Transcript Business Cycle Indicators

Predicting Recessions and Slowdowns:
A Robust Approach
Pami Dua
Delhi School of Economics, University of Delhi
and
Economic Cycle Research Institute, New York
Presentation to 15th Conference of
Commonwealth Statisticians
February 7, 2011
Objectives
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Can we Predict Recessions?
Business Cycle Analysis: Background
Indicator Analysis: A Robust Approach
Can we Predict Recessions?
The sheer severity of the Great Recession for many
developed economies – most importantly the United
States – motivates the vital question of whether the
recession, or the crisis that triggered it, could have been
foreseen.
Can we Predict Recessions?
A few years ago, the International Monetary Fund completed a 63country study of the ability of economists’ consensus forecasts to
predict recessions. The IMF concluded:
“The record of failure to predict recessions is virtually
unblemished.”
The real challenge is not to identify the best model to predict
recessions ex post in a specific economy over a given time frame,
but to identify approaches that are robust enough to perform well
in real time under diverse structural conditions.
Can we Predict Recessions?
Key is to make timely recession calls in fast-changing emerging
markets as well as in mature economies undergoing material
structural changes.
Thus it would do little good to develop models optimized on the
basis of past performance if the future is likely to be quite different.
Real time forecasting failure cannot therefore always be blamed
on “parameter drift” or “this time it’s different” as an excuse for
forecast error.
Can we Predict Recessions?
Econometric models are “falsifiable” since these can be tested
against real data.
On the other hand, the leading indicator approach relies on
descriptive observations of sequences of events in the vicinity of
cyclical turning points that are not ‘falsifiable’.
The pioneers of business cycle research were Wesley C. Mitchell
and Arthur F. Burns, who in 1938 identified the very first “leading
indicators of cyclical revival” . They were later joined by Geoffrey
H. Moore who developed the first ever list of “leading indicators of
cyclical revival and recession.”
Can we Predict Recessions?
Steps in indicator analysis:
 Define a business cycle
 Define a recession
 Determine the reference chronology – benchmark for
determining recession-forecasting performance
 Identify leading indicators on the basis of the reference
chronology
Business Cycle Analysis:
Background
The Classical Business Cycle
“Business cycles are a type of fluctuation found in the aggregate
economic activity of nations that organize their work mainly in
business enterprises.
A cycle consists of expansions occurring at about the same time
in many economic activities, followed by similarly general
recessions, contractions, and revivals which merge into the
expansion phase of the next cycle.
This sequence of changes is recurrent but not periodic.
In duration business cycles vary from more than one year to ten or
twelve years; they are not divisible into shorter cycles of similar
character with amplitudes approximating their own.”
-- Burns and Mitchell, 1946
Recessions and Expansions
A recession is the phase of the business cycle marked
by pronounced, pervasive and persistent declines in the
key measures of aggregate economic activity, i.e.,
output, employment, income and sales.
An expansion is the phase of the business cycle marked
by pronounced, pervasive and persistent increases in
the key measures of aggregate economic activity, i.e.,
output, employment, income and sales.
Alternating expansions and recessions make up the
business cycle.
Business Cycles, Growth Cycles,
Growth Rate Cycles
 The business cycle is a consensus of cycles in many
activities, which have a tendency to peak and trough around
the same time.
 A growth cycle traces the ups and downs through deviations
of the actual growth rate of the economy from its long-run
trend rate of growth.
 Growth rate cycles are the cyclical upswings and downswings
in the growth rate of economic activity.
Business Cycles and Growth Rate Cycles
Indicator Approach to Monitoring
Economic Activity
 A coincident indicator measures current
economic activity. It turns down when the
economy turns down and up when the economy
turns up.
 A leading indicator predicts future economic
activity. It turns down before the economy
enters a recession and up before the expansion
begins.
Composite Indexes
 A composite index is constructed from a number of
individual economic indicators. By construction, it has
more information than any individual component of the
index.
 A composite coincident index comprises variables that
collectively represent the current state of the economy. It
indicates whether the economy is currently expanding or is
in a recession.
 A composite leading index includes variables that
collectively anticipate turning points of the business cycle.
This is used as a predictive tool to gauge if and
approximately when a recession or an expansion might take
place.
Leading Indexes can Time Turns
Lead
Leading Index
Target
The Recession as a Vicious Cycle
A recession occurs when a decline in some measure of aggregate
economic activity sets off cascading declines in the other
coincident measures of activity.
Thus, when a dip in sales causes a drop in production, triggering
declines in employment and income, which in turn feed back into
a further fall in sales, a vicious cycle results and a recession
ensues.
This domino effect of the transmission of economic weakness
from sales to output to employment to income, feeding back into
further weakness in all of these measures in turn, is what marks a
recessionary downturn.
This effect spreads from industry to indutry, region to region, and
indicator to indicator.
The Expansion as a Virtuous Cycle
At some point, the vicious cycle is broken and an
analogous self-reinforcing virtuous cycle begins, with
increases in output, employment, income and sales
feeding into each other – the hallmark of a business
cycle expansion.
How the Virtuous Cycle Works
Turning Points:
Business Cycle Peaks and Troughs
Because recessions can be characterized as vicious
cycles and expansions as virtuous cycles, the transition
points between the vicious and virtuous cycles, based
on the consensus of the coincident indicators (output,
employment, income and sales), properly mark the start
and end dates of recessions (peaks and troughs).
That is also why “two down quarters of GDP” is not an
adequate definition, nor a proper criterion, for a
recession.
Business Cycle Chronologies
The historical dates of business cycle peaks and troughs
are thus based on the consensus of the dates of the
peaks and troughs in the broad measures of output,
employment, income and sales.
For 20 economies, ECRI maintains business cycle peak
and trough dates based on the same approach.
The up-to-date list of business cycle dates for 20
countries including the U.S. is available here:
http://www.businesscycle.com
Growth Rate Cycle Chronologies
Growth rate cycles are made up of alternating periods of
rising and falling economic growth.
They are based on the growth rates of the coincident
indicators whose levels relate to business cycles, and
do not rely on estimation of the current trend. Hence,
growth rate cycles, along with business cycles, are
useful for real-time monitoring of the economy.
For this reason, ECRI maintains growth rate cycle
chronologies for 20 countries:
http://www.businesscycle.com
Turning Points are Hard to Predict
Forecast Error
Target
Consensus Forecast
Taming the Cycle
Effects of Higher Trend
& Lower Volatility on Business Cycles
8
Reducing Recessions:
Raise trend rate of
growth
Lower amplitude of
cycles
4
0
Recessions
-4
8
4
0
Higher Trend: No Recessions
-4
88
4
00
-4
-4
Lower Volatility: No Recessions
Hence the need to anticipate
After Chrysler’s near-death experience in early
1980’s the then Chairman, Lee Iacocca told his
Chief Economist:
"All I want from you is that you let me know six
months before the next downturn."
Robustness of Indicator Analysis
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Based on an understanding of business cycle theory,
Moore examined the empirical record of the behaviour
of a list of indicators at business cycle peaks and
troughs. This empirical testing – based on U.S. data
from 1870 to 1938 – determined the final selection of
Moore’s 1950 list of eight leading indicators of
recession and recovery.
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This entire process was rooted in business cycle theory:
not in falsifiable statistical models, to be sure, but in a
theoretical, conceptual understanding of the drivers of
the business cycle, nevertheless. Empirical testing
played only a secondary role in this process.
Robustness of Indicator Analysis
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Nearly half a century later, Moore asked the question:
we know that the original leading indicators anticipated
both recessions and recoveries in the late 19th and
early 20th centuries, but what have they done for us
lately?
He tested their “out-of-sample” performance, so to say,
in the second half of the 20th century (Moore and
Cullity, 1994). All the leading indicators continued to
lead at US business cycle turning points.
Robustness of Indicator Analysis
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We recently completed a similar analysis for the US
from the mid 20th century through the early 21st century,
including the Great Recession. Results are similar.
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We also gathered data on the same indicators, or their
closest equivalents, in all the Group of Seven (G7)
economies other than the U.S. in the postwar period.
Remarkably, when we compared their turning points
with the respective business cycle chronologies
established independently by ECRI on the same basis
as in the U.S., their performance held up.
Robustness of Indicator Analysis
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Next, we conducted a similar analysis, but on the basis
of growth rate cycles (acceleration-deceleration cycles,
consisting of alternating cyclical upswings and
downswings in economic growth) rather than classical
business cycles.
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We found that the growth rates of the same leading
indicators continued to lead the respective growth rate
cycle turning points, which had been determined
independently by ECRI for all the G7 economies
Average Leads, in Months, of
Eight Leading Indicators Selected in 1950
9
8
7
6
5
4
3
2
1
G7 excl. U.S.
0
Before 1938:
Business cycles
U.S.
1948-2008:
Business cycles
1948-2008:
Growth rate cycles
Robustness of Indicator Analysis
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We also constructed a composite leading index out of
Moore’s original list of U.S. leading indicators. That
leading index covers 107 years and 21 recessions,
including the 1907-08 and 1920-21 depressions, the
entire period of the Great Depression, and the more
recent Great Moderation. Again, no data fitting was
involved in creating the index.
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So how did the Index of Original Leading Indicators
(IOLI) perform during the Great Recession, which
caught so many by surprise? As a matter of record, it
peaked in July 2007, five months before the official
December 2007 U.S. business cycle peak. It
subsequently troughed in March 2009, three months
before the June 2009 U.S. business cycle trough.
Robustness of Indicator Analysis
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Over its 107-year span, the IOLI exhibits a median
lead of 4.5 months at US business cycle peaks and
three months at business cycle troughs, leading at
93% of business cycle turning points.
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In the out-of-sample post-war period, the statistics are
similar: the IOLI has a median lead of six months at
business cycle peaks and three months at business
cycle troughs, leading at 91% of business cycle
turning points.
Robustness of Indicator Analysis
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What we have shown is that, when evaluated
against those objective cyclical benchmarks, the
original leading indicators of recession and
recovery – selected primarily on a conceptual basis
– continue to exhibit remarkably robust
performance under a wide range of conditions.
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Whether we are faced with the specific likelihood of
more frequent U.S. recessions, as ECRI’s research
suggests, or with unforeseeable changes in
structural conditions that may shape the next cycle,
it is our belief that it would surely be prudent to rely
on a time-tested, robust approach to business
cycle forecasting.
Way Forward
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The field of economic forecasting faces formidable
challenges in the years ahead. Robust leading
indicators can provide only a partial answer.
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Unlike econometric models, leading indicators are
designed to predict only the timing of cyclical turning
points, not forecasts of the magnitude of economic
variables. Nor can they answer “what if” questions
which are central to policy decisions.

This approach should therefore be seen as a
complementary tool but one that is capable of
providing invaluable guidance in the lead-up to
recessions and recoveries, preventing decision makers
from being blindsided by the inevitable turning points
in years to come.
Thank You!
Annualized Growth in U.S. Coincident Indicators
in Postwar U.S. Expansions (%)
12
10
8
6
4
2
Industrial Production
Mfg &Trade Sales
0
49-53
54-57
Personal Income
58-60
61-69
70-73
GDP
75-80
80-81
82-90
Employment
91-01
01-07
Three Key Aspects of the Economy
Economic Growth
Employment
Inflation
The State of the Art
Inflation
Imports
Manufacturing
Trade
Balance
Construction
Economic Growth
Non-Mfg
Non-Financial
Employment
Exports
Services
Financial
Mfg
Domestic
Long Leading, Weekly Leading,
Short Leading & Coincident
Foreign
Trade
Employment
Future Inflation Gauge
Home Prices
Crack of the Bullwhip
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Around the globe, recession is being
transmitted in amplified form to the more
export-oriented economies
Ruth Mack, a colleague of ECRI founder Dr.
Geoffrey H. Moore, uncovered this link in a
study of shoe, leather and hides
When Mack did her study, shoes were not
impulse buys but expensive products that
consumers would buy in good times
In not so good times, consumers would get
their shoes repaired and postpone the
purchase, implying that shoe demand was
moderately cyclical
Crack of the Bullwhip
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An increase in inventories of shoes and shoe leather
due to a drop in demand resulted in shoemakers
reducing production and orders for leather
Thus slowdown in shoe demand would result in an
actual decline in the demand for leather, which is
made from cattle hides
This would trigger a sharp plunge in the demand for
hides
Thus small shifts in demand growth at the consumer
level are amplified through the supply chain into big
swings in demand as we move up the supply chain
away from the consumer
This is the BULLWHIP EFFECT because a little flick of
the wrist produces a big arc at the end of the whip
Shoe-Leather-Hide Sequence:
The Bullwhip Effect
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Frontline demand is
cyclical
Midline demand is
more cyclical
Demand early in the
supply-chain is most
cyclical but supply is
relatively insensitive,
so prices are highly
cyclical
Shoe Demand:
Growth Slows
Leather Demand:
Level Falls
Hides Demand:
Level Plunges
Bullwhip Effect Bottom Line
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Contractions in the global economy are
concentrated in the developed
countries
Economies that are heavily involved in
the exports of manufactured goods will
be lashed by the Bullwhip Effect and
their suppliers – especially the
producers of industrial commodities,
including oil – will be in even worse
predicaments