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PMI sub-indices have been shown to provide a considerable amount
of value beyond the market-sensitive headline PMI figure, which is
designed to be a barometer of manufacturing business conditions and
a gauge of overall economic health. In practice, PMI sub-indices
also hold the potential to assist in forecasting the highly-watched
headline manufacturing PMI figures, providing even earlier signals
and indications of economic conditions than the headline PMI
itself.
The headline PMI and its sub-indices
The headline manufacturing PMI aggregates five survey indicators
(sub-indices) into a single-figure diffusion index to provide an
overall barometer of manufacturing business conditions.
Furthermore, given the timeliness attribute of capturing changes
taking place in the manufacturing sector, PMI sub-indices can also
be useful in helping to forecast the upcoming month's headline
PMI.
Forecasting the headline PMI
Forecasting as a technique is one that uses historical data to
make predictions on future conditions. While a vast number of
economic indicators relevant to manufacturing sector conditions for
the forecasting of the headline manufacturing PMI may exist, they
vary in availability, timeliness and relevance. PMI sub-indices
therefore present themselves as ideal candidates in forecasting the
headline PMI, detailing the specific manufacturing sector
conditions, as they are available on the first working day of each
month and can be easily integrated into one's modelling setup.
For the purpose of predicting the upcoming months' headline
manufacturing PMI, we will demonstrate a simple model utilising a
linear regression and using the PMI sub-indices of the country in
study and a trade weighted headline index of major trading
partners.
This model assumes the following generic equation:
where, S={1,…,n} refers to the country's PMI sub-indices and X
refers to the weighted headline PMI of key trading partners.
The time-lag for the independent variables may also be adjusted
in accordance to the forecast period one is interested in.
Forecasting Eurozone Manufacturing PMI
To sieve through the array of manufacturing PMI sub-indices
available for ones that are found to be of the highest statistical
significance, we first ran a regression of all the sub-indices
against the headline PMI with a one-month lead. Using the last 10
years of Eurozone Manufacturing PMI data, four sub-indices were
found to be statistically significant - Future Output, Input Prices
Index, Output Index and Suppliers' Delivery Times. The model was
further enhanced with another independent variable made up of
headline PMI performance, equally weighted across the eurozone's
top three trading partners - namely US, UK and China - to capture
changing external conditions.
Results showed an R-squared value of at least 91% for this model
with data assessed between 2012 and January 2022, which is a strong
model for predicting the closely followed month ahead headline
manufacturing PMI.
Eurozone Manufacturing PMI and model forecast with
1-month lead
Forecasting Japan Manufacturing PMI
Repeating the same methodology for the forecasting of Japan
Manufacturing PMI, the sub-indices found to be statistically
significant for a one-month lead is noted to be different from that
of the eurozone. Future Output, New Orders and Stocks of Finished
Goods indices presented themselves in the case of Japan.
Additionally, the external trade component had also been added,
making a total of four independent variables for this model.
While the R-squared value had declined slightly in comparison to
the eurozone case, down to 87% for the model with one-month lead,
it remains a strong reading.
Japan Manufacturing PMI and model forecast with 1-month
lead
Why forecast the headline PMI?
The ability to accurately anticipate a market-moving economic
statistic clearly has obvious value for those engaged in short-term
trading strategies around economic statistics and highlights the
value of looking "below the hood" of the headline PMI statistics
for clues on the future trajectory of sector or country
performance. Further aspects of the broader usefulness of the
headline PMI in work across economics, financial markets and supply
chain management is more fully documented in our
PMI use-case library.
One of our
latest research notes on estimating the short-term FX
equilibria using the headline manufacturing PMI - also
utilising the Eurozone Manufacturing PMI looking at EUR/USD -
extends the purpose of forecasting the headline PMI in giving an
early indication of what could be the short-term fair value for
various currency pairs.
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.
