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Home / Publications / Research / Economic Brief / 2021

Economic Brief
February 2021, No. 21-04

Seek and Ye Shall Not Find: The Absence of Hysteresis in
U.S. Macroeconomic Data
Article by: Luca Benati and Thomas A. Lubik

Economists are keenly interested in longer-run economic phenomena that
interact with short-run shocks and business cycles. A particularly well-known
example is hysteresis, which posits that disturbances typically thought of as
transitory actually can have permanent e ects. While this concept is wellrecognized in theoretical modeling, empirical evidence has been sparse. After
conducting a thorough analysis of U.S. macroeconomic data, we conclude that
there has been no hysteresis in the United States for the past 60 years.
Hysteresis is the idea that economic shocks that are generally considered temporary can
sometimes have permanent e ects. A prime example is when the Federal Reserve
increases its target interest rate to stem rising in ation. The e ects of such a policy action
would normally fade out over time, but if hysteresis exists, a temporary hike could lead to
permanently higher unemployment.
The possible existence of hysteresis has wide-ranging implications for the conduct of
monetary policy and other stabilization policies. If the e ect is quantitatively important, this
would mean that any policy action would have stronger e ects than typically believed, a
revelation that might change how the Fed approaches policy. Speci cally, in a downturn,
monetary policy would have to be more aggressive to prevent hysteresis in the labor
market. Similarly, in better times, it would make sense to "run the economy hot" to
permanently reduce the unemployment rate.
A secondary concern is that policy goals, such as a low and stable unemployment rate,
would become moving targets, which would make calibrating the policy stance more
di cult. For example, if a contractionary policy action a ects the long-run, or "natural," rate
of unemployment, then the action would have to be stronger to close the gap between the
observed current rate and the unobserved natural rate since policy would move both rates
in the same direction but at di erent speeds.


Economic Mechanisms Behind Hysteresis
Economists understand how hysteresis can arise in economic models. A key example is the
labor market. Suppose an economy were a ected by a long and deep recession, such as
the Great Recession of 2007–09. It produced the highest rate of long-term unemployment
— at its peak, almost half of the overall unemployment rate — since the Great Depression.
This outcome was especially challenging because job- nding rates for the long-term
unemployed decline dramatically relative to workers who have lost jobs recently. At some
point, the long-term unemployed are likely to become discouraged and drop out of the
labor force, which could reduce employment and GDP permanently. Thus, a disturbance
that usually would be considered temporary, such as the changing risk appetites for certain
nancial instruments that precipitated the Great Recession, can a ect output
Another mechanism that generates hysteresis in economic models is the disruption of
knowledge creation and business formation. Consider a model with a random but steady
ow of ideas from innovators who require capital to turn their ideas into products and
businesses. If a shock to the economy interrupts this process, even though the shock
appears to be temporary, the shock would permanently decrease output. In other words, if
Thomas Edison had not secured timely investor support (luckily, the U.S. economy was
awash in liquidity when he patented his lightbulb lament), then perhaps we would be
writing this Economic Brief in candlelight and U.S. GDP would be on a much lower path.

Searching for Hysteresis
In a recent working paper, we investigate the empirical case for the presence of hysteresis
in aggregate data in the United States, the euro area and the United Kingdom.
The fundamental challenge to nding evidence of hysteresis is to separate permanent
components from transitory components in macroeconomic data. For example, GDP in
these three major economies has trended upward over time at fairly stable rates, but there
have been persistent movements around the respective trends, even to the point where the
trends on occasion appeared to be shifting. It has become standard in the statistical
analysis of GDP and its components — such as consumption, investment and employment
— to model the behavior of GDP as a so-called "unit root process with drift." The
characteristic feature of such a process is that once the trend is disturbed, it never returns
to the path it would have followed without the disturbance; that is, shocks to the process
have permanent e ects.
Qualitatively similar reasoning can be applied to the natural unemployment rate: After
every business cycle, it does not seem to return to its previous level, so the natural rate of
unemployment appears to be shifting.2 This evidence suggests that hysteresis e ects are


a ecting labor market outcomes.
Another challenge in the search for hysteresis is to separate shocks that are commonly
understood to have permanent e ects from those that are commonly believed to produce
transitory outcomes. Economists unambiguously place changes in total factor productivity
— the ultimate engine of economic growth — in the permanent category. The development
of the steam engine, for example, led to a surge of economic activity in the 18th century
that has persisted until now and will continue in the future. In the latter category of
transitory shocks — de ned as shocks that a ect movements around a long-term growth
path — economists typically include monetary policy shocks, stimulus checks and
alternating attitudes toward work versus leisure. Such shocks do not change long-term
economic growth potential.
For simplicity, we label permanent shocks as supply shocks and temporary shocks — that
is, those commonly considered to be temporary — as demand shocks. In the latter
category, however, we recognize the possibility of a hysteresis shock, namely an aggregate
demand shock that has permanent e ects. This is what makes the notion of hysteresis
important: the idea that economic-stabilization policies can have unintended consequences
when the potential presence of hysteresis is ignored.
But accounting for the potential presence of hysteresis is di cult. In a way, it is very much a
knife-edge proposition between shocks that are highly persistent but transitory and those
that are truly permanent. In fact, it might simply be impossible to distinguish highly
persistent behavior from permanent behavior in the timeframes of data that economists
typically have available. Similarly, disentangling demand shocks and supply shocks, while
relatively straightforward in theory, is often fraught with statistical uncertainty in practice.
Against these caveats, we deploy various statistical techniques and identi cation
assumptions that are designed to sharpen the inference of our ndings and allow us to
extract meaningful hysteresis shocks.

A Statistical Model of the U.S. Economy
In our search for hysteresis, we start by specifying a structural vector autoregressive (SVAR)
model to describe the evolution of the U.S. economy over the past 60 years. This SVAR
captures the interconnectedness of the main macroeconomic aggregates, selected labor
market variables and short-term and long-term interest rates. The behavior of these
variables over time is governed by their past values and driven by shocks.
Our rst key modeling assumption is allowing for the possibility of cointegration, a
statistical relationship in which variables trend together tightly in the long run but only
loosely in the short run. Notable examples are GDP, consumption and investment, which
should share the same long-run growth trend. A similar cointegrated relationship might
exist among interest rates of di erent maturities and also among labor market variables.


Wherever we nd cointegration, we subsequently impose it on the estimation of the SVAR.
This procedure helps sharpen the inference — that is, reduce the uncertainty surrounding
the presence of hysteresis e ects — but more importantly, it allows us to disentangle
permanent components from transitory components in the variables. This separation
becomes the key element behind our second assumption.
In the next step, we use the estimated cointegrated SVAR to disentangle temporary and
permanent supply and demand shocks. The identi cation assumptions to achieve this are
broadly consistent with a variety of economic theories and have been used previously in
the literature. Speci cally, we assume that a permanent and positive aggregate supply
shock is identi ed by its e ect on GDP and the price level in the long run. (It raises GDP and
lowers prices.) In the short run, temporary demand shocks impact GDP and prices in the
same direction, while temporary supply shocks impact GDP and prices in opposite
directions. Finally, the long-run impact of demand shocks on GDP and prices crucially
hinges on whether there is hysteresis. Without hysteresis, GDP would remain unchanged in
the long run, and the only impact would be on the price level. If there is hysteresis, demand
shocks would permanently shift GDP in the same direction, while their impact on prices
would be ambiguous.
The search for hysteresis therefore boils down to a very simple test: Do identi ed
permanent demand shocks in a cointegrated SVAR move output in the long run? This
question assumes that the estimation method can identify hysteresis shocks at all, which is
not necessarily a given. If the answer is yes, if these shocks exist and are substantially
di erent from zero, then we have found what we were seeking.

No Hysteresis — Except by Statistical Decree
The evidence from U.S. macroeconomic data based on the approach described above
shows clearly that there is no hysteresis. Speci cally, the algorithm we use to extract the
various types of shocks from the estimated cointegrated SVAR cannot nd any aggregate
demand shocks that have permanent e ects on GDP. Consequently, we conclude that
macroeconomic dynamics in the United States are determined by transitory supply and
demand shocks around a permanent trend component that is bu eted by long-run supply
Naturally, this nding is subject to many caveats, and it could be just a uke of the data. In
order to address the latter possibility, we implement an alternative statistical methodology
to try to establish if it is at all possible to nd hysteresis shocks given the empirical
speci cation (which is widely used in the literature) and the identi cation assumption
(which is also standard and fairly basic).


Our alternative statistical methodology is the Bayesian approach to estimation and
inference. It allows us to incorporate additional information, such as additional data
sources or various ranges in which estimation results are likely to be found. Repeating the
previous exercise under the same identi cation assumptions, we nd the same result. The
possibility that there are hysteresis shocks that move output permanently is nearly zero in
this analysis, and the quantitative importance of such a shock in explaining the long-run
behavior of GDP would be very small.
We then consider a speci cation that imposes the presence of hysteresis on the shock
identi cation. In this case, hysteresis arises by de nition. The point of this exercise is to
make sure that if there were a permanent e ect from a demand shock on GDP, our
methodology would have found it. Applying this same analysis to data from the euro area
and the United Kingdom, we nd essentially the same result. In neither case could we
identify hysteresis shocks unless we imposed their existence ex ante.

Economists have increasingly turned their attention to longer-run economic phenomena
that interact with short-run shocks and business cycles.3 A particularly well-known
application and example is hysteresis, which posits that disturbances typically thought of as
transitory actually can have permanent e ects. While this is a recognized idea in theoretical
modeling, empirical evidence has been di cult to come by, perhaps largely because the
object of interest, namely outcomes in the long run, are still far away. In a recent working
paper, we apply sophisticated empirical techniques to dig into this question. Our answer is
perhaps surprisingly unequivocal: There is no hysteresis in aggregate U.S. data. GDP is
driven in the long run by aggregate supply movements, while demand disturbances only
matter for movements around this trend.
Luca Benati is a professor of economics at the University of Bern. Thomas A. Lubik is a
senior advisor in the Research Department of the Federal Reserve Bank of Richmond.


This issue, with special reference to the Great Recession, is discussed in Andreas Hornstein and
Thomas A. Lubik, "The Rise in Long-Term Unemployment: Potential Causes and Implications,"
Federal Reserve Bank of Richmond Economic Quarterly, Second Quarter 2015, vol. 101, no. 2, pp.
125–149. The precise economic mechanism that makes it di cult for the long-term unemployed
to nd jobs could be an insider-outsider theory of the labor market (which prevents wages from
adjusting downward), as advanced by Olivier J. Blanchard and Lawrence H. Summers, "Hysteresis
and the European Unemployment Problem," NBER Macroeconomics Annual, 1986, vol. 1, pp. 15–
78. An alternative hypothesis is high reservation wages by the unemployed, as suggested by Lars
Ljungqvist and Thomas J. Sargent, "The European Unemployment Dilemma," Journal of Political
Economy, June 1998, vol. 106, no. 3, pp. 514–550.



This pattern is documented by Luca Benati and Thomas A. Lubik, "The Time-Varying Beveridge
Curve," in Advances in Non-Linear Economic Modeling: Theory and Applications, edited by Frauke
Schleer-van Gellecom, Berlin: Springer-Verlag, 2014, pp. 167–204. They show that the U.S.
unemployment rate achieves a new long-run (or natural) level only after deep and prolonged

These e orts are discussed in Renee Haltom, Thomas A. Lubik, Christian Matthes and Fabio
Verona, "Moving Macroeconomic Analysis Beyond Business Cycles," Federal Reserve Bank of
Richmond Economic Brief No. 19-04, April 2019.

This article may be photocopied or reprinted in its entirety. Please credit the authors,
source, and the Federal Reserve Bank of Richmond and include the italicized statement
Views expressed in this article are those of the authors and not necessarily those of the Federal
Reserve Bank of Richmond or the Federal Reserve System.

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