macroresilience

resilience, not stability

Archive for July, 2013

Interest on Excess Reserves and Inflation

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Martin Feldstein tries to answer the question: “Why has the Federal Reserve’s printing of so much money not caused higher inflation?” and comes up with a seemingly obvious answer – because the Fed pays interest on excess reserves. Like many others, Feldstein sees the payment of interest on excess reserves (IOER) as a “fundamental” change in Fed policy. The reality however is that the payment of IOER is a necessary prerequisite for any regime in which the Fed wishes to sustain a positive Fed Funds rate in the presence of excess reserves. IOER is a red herring and there is simply no way in which the Fed can generate inflation by tinkering with it.

The easiest way to understand this is to look at all the possible configurations of the Fed Funds rate and IOER. Ignoring the ludicrous scenario in which IOER is greater than the Fed Funds rate, there are three other configurations:

  1. Fed Funds and IOER are both equal to 0%.
  2. Fed Funds is above 0% and IOER is equal to 0%.
  3. Fed Funds is equal to 0% and IOER is below 0%.

In the first configuration, payment of interest on reserves clearly does not matter. If the Fed Funds rate itself is at zero, then clearly banks have no incentive to try and get rid of excess reserves.

The second configuration is often invoked as a scenario that could generate inflation. But if the Fed Funds rate is above 0% and IOER is 0%, then there can be no excess reserves in the system. If the central bank wants to sustain a positive Fed Funds rate, it must either pay interest on reserves or mop up all excess reserves. If there are any excess reserves, the Fed Funds market rate immediately falls to 0%. And we’re back to configuration 1 where both the Fed Funds and IOER are equal to 0%. To put it differently, if IOER is equal to 0% and the Fed Funds rate is above 0%, there cannot be any excess reserves in the system.

The third configuration is more interesting. Even if we have hit the zero-bound, why can’t the Fed enforce a negative IOER to force banks to try and get rid of their excess reserves and trigger the monetarist ‘hot potato’ effect? If the central bank charges a small negative rate on reserves, the effects will be negligible. Banks will pass on this cost to deposit-holders in the form of negative deposit rates or extra fees. In the absence of any alternative liquid and nominally safe investment options, most depositors will pay this safety premium.

But what if the Fed charges a significantly negative interest rate on reserves? For example, what if it costs 5% to hold excess reserves? In a world where all money is electronic, this may just work. But in a world where bank depositors possess the option to take their cash out in the form of bank notes, highly negative interest rates on reserves are impossible to enforce. In other words, if IOER is -5%, then you and I can earn a higher interest rate of 0% by simply taking our money out of the bank and holding currency instead.

To summarise, there is no avalanche of inflation coming our way no matter what the Fed pays out as interest on excess reserves.

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Written by Ashwin Parameswaran

July 24th, 2013 at 11:55 am

Posted in Monetary Policy

Invention Is Not The Same As Innovation

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As Reihan Salam argues, economic innovation is not just about basic research and technological breakthroughs. As Amar Bhide has said, “the willingness and ability of lower-level players to create new know-how and products is at least as important to an economy as the scientific and technological breakthroughs on which they rest”. History in fact provides us with at least two prominent examples where basic scientific research and invention did not translate into adequate economic innovation.

The first is the experience of the Soviet economic system. In The Soviet Union, most of the research and development was conducted by designated research institutes who were also partially responsible for implementing the new discoveries and inventions within the relevant industrial enterprise. The Soviets were reasonably successful in coming up with new inventions in their research institutes. Yet even when new products and technologies had been invented, the Soviet research institutes struggled to convince incumbent firms to introduce them into production.

Now how is this example relevant to a capitalist economy? Some of you may argue that unlike the communist enterprises in the Soviet Union, capitalist enterprises are strongly incentivised to jump upon any innovation that would come out of a research institute. But in reality there was no shortage of positive incentives to innovate or increase production for managers of Soviet enterprises. Soviet managers were not motivated by the communist ideal but by that most capitalist of incentives, the bonus. The economist Joseph Berliner estimated that a director of a coal-mine could earn as much as 150% of his base salary as a bonus just for outperforming plan production targets by 5%. On top of this, Soviet managers were provided with ‘innovation’ bonuses as the Soviet planning authorities became increasingly concerned with the slow pace of productivity growth in the 1950s and 60s. But none of these bonuses worked. In fact the bonuses served to further discourage the rollout of any risky innovation that could endanger the fulfilment of short-term plan targets. Managers would focus on low-risk process innovation to fulfil their innovation targets and focused on maximising their short-term ‘plan fulfillment’ bonuses. Ultimately the Soviet system could not replicate the real threat of failure that compels firms in a free enterprise economy to chase disruptive innovation for fear that an upstart new entrant may overtake them.

The second prominent example is the history of modern capitalism itself. Invention and scientific research are not what define the modern era of rapid growth that started in Britain in the early 19th century. As Jack Goldstone has argued, the technical innovations underpinning the “engine revolution” that England underwent in the early 19th century were present elsewhere. Countries like France were even widely regarded to be more advanced in the sciences than England. Yet it was in England that these innovations were so effectively put into economic use.

None of this is meant to undermine the importance of basic research funded by the government. But disruptive economic innovation also requires a truly competitive private sector where incumbents are faced with the threat of failure and barriers to entry for new firms are minimal. The ‘Great Stagnation’ is not driven by the lack of basic research and invention. It is driven by the lack of competition for incumbent large firms and the excessive barriers to entry that new firms and small businesses have to face in the neoliberal era.

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Written by Ashwin Parameswaran

July 11th, 2013 at 1:01 pm

Posted in Resilience

Explaining The Neglect of Doug Engelbart’s Vision: The Economic Irrelevance of Human Intelligence Augmentation

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Doug Engelbart’s work was driven by his vision of “augmenting the human intellect”:

By “augmenting human intellect” we mean increasing the capability of a man to approach a complex problem situation, to gain comprehension to suit his particular needs, and to derive solutions to problems.

Alan Kay summarised the most common argument as to why Engelbart’s vision never came to fruition1:

Engelbart, for better or for worse, was trying to make a violin…most people don’t want to learn the violin.

This explanation makes sense within the market for mass computing. Engelbart was dismissive about the need for computing systems to be easy-to-use. And ease-of-use is everything in the mass market. Most people do not want to improve their skills at executing a task. They want to minimise the skill required to execute a task. The average photographer would rather buy an easy-to-use camera than teach himself how to use a professional camera. And there’s nothing wrong with this trend.

But why would this argument hold for professional computing? Surely a professional barista would be incentivised to become an expert even if it meant having to master a difficult skill and operate a complex coffee machine? Engelbart’s dismissal of the need for computing systems to be easy-to-use was not irrational. As Stanislav Datskovskiy argues, Engelbart’s primary concern was that the computing system should reward learning. And Engelbart knew that systems that were easy to use the first time around did not reward learning in the long run. There is no meaningful way in which anyone can be an expert user of most easy-to-use mass computing systems. And surely professional users need to be experts within their domain?

The somewhat surprising answer is: No, they do not. From an economic perspective, it is not worthwhile to maximise the skill of the human user of the system. What matters and needs to be optimised is total system performance. In the era of the ‘control revolution’, optimising total system performance involves making the machine smarter and the human operator dumber. Choosing to make your computing systems smarter and your employees dumber also helps keep costs down. Low-skilled employees are a lot easier to replace than highly skilled employees.

The increasing automation of the manufacturing sector has led to the progressive deskilling of the human workforce. For example, below is a simplified version of the empirical relationship between mechanisation and human skill that James Bright documented in 1958 (via Harry Braverman’s ‘Labor and Monopoly Capital’). However, although human performance has suffered, total system performance has improved dramatically and the cost of running the modern automated system is much lower than the preceding artisanal system.

AUTOMATION AND DESKILLING OF THE HUMAN OPERATOR

Since the advent of the assembly line, the skill level required by manufacturing workers has reduced. And in the era of increasingly autonomous algorithmic systems, the same is true of “information workers”. For example, since my time working within the derivatives trading businesses of investment banks, banks have made a significant effort to reduce the amount of skill and know-how required to price and trade financial derivatives. Trading systems have been progressively modified so that as much knowledge as possible is embedded within the software.

Engelbart’s vision runs counter to the overwhelming trend of the modern era. Moreover, as Thierry Bardini argues in his fascinating book, Engelbart’s vision was also neglected within his own field which was much more focused on ‘artificial intelligence’ rather than ‘intelligence augmentation’. The best description of the ‘artificial intelligence’ program that eventually won the day was given by J.C.R. Licklider in his remarkably prescient paper ‘Man-Computer Symbiosis’ (emphasis mine):

As a concept, man-computer symbiosis is different in an important way from what North has called “mechanically extended man.” In the man-machine systems of the past, the human operator supplied the initiative, the direction, the integration, and the criterion. The mechanical parts of the systems were mere extensions, first of the human arm, then of the human eye….

In one sense of course, any man-made system is intended to help man….If we focus upon the human operator within the system, however, we see that, in some areas of technology, a fantastic change has taken place during the last few years. “Mechanical extension” has given way to replacement of men, to automation, and the men who remain are there more to help than to be helped. In some instances, particularly in large computer-centered information and control systems, the human operators are responsible mainly for functions that it proved infeasible to automate…They are “semi-automatic” systems, systems that started out to be fully automatic but fell short of the goal.

Licklider also correctly predicted that the interim period before full automation would be long and that for the foreseeable future, man and computer would have to work together in “intimate association”. And herein lies the downside of the neglect of Engelbart’s program. Although computers do most tasks, we still need skilled humans to monitor them and take care of unusual scenarios which cannot be fully automated. And humans are uniquely unsuited to a role where they exercise minimal discretion and skill most of the time but nevertheless need to display heroic prowess when things go awry. As I noted in an earlier essay, “the ability of the automated system to deal with most scenarios on ‘auto-pilot’ results in a deskilled human operator whose skill level never rises above that of a novice and who is ill-equipped to cope with the rare but inevitable instances when the system fails”.

In other words, ‘people make poor monitors for computers’. I have illustrated this principle in the context of airplane pilots and derivatives traders but Atul Varma finds an equally relevant example in the ‘near fully-automated’ coffee machine which is “comparatively easy to use, and makes fine drinks at the push of a button—until something goes wrong in the opaque innards of the machine”. Thierry Bardini quips that arguments against Engelbart’s vision always boiled down to the same objection – let the machine do the work! But in a world where machines do most of the work, how do humans become skilled enough so that they can take over during the inevitable emergency when the machine breaks down?

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Written by Ashwin Parameswaran

July 8th, 2013 at 3:54 pm

Implementing The Helicopter Drop

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Why are helicopter drops off limits for modern central banks and governments? Why do central banks and governments prefer to buy assets from banks and the rich rather than send money to the masses? There are three major reasons:

  1. If the central bank simply prints money out of thin air and credits it to the people, then it suffers a loss. If the helicopter drop is sufficiently large, then the central bank may even become technically insolvent. Although this has very few technical implications for the functioning of a central bank, the political implications are significant. Opponents of the stimulus will latch on to the losses as a sign of monetary irresponsibility. The political implications and fear of loss of central banking independence may even have a negative impact on the economy. Understandably, central banks prefer to avoid such a situation. By buying financial assets, central bank governors can at least postpone losses for long enough that it becomes the next governor’s headache.
  2. If the helicopter drop is financed by a bond issuance by the government, then many market participants fear that the government debt will increase to unsustainable levels that cannot be paid back.
  3. If the helicopter drop is financed by a bond issued by the government and bought by the central bank, then some commentators fear that we will have crossed the rubicon into the dangerous world of monetised fiscal deficits.

I have written in the past on how these concerns are largely mistaken. But perceptions matter, not least because markets are reflexive. So the question is: How can we design a systematic program of helicopter drops that tackles the above concerns? The below is one possible solution:

  • The helicopter drop should be financed by a perpetual bond issued by the government and bought by the central bank. The perpetual bond pays an overnight floating interest rate equivalent to the Federal Funds rate.

The perpetual nature of the bond means that the government will never have to pay it back. The floating rate paid on the bond means that interest rate risk on the central bank’s balance sheet is negligible and it can hold the bond at par value on its balance sheet. The central bank’s inflation target is left unchanged which means that fiscal deficits cannot be monetised without limit.

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Written by Ashwin Parameswaran

July 2nd, 2013 at 3:35 pm

Creation, Destruction and Stagnation

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Many people think that Joseph Schumpeter was the first person to explore the idea of ‘creative destruction’. But as Hugo and Erik Reinert explain in a fascinating paper, the idea of ‘creative destruction’ has a long history. In the same paper, they also provide some subtle insights into the meaning of creative destruction.

First, creation implies destruction. When Apple created the smartphone, it necessarily annihilated the sales of dumb-phones and cameras. However “this relationship exists only in one direction and does not function when reversed. Denial does not imply affirmation, destruction itself does not lead to creation”. Nietzsche often explored this theme in aphorisms such as:

Whoever must be a creator always annihilates.

affirmation requires denial and annihilation.

You must wish to consume yourself in your own flame: how could you wish to become new unless you had first become ashes!

Second, the opposite of creative destruction is stagnation. The ‘Great Stagnation’ is the logical consequence of an economic environment where both job creation and destruction are falling.

Source

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Written by Ashwin Parameswaran

July 1st, 2013 at 6:15 pm

Posted in Resilience