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Remarks by Governor Laurence H. Meyer

Economic forecasting
Before the Downtown Economics Club 50th Anniversary Dinner, New York, NY
June 3, 1998
Let me offer my congratulations on achieving this milestone – the 50th anniversary of the
Downtown Economics Club. My talk this evening is not a forecast, but rather focuses on
forecasting and reflects a perspective shaped by both my earlier experience as a forecaster
and my new responsibilities as a policymaker. Nevertheless, I will not ignore a critical issue
for both forecasters and policymakers today: can the recent exceptional performance of the
U.S. economy be explained by traditional macroeconometric models, and, if it cannot, what
are the implications for the changing structure of the U.S. economy?
Let me also remind you that, as always, the views I express are my own. I am not speaking
on behalf of either the Board of Governors or the FOMC.
Start with a Paradigm and End with a Story
Forecasting based on structural models, my preferred approach, is not the only way to go
and diversity in our profession, as in others, is to be valued, not just tolerated. Atheoretical
statistical approaches, such as VARs, for example, provide a cheap alternative that, at least
over short horizons, yield forecasts about as accurate as significantly larger structural
models. But let me offer some reasons why I value the traditional model-based approach to
forecasting and policy analysis.
First, model based forecasting begins with a paradigm, a vision of how the economy works.
I suppose the VAR paradigm is that everything depends on everything else, though, in
practice, only a small number of variables can be feasibly included. But the structural model
approach begins with a vision of how the economy works. Consumers of forecasts, in both
the government and in the private sector, want to know why, not just what. VAR’s can
cheaply tell us what. Model-based forecasts also provide a vision of why.
Second, and closely related, a model-based forecast ends with a story. When I was in the
private sector and was asked what I did for a living I often responded that I was a story
teller. My experience as a commercial forecaster taught me that clients did not want to be
buried in computer output or have their vision confined to point estimates. They demanded a
coherent story that tied the forecast together. A model-based forecast essentially has the
ability to defend itself, as long as the model is not so add factored that the fundamental
paradigm is lost in the process.
Third, in between the paradigm and the story, macroeconometric models both rely on theory
grounded in microfoundations and reflect the regularities found in historical data. Models
predict the impact of new shocks through “tried and true” regularities.
Fourth, model-based forecasting is a framework that allows a forecaster to learn from and

indeed use past mistakes to improve future forecasts. This is clearly one of the keys to good
forecasting. It is important to try to identify why you were wrong and to establish what part
or parts of the model were responsible for the greatest errors. Responding to mistakes can
certainly be aided by statistical analysis, but there is often room for judgment in deciding
whether to continue a trend in an error pattern, hold it at its last value, or decay it, more or
less rapidly.
Fifth, atheoretical statistical approaches, as typically used, yield unconditional forecasts.
Most commercial and government forecasters very much want a conditional forecast. Part of
the explanation is the value of contingency analysis, bracketing a baseline forecast with
alternative forecasts based on more optimistic and pessimistic assumptions, and developing
a contingency analysis of major risks to the forecast.
Despite my appreciation of structural models in forecasting, I do not believe in mechanical
model-based forecasting – estimating the model and letting it make the forecast without
intervention of the forecaster. When LHM&A won forecasting awards, I was often asked
about my formula for success. I reported my recipe as one part science, one part judgment,
and one part luck. The science was the model. Art refers to the role of judgment. You
always have to appreciate that your model is too simple and does not account for some
phenomena, especially those that are hard to deal with quantitatively. Periodically, one or
more of these type of variables changes. Then you have to use your best judgment as an
economist to predict the effect. And luck – well that speaks for itself.
The Paradigm
Let me now turn to the paradigm. In macroeconomics, I suppose, the phrase “the paradigm”
seems wholly out of place. So I mean the paradigm that is widely associated with traditional
macro models, though there are, of course, some meaningful differences even within this
I view the traditional model paradigm as an updated and eclectic version of the neoclassical
synthesis. It is defined by three key principles. First, the models are Keynesian in their
short-run properties. Specifically, they allow for sticky prices and as a result output is
demand-determined in the short run. Second, the models are Classical in their long-run
properties. Specifically output is supply-determined in the long run, inflation is principally a
monetary phenomenon, real interest rates are determined by forces of productivity and thrift,
and nominal interest rates vary with inflation. Third, the price-wage dynamics in the model,
most often captured in the Phillips Curve, provides the core of the adjustment mechanism
that guides the transition from short run to long run. This sector essentially pins down just
how sticky prices are in the short run and how long it takes for price flexibility to push the
economy to a long-run equilibrium.
Implications of the Paradigm for Inflation and Growth
Today, the challenge of explaining recent economic performance leads me to focus my
attention on the implications of the paradigm sketched above for growth and inflation.
The growth framework that is embodied in this paradigm is generally the neoclassical model
in which long-run growth is tied down by exogenous trends in population and multi-factor
productivity. Capital deepening – that is, increases in capital relative to labor -- can also
have an influence on the growth of labor productivity. The paradigm allows for an important
but limited influence of fiscal policy on the level of output in the long run, principally via

changes in the structural budget deficit and supply-side tax policy. The models generally
exhibit neutrality, meaning that a higher level of money supply results in proportionate
changes in the price level with no effect on equilibrium values of real variables, implying
that monetary policy pins down inflation, but does not affect real growth in the long run. A
change in the trend rate of growth, in this framework, therefore would reflect some
combination of exogenous changes in population and/or multi-factor productivity trends
and/or endogenous capital deepening.
In these models, as noted earlier, inflation is principally or exclusively a monetary
phenomenon in the long run. Even the recent experience of instability in money demand
functions does not make inflation any less of a monetary phenomenon. Nominal income
growth is, of course, tied down by M and V, as Irving Fisher taught us long ago. But even if
inflation is not precisely related to money growth in the long run, because of shifts in
velocity, the monetary authority ultimately determines and is therefore responsible for
inflation in the long run.
Having asserted the primacy of monetary forces in determining inflation in the long run,
some may wonder at my commitment to the Phillips Curve. You shouldn’t! The Phillips
Curve, as I hope is well known, does not pin down the long-run inflation rate. In the vertical
Phillips Curve, at least, any stable inflation rate is compatible with equilibrium in the labor
and product markets. Instead, the Phillips Curve specifies short-run inflation dynamics -how and why inflation moves from one path to another -- and highlights the critical role of
excess demand as a proximate source of rising inflation.
It is sometimes asserted, incorrectly of course, that the Phillips Curve dictates an inverse
relationship between the change in inflation and unemployment and therefore is clearly
disconfirmed by the recent experience, as well as most of the observations in the 1970s and
some in the 1980s. That was true of the late-1960s' permanent trade-off specification, but
certainly is not true in the version that has been in place since at least the mid-1970s.
This paradigm now always incorporates into the model a second proximate source of
changes in inflation – supply shocks. These refer to changes in the price of some goods that
are unrelated to the balance between supply and demand in the domestic economy. The
classic examples are weather-induced changes in food prices or OPEC-inspired changes in
oil prices. I will return to this subject below, in reference to the current episode. But let me
also emphasize that supply shocks themselves result only in temporary departures of
inflation from the underlying rate justified by money growth. They do not at all undermine
the principle that inflation in the long run is a monetary phenomenon.
Evolution of the Traditional Model
I want now to discuss four developments of special importance in the evolution of practice
in model-based forecasting, post the MPS model of late 1960s vintage. The underlying core
of life cycle consumption, neoclassical investment and labor demand, and inventorytheoretic money demand remains intact. The most important change was, as just noted, the
transition from a Phillips Curve that allowed a long-run trade-off between inflation and
unemployment to the vertical, natural rate specification. This change was well entrenched
by the mid-1970s and was accompanied by a more consistent treatment of inflation in the
models, including more careful differentiation of nominal and real interest rates. In addition,
following the adverse supply shocks of the early 1970s, the models moved to explicitly
incorporate supply shocks into the models.

The second development of special importance is the increased openness of the U.S.
economy. Today, imports are a more important part of the short-run dynamics of the model,
including a significant role as stabilizer of shocks to domestic demand. But this openness
has also subjected the U.S. economy to shocks from abroad and forced forecasters to pay
increasing attention to and incorporate in more detail international linkages. The recent
episode of troubles among emerging Asia economies was outside the boundaries of
coverage in some models, requiring add factoring of import and export equations to
compensate. The experience suggests the importance of sufficiently broad measures of
foreign economic activity and exchange rates in models, increasing the span of the world
that forecasters have to give attention to in conditioning their forecasts for the U.S.
Increased mobility of capital also has sharpened the responsiveness of real exchange rates to
real interest rate differentials across countries. Combined with the increased importance of
imports and exports, this has increased the importance of the exchange rate channel in the
transmission of monetary policy. It now accounts for about one-third of the interest
responsiveness of aggregate demand to changes in interest rates over the one to three year
horizon in the Board staff’s model. Nevertheless, the overall interest sensitivity of aggregate
demand appears to be nearly unchanged, with the increased role of exchange rates
principally offset by decreased interest sensitivity of housing due to the elimination of
Regulation Q and innovations in the financing of home purchases.
Finally, international developments are clearly playing an important role in the recent
restraint on U.S. inflation. No doubt that the three-year appreciation of the dollar has played
a powerful role. So has the lack of conformity in the business cycles in Europe and Japan
relative to the U.S. The latter is especially important due to increased trade flows that
effectively make capacity more of a global concept in some industries. I expect that our
inflation performance would have been less exceptional if Europe and Japan’s cycles had
precisely matched our own and if the dollar had remained stable over the past three years.
A third evolution of structural models is the use of reaction functions to characterize
monetary policy. At LHM&A, we offered our clients the choice of monetary policy regime.
They could exogenize a short-term interest rate, a measure of the money supply,
nonborrowed reserves, or switch on a policy reaction function. All these options have their
uses, but in a period when there is serious doubt about the stability of money demand,
monetary policy reaction functions provide an alternative approach to anchoring the
determination of short-term interest rates.
I have previously noted the irony that policy reaction functions appear to be used more in
models at the Federal Reserve where monetary policy is made than in the private sector
where monetary policy has to be forecast. Many forecasters would prefer to rely on their
interpretation of what various FOMC members say, or what one especially significant
member of the FOMC says or does not say (and I am definitely not talking about myself), in
setting the funds rate in the initial quarter. But after the first quarter or two, a policy reaction
function provides a systematic way to relate monetary policy to the evolution of the forecast.
A policy rule is also consistent with my answer when someone asks me, usually in jest, how
the federal funds rate will change over the next several meetings. They are initially surprised
that I would even answer such a question. But I do and I do so honestly. The answer is: It
depends. Specifically, it depends on how utilization rates, growth, and inflation change over
time and, at times, on changes in the forecast of these variables going forward.

The last major change in modeling is the ongoing attempt to incorporate more explicitly the
role of expectations and to model more richly the formation of expectations. Most
traditional macro models continue to attempt to capture expectations through distributed
lags, an approach that incorporates in a rough way both adjustment costs and expectations
formation. In most cases, a backward-looking adaptive expectations framework remains the
conventional practice. This is an area in which the recently introduced FRB-US model, the
successor to the MPS model at the Board, has significantly innovated.
The thrust of the new work is to separate macro-dynamics into adjustment cost and
expectations-formation components, with adjustment costs imposing a degree of inertia and
expectations introducing a forward-looking element into the dynamics. One result is a
structure that integrates rational expectations into a sticky price model.
The model retains the neoclassical synthesis vision of the MPS model -- short-run output
dynamics based on sticky prices and long-run Classical properties associated with price
flexibility -- and therefore yields multiplier results, both in the short and longer runs, that
frequently are very similar to those produced by the MPS model. The result is that the model
produces, for the most part, what may be the best of two worlds – a modern form and
traditional results! But the better articulated role of expectations in the new model also
allows a richer analysis of the response to those policy actions which might have significant
impacts on expectations of key variables such as inflation and/or interest rates.
Explaining Recent Performance
When I talk about the challenge for monetary policy in the current environment, I often see
a surprised look on the faces in the audience. What challenge? The economy is performing
exceptionally. The only challenge, I am often told, is not to screw it up! But the first
challenge is to understand the source of the exceptional performance. The second is to
position monetary policy in light of the answer to the first challenge.
The surprises, from the perspective of the traditional models, have been the strength of
domestic demand and, especially, the decline in inflation despite steadily rising utilization
rates in the labor market to a level well below virtually anyone’s estimate of the NAIRU.
Many, though perhaps not all, of the explanations for this exceptional performance fit well
enough within the context of traditional models – through some combination of normal
model error, exogenous shocks, and changes in parameters, the latter reflecting structural
changes in the economy.
A significant part of the surprise in domestic demand reflects the unexpectedly sharp run-up
in equity prices. The latter has sharply lowered the private saving rate and boosted consumer
spending, contributed to the buoyancy of the housing market, and reduced the real cost of
capital to businesses, encouraging a more robust pace of business fixed investment.
Virtually all traditional models, I expect, have underpredicted the dramatic rise in stock
prices. But there has also been a correlated set of other demand surprises, including, perhaps
most importantly, in inventory investment.
I have emphasized the role of temporary favorable supply shocks as an important part of the
explanation for the pattern in inflation and unemployment. I noted earlier the role of classic
supply shocks – energy and food prices – as a source of temporary shocks to inflation in
traditional models. In the current cycle many have pointed to a richer set of special forces

acting on inflation – including the appreciation of the dollar, sharper declines in computer
prices, and unusual moderation in health care costs.
I do not believe that the current experience can be understood without placing an important
weight on such favorable supply shocks. On the other hand, I do not believe that supply
shocks alone can fully explain the recent exceptional performance. I have written previously
about the need to balance regularities and possibilities in explaining the current episode. The
regularities refer to the historical regularities embedded in our traditional models, including
the role of supply shocks, though these are often modeled too narrowly to do full justice to
the current experience. Possibilities refer to more permanent structural changes that may
have improved the performance characteristics of the economy, including a lower level of
the NAIRU and a higher trend rate of productivity growth.
Structural change in the economy poses a potentially difficult problem for
macroeconometric models. They are built on a base of a relatively long time series and
therefore give relatively little weight in parameter estimation to the most recent
observations. In many cases, this is a strength, but it can also, at times, be a significant
weakness. It is useful to identify two errors that can be made in light of possible structural
change. First, the model builder could fail to account in a timely way for structural change
and therefore make poor forecasts. Model builders require a high burden of statistical proof
before they jettison old specifications that have worked in the past, in favor of new, as yet
unproven, ones. Thus it could take a pattern of systematic forecast errors built up over time
before the model builder concedes a specification has been altered by structural change in
the economy.
In the second type of error, any forecaster could quickly translate what may be random
errors in the “model” into a presumed structural change, when in fact no such change has
occurred. The latter adjustment might nevertheless mop up the errors for a few quarters, but
would ultimately undermine the accuracy of forecasts going forward. Model-based
forecasters may, I expect, be more likely to make the first error. Forecasters who pay much
more attention to current observations and correspondingly less weight to past observations
are perhaps more likely to make the second type of error. My experience suggests that the
former approach is better on average, but certainly not better in every episode. Only time
will tell which approach will prove to work better in the current episode.
I would be inclined to relax the statistical criteria for structural change when there is a
plausible story and sufficient anecdotal evidence to support the change. This leads me to
more quickly accept the suggestion of recent data that there may have been a decline in
NAIRU, from near 6% in the decade preceding this expansion to about 5 ½% today. This
could be rationalized as arising from increased worker insecurity, reflecting increased
concern about job obsolescence because of technological change and increased recognition
of the flux in the labor market associated with frequent corporate restructuring. It might also
be related to the unusual divergence between labor and product market measures of supplydemand balance. The absence of indications of excessive demand pressures in product
markets, in my view, is a powerful part of the absence of pricing leverage firms regularly
report. As a result, there may be greater reluctance to pay up for labor, even when labor
markets are very tight, given the difficulty in passing on higher wage costs in higher prices.
In the case of productivity growth, on the other hand, I have more questions about a
structural break. I do believe in and take into account capital deepening. Such increases in

the capital-labor ratio generate endogenous changes in the near-term productivity trend
which many models explicitly allow for. Given the investment boom in the current
expansion and the resulting high rate of net investment, it is very plausible that there should
be some acceleration in productivity relative to what it otherwise would have been.
Coming into this expansion, the estimate for the productivity trend was generally 1.1% per
year. But the growth in productivity over this cycle has in fact been less than this trend rate,
despite the recent strong cyclical growth. Because the trend rate cuts across expansions and
recessions, we would have ordinarily expected to see above-average productivity growth
over the expansion. The source of this diminished productivity growth is the unexpected
weakness in productivity growth – near zero – over the two-year period, 1994 to 1995. The
recent acceleration in productivity is mostly consistent with the sharp acceleration in GDP
growth over 1996 through early 1998.
Looking forward, I assume that the earlier trend, adjusted for technical revisions in the price
index and taking into account recent capital deepening, justifies an estimate of 1.3% to 1.4%
for trend non-farm productivity growth in 1998. This will rise further to 1.4% or 1.5% next
year and going forward, due to further technical revisions in the price index. I should stress
that part of this pick-up in productivity is not real; if BEA revised history in line with their
new technical procedures, the old rate of productivity growth would be somewhat higher as
Implications for Monetary Policy
So what does all this imply for the conduct of monetary policy? It suggests that policy is
now being made in an environment characterized by even greater uncertainty about key
parameters than is normally the case. And such uncertainty often justifies more caution
about changes in policy.
But this shouldn’t distract us from the essential reality that there are limits – limits to the
sustainable level of production at any given point in time and to the sustainable growth in
output over time. When I express my concerns about the sustainability of 4 – 5% growth and
a 4.3% unemployment rate, I sometimes hear from those who insist that the old paradigm of
limits has been replaced by the new era paradigm, in which global competition and
productivity improvement on demand guarantee that any level of utilization rates and any
level of growth can be sustained with low stable inflation. Needless to say, I reject this
vision. Old limits may give way to new limits, but if the new limits are not respected, there
will be a price to pay.
A concern in the current environment is that, when the restraining effects of the collection of
favorable supply shocks dissipates or reverses, significant demand pressures will be
unmasked, resulting in a double hit on inflation. Such an outcome is not inevitable. Indeed,
many private sector forecasts tell a story in which this eventuality does not arise or does so
only to a very limited degree. These forecasts trace out what I have referred to as a “reverse
soft landing” in which growth slows, virtually immediately, to below trend, utilization rates
in labor markets ease, and the economy returns to a sustainable balance between supply and
demand just as the favorable supply shocks dissipate. This is not an implausible forecast, by
any means.
The two numbers perhaps most startling in the current environment are 4.3 and 100. The 4.3
is the percent unemployed, the lowest level in more than a quarter of a century. The 100 is

the billions of dollars of inventory investment in the first quarter, a record level, nearly
double the forecast going into the quarter, and between 3 and 4 times the amount of
inventory investment compatible with trend growth. This should unquestionably contribute
to some drag on production going forward.
A second force for moderation is the continuing external drag – reflecting not only spillover
from the Asian emerging economies, but also from the deteriorating performance in Japan
and the weight of the cumulative past appreciation of the dollar relative to other developed
economies. And in the last month or so, the downside risk associated with Asia, Japan and
other emerging and transitional economies, including Latin America and Russia, appears to
have increased.
Finally, there is a prospect that some of the recent positive demand surprises may fade. Even
the failure of the stock market to move to further highs this year, for example, would result
in a much diminished positive impulse from wealth effects on spending over 1999.
The issue is really not whether or not the economy slows. I believe it will, though this belief
has been tested and found wanting too often to want to dwell on in this expansion. But the
issue is how much growth slows and when. To trend or below, or to a level still above
trend? Immediately or later in the year, in the meantime leaving labor markets still tighter
than they are today?
We also have to balance the decline in unemployment against the fall in inflation. Taylor
rules represent one such balancing act and generally find that the two developments have
recently provided nearly offsetting prescriptions of the federal fund rate, thereby justifying
the nearly steady federal funds rate. In the presence of temporary supply shocks, however, it
is useful to use a forecast of inflation, looking beyond the temporary effect, when
interpreting such rules. For example, while the overall CPI increased 1.5% over the four
quarters ended in the first quarter, the Blue Chip Consensus Forecast is for a 2.5% increase
over 1999.
So what is the underlying rate of inflation today? Is the 1½% increase in the overall CPI
over the last year an appropriate point of departure? That depends on your view about
whether oil prices might fall again next year, or rise. Or whether the dollar will continue to
appreciate, or reverse itself next year. Or whether health care costs are in the process of
Even using the core measure, is the underlying inflation rate 2.1%, as in the 12-month
change, slightly below the 2.2% last year and therefore showing no sign of reversal? Or is
the pattern in three-month and six-month readings telling us something important? The 6month compound annual rate of core CPI inflation is 2.5% and the 3-month is 2.8%. These
higher frequency inflation rates are not only greater than the lower frequency rates, but they
show a different trend. Once again, this highlights the importance of judgment in the
forecast. How much data do we need to establish a change in trend?
You will note that I seem to need less data on inflation to question the trend than I did on
productivity. I admit it. I have been watching for a rebound in inflation and have not been
expecting a sharper increase in productivity, beyond the adjustment I have already made for
capital deepening. There is a danger of only seeing what you expect and not respecting the
data. But there is also the issue of adjusting thresholds for accepting changes in trend

conditional on the underlying plausibility of the change.
Fundamentally the challenge for monetary policy is to facilitate a transition from the current
exceptional but unsustainable state to the best possible sustainable state. The transition
might well occur while we play spectator and the reverse soft landing plays out. Or it could
involve our more active participation. It depends!
Let me conclude by again congratulating you on your 50th anniversary. And the best wishes
I can give you on this occasion is for accurate forecasts for the next fifty years.
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