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The headline PMI was designed as an overall barometer of
manufacturing business conditions in the 1980s, bringing together
the results of five questions from the NAPM (now ISM) survey of
purchasing managers into one single-figure diffusion index.
The components with their respective weights are shown
below:
Note that not all PMI survey indices are used in the calculation
of the PMI (the price indices in particular are excluded). Also
note that the suppliers' delivery times index is inverted such that
longer delivery times (sub-50 readings) are associated with busier
periods of economic activity and vice versa.
The rationale behind the methodology was that those components
which tend to lead the business cycle are accorded the highest
weight and those which tend to lag are given the lowest weight.
Hence the new orders index, which tends to move in advance of other
indicators, gets the highest weight. Production is usually quickly
altered in response to any significant order book change, and
therefore receives the second-highest weight, and eventually
employment levels are also altered. At such times of production
capacity growth (or contraction), suppliers also get busier (or
less busy), meaning delivery times can lengthen (or shorten), and
eventually the altered buying process feeds through to changes in
inventories.
Putting theory into practice
The theory does indeed generally work in practice, as chart 1
shows, albeit with some notable exceptions which we will discuss
later. In this instance we illustrate the PMI and its five
components using the eurozone PMI from IHS Markit.
The lagging nature of employment and inventories (stocks of
purchases) are clearly demonstrated in chart 1. To help further
assess the leads and lags of the PMI's components, the correlations
of the five components with the headline PMI are shown in table 2
(again using the eurozone PMI), while table 3 highlights the leads
and lags against official manufacturing production growth (as
measured by the three-month-on-three-month change). Note that the
leads and lags shown in table 3 do not take into account the
earlier publication of the PMI data ahead of the official data,
which represents approximately one additional month of lead for the
PMI.
The correlations and leads and lags (highlighted in yellow) in
table 2 further add to the suggestion that the theory behind the
PMI weighting system derived in the 1980s still largely holds for
the eurozone PMI. This is further supported by table 3. For
example, the highest correlation (highlighted in yellow) for the
new orders index is observed when this index leads official
manufacturing production growth by one month, while the output
index exhibits its highest correlation with no lead or lag.
Suppliers' delivery times, employment and stocks of purchases, in
contrast, all lag changes in production.
PMI lags the new orders sub-index
As expected, the new orders and output indices exhibit a higher
correlation with official manufacturing production than the
headline PMI as these sub-indices are tracking demand and factory
production. Interestingly, however, with the new orders index also
acting with a lead over the headline PMI and other indices, it is
arguably the most useful and reliable single advance indicator of
official manufacturing production.
The tables also show correlations of the other survey
sub-indices which are not included as components in the calculation
of the PMI, some of which provide interesting food for thought. For
example, since the PMI methodology was devised in the 1980s,
manufacturing has seen a shift to the use of just-in-time
production, which likely explains why the quantity of purchases
index (which tracked inputs bought by factories) now performs
extremely well as an indicator of production.
Similarly, the backlogs of work index displays high correlations
with both the headline PMI and the official manufacturing
production data, though it should be noted was only included as a
PMI question in 2002 meaning comparisons with other indices are not
strictly accurate. The high correlation nevertheless hints strongly
that this index can provide a great deal of information with
respect to production capacity utilisation.
Supply delays have distorted the headline PMI
signals
The pandemic has, however, recently thrown up new issues to
further highlight the value of the PMI's sub-indices over and above
the headline PMI.
Most notably, the supply shock caused initially by the closure
of factories in China and the subsequent curding of production
capabilities (and transport capacity) around the world has meant
the suppliers' delivery times has acted to distort the signal from
the headline PMI. By signalling longer deliveries due to factory
closures rather than strong demand for inputs, the headline PMI has
at times understated the downturn or overstated growth relative to
the survey's output gauge. The latest data at the time of writing,
for example, show eurozone industrial output being constrained
relative to order book growth to an unprecedented degree due to
materials shortages.
This order book/output divergence meanwhile helps to illustrate
that, while the new orders index provides a reliable
advance indication of production, the most useful and
reliable coincident indicator of official manufacturing
output is the PMI survey' output sub-index rather than the headline
indicator, a finding which is confirmed by the correlation shown in
table 3.
PMI indices reveal the underlying trend
One further observation to consider, underscored by chart 2, is
that the official data are more volatile than the PMI indices. The
use of a moving average to smooth the official data therefore
serves to highlight how useful the PMI is in cutting through the
volatile 'noise' of the official data to thereby reveal the
underlying growth rate in the economy (see chart 4).
Building new indicators
So far we have only looked at the headline PMI and its five
components. However, to really understand the dynamics of the
manufacturing sector at any time, users really need to look at all
of the survey's subindices to understand the interplays of demand,
supply and production in order to fully appreciate growth momentum.
Often this is aided by looking at ratios between different survey
indices.
One such ratio is shown in chart 5, which looks at the extent to
which new orders inflows are diverging from the amount of
inventories of finished stock held by manufacturers. The theory
here is that if orders start to rise while inventories are low or
falling, production will soon be raised, and vice versa. As chart 4
shows, this ratio clearly acts not only as good lead-indicator of
official production data (a correlation of 0.81 with the ratio one
month ahead of the official 3m/3m % change, beating all individual
sub-indices), it also acts as the best leading indicator of the
headline PMI[1] that we have so far found if the user is seeking an
insight into the PMI trend three or more months ahead.
Tracking other variables
Note that in this note we are only looking at signals for
production, with GDP nowcasting, price, employment, capacity and
other signals investigated in a growing library of other notes
which can be
found here.
1 Note that an even stronger correlation and signal is
achieved by using an average of the new orders and backlogs of work
indices in the above ratio as opposed to just the new orders index,
though the history of the backlogs of work index only extends back
to November 2002.
Chris Williamson, Chief Business Economist, IHS
Markit
Purchasing Managers' Index™ (PMI™) data are compiled by IHS Markit for more than 40 economies worldwide. The monthly data are derived from surveys of senior executives at private sector companies, and are available only via subscription. The PMI dataset features a headline number, which indicates the overall health of an economy, and sub-indices, which provide insights into other key economic drivers such as GDP, inflation, exports, capacity utilization, employment and inventories. The PMI data are used by financial and corporate professionals to better understand where economies and markets are headed, and to uncover opportunities.
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