Duncan Brown’s interesting NGDP wonkery

If you write a blog you obviously want people to read what you write and even better you want to inspire discussion. I was therefore very happy when Duncan Brown sent me his two latest blog posts, which both are inspired by stuff I have written.

Duncan’s posts are very interesting. The first post – Shocking supply and volatile demand – uses a (crude) method I developed to decompose demand and supply inflation. Duncan utilizes this method – Quasi-Real Price Index – on UK data. The second post – In the 1950s, Rab Butler sets an NGDPLPT mandate… - also uses one of my ideas and that is to look a what inflation historical would have been had the central bank had an NGDP target. Duncan looks at the UK, while I earlier have looked at the US.

A Quasi-Real Price Index for the UK

I first time suggested that inflation could be decompose between supply and demand shocks with what I inspired by the brilliant David Eagle termed a Quasi-Real Price Index in a blog post in December 2011.

This is from my 2011 post – A method to decompose supply and demand inflation:

David Eagle in a number of his papers on Quasi-Real Indexing starts out with the equation of exchange:

(1) M*V=P*Y

Eagle rewrites this to what he calls a simple equation of exchange:

(2) N=P*Y where N=M*V

This can be rewritten to

(3) P=N/Y

(3) Shows that consumer prices (P) are determined by the relationship between nominal GDP (N), which is determined by monetary policy (M*V) and by supply factors (Y, real GDP).

We can rewrite as growth rates:

(4) p=n-y

Where p is US headline inflation, n is nominal GDP growth and y is real GDP growth.

Introducing supply shocks

If we assume that we can separate underlining trend growth in y from supply shocks then we can rewrite (4):

(5) p=n-(yp+yt)

Where yp is the permanent growth in productivity and yt is transitory (shocks) changes in productivity.

Defining demand and supply inflation

We can then use (5) to define demand inflation pd:

(6) pd=n- yp

And supply inflation, ps, can then be defined as

(7) ps=p-pd (so p= ps+pd)

Duncan uses this method on UK data and I must say that his results are vey interesting.

Here is a graph from Duncan’s post on the decomposing of UK inflation.

UK-qrpi

Based on his results he concludes:

“Policy may have looked loose in terms of interest rates, but relative to context, this was one of the most extreme tightenings on record. The implication is that while we’re always going to be prey to supply shocks which will create some volatility in output and employment, we need to be careful to allow demand to grow in a predictable, sustainable way. The trouble with an inflation target is that the nightmare combination of an adverse supply shock and a damaging tightening of monetary conditions looks – as it did at the time – like things are on track. Policy should aim to stabilise demand inflation, even as supply inflation moves around; it is a pity that the mandate most likely to be able to achieve this result (a nominal output level path) has been ruled out by the Treasury.”

As a Market Monetarist it is hard to disagree with Duncan’s statement. However, it should certainly also be noted that Duncan’s results give reason to think that the nature of the present crisis in the UK economy to some extent is different from the crisis in the US or the euro zone economies. Hence, it seems like the present subdued growth in the UK economy to a larger extent than is the case in the US or the euro zone (overall) is due to supply side problems (Weak demand is the primary problem, but supply issues seem more important than in the US). In that sense the UK economy might share some similarities with the Icelandic economy. See my earlier post here on why the Geyser crisis to a large extent was caused by an supply shock rather and a demand shock.

A counterfactual inflation story for the UK

In his second post Duncan tells the counterfactual story of what inflation would have been in the UK since the 1950s if the Bank of England had been targeting an 5% NGDP growth path. The method is similar to the one I used in my post The counterfactual US inflation history – the case of NGDP targeting.

You can see Duncan’s counterfactual inflation data in this graph.

Duncan’s results for the UK are rather similar to the result I got for the US. However, it seems that UK inflation under NGDP targeting than would have been in the case in the US in recent years. That do indicate that that the low growth in the UK economy to a larger extent than is the case in US. That, however, also mean you need lower demand inflation to achieve the Bank of England’s present 2% inflation target.

It is not all I agree with in Duncan’s two post – for example I think he misinterprets his results to mean that the primary shocks to the UK economy has been supply, while I think his results in fact shows that demand shocks have been the primary driver of the UK business cycle – but I would nonetheless recommend to all of my readers to have a look at Duncan’s blog. It’s good wonkery.

 

 

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Guest post: GDP-Linked Bonds (by David Eagle)

Guest post: GDP-Linked Bonds, Another Whole Literature to Synthesize into Market Monetarism

by David Eagle

As Dale Domian and I have been frustrated at our continuous attempts to publish our quasi-real indexing research, I have kept reminding myself of one thing and that is that we were the first to design quasi-real indexing (Eagle and Domian, 1995. “Quasi-Real Bonds–Inflation-Indexing that Retains the Government’s Hedge Against Aggregate-Supply Shocks,” Applied Economic Letters).  However, I have recently encountered some good news and some bad news concerning quasi-real indexing.

First, the bad news: It turns out that Dale and I were not the first to come up with the notion of quasi-real indexing.  Somebody actually beat us by two years.  The reference is is Robert Shiller’s Macro Markets: Creating Institutions for Managing Society’s Largest Economic Risks”.

Actually, Shiller did not use the term “quasi-real indexing.”  Instead, he used “GDP-linked bonds.”  Shiller shares the same origins for these bonds as Dale and I do.  We all started thinking about government bonds.  At the time of our 1995 paper, the U.S. government was considering inflation-indexed bonds.  Instead, we proposed an alternative bond that would be safer for the government.  Unfortunately, the U.S. government decided to issue TIPS, an inflation-indexed bond, rather than either Shiller’s proposal or Dale’s and my proposal.

Now the good news: A significant literature has evolved concerning GDP-linked bonds.  The existence of this literature provides the market monetarists another literature to bring into the Market Monetarism literature.  In particular, I have come to recognize that quasi-real indexing basically provides insurance against the central bank not meeting its nominal GDP target even if the central bank is not targeting GDP.  If those in the GDP-linked-bond literature can recognize that that is what their GDP-linked bonds do, they will then realize that George Selgin was right in Less than Zero about how risk on loans should be shared between borrowers and lenders.  Also, they should realize that nominal bonds will achieve the same effect as GDP-linked bonds as long as the central bank successfully targets nominal GDP.

You can find GDP-linked bonds in Wikipedia; unfortunately, you cannot find “quasi-real indexing” there (yet).  More recently Professor Shiller joined Mark Kamstra in a paper proposing “Trills,” which are a GDP-linked bond.  Other literature concerning GDP-linked bonds include:

Mark Kamstra and Robert J. Shiller: “The Case for Trills: Giving Canadians and their Pension Funds a Stake in the Wealth of the Nation.”

Kruse, Susanne, Matthias Meitner and Michael Schroder, “On the pricing of GDP-linked financial products.” Applied Financial Economics 15: 1125-1133, 2005.

Griffith-Jones, Stephany, and Krishnan Sharma, “GDP-Indexed Bonds: Making It Happen.” DESA Working Paper No. 21, 2006.

Schröder, Michael; Heinemann, Friedrich; Kruse, Susanne; Meitner, Matthias; “GDP-linked Bonds as a Financing Tool for Developing Countries and Emerging Markets”

Travota, Alexandra “On the Feasibility and Desirability of GDP-Indexed Concessional Lending,”

Also, some blog posts exist on GDP-linked bonds:

Jonathan Ford: The Case for GDP Bonds

: GDP-Linked Securities

Also, a very recent blog post in the WSJ.com just covered Robert Shiller’s proposal of these GDP-linked bonds:

“Worried About U.S. Debt? Shiller Pushes GDP-Linked Bonds”

I myself am still reading these other papers, books, and blog posts.

The reality is that if not only the U.S. government issued quasi-real bonds or GDP-linked bonds, but also European governments issued them as well, then the European sovereign debt crisis would not be at all as serious a problem as it is today.  Also, as most market monetarists know, if the European Central Banks had been targeting nominal GDP successfully, then the European sovereign debt crisis would be of a much smaller magnitude than it has become.  Paul Krugman has noted how the increase in European sovereign debt coincided with the beginning of the last recession.  I hope that Professor Krugman will look into the GDP-linked-bond and quasi-real-indexing literatures to learn how these types of bonds would have prevented this increase to happen.

Actually, Argentina has recently issued some GDP-linked bonds as one of the above blogs points out.

In economics, we have a lot of unconnected literatures that needs to be brought together. Obviously, Dale and my “quasi-real indexing” needs to be synthesized into the GDP-linked bond literature.  However, synthesizing both of these literatures along with the wage-indexation literature and the nominal GDP targeting literature leads to the incredible conclusions: (1) Much of the Pareto-efficiency associated with complete markets can be achieved either through quasi-real indexing of all contracts or by the central bank (successfully) targeting nominal GDP, (2) Most of the negative economic effects of the business cycle would be eliminated either through quasi-real indexing  or nominal GPD targeting.

I hope this post encourages those involved in the GDP-linked bond literature, wage indexation literature, and the literature on NGDP targeting to work on synthesizing all of their literatures together.

© Copyright (2012) by David Eagle

Let the Fed target a Quasi-Real PCE Price Index (QRPCE)

The Federal Reserve on Wednesday said it would target a long-run inflation target of 2%. Some of my blogging Market Monetarist friends are not too happy about this – See Scott Sumner and Marcus Nunes. But I have an idea that might bring the Fed very close to the Market Monetarist position without having to go back on the comments from Wednesday.

We know that the Fed’s favourite price index is the deflator for Private Consumption Expenditure (PCE) for and the Fed tends to adjust this for supply shocks by referring to “core PCE”. Market Monetarists of course would welcome that the Fed would actually targeting something it can influence directly and not react to positive and negative supply shocks. This is kind of the idea behind NGDP level targeting (as well as George Selgin’s Productivity Norm).

Instead of using the core PCE I think the Fed should decomposed the PCE deflator between demand inflation and supply by using a Quasi Real Price Index. I have spelled out how to do this in an earlier post.

In my earlier post I show that demand inflation (pd) can be calculated in the following way:

(1) Pd=n-yp

Where n is nominal GDP growth and yp is trend growth in real GDP.

Private Consumption Expenditure growth and NGDP growth is extremely highly correlated over time and the amplitude in PCE and NGDP growth is nearly exactly the same. Therefore, we can easily calculate Pd from PCE:

(2) Pd=pce-yp

Where pce is the growth rate in PCE. An advantage of using PCE rather than NGDP is that the PCE numbers are monthly rather than quarterly which is the case for NGDP.

Of course the Fed is taking about the “long-run”. To Market Monetarists that would mean that the Fed should target the level rather growth of the index. Hence, we really want to go back to a Price Index.

If we write (2) in levels rather than in growth rates we basically get the following:

(3) QRPCE=PCE/RGDP*

Where QRPCE is what we could term a Quasi-Real PCE Price Index, PCE is the nominal level of Private Consumption Expenditure and RGDP* is the long-term trend in real GDP. Below I show a graph for QRPCE assuming 3% RGDP in the long-run. The scale is natural logarithm.

I have compared the QRPCE with a 2% trend starting the 2000. The starting point is rather arbitrary, but nonetheless shows that Fed policy ensured that QRPCE grew around a 2% growth path in the half of the decade and then from 2004-5 monetary policy became too easy to ensure this target. However, from 2008 QRPCE dropped sharply below the 2% growth path and is presently around 9% below the “target”.

So if the Fed really wants to use a price index based on Private Consumption Expenditure it should use a Quasi-Real Price Index rather than a “core” measure and it should of course state that long-run inflation of 2% means that this target is symmetrical which means that it will be targeting the level for the price index rather the year-on-year growth rate of the index. This would effectively mean that the Fed would be targeting a NGDP growth path around 5% but it would be packaged as price level targeting that ensures 2% inflation in the long run. Maybe Fed chairman Bernanke could be convince that QRPCE is actually the index to look at rather than PCE core? Packaging actually do matter in politics – and maybe that is also the case for monetary policy.

Guest Blog: The Two Fundamental Welfare Principles of Monetary Economics (By David Eagle)

I am extremely happy that David Eagle is continuing his series of guest blogs on my blog.

I strongly believe that David’s ideas are truly revolutionary and anybody who takes monetary policy and monetary theory serious should study  these ideas carefully. In this blog David presents what he has termed the “Two Fundamental Welfare Principles of Monetary Economics” as an clear alternative to the ad hoc loss functions being used in most of the New Keynesian monetary literature.

To me David Eagle here provides the clear microeconomic and welfare economic foundation for Market Monetarism. David’s thinking and ideas have a lot in common with George Selgin’s view of monetary theory – particularly in “Less than zero” (despite their clear methodological differences – David embraces math while George use verbal logic). Anybody that reads and understands David’s and George’s research will forever abandon the idea of a “Taylor function” and New Keynesian loss functions.

Enjoy this long, but very, very important blog post.

Lars Christensen

—————–

Guest Blog: The Two Fundamental Welfare Principles of Monetary Economics

by David Eagle

Good Inflation vs. Bad Inflation

At one time, doctors considered all cholesterol as bad.  Now they talk about good cholesterol and bad cholesterol.  Today, most economists considered all inflation uncertainty as bad, at least all core inflation uncertainty.  However, some economists including George Selgin (2002), Evan Koenig (2011), Dale Domian, and myself (and probably most of the market monetarists) believe that while aggregate-demand-caused inflation uncertainty is bad, aggregate-supply-caused inflation or deflation actually improves the efficiency of our economies.  Through inflation or deflation, nominal contracts under Nominal GDP (NGDP) targeting naturally provide the appropriate real-GDP risk sharing between borrowers and lenders, between workers and employers, and more generally between the payers and receivers of any prearranged nominal payment.  Inflation targeting (IT), price-level targeting (PLT), and conventional inflation indexing actually interfere with the natural risk sharing inherent in nominal contracts.

I am not the first economist to think this way as George Selgin (2002, p. 42) reports that “Samuel Bailey (1837, pp. 115-18) made much the same point.”  Also, the wage indexation literature that originated in the 1970s, makes the distinction between demand-induced inflation shocks and supply-induced inflation shocks, although that literature did not address the issue of risk sharing.

The Macroeconomic Ad Hoc Loss Function vs. Parerto Efficiency

The predominant view of most macroeconomists and monetary economists is that all inflation uncertainty is bad regardless the cause.  This view is reflected in the ad hoc loss function that forms the central foundation for conventional macroeconomic and monetary theory.  This loss function is often expressed as a weighted sum of the variances of (i) deviations of inflation from its target and (ii) output gap.  Macro/monetary economists using this loss function give the impression that their analyses are “scientific” because they often use control theory to minimize this function.  Nevertheless, as Sargent and Wallace (1975) noted, the form of this loss function is ad hoc; it is just assumed by the economist making the analysis.

I do not agree with this loss function and hence I am at odds with the vast majority of the macro/monetary economists.  However, I have neoclassical microfoundations on my side – our side when we include Selgin, Bailey, Koenig, Domian, and many of the market monetarists.  This ad hoc social loss function used as the basis for much of macroeconomic and monetary theory is basically the negative of an ad hoc social utility function.  The microeconomic profession has long viewed the Pareto criterion as vastly superior to and more “scientific” than ad hoc social utility functions that are based on the biased preconceptions of economists.  By applying the Pareto criterion instead of a loss function, Dale Domian and I found what I now call, “The Two Fundamental Welfare Principles of Monetary Economics.”  My hope is that these Fundamental Principles will in time supplant the standard ad hoc loss function approach to macro/monetary economics.

These Pareto-theoretic principles support what George Selgin (p. 42) stated in 2002 and what Samuel Bailey (pp. 115-18) stated in 1837.  Some economists have dismissed Selgin’s and Bailey’s arguments as “unscientific.”  No longer can they legitimately do so.  The rigorous application of neoclassical microeconomics and the Pareto criterion give the “scientific” support for Selgin’s and Bailey’s positions.  The standard ad-hoc-loss-function approach in macro- and monetary economics, on the other hand, is based on pulling this ad hoc loss function out of thin air without any “scientific” microfoundations basis.

Macroeconomists and monetary economists have applied the Pareto criterion to models involving representative consumers.  However, representative consumers miss the important ramifications of monetary policy on diverse consumers.  In particular, models of representative consumers miss (i) the well-known distributional effect that borrowers and lenders are affected differently when the price level differs from their expectations, and (ii) the Pareto implications about how different individuals should share in changes in RGDP.

The Two Direct Determinants of the Price Level

Remember the equation of exchange (also called the “quantity equation), which says that MV=N=PY where M is the money supply, V is income velocity, N is nominal aggregate spending as measured by nominal GDP, P is the price level, and Y is aggregate supply as measured by real GDP.  Focusing on the N=PY part of this equation and solving for P, we get:

(1) P=N/Y

This shows there are two and only two direct determinants of the price level:

(i)             nominal aggregate spending as measured by nominal GDP, and

(ii)           aggregate supply as measured by real GDP.

This also means that these are the two and only two direct determinants of inflation.

The Two Fundamental Welfare Principles of Monetary Economics

When computing partial derivatives in calculus, we treat one variable as constant while we vary the other variable.  Doing just that with respect to the direct determinants of the price level leads us to The Two Fundamental Welfare Principles of Monetary Economics:

Principle #1:    When all individuals are risk averse and RGDP remains the same, Pareto efficiency requires that each individual’s consumption be unaffected by the level of NGDP.

Principle #2:    For an individual with average relative risk aversion, Pareto efficiency requires that individual’s consumption be proportional to RGDP.[1]

Dale Domian and I (2005) proved these two principles for a simple, pure-exchange economy without storage, although we believe the essence of these Principles go well beyond pure-exchange economies and apply to our actual economies.

My intention in this blog is not to present rigorous mathematical proofs for these principles.  These proofs are in Eagle and Domian (2005).  Instead, this blog presents these principles, discusses the intuition behind the principles, and gives examples applying the principles.

Applying the First Principle to Nominal Loans:

I begin by applying the First Principle to borrowers and lenders; this application will give the sense of the logic behind the First Principle.  Assume the typical nominal loan arrangement where the borrower has previously agreed to pay a nominal loan payment to the lender at some future date.  If NGDP at this future date exceeds its expected value whereas RGDP is as expected, then the price level must exceed its expected level because P=N/Y.  Since the price level exceeds its expected level, the real value of the loan payment will be lower than expected, which will make the borrower better off and the lender worse off.  On the other hand, if NGDP at this future date is less than its expected value when RGDP remains as expected, then the price level will be less than expected, and the real value of the loan payment will be higher than expected, making the borrower worse off and the lender better off.  A priori both the borrower and the lender would be better off without this price-level risk.  Hence, a Pareto improvement can be made by eliminating this price-level risk.

One way to eliminate this price-level risk is for the central bank to target the price level, which if successful will eliminate the price-level risk; however, doing so will interfere will the Second Principle as we will explain later.  A second way to eliminate this price-level risk when RGDP stays the same (which is when the First Principle applies), is for the central bank to target NGDP; as long as both NGDP and RGDP are as expected, the price level will also be as expected, i.e., no price-level risk..

Inflation indexing is still another way to eliminate this price-level risk.  However, conventional inflation indexing will also interfere with the Second Principle as we will soon learn.

That borrowers gain (lose) and lenders lose (gain) when the price level exceeds (fall short of) its expectations is well known.  However, economists usually refer to this as “inflation risk.” Technically, it is not inflation risk; it is price-level risk, which is especially relevant when we are comparing inflation targeting (IT) with price-level targeting (PLT).

An additional clarification that the First Principle makes clear concerning this price-level risk faced by borrowers and lenders is that risk only applies as long as RGDP stays the same.  When RGDP changes, the Second Principle applies.

Applying the Second Principle to Nominal Loans under IT, PLT, and NT:

The Second Principle is really what differentiates Dale Domian’s and my position and the positions of Bailey, Selgin, and Koenig from the conventional macroeconomic and monetary views.  Nevertheless, the second principle is really fairly easy to understand.  Aggregate consumption equals RGDP in a pure exchange economy without storage, capital, or government.  Hence, when RGDP falls by 1%, aggregate consumption must also fall by 1%.  If the total population has not changed, then average consumption must fall by 1% as well.  If there is a consumer A whose consumption falls by less than 1%, there must be another consumer B whose consumption falls by more than 1%.  While that could be Pareto justified if A has more relative risk aversion than does B, when both A and B have the same level of relative risk aversion, their Pareto-efficient consumption must fall by the same percent.  In particular, when RGDP falls by 1%, then the consumption level of anyone with average relative risk aversion should fall by 1%.  (See Eagle and Domian, 2005, and Eagle and Christensen, 2012, for the basis of these last two statements.)

My presentation of the Second Principle is such that it focuses on the average consumer, a consumer with average relative risk aversion.  My belief is that monetary policy should do what is optimal for consumers with average relative risk aversions rather than for the central bank to second guess how the relative-risk-aversion coefficients of different groups (such as borrowers and lenders) compare to the average relative risk aversion.

Let us now apply the Second Principle to borrowers and lenders where we assume that both the borrowers and the lenders have average relative risk aversion.  (By the way “relative risk aversion” is a technical economic term invented Kenneth Arrow, 1957, and John Pratt, 1964.)  Let us also assume that the real net incomes of both the borrower and the lender other than the loan payment are proportional to RGDP.  Please note that this assumption really must hold on average since RGDP is real income.  Hence, average real income = RGDP/m where m is the number of households, which means average real income is proportional to RGDP by definition (the proportion is 1/m).

The Second Principle says that since both the borrower and lender have average relative risk aversion, Pareto efficiency requires that both of their consumption levels must be proportional to RGDP.  When their other real net incomes are proportional to RGDP, their consumption levels can be proportional to RGDP only if the real value of their nominal loan payment is also proportional to RGDP.

However, assume the central bank successfully targets either inflation or the price level so that the price level at the time of this loan payment is as expected no matter what happens to RGDP.  Then the real value of this loan payment will be constant no matter what happens to RGDP.  That would mean the lenders will be guaranteed this real value of the loan payment no matter what happens to RGDP, and the borrowers will have to pay that constant real value even though their other net real incomes have declined when RGDP declined.  Under successful IT or PLT, borrowers absorb the RGDP risk so that the lenders don’t have to absorb any RGDP risk.  This unbalanced exposure to RGDP risk is Pareto inefficient when both borrowers and lenders have average relative risk aversion as the Second Principle states.

Since IT and PLT violate the Second Principle, we need to search for an alternative targeting regime that will automatically and proportionately adjust the real value of a nominal loan payment when RGDP changes?  Remember that the real value of the nominal loan payment is xt=Xt/P.  Replace P with N/Y to get xt=(Xt/Nt)Yt, which means the proportion of xt to Yt equals Xt/Nt.  When Xt is a fixed nominal payment, the only one way for the proportion Xt/Nt to equal a constant is for Nt to be a known in advance.  That will only happen under successful NGDP targeting.

What this has shown is that the proportionality of the real value of the loan payment, which is needed for the Pareto-efficient sharing of RGDP risk for people with average relative risk aversion, happens naturally with nominal fixed-payment loans under successful NGDP targeting.  When RGDP decreases (increases) while NGDP remains as expected by successful NGDP targeting, the price level increases (decreases), which decreases (increases) the real value of the nominal payment by the same percentage by which RGDP decreases (increases).

The natural ability of nominal contracts (under successful NGDP targeting) to appropriately distribute the RGDP risk for people with average relative risk aversion pertains not just to nominal loan contracts, but to any prearranged nominal contract including nominal wage contracts.  However, inflation targeting and price-level targeting will circumvent the nominal contract’s ability to appropriate distribute this RGDP risk by making the real value constant rather than varying proportionately with RGDP.

Inflation Indexing and the Two Principles:

Earlier in this blog I discussed how conventional inflation indexing could eliminate that price-level risk when RGDP remains as expected, but NGDP drifts away from its expected value.  While that is true, conventional inflation indexing leads to violations in the Second Principle.  Consider an inflation indexed loan when the principal and hence the payment are adjusted for changes in the price level.  Basically, the payment of an inflation-indexed loan would have a constant real value no matter what, no matter what the value of NGDP and no matter what the value of RGDP.  While the “no matter what the value of NGDP” is good for the First Principle, the “no matter what the value of RGDP” is in violation of the Second Principle.

What is needed is a type of inflation indexing that complies with both Principles.  That is what Dale Domian’s and my “quasi-real indexing” does.  It adjusts for the aggregate-demand-caused inflation, but not to the aggregate-supply-caused inflation that is necessary for the Pareto-efficient distribution of RGDP among people with average relative risk aversion.

Previous Literature:

Up until now, I have just mentioned Bailey (1837) and Selgin (2002) without quoting them.  Now I will quote them.  Selgin (2002, p. 42) states, ““ …the absence of unexpected price-level changes” is “a requirement … for avoiding ‘windfall’ transfers of wealth from creditors to debtors or vice-versa.”  This “argument … is perfectly valid so long as aggregate productivity is unchanging. But if productivity is subject to random changes, the argument no longer applies.”  When RGDP increases causing the price level to fall, “Creditors will automatically enjoy a share of the improvements, while debtors will have no reason to complain: although the real value of the debtors’ obligations does rise, so does their real income.”

Also, Selgin (2002, p. 41) reports that “Samuel Bailey (1837, pp. 115-18) made much the same point.  Suppose … A lends £100 to B for one year, and that prices in the meantime unexpectedly fall 50 per cent. If the fall in prices is due to a decline in spending, A obtains a real advantage, while B suffers an equivalent loss. But if the fall in prices is due to a general improvement in productivity, … the enhanced real value of B’s repayment corresponds with the enhanced ease with which B and other members of the community are able to produce a given amount of real wealth. …Likewise, if the price level were … to rise unexpectedly because of a halving of productivity, ‘both A and B would lose nearly half the efficiency of their incomes’, but ‘this loss would arise from the diminution of productive power, and not from the transfer of any advantage from one to the other’.”

The wage indexation literature as founded by Grey and Fischer recognized the difference between unexpected inflation caused by aggregate-demand shocks and aggregate-supply shocks; the main conclusion of this literature is that when aggregate-supply shocks exist, partial rather than full inflation indexing should take place.  Fischer (1984) concluded that the ideal form of inflation indexing would be a scheme that would filter out the aggregate-demand-caused inflation but leave the aggregate-supply-caused inflation intact.  However, he stated that no such inflation indexing scheme had yet been derived, and it would probably be too complicated to be of any practical use.  Dale Domian and I published our quasi-real indexing (QRI) in 1995 and QRI is not that much more complicated than conventional inflation indexing.  Despite the wage indexation literature leading to these conclusions, the distinction between aggregate-demand-caused inflation and aggregate-supply-caused inflation has not been integrated into mainstream macroeconomic theory.  I hope this blog will help change that.

Conclusions:

As the wage indexation literature has realized, there are two types of inflation:  (i) aggregate-demand-caused inflation and (ii) aggregate-supply-caused inflation.  The aggregate-demand-caused inflation is bad inflation because it unnecessary imposes price-level risk on the parties of a prearranged nominal contract.  However, aggregate-supply-caused inflation is good in that that inflation is necessary for nominal contracts to naturally spread the RGDP risk between the parties of the contract.  Nominal GDP targeting tries to keep the bad aggregate-demand-caused unexpected inflation or deflation to a minimum, while letting the good aggregate-supply-caused inflation or deflation take place so that both parties in the nominal contract proportionately share in RGDP risk.  Inflation targeting (IT), price-level targeting (PLT), and conventional inflation indexing interfere with the natural ability of nominal contracts to Pareto efficiently distribute RGDP risk.  Quasi-real indexing, on the other hand, gets rid of the bad inflation while keeping the good inflation.

Note that successful price-level targeting and conventional inflation indexing basically have the same effect on the real value of loan payments.   As such, we can look at conventional inflation indexing as insurance against the central bank not meeting its price-level target.

Note that successfully NGDP targeting and quasi-real indexing have the same effect on the real value of loan payments.  As such quasi-real indexing should be looked at as being insurance against the central bank not meeting its NGDP target.

A couple of exercises some readers could do to get more familiar with the Two Fundamental Welfare Principles of Welfare Economics is to apply them to the mortgage borrowers in the U.S. and to the Greek government since the negative NGDP base drift that occurred in the U.S. and the Euro zone after 2007.  In a future blog I very likely present my own view on how these Principles apply in these cases.

References:

Arrow, K.J. (1965) “The theory of risk aversion” in Aspects of the Theory of Risk Bearing, by Yrjo Jahnssonin Saatio, Helsinki.

Bailey, Samuel (1837) “Money and Its Vicissitudes in Value” (London: Effingham Wilson).

Debreu, Gerard, (1959) “Theory of Value” (New York:  John Wiley & Sons, Inc.), Chapter 7.

Eagle, David & Dale Domian, (2005). “Quasi-Real Indexing– The Pareto-Efficient Solution to Inflation Indexing” Finance 0509017, EconWPA, http://ideas.repec.org/p/wpa/wuwpfi/0509017.html.

Eagle, David & Lars Christensen (2012). “Two Equations on the Pareto-Efficient Sharing of Real GDP Risk,” future URL: http://www.cbpa.ewu.edu/papers/Eq2RGDPrisk.pdf.

Sargent, Thomas and Neil Wallace (1975). “’Rational’ Expectations, the Optimal Monetary Instrument, and the Optimal Money Supply Rule”. Journal of Political Economy 83 (2): 241–254.

Selgin, George (2002), Less than Zero: The Case for a Falling Price Level in a Growing Economy. (London: Institute of Economic Affairs).

Koenig, Evan (2011). “Monetary Policy, Financial Stability, and the Distribution of Risk,” Federal Reserve Bank of Dallas Research Department Working Paper 1111.

Pratt, J. W., “Risk aversion in the small and in the large,” Econometrica 32, January–April 1964, 122–136.

© Copyright (2012) by David Eagle

 


[1] Technically, the Second Principle should replace “average relative risk aversion” with “average relative risk tolerance,” which is from a generalization and reinterpretation by Eagle and Christensen (2012) of the formula Koenig (2011) derived.

Guest post: Why I Support NGDP Targeting (by David Eagle)

Welcome to David Eagle

I am extremely happy that professor David Eagle have accepted to write a series of guest blogs on my blog. I only recently became aware of David’s impressive research, but consider it to be truly original and in my view his research presents an extremely strong theoretical and empirical case for Nominal GDP level targeting, which of course is at the core of Market Monetarist thinking.

I have already written a number of posts on David’s research and even tried to elaborate on his research specifically in terms of suggesting a method – based on David’s research – to decompose inflation between demand inflation and supply inflation based on what I strongly inspired by David has termed a Quasi-Real Price Index (QRPI) and it is my hope that my invitation to David to write the guest blogs will help give exposure to his very interesting research. Furthermore, I hope that other researchers will be inspired by David’s truly path-breaking research to conduct research into the advantages of NGDP level targeting and related topics.

So once again, thank you David. It is an honour to host your guest blogs.

Lars Christensen  

 

Why I Support NGDP Targeting

By David Eagle

Nominal GDP (NGDP) represents the total spending in the economy, which in essence is the total aggregate demand in the economy.  The term “nominal” means that we ignore the effect of inflation on the value of the spending.  If we adjust for the effect of inflation, we then get a “real” value.  In particular, real GDP (RGDP) represents the total spending adjusted for the effect of inflation on the purchasing power of that spending.  RGDP also represents the conventional measure of total real supply in the economy because usually demand equals supply in a free economy.  I believe that, for most contingencies in the economy, both monetary policy and fiscal policy (as far as its aggregate-spending effects) should focus on targeting the total spending in the economy as measured by NGDP.  That way we will (i) reduce the prolonged high unemployment that has usually followed past recessions, (ii) minimize the demand-caused inflation uncertainties people experience while maintaining the role inflation or deflation plays in the sharing of aggregate-supply risk, (iii) reduce the likelihood of the economy experiencing a liquidity trap, and (iv) eliminate the “stimulate-the-economy” excuse for perpetual fiscal deficits when NGDP is at or above its target.

While I support nominal-GDP targeting (NT), I do not support nominal-GDP-growth-rate targeting (ΔNT).  I have long been an opponent of inflation targeting (IT), and I view ΔNT to be almost as bad as IT.  Both ΔNT and IT expose the economy to negative NGDP base drift, which is the source of several economic problems: (i) prolonged unemployment following recessions, (ii) greater uncertainty for borrowers, lenders, and other payers and receivers of fixed nominal future payments, and (iii) price-level indeterminacy, which can manifest itself in a liquidity trap like what many central banks throughout the world are currently facing.

I also am an opponent of price-level targeting (PLT) even though the NGDP base drift under PLT will be substantially less than under IT.  The reason is because Pareto efficiency requires people with average relative risk aversion to proportionately share in the risks of changes in real aggregate output.  Nominal contracts under NT naturally lead to this proportionate sharing.  However, PLT circumvents that proportionate sharing so that borrowers and other payers of fixed nominal payments absorb all the aggregate-supply risk of those payments in order to protect lenders and other receivers of fixed nominal payments from this risk.

I find that NT Pareto dominates PLT, IT, and ΔNT.  The only reason why NT is not Pareto efficient is a central bank cannot always meet its NGDP target.  I also find through empirical simulations that NT can eliminate the vast majority of the higher-than-normal, long-term unemployment that has usually plagued our economies following recessions.  Hence, I look at NT as the most desirable targeting regime from both a theoretical, Pareto-efficiency standpoint and from an empirical standpoint.

In the upcoming weeks, I plan to write several more guest blogs for “The Market Monetarist” to explain the theoretical and empirical justification for the points I have made in this introduction.  In some cases I will explain the full basis for that justification; in other cases, I will refer to other papers I or others have written.  My proposed blogs (which may change as I write this blogs) are as follows:

  1. Understanding NGAP, NGDP Base Drift, and Growth Vs. Level Targeting
  2. The Two Fundamental Welfare Principles of Monetary Economics
  3. Why Price-Level Targeting Pareto Dominates Inflation Targeting
  4. NGDP Base Drift – Why Recessions are followed by Prolonged High Unemployment
  5. NGDP Base Drift, Price Indeterminacy, and the Liquidity Trap
  6. Three Reasons to Target the Level of rather than the Growth Rate of Nominal GDP

My second blog will use examples to explain the concepts of NGAP, NGDP base drift, and the difference between targeting the level of NGDP and Targeting the growth rate of Nominal GDP.  This blog will also summarize the difference between price-level targeting and inflation targeting, and discuss the concepts of PGAP and price-level base drift.

© Copyright (2012) David Eagle

 

Divisia Money and “A Subjectivist Approach to the Demand for Money”

Recently Scott Sumner have brought up William Barnett’s new book “Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy”. The theme in Barnett’s book is basically that “normal” money supply numbers where subcomponents of the money supply is added up with equal weight give wrong measure of the “real” money supply. Instead Barnett’s recommend using a so-called Divisia Money method of the money supply.

Here is a William Barnett’s discription of divisia money (from the comment section on Scott’s blog):

“Unlike the Fed’s simple-sum monetary aggregates, based on accounting conventions, my Divisia monetary aggregates are based on microeconomic aggregation theory. The accounting distinction between assets and liabilities is irrelevant and is not the same for all economic agents demanding monetary services in the economy. What is relevant is market data not accounting data.”

And here is the official book discription of Barnett’s book:

“Blame for the recent financial crisis and subsequent recession has commonly been assigned to everyone from Wall Street firms to individual homeowners. It has been widely argued that the crisis and recession were caused by “greed” and the failure of mainstream economics. In Getting It Wrong, leading economist William Barnett argues instead that there was too little use of the relevant economics, especially from the literature on economic measurement. Barnett contends that as financial instruments became more complex, the simple-sum monetary aggregation formulas used by central banks, including the U.S. Federal Reserve, became obsolete. Instead, a major increase in public availability of best-practice data was needed. Households, firms, and governments, lacking the requisite information, incorrectly assessed systemic risk and significantly increased their leverage and risk-taking activities. Better financial data, Barnett argues, could have signaled the misperceptions and prevented the erroneous systemic-risk assessments.

When extensive, best-practice information is not available from the central bank, increased regulation can constrain the adverse consequences of ill-informed decisions. Instead, there was deregulation. The result, Barnett argues, was a worst-case toxic mix: increasing complexity of financial instruments, inadequate and poor-quality data, and declining regulation. Following his accessible narrative of the deep causes of the crisis and the long history of private and public errors, Barnett provides technical appendixes, containing the mathematical analysis supporting his arguments.”

Needless to say I have ordered the book at look forward to reading. I am, however, already relatively well-read in the Divisia money literature and I have always intuitively found the Divisia concept interesting and useful and which that more central bank around the world had studied and published Divisia money supply numbers and fundamentally I think Divisia money is a good supplement to studying market data as Market Monetarists recommend. Furthermore, it should be noted that the weight of the different subcomponents in Divisia money is exactly based on market pricing of the return (the transaction service) of different components of the money supply.

My interest in Divisia money goes back more than 20 years (I am getting old…) and is really based on an article by Steven Horwitz from 1990. In the article “A Subjectivist Approach to the Demand for Money” Steve among other thing discusses the concept of “moneyness”. This discussion I think provide a very good background for understanding the concept of Divisia Money. Steve does not discuss Divisia Money in the article, but I fundamentally think he provides a theoretical justification for Divisa Money in his excellent article.

Here is a bit of Steve’s discussion of “moneyness”:

“Hicks argues that money is held because investing in interest-earning assets involves transactions costs ; the act of buying a bond involves sacrificing more real resources than does acquiring money. It is at least possible that the interest return minus the transactions costs could be negative, making money’s zero return preferred.

While this approach is consistent with the observed trade-off between interest rates and the demand for money (see below), it does not offer an explanation of what money does, nor what it provides to its holder, only that other relevant substitutes may be worse choices. By immediately portraying the choice between money and near-moneys as between barrenness and interest, Hicks starts off on the wrong track. When one “objectifies” the returns fro111each choice this way, one is led to both ignore the yield on money held as outlined above and misunderstand the choice between holding financial and non-financial assets. The notion of a subjective yield on money can help to explain better the relationship between money and near-moneys.

One way in which money differs from other goods is that it is much harder to identify any prticular good as money because goods can have aspects of money, yet not be full-blooded moneys. What can be said is that financial assets have degrees of “moneyness” about them, and that different financial assets can be placed along a moneyness continium. Hayek argues that: “it would be more helpful…if “money”were an adjective describing a property which different things could possess to varying degrees. A pure money asset is then defined as the generally accepted medium of exchange. Items which can he used as lnedia of exchange, but are somewhat or very much less accepted are classified as near-moneys.

Nonetheless, money and near-moneys share an important feature Like all other objects of exchange, their desirability is based o n their utility yield. However in the case of near-moneys, that yield is not simply availability. Near-moneys do yield some availability services, but not to the degree of pure money. ‘The explanation is that by definition, near-moneys are not as generally acceptable and therefore cannot he available for all the same contingencies as pure money. For example, as White argues, a passbook savings account is not the same as pure money because, aside from being not directly transferrable (one has to go to the hank and make a withdrawal, unlike a demand deposit), it is not generally acceptable. Even a demand deposit is not quite as available as currency or coin is – some places will not accept checks. These kinds of financial assets have lower availability yields than pure money because they are simply not as marketable.”

If you read Steve’s paper and then have a look at the Divisia numbers – then I am pretty sure that you will think that the concept makes perfect sense.

And now I have written a far too long post – and you should not really have wasted your time on reading my take on this issue as the always insightful Bill Woolsey has a much better discussion of the topic here.

NGDP targeting would have prevented the Asian crisis

I have written a bit about boom, bust and bubbles recently. Not because I think we are heading for a new bubble – I think we are far from that – but because I am trying to explain why bubbles emerge and what role monetary policy plays in these bubbles. Furthermore, I have tried to demonstrate that my decomposition of inflation between supply inflation and demand inflation based on an Quasi-Real Price Index is useful in spotting bubbles and as a guide for monetary policy.

For the fun of it I have tried to look at what role “relative inflation” played in the run up to the Asian crisis in 1997. We can define “relative inflation” as situation where headline inflation is kept down by a positive supply shock (supply deflation), which “allow” the monetary authorities to pursue a easy monetary policies that spurs demand inflation.

Thailand was the first country to be hit by the crisis in 1997 where the country was forced to give up it’s fixed exchange rate policy. As the graph below shows the risks of boom-bust would have been clearly visible if one had observed the relative inflation in Thailand in the years just prior to the crisis.

When Prem Tinsulanonda became Thai Prime Minister in 1980 he started to implement economic reforms and most importantly he opened the Thai economy to trade and investments. That undoubtedly had a positive effect on the supply side of the Thai economy. This is quite visible in the decomposition of the inflation. From around 1987 to 1995 Thailand experience very significant supply deflation. Hence, if the Thai central bank had pursued a nominal income target or a Selgin style productivity norm then inflation would have been significantly lower than was the case. Thailand, however, had a fixed exchange rate policy and that meant that the supply deflation was “counteracted” by a significant increase in demand inflation in the 10 years prior to the crisis in 1997.

In my view this overly loose monetary policy was at the core of the Thai boom, but why did investors not react to the strongly inflationary pressures earlier? As I have argued earlier loose monetary policy on its own is probably not enough to create bubbles and other factors need to be in play as well – most notably the moral hazard.

Few people remember it today, but the Thai devaluation in 1997 was not completely unexpected. In fact in the years ahead of the ’97-devaluation there had been considerably worries expressed by international investors about the bubble signs in the Thai economy. However, the majority of investors decided – rightly or wrongly – ignore or downplay these risks and that might be due to moral hazard. Robert Hetzel has suggested that the US bailout of Mexico after the so-called Tequila crisis of 1994 might have convinced investors that the US and the IMF would come to the rescue of key US allies if they where to get into economic troubles. Thailand then and now undoubtedly is a key US ally in South East Asia.

What comes after the bust?

After boom comes bust it is said, but does that also mean that a country that have experience a bubble will have to go through years of misery as a result of this? I am certainly not an Austrian in that regard. Rather in my view there is a natural adjustment when a bubble bursts, as was the case in Thailand in 1997. However, if the central bank allow monetary conditions to be tightened as the crisis plays out that will undoubtedly worsen the crisis and lead to a forced and unnecessarily debt-deflation – what Hayek called a secondary deflation. In the case of Thailand the fixed exchange rate regime was given up and that eventually lead to a loosening of monetary conditions that pulled the

NGDP targeting reduces the risk of bubbles and ensures a more swift recovery

One thing is how to react to the bubble bursting – another thing is, however, to avoid the bubble in the first place. Market Monetarists in favour NGDP level targeting and at the moment Market Monetarists are often seen to be in favour of easier monetary policy (at least for the US and the euro zone). However, what would have happened if Thailand had had a NGDP level-targeting regime in place when the bubble started to get out of hand in 1988 instead of the fixed exchange rate regime?

The graph below illustrates this. I have assumed that the Thailand central bank had targeted a NGDP growth path level of 10% (5% inflation + 5% RGDP growth). This was more or less the NGDP growth in from 1980 to 1987. The graph shows that the actually NGDP level increased well above the “target” in 1988-1989. Under a NGDP target rule the Thai central bank would have tightened monetary policy significantly in 1988, but given the fixed exchange rate policy the central bank did not curb the “automatic” monetary easing that followed from the combination of the pegged exchange rate policy and the positive supply shocks.

The graph also show that had the NGDP target been in place when the crisis hit then NGDP would have been allowed to drop more or less in line with what we actually saw. Since 2001-2 Thai NGDP has been more or less back to the pre-crisis NGDP trend. In that sense one can say that the Thai monetary policy response to the crisis was better than was the case in the US and the euro zone after 2008 – NGDP never dropped below the pre-boom trend. That said, the bubble had been rather extreme with the NGDP level rising to more than 40% above the assumed “target” in 1996 and as a result the “necessary” NGDP was very large. That said, the NGDP “gap” would never have become this large if there had been a NGDP target in place to begin with.

My conclusion is that NGDP targeting is not a policy only for crisis, but it is certainly also a policy that significantly reduces the risk of bubbles. So when some argue that NGDP targeting increases the risks of bubble the answer from Market Monetarists must be that we likely would not have seen a Thai boom-bust if the Thai central bank had had NGDP target in the 1990s.

No balance sheet recession in Thailand – despite a massive bubble

It is often being argued that the global economy is heading for a “New Normal” – a period of low trend-growth – caused by a “balance sheet” recession as the world goes through a necessary deleveraging. I am very sceptical about this and have commented on it before and I think that Thai experience shows pretty clearly that we a long-term balance sheet recession will have to follow after a bubble comes to an end. Hence, even though we saw significant demand deflation in Thailand after the bubble busted NGDP never fell below the pre-boom NGDP trend. This is pretty remarkable when the situation is compared to what we saw in Europe and the US in 2008-9 where NGDP was allowed to drop well below the early trend and in that regard it should be noted that Thai boom was far more extreme that was the case in the US or Europe for that matter.

David Davidson and the productivity norm

Mattias Lundbeck research fellow at the Swedish free market think tank Ratio has an interesting link to a paper by Gunnar Örn over at Scott Sumner’s blog. The paper is from 1999 and is in Swedish (so sorry to those of you who do not read and understand Scandinavian…).

The paper reminded me that David Davidson – who was a less well known member of the Stockholm School – was a early proponent of a variation of the productivity norm. Davidson suggested that the monetary authorities should decompose the price index between supply factors and monetary/demand factors. Hence, this is pretty much in line with what I recently have suggested with my Quasi-Real Price Index (strongly inspired by David Eagle). Davidson’s method is different from what I have suggested, but the idea is nonetheless the same.

George Selgin has discussed Davidson’s idea extensively in his research. See for example here from “Less than Zero”:

“In his own attempt to assess the wartime inflation Swedish economist David Davidson came up with an ‘index of scarcity’ showing the extent to which the inflation was due to real as opposed to monetary factors (Uhr, 1975, p. 297). Davidson subtracted his scarcity index from an index of wholesale prices to obtain a residual representing the truly monetary component of the inflation, that is, the component reflecting growth in aggregate nominal spending.”

I hope in the future to be able to follow up on some of Davidson’s work and compare his price decomposition with my method (I should really say David Eagle’s method). Until then we can hope that some of our Swedish friends will pitch in with comments and suggestions.

——-

Mattias has a update on his blog on this comment. See here (Swedish)

 

Scott is right: Recessions are always and everywhere a monetary phenomenon – just look at QRPI

Scott Sumner has a couple of fascinating posts on recessions on his blog (see here and here).

Scott argues strongly that recessions are a result of nominal shocks rather than real shocks. Scott uses an innovative measure to identify US recessions since 1948. Scott claims that the US economy can be said to be in recession if the unemployment rate increases by 0.6% or more over a 12 months period. That gives 11 recessions since 1948 in the US.

I have compared the timing of these recessions with my measure of “demand inflation” based on my Quasi-Real Price Index (QRPI). If Scott is right that nominal shocks are the key (the only?) driver of recessions then there should be a high correlation between demand inflation and recessions.

The correlation between the two measures is remarkably strong. Hence, if we define a negative nominal shock as a drop in demand inflation below 0% then we have had 7 negative nominal shocks since 1948 in the US. They all coincide with the Sumner-recessions – both in timing and length.

The only four of Scott’s recessions not “captured” by the QRPI development are the recessions in 1970s and the 1980s where demand inflation (and headline inflation) was very high. Furthermore, it should be noted that in two out of four “unexplained” recessions demand inflation nonetheless dropped significantly – also indicating a negative nominal shocks. This basically means that 9 out of 11 recessions can be explained as being a result of nominal shocks rather than real shocks.

Hence, the evidence is very strong that if demand inflation drops below zero then the US economy will very likely enter into recession.

So yes, Scott is certainly right – recessions are always and everywhere a monetary phenomenon! (at least in 80%  of the time). So if the Fed want to avoid recessions then it should pursuit a target for 2% growth path for QRPI or a 5% growth path for NGDP!

US Monetary History – The QRPI perspective: 1970s

I am continuing my mini-series on US monetary history through the lens of my decomposition of supply inflation and demand inflation based on what I inspired by David Eagle have termed a Quasi-Real Price Index (QRPI). In this post I take a closer look at the 1970s.

The economic history of the 1970s is mostly associated with two major oil price shocks – OPEC’s oil embargo of 1973 and the 1979-oil crisis in the wake of the Iranian revolution. The sharp rise in oil prices in the 1970s is often mentioned as the main culprit for the sharp increase in US inflation in that period. However, below I will demonstrate that rising oil prices actually played a relatively minor role in the increase in US inflation in that period.

The graph below shows the decomposition of US inflation in 1970s. As I describe in my previous post demand inflation had already started to inch up in the second half of 1960s and was at the start of the 1970s already running at around 5%.

After a drop in demand inflation around the relatively mild 1969-70 recession demand inflation once again started to pick up from 1971 and reached nearly 10% at the beginning of 1973. This was well before oil prices had picked up. In fact if anything supply inflation helped curb headline inflation in 1970-71.

The reason for the drop in supply inflation might be partly explained by the Nixon administration’s use of price and wage controls to curb inflationary pressures. These draconian measures can hardly be said to have been successful and to the extent it helped curb inflation in the short-term it provided Federal Reserve chairman Arthur Burns with an excuse to allow the monetary driven demand inflation to continue to accelerate. It is well known that Burns – wrongly – was convinced that inflation primarily was a cost-push phenomenon and that he in the early 1970 clearly was reluctant to tighten monetary policy because he had the somewhat odd idea that if he tightened monetary policy it would signal that inflation was out control and that would undermine the wage controls. Robert Hetzel has a very useful discussion of this in his “The Monetary Policy of the Federal Reserve”.

As a result of Burn’s mistaken reluctance to tighten monetary policy demand inflation kept inching up and when then the oil crisis hit in 1974 headline inflation was pushed above 10%. However, at that point almost half of the inflation still could be attributed to demand inflation and hence to overly loose monetary policies.

Headline inflation initially peaked in 1974 and as oil prices stopped rising headline inflation gradually started to decline. However, from 1976 demand inflation again started inching and that pushed up headline inflation once again.

In 1979 Paul Volcker became Federal Reserve chairman and initiated the famous Volcker disinflation. Scott Sumner has argued that Volcker didn’t really tighten monetary policy before 1981. I agree with Scott that that is the conclusion that if you look at market data such as bond yields and the US stock market. Both peaked in 1981 rather than 1979 indicating that Volcker didn’t really initiate monetary tightening before Ronald Reagan became president in 1981. However, my measure for demand inflation tells a slightly different story.

Hence, demand inflation actually peaked already in the first quarter of 1979 and dropped more than 5%-point over the next 12 month. However, as demand inflation started to decline the second oil crisis of the decade hit and that towards 1980 pushed headline US inflation up towards 13%.

So there is no doubt that rising oil prices indeed did contribute to inflation in the US in the 1970s, however, my decomposition of the inflation data clearly shows that the primary reason for the high and increase through the decade was the Federal Reserve’s overly loose monetary policy.

Finally it should be noted that the 1970s-data show some strength and weaknesses in my decomposition method. It is clearly a strength that the measure shows the impact of the oil price shocks, but it is also notable that these shocks takes 3-4 years to play out. So while oil prices spiked fast in for example 1974 and then settle at a higher level the supply shock to inflation seems to be more long lasting. This indicates some stickiness in prices that my decomposition method does not fully into account. As one of my commentators “Integral” has noted in an earlier comment it is a weakness with this decomposition method that it does not take into account the upward-sloping short-run AS curve, but rather it is assumed that all supply shocks shifts the vertical long-run AS curve left and right. I hope I will be able to address this issue in future posts.

In my next post I will have a closer look at how Paul Volcker beat the “Great Inflation”.

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