What does globalisation mean for monetary policy?

Globalisation poses many puzzles for the making of monetary policy, but until quite recently few central bankers had given it much thought (aside from the effect of Chinese goods deflation). Just under a year ago though Dallas Fed president Richard Fisher gave a speech at Harvard University on Globalization and Monetary Policy. In it he argued that in an globalising world, the usefulness of measures such as the (domestic) output gaps and Phillips curve was in question:

How can economists quantify with such precision what the U.S. can produce with existing labor and capital when we don’t know the full extent of the global labor pool we can access? Or the totality of the financial and intellectual capital that can be drawn on to produce what we produce?

As long as we are able to hold back the devil of protectionism and keep open international capital markets and remain an open economy, how can we calculate an “output gap” without knowing the present capacity of, say, the Chinese and Indian economies?

How can we fashion a Phillips curve without imputing the behavioral patterns of foreign labor pools? How can we formulate a regression analysis to capture what competition from all these new sources does to incentivize American management?

Until we are able to do so, we can only surmise what globalization does to the gearing of the U.S. economy, and we must continue driving monetary policy by qualitative assessment as we work to perfect our quantitative tool kit. At least that is my view.

The speech, one of the first to broach the subject, was overlooked by most - but not all. Earlier this year Janet Henry at HSBC produced a report on measuring the global output gap, and the implications for US inflation. Fisher returned the favour today, visiting London to speak at an HSBC seminar on Monetary Policymaking in a Globalized World. Fisher restated the case for looking beyond national borders:

In U.S. monetary policymaking circles, we work with cost calculations, assumptions about production functions and formulae for policy optimization that were developed before the world economic map was redrawn by the entry of new players and new technologies that changed our “ways of doing things.”

Consequently, the majority of the economic indicators we use to develop monetary policy today only look within our own borders. We measure domestic wages and incomes, domestic capacity utilization, domestic prices and domestic industrial activity. Where we do look beyond our border, we focus narrowly on foreign activity’s impact on our economy through trade and current account balances and relative currency values.

What about global wages, global capacity utilization and global industrial activity? What about the reconfiguration of assignments and tasks within businesses that take place in cyberspace, enabled by the Internet and intranet? I submit that these nondomestic activities and trends are growing more important to our economic welfare and that they condition how we develop and frame monetary policy.

Fisher made a plea for better data and analytical tools. He singled purchasing power parity (PPP) out for criticism, dubbing it "one of my pet peeves":

The raw material for PPP calculations is gathered under the guidance of the International Comparison Program, or ICP, which is coordinated by the World Bank and the OECD. Upon close examination, the ICP’s price comparisons appear to be fraught with errors. The problems seem to stem from the minuscule amount of resources devoted to gathering raw data. The rich countries of the EU, for example, devote something like one staff member per annum to gathering data for the ICP, a grossly deficient manpower commitment when you consider how many staff years go into the construction of national consumer price indexes and other metrics.

One can only imagine how shoddy the situation is in less developed countries. Until statistical agencies like the ICP develop accurate measurements of purchasing-power-adjusted output, this oft-quoted measurement device will be of limited utility for policymakers and might even lead to false conclusions.

In many emerging economies, the data needed to measure output gaps "simply don't exist". He gave other examples too:

For example, despite the boom in fixed-asset investment under way in China, there are no official estimates of its capital stock, which is a basic component in measuring an output gap. Data that might serve as a substitute, such as capacity utilization or unemployment figures, are spotty at best, released erratically and difficult to interpret.

As to the implications for the FOMC? Fisher concluded on this note:

My point is simply that the committee’s wisdom would be enhanced, and the economy would benefit, from having analytical tools to help us build more practicable models than what we currently have to guide our thinking as we make monetary policy in a complicated, reconfigured, globalized world. Today I appeal to you and your firms to help us develop these analytical tools either directly or by demanding them in the marketplace, where you wield considerable influence.

Comments

[Lafayette]

"How can we formulate a regression analysis to capture what competition from all these new sources does to incentivize American management?"

A better question might be "Why should we?".

Trying to use empirical economic data to forecast individual and not collective behaviour is dangerous. There are simply too many components involved, themselves the product of other forecasts, to make any such prevision believable.

It never ceases to amaze ... the presumption of some to forecast the behaviour of others. As if the "others" were all "rational" individuals behaving rationally.

Emotion, intuition, risk-taking ... they too have their effect on human behaviour. But, are they predictable?

[Arthur Eckart]

Individuals are generally rational. What may seem irrational is due to differences in information. A person with less information than another may seem to make irrational choices to the person with more information. Conversely, a person with more information than another may seem to make irrational choices to the person with less information. Nonetheless, their choices are rational, although perceived as irrational. Economists typically use aggregate data, which is the sum of individual data. Of course, a large general equilibrium model, e.g. to understand a large economy, is beyond the capabilities of people (which takes place in hundreds of dimensions). Nonetheless, economists will tie-together various models to achieve a crude understanding.

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Canada switched to metric in an effort to make dealing with other countries easier. Prior to the switch, it was difficult to deal with it was difficult. Now all the business done by Canada in a metric system would make trade so much easier.

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