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Close relationships between PMI and GDP data can be exploited
to provide advance estimated growth rates
PMI 50.0 no-change does not always translate to neutral GDP
outcome
Evidence suggests 50.0 no-change marks and GDP growth rates are
inversely linked to country's level of economic development
IHS Markit's PMI survey diffusion indices are designed to
capture business cycle developments. They do this by replicating
the industrial make-up of an economy and subsequently tend to
achieve high correlations with other yardsticks of economic
activity, most notably gross domestic product (GDP) figures.
Moreover, given the timeliness of PMI data, which are usually
released well ahead of equivalent GDP statistics, there is a
natural tendency to map the two series together and generate
real-time estimates of current GDP growth (often referred to as
'nowcasting' as discussed here).
As PMIs are diffusion indices, and are bounded between 0 and
100, with 50.0 representing a no-change or neutral point, then the
link between PMI and GDP growth will usually be estimated via
linear regression.
Intuitively, PMI readings of 50.0 over a calendar quarter should
approximately equate to a similar result for GDP (i.e. economic
stagnation). However, this is not always the case: indeed, we - and
many PMI users - have observed a variance between countries as to
what PMI = 50.0 (and other readings) usually equate to in terms of
GDP growth.
This note aims to provide more clarity around what the 50.0
no-change mark means in terms of GDP growth from the perspective of
a nation's level of economic development.
Broadly speaking, our research finds that, while an average
figure of 50.0 often implies broadly flat GDP in so-called
developed economies (particularly in Western Europe), this is not
the case for faster growing emerging markets where PMI readings
close to 50.0 are often associated with strongly positive GDP
growth outturns.
Indeed, we find there exists an inverse relationship between the
level of development and implied PMI GDP growth rates at the 50.0
no-change level.
Background
Across our global PMI dataset, readings of 50.0 imply different
GDP growth rates in different nations. Typically, a PMI reading of
50.0 in more developed economies maps to a GDP growth rate of
around 0%, whereas the same reading in emerging markets often
points to positive GDP growth.
For example, in the Eurozone a PMI Output Index reading of 50.0
visually approximates to 0% year-on-year GDP growth, whereas an
Output Index reading of 50.0 in China maps to year-on-year GDP
growth of around 7% (see charts below).
This paper looks at these relationships more closely on a
country-by-country basis, with the aim to more formally establish a
broad relationship between the PMI's implied GDP growth and a
barometer of a country's level of economic development.
Country Analysis
The PMI surveys ask respondents to provide answers to several
questions covering areas such as output, new orders, employment,
inventories and prices. From the list of PMI indices available, we
feel that two are intuitively the most suitable for tracking
changes in GDP, namely the headline PMI* and the Output Index.
Subsequently, for each country where whole economy or composite
(covering manufacturing and services) PMI data are available, we
ran separate OLS regressions, with quarterly averages of the
headline PMI or Output Index as an explanatory variable against
year-on-year GDP growth as a dependent variable.
With the relationships between PMI data and GDP established, the
independent variable was set to 50.0 and the implied GDP growth
rate was subsequently estimated. The results of this exercise are
shown in the chart below.
As anticipated a reading of 50.0 generally points to zero or
minimal GDP growth in most European countries, while in African and
developing Asian economies, 50.0 often signals a noticeable level
of positive GDP growth.
Economic Development
Using the implied country growth rates developed in the previous
section, we have formalised the relationship between the PMI 50.0
no-change mark and a country's "neutral" GDP growth rate.
The relationship was developed in the context of a country's
level of economic development, which we measured via two variables:
United Nations Human Development Index (HDI) and government
spending as a percentage of GDP (as estimated by the World
Bank).
Subsequently, we ran an OLS regression with the implied "50.0 =
no-change" annual GDP growth rates as the dependent variable
against two explanatory variables: HDI and government spending.
The results of the regression, charted below, show that the two
independent variables were both significant at the 1% level, whilst
explanatory power was also strong, with the regression yielding a
R-squared statistic of 0.71.
Moreover, both explanatory variables had an inverse relationship
with the PMI implied growth rates i.e. that is, as HDI and
government spending increase, the implied growth rate of 50.0
no-change readings falls towards zero.
Summary
The observed relationship between economic development and
implied GDP growth rates when a country's PMI is at a level of 50.0
helps us understand the performance of a country's economy in two
ways.
Firstly, the country-by-country relationships between PMI data
and GDP may be used to provide robust implications for GDP growth
when PMI figures are released each month.
Secondly, with our "rule-of-thumb" relationship between HDI,
government spending and the implied GDP growth value when PMI data
are around the 50.0 no-change mark, we can estimate an expected GDP
growth rate for surveys where insufficient data exists (such as
newly established PMI surveys with short histories and/or or
nations with incomplete or low-frequency GDP figures).
For example, our work has already proven useful in estimating
implied GDP growth rates in some Middle Eastern countries, where
non-oil GDP data are available only annually and PMI history is
short (see appendix below).
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.
