and economic growth technologies in the field… encourag[ing] researchers to build scal[ing] into the R&D process, from the beginning. Yet… there are few generalizable mechanisms for scaling evidence-based interventions in emerging markets…. [Thus] DIL[s]… annual State of the Science conference [is] on The Science of Scaling:

The conference will bring together academic researchers, development practitioners, technology developers, and investors to review the evidence on scaling successful anti-poverty innovations…. Are there proven methods for technology transfer from university to government agencies and non-governmental organizations? Why do some products and interventions scale quicker than others? What facilitates the adoption of new technologies by end-users? This event will explore these questions and help articulate a research agenda for the “Science of Scaling”…

http://delong.typepad.com/2016-09-26-08.3057-scanner-pro.pdf

2016 09 26 08 3057 Scanner Pro pdf 1 page

Must-Read: Blum Center: The Science of Scaling: Building Evidence to Advance Anti-Poverty Innovations

Must-Read: Blum Center: The Science of Scaling: Building Evidence to Advance Anti-Poverty Innovations:

September 26 @ 8:00 am – 5:00 pm
100 Blum Hall, Haviland Road
U.C. Berkeley
Berkeley, CA 94720 United States

The Development Impact Lab (DIL), headquartered at UC Berkeley and funded by USAID…

…has developed a “Development Engineering (Dev Eng)”… interdisciplinary framework for designing and testing new povertyalleviation and economic growth technologies in the field… encourag[ing] researchers to build scal[ing] into the R&D process, from the beginning. Yet… there are few generalizable mechanisms for scaling evidence-based interventions in emerging markets…. [Thus] DIL[s]… annual State of the Science conference [is] on The Science of Scaling:

The conference will bring together academic researchers, development practitioners, technology developers, and investors to review the evidence on scaling successful anti-poverty innovations…. Are there proven methods for technology transfer from university to government agencies and non-governmental organizations? Why do some products and interventions scale quicker than others? What facilitates the adoption of new technologies by end-users? This event will explore these questions and help articulate a research agenda for the “Science of Scaling”…

Underemployment for recent U.S. college graduates

One of the many U.S. labor market concerns that economists and policymakers wrestle with is the problem of underemployed college graduates. The stereotype of the recent grad who is working as a coffee shop barista might come to mind. The worry is that while these recent graduates could get work for the time being, they might end up being stuck in this underemployed state for a considerable time. Underemployment is a significant problem for many college grads, yet it turns out the jobs they are getting aren’t exactly like those barista positions—and underemployment itself is mostly a temporary phenomenon. That’s the good news in a recent research report. The disturbing news is that the rise in such temporary underemployment for college grads may be a long-term trend.

These findings in a recent National Bureau of Economic Research working paper most immediately shed light on underemployment for recent grads in the aftermath of the Great Recession. The paper, by Jaison R. Abel and Richard Deitz of the Federal Reserve Bank of New York, looks not just at the incidence of underemployment but also the kind of jobs that college grads ended up taking. By looking at the skill requirements of different occupations compiled by the U.S. Department of Labor, Abel and Deitz categorize jobs into those that would require a college degree and those that wouldn’t. That lets them calculate how much underemployment there was from 2009 to 2013.

By looking at the wages that different occupations made during that period, the authors sort jobs into skill levels based on how much workers in those positions earned. What they find is that recent college grads were underemployed, but they nonetheless were working in jobs that still allowed for some use of their skills, at least compared to the jobs that workers of a similar age but without a degree were working in. And eventually the college grads moved up into jobs that would fully use their college education. In other words, the jobs of underemployed grads didn’t live up to the barista stereotype—the jobs were temporary stops on the way to higher paying jobs. Of course, this doesn’t mean their underemployment didn’t or won’t have a scaring effect on these workers’ future income gains. It will. But not as large as some might think.

But there’s another important angle to this story. Abel and Deitz show that underemployment was still increasing up until mid-2014, which is about five years after the end of the Great Recession. What’s more, underemployment for recent grads was increasing even before the recession started in late 2007. That means there is evidence this problem of temporary underemployment for college grads also is a long-term trend in the U.S. economy.

The co-authors point to research showing a potential decline in demand for skills since 2000 as the possible explanation. Such a reversal in demand would mean that the skills that graduates do pick up in college are less in demand than in the past. Such a trend would have big implications for how we think about higher education, the importance of full employment, and efforts to reduce inequality.

Must-Reads: September 26, 2016


Should Reads:

Must-Read: Barry Eichengreen: Closing Remarks to Policy Challenges in a Diverging Global Economy

Must-Read: Barry Eichengreen: Closing Remarks to Policy Challenges in a Diverging Global Economy:

It is one of the great pleasures of my association with the Federal Reserve Bank of San Francisco to give these closing remarks…

Having done this twice before, in 2011 and 2013, this affords me the opportunity not just to highlight some insights from this year’s papers but also to look back at the conclusions of those earlier conferences and see how they stack up in light of recent events.

Must-Read: Nick Rowe: Cheshire Cats and New Keynesian Central Banks

Must-Read: Nick Rowe continues his long twilight struggle to try to explain what is really going on in the New Keynesian DSGE model to the world. I think this is a Sisyphean task:

Nick Rowe: Cheshire Cats and New Keynesian Central Banks:

How can money disappear from a New Keynesian model, but the Central Bank still set a nominal rate of interest and create a recession by setting it too high?…

Ignore what New Keynesians say about their own New Keynesian models and listen to me instead. I will tell you how it is possible…. The Cheshire Cat has disappeared, but its smile remains. And its smile (or frown) has real effects. The New Keynesian model is a model of a monetary exchange economy, not a barter economy. The rate of interest is the rate of interest paid on central bank money, not on bonds. Raising the interest rate paid on money creates an excess demand for money which creates a recession. Or it makes no sense at all.

I will take “it makes no sense at all” for $2000, Alex…

Must-Read: Mark Pesce: Zombie Moore’s Law: Hardware Eats Software

Must-Read: Mark Pesce: Zombie Moore’s Law: Hardware Eats Software:

Intel announce some next-generation CPUs that aren’t very much faster… delays… some of its 10nm process CPUs; and Apple’s new A10 chip, powering iPhone 7, is as one of the fastest CPUs ever…

Intel’s slavish devotion to [the] single storyline [that] more transistors and smaller transistors are what everyone needs. That… gave us thirty years of Wintel, but… the CPU is all grown up. Meanwhile… every twelve months another A-series System-on-a-Chip makes its way into the Apple product line, and every time performance increases enormously…. But the bulk of the speed gains in the A-series (about a factor of twelve over the last five years) don’t come from making more, smaller transistors. Instead, they come from Apple’s focus on using only those transistors needed for their smartphones and tablets…. Every aspect of Apple’s chip is highly tuned to both workload and iOS kernel-level task management. It’s getting hard to tell where Apple’s silicon ends and its software begins. And that’s exactly the point….

Apple isn’t alone; NVIDIA has been… adding custom bits to move… work previously done in software–such as rendering stereo pairs for virtual reality displays–into the hardware. A process that used to cost 2x the compute for every display frame now comes essentially for free…. For the last fifty years… the cheap gains of ever-faster CPUs versus the hard work of designing and debugging silicon circuitry meant only the most important or time-critical tasks migrated into silicon. Now… wringing every last bit of capacity out of the transistor… is already well underway…