Milton Friedman is said to have mesmerised several countries with a flying visit!?

Milton Friedman visited Australia in 1975. He spoke with government officials and appeared on the  TV show  Monday Conference. Apparently, that was enough for him to take over Australian monetary policy setting for the foreseeable future.


When working at the next desk to the monetary policy section in the late 1980s, I heard not a word of Friedman’s Svengali influence:

  • The market determined interest rates, not the reserve bank was the mantra for several years. Joan Robinson would be proud that her 1975 visit was still holding the reins.
  • Monetary policy was targeting the current account. Read Edwards’ bio of Keating and his extracts from very Keynesian treasury briefings to Keating signed by David Morgan that reminded me of macro101.

See Ed Nelson’s (2005) Monetary Policy Neglect and the Great Inflation in Canada, Australia, and New Zealand who used contemporary news reports from 1970 to the early 1990s to uncover what was and was not ruling monetary policy. For example:

“As late as 1990, the governor of the Reserve Bank rejected central-bank inflation targeting as infeasible in Australia, and cited the need for other tools such as wages policy (AFR, October 18, 1990).”

Bernie Fraser was still sufficiently deprogrammed in 1993 to say that “…I am rather wary of inflation targets.” Easy to then announce one in the same speech when inflation was already 2-3%.


When as a commentator on a Treasury seminar paper in 1986, Peter Boxhall – fresh from the US and 1970s Chicago educated – suggested using monetary policy to reduce the inflation rate quickly to zero, David Morgan and Chris Higgins almost fell off their chairs. They had never heard of such radical ideas.

In their breathless protestations, neither were sufficiently in-tune with their Keynesian educations to remember the role of sticky wages or even the need for the monetary growth reductions to be gradual and, more importantly, credible as per Milton Freidman and as per Tom Sargent’s End of 4 big and two moderate inflations papers.

I was far too junior to point to this gap in their analytical memories about the role of sticky wages, and I was having far too much fun watching the intellectual cream of the Treasury senior management in full flight. At a much later meeting, another high flying deputy secretary was mystified as to why 18% mortgage rates were not reining in the current account in 1989.

Friedman’s Svengali influence did not extend to brainwashing in the monetarist creed that the lags on monetary policy were long and variable. The 1988 or 1989 budget papers put the lag on monetary policy at 1 year, which is short and rapier, if you ask me.


What 3 skills do public policy analysts need?

I used to argue that the quality of public policy making would double if public policy analysts remembered the first 6 weeks of microeconomics 101 but on reflection more than that is required.

I picked up my initial insight out when working as a graduate economist in the Australian Department of Finance. That was a few years ago.


I am now concluded that policy analysts also need to know the basics of the economics of tax incidence. Who pays the tax depends on the elasticities of supply and demand rather than who writes the check to the taxman.

The number of times that I have read media and public policy analysis saying who pays the tax is the writer of the cheque to the taxman is beyond counting.


There is also what to do about unemployment and inflation. Do not just do something, sit there might be good advice on most occasions. As Tim Kehoe and Gonzalo Fernandez de Cordoba explain in the context of first do no harm:

Looking at the historical evidence, Kehoe and Prescott conclude that bad government policies are responsible for causing great depressions.

In particular, they hypothesize that, while different sorts of shocks can lead to ordinary business cycle downturns, overreaction by the government can prolong and deepen the downturn, turning it into a depression.

The three lags on monetary policy

There are large uncertainties about the size and timing of responses to changes in monetary policy. There is a close and regular relationship between the quantity of money and nominal income and prices over the years. However, the same relation is much looser from month to month, quarter to quarter and even year to year. Monetary changes take time to affect the economy and this time delay is itself highly variable. The lags on monetary policy are three in all:

  1. The lag between the need for action and the recognition of this need (the recognition lag)

  2. The lag between recognition and the taking of action (the legislation lag)

  3. the lag between action and its effects (the implementation lag)

These delays mean that is it difficult to ascertain whether the effects of monetary policy changes in the recent past have finished taking effect.

Secondly, it is difficult to ascertain when proposed changes in monetary policy will take effect. Thirdly, feedbacks must be assessed. The magnitude of the monetary adjustment necessary to deal with the problem at hand is never obvious.

It is common for a central bank to act incrementally. The central bank makes small adjustments to monetary conditions over time as more information is available on the state of the economy and forecasts are updated.

Most discussions on monetary policy focus on the implementation lag. This lag depends on the fundamental characteristics of the economy.

A long and variable implementation lag means that it is difficult for central banks to ascertain what is happening now or forecast what will happen. Central banks may stimulate the economy after it is well on the way to recovery and tighten monetary policy when the economy is already going into a recession.

In his classic A Program for Monetary Stability, published in 1959, Milton Friedman summarised his empirical findings on length and variability of the lags on monetary policy:

on the average of 18 cycles, peaks in the rate of change in the stock of money tend to preceded peaks in general business by about 16 months and troughs in the rate of change in the stock of money to precede troughs in general business by about 12 months. For individual cycles, the recorded lead has varied between 6 and 29 months at peaks and between 4 and 22 months at troughs.

With lags as variable as those estimated by Friedman, it is difficult to see how any policy maker could know which direction to adjust his policy, much less the precise magnitude needed. Long lags greatly complicate good forecasting. A forecaster cannot know what the state of the economy will be when his policy takes effect.

Many Keynesians, Friedman notes, advocate “leaning against the wind.” By this they mean, in some sense, that the monetary (and fiscal) authorities should try to balance out the private sector’s excesses rather than passively hope that it adjusts on its own.

Friedman tested the Fed’s success at leaning “against the wind” by checking whether the rate of money growth has truly been lower during expansions and higher during contractions. He admits that this method of grading he Fed’s performance is open to criticism, but decides to go ahead and see what turns up. He finds that Fed has – for the periods surveyed – been unsuccessful.

By this criterion, for eight peacetime reference cycles from March 1919 to April 1958. Actual policy was in the ‘right’ direction in 155 months, in the ‘wrong’ direction in 226 months; so actual policy was ‘better’ than the [constant 4% rate of money growth] rule in 41% of the months.

Nor is the objection that the inter-war period biased his study is good since Friedman found that:

For the period after World War II alone, the results were only slightly more favourable to actual policy according to this criterion: policy was in the ‘right’ direction in 71 months, in the ‘wrong’ direct in 79 months, so actual policy was better than the rule in 47% of the months. [2]

One of the best ways to parry a metaphor is with another metaphor. Keynesians have a host of metaphors in their rhetorical arsenal; one frequently voiced is that a wise government should “lean against the wind” when choosing policy. Friedman counters:

We seldom know which way the economic wind is blowing until several months after the event, yet to be effective, we need to know which way the wind is going to be blowing when the measures we take now will be effective, itself a variable date that may be a half year or a year or two from now. Leaning today against next year’s wind is hardly an easy task in the present state of meteorology.

By scrutinising the practice of monetary policy over the decades, Friedman manages to produce objections that both Keynesians and non-Keynesians must take seriously. A key part of any response to Friedman rests on the ability of forecasters to do their jobs with tolerable accuracy.

The most important aspect of monetary strategy is timing

The simplest statement to make about the lags in monetary policy is they are long and variable. This simple statement is also the key insight to understanding the actual implementation of monetary policy. Hence, how many months or years in advance must a central bank forecast to achieve its monetary goals? In 1994, the Economist said:

But [central banks] cannot afford to wait until inflation is actually rising before they act. Monetary policy does not change the speed of the economy instantly: it can take 18 months or more for a rise in interest rates to have its full impact on inflation. The target of policy ought therefore to be future not current inflation, in order to prevent a surge in 1996. The earlier interest rates are raised, the better the chances of engineering a smooth slowdown to a sustainable rate of growth before slack in the economy is exhausted.

Economists differ about the length of those lags. Uncertainty about the average length of those lags and the variability of those lags makes discretion most difficult. Activist policy can improve welfare only if the information about economic structure and economists’ ability to forecast is sufficiently accurate.


Friedman is the most famous and persuasive critic of Keynesianism on the grounds of lags. He has two main arguments: first, that there are “long and variable lags” between the identification of a problem and the effects of the designed remedy; second, that activist policy often itself becomes a source of instability since policy itself becomes a variable that the market must guess.

Friedman’s critique does not depend on the quantity theory of money. Keynesian policies do not necessarily follow even if the Keynesian theory of the business cycle were conclusively proved.

It must also be demonstrated that the government has the ability and willingness of the government to act as the theory prescribes. We are therefore further assuming that central banks have the incentive to stabilise the economy. If the government lacks the information required to stabilise the economy, issues of public choice incentives become fully redundant. Incentives to pursue an objective do not matter if the objective itself is unattainable.

After reading the annual reports of the Fed, Milton Friedman noticed the following pattern

Milton Friedman reading fed annual reports


The success of monetarism and the death of the correlation between monetary growth and inflation

The Velocity of Money

Monetarists blame fluctuations in inflation on excessively volatile growth in monetary aggregates. In 1982, Friedman defined monetarism in an essay on defining monetarism as follows:

Like many other monetarists, I have concluded that the most important thing is to keep monetary policy from doing harm.

We believe that a steady rate of monetary growth would promote economic stability and that a moderate rate of monetary growth would prevent inflation

The U.S. data supported this hypothesis about the volatility of monetary growth and inflationuntil 1982, but since 1983 monetary aggregates have been essentially uncorrelated with subsequent inflation in the U.S.

Levis Kochin pointed out in 1979 that a well designed monetary policy would lead to zero correlation between any measure of monetary policy and subsequent inflation. The reason for this is the correlation between any variable and a constant is zero.

If monetary growth is stable, say, a constant growth rate of 4% per year, as advocated by Milton Friedman, monetary growth will have no correlations with any variable:

Poole (1993, 1994) and Tanner (1993) also argue that one predictable consequence of optimal monetary policy is that the correlation between monetary policy instruments and policy goals will be driven to zero.

Poole further contends that it is obvious to any careful reader of Theil (1964) that optimally variable policy will give rise to a zero correlation between policy and goal variable…

In 1966 Alan Walters, a U.K. monetarist, observed:

If the [monetary] authority was perfectly successful then we should observe variations in the rate of change of the stock of money but not variations in the rate of change of income… [a]ssuming that the authority’s objective is to stabilize the growth of income.

Milton Friedman in 2003, wrote about how the Fed acquired a good thermostat:

The contrast between the periods before and after the middle of the 1980s is remarkable.

Before, it is like a chart of the temperature in a room without a thermostat in a location with very variable climate; after, it is like the temperature in the same room but with a reasonably good though not perfect thermostat, and one that is set to a gradually declining temperature.

Sometime around 1985, the Fed appears to have acquired the thermostat that it had been seeking the whole of its life…

Prior to the 1980s, the Fed got into trouble because it generated wide fluctuations in monetary growth per unit of output. Far from promoting price stability, it was itself a major source of instability as Chart 1 illustrates.

Yet since the mid ’80s, it has managed to control the money supply in such a way as to offset changes not only in output but also in velocity.

Nick Rowe explained the difficulty of causation and correlation under different policy regimes and Milton Friedman’s thermostat superbly as an econometric problem Nick Rowe:

If a house has a good thermostat, we should observe a strong negative correlation between the amount of oil burned in the furnace (M), and the outside temperature (V).

But we should observe no correlation between the amount of oil burned in the furnace (M) and the inside temperature (P). And we should observe no correlation between the outside temperature (V) and the inside temperature (P).

An econometrician, observing the data, concludes that the amount of oil burned had no effect on the inside temperature. Neither did the outside temperature. The only effect of burning oil seemed to be that it reduced the outside temperature. An increase in M will cause a decline in V, and have no effect on P.

A second econometrician, observing the same data, concludes that causality runs in the opposite direction. The only effect of an increase in outside temperature is to reduce the amount of oil burned. An increase in V will cause a decline in M, and have no effect on P.

But both agree that M and V are irrelevant for P. They switch off the furnace, and stop wasting their money on oil.

Subsequent work of Levis Kochin showed that if the effects of fluctuations in monetary aggregates were not precisely known then the optimal policy would produce negative correlations between monetary aggregates and inflation:

The negative correlation results from coefficient uncertainty because the less certain we are about the size of a multiplier, the more cautious we should be in the application of the associated policy instrument.

Therefore, although optimal policy leads to lack of correlation between the goal and control variables if the coefficient is known, it will lead to a negative relationship if there is coefficient uncertainty. The higher the uncertainty, the more cautious will be the optimal policy response. Also, if the control variable can’t be controlled perfectly then the correlation between the goal and the control variable becomes positive i.e., the control errors are random…

Uncertainty about the impact of a policy  will stay the hand of any bureaucrat , much less a central banker, as Kochin and his co-author explain:

Uncertainty should lead to less policy action by the policymakers. The less policymakers are informed about the relevant parameters, the less activist the policy should be. With poor information about the effects of policy, very active policy runs a higher danger of introducing unnecessary fluctuations in the economy.

The mirage of cost-push inflation

It does appear  too many that rising costs push up prices, but this impression is an illusion caused by the way inventories delay the effect of money supply increases on retail prices.

When increased money growth causes total spending to rise more quickly, sales of particular businesses will increase. But sales fluctuate from day to day and week to week, so managers of these businesses cannot immediately know that this sales increase will last.

As sales continue to rise, restaurants will use up their inventories. Larger orders will then be placed with suppliers, and inventories of these suppliers will begin to shrink.

The retail price has not yet changed because inventories have absorbed the initial impact of the increased spending.

But as more orders to replace depleted inventories work their way down the chain of distribution, orders for  too wholesalers also will rise faster.

The available inventories are inadequate to meet the rising amounts demanded at existing prices.

As a result, wholesale prices will rise as packers bid more intensely for scarce factory supplies. These higher prices then cause factories and other base suppliers to raise their prices; and higher wholesale prices cause retailers  to charge more.

As higher prices work their way up the distribution chain to the consumer, they create an illusion that higher costs are pushing up prices.

But both costs and prices are being pulled up by the increased spending caused by a more rapidly growing money stock. Because the effects of more money and more spending are delayed by inventories, hasty conclusions about the cause of inflation can be deceptive.

HT: Bill Allen

David Hume on the long and variable lags on monetary policy

Macroeconomic forecasting has had a turbulent history

Most early discussions argued against econometric forecasting in principle:

  • Forecasting was not properly grounded in statistical theory,
  • It presupposed that causation implies predictability, and
  • The forecasts themselves were invalidated by the reactions of economic agents to them.

A long tradition argued that social relationships were too complex, too multifarious and too infected with capricious human choices to generate enduring, stable relationships that could be estimated.

These objections came before Hayek’s point that much of all social knowledge is not capable of summation in statistics or even language.

The limitations of forecasting are well-known. Forecasts are conditional on a number of variables; there are important unresolved analytical differences about the operation of the economy; and large uncertainties about the size and timing of responses to macroeconomic changes. Shocks to the output, prices, employment and other variables are partly permanent and partly transitory.

At the practical level, forecasting requires that there are regularities on which to base models, such regularities are informative about the future and these regularities are encapsulated in the selected forecasting model.

We have very little reliable information about the distribution of shocks or about how the distributions change over time. Forecast errors arise from changes in the parameters in the model, mis-specification of the model, estimation uncertainty, mis-measurement of the initial conditions and error accumulation.

In the 1980s, data mining and publications bias were so strong and statistical inferences were so fragile that Ed Leamer’s 1983 Let’s Take the Con out of Econometrics paper made up-and-coming applied economists despair for their professional field and for their own careers:

The econometric art as it is practiced at the computer terminal involves fitting many, perhaps thousands, of statistical models. One or several that the researcher finds pleasing are selected for reporting purposes.

This search for a model is often well intentioned, but there can be no doubt that such a specification search invalidates the traditional theories of inference….

[A]ll the concepts of traditional theory…utterly lose their meaning by the time an applied researcher pulls from the bramble of computer output the one thorn of a model he likes best, the one he chooses to portray as a rose.

… This is a sad and decidedly unscientific state of affairs we find ourselves in.

Hardly anyone takes data analyses seriously.

Or perhaps more accurately, hardly anyone takes anyone else’s data analyses seriously.

Like elaborately plumed birds who have long since lost the ability to procreate but not the desire, we preen and strut and display our t-values [which measure statistical significance].

Leamer still doubts the progress towards techniques that separate sturdy from fragile inferences. Economists by and large simply do not want to hear that they cannot make major conclusions from the data sets. But not that they really do, but that is for a forthcoming post.

Before the great moderation spread wide, Brunner and Meltzer found that in the 1970s and 1980s, the 95% confidence intervals on next year’s forecasts for Gross Domestic Product and the Consumer Price Index are such that government and private forecasters in the USA and Europe could not distinguish between a recession and a boom, nor say whether inflation will be zero or ten per cent.

A review this week by Ahir and Lounganishows found that recent forecasting by the private and public sector has not improved:

none of the 62 recessions in 2008–09 was predicted as the previous year was drawing to a close.

Figure 1. Number of recessions predicted by September of the previous year

Source: Ahir and Loungani 2014, “There will be growth in the spring”: How well do economists predict turning points?”

A policy-maker who adjusts policy based on forecasts for the following year has little reason to be confident that he has changed policy in the right direction.

While at graduate school, I wrote what was published as Official Economic Forecasting Errors in Australia 1983-96.

Australian Treasury forecasting errors were so large relative to the mean annual rate of change in real GDP and the inflation rate that, on average, forecasters could not distinguish slow growth from a deep recession or stable prices from moderate inflation.

The biography of Paul Keating by Edwards suggested that the Government of the day was well aware of the poor value of forecasts. So much so that forecasts may not have actually played a significant role in monetary policy making in Australia in the late 1980s onwards. John Stone said this to Keating when he assumed office as Treasurer in 1983:

As you know, we (and I in particular) have never had much faith in forecasting.

Not infrequently, our forecasts turn out to be seriously wrong.

… We simply do the best we can, in as professional manner as we can — and, if it is any consolation, no one seems to be able to do any better, at least in the long haul.

We always emphasize the uncertainties that attach to the forecasts — but we cannot ensure that such qualifications are heeded and plainly they often are not

To cast my results in Milton Friedman’s nomenclature for monetary lags, the recognition lag on a forecasting based monetary policy appears to be infinite because forecasters do not know if there will be a recession or 10% inflation afoot when their monetary policy changes take hold in 18 to 24 months.

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