Read what the experts are saying about Purchasing Managers' Index (PMI™) by S&P Global. These articles illustrate how PMI and other business survey data can be used to better understand economic trends, the business environment and the financial markets. The papers highlight the value of early data in planning and forecasting, and why it's critical to understanding the health of economies and sectors.

PMI and supply chains

Supply Chain Disruptions, Inflation, and the Fed

Federal Reserve Bank of Richmond | By John Mullin

Today's inflationary snarls reflect both supply shocks and policy stimulus. There is no precedent in recent history for the supply chain disruptions that currently afflict the global economy. The scope of the problem is seen, among other places, in the recent behavior of the JPMorgan Global Purchasing Managers Indices (PMI) delivery time index, which provides a measure of delivery delays around the globe. Ordinarily, the delivery index tends to closely track the JPMorgan PMI new orders index.

PMI and GDP nowcasting

Nowcasting world GDP and trade using global indicators

Bank of England | By Kate Stratford

Official estimates of world GDP and trade are only available with a lag, but more timely global indicators can give an early steer on growth. A combination of these indicators has performed much better at tracking world GDP and trade growth since 2008 than a simple benchmark model. The global manufacturing PMI export orders index has been the single best indicator during this period.

The Importance of Being Timely

Journal of Forecasting | By Paul Smith

Policymakers want to know about real‐time economy performance. However, closely watched macroeconomic time series produced by national statistics offices are published infrequently, with a time lag and subject to revision. Such issues create uncertainty in tracking economic developments, a by‐product of which is to raise the value of business and consumer surveys. Although providing less granularity than official data series, the surveys are released in a timelier manner and are subject to little revision. Using real‐time data sourced from the Deutsche Bundesbank, the OECD and the Office for National Statistics, an assessment of the role that the popular and widely used Purchasing Managers' Index (PMI) play in reducing forecasting errors in a simple 'nowcasting' framework is undertaken. The empirical exercise is conducted for five developed economies and also covers the period of the Great Recession. The conclusion is clear: timing matters.

Nowcasting the Global Economy

Bank of Canada | By James Rossiter

Forecasts of global economic activity and inflation are important inputs when conducting monetary policy in small open economies such as Canada. As part of the Bank of Canada's broad agenda to augment its short-term forecasting tools, the author constructs simple mixed-frequency forecasting equations for quarterly global output, imports, and inflation using the monthly global Purchasing Managers Index (PMI). When compared against two benchmark models, the results show that the PMIs are useful for forecasting developments in the global economy. As the forecasts are updated throughout the quarter with the monthly release of the PMI, forecasting performance generally improves. An analysis of the forecasts over the period of the Great Recession (in particular, 2008Q4 to 2009Q2) shows that, while models that include the "soft" PMI indicators did not fully capture the sharp deterioration in the global economy, they nevertheless improved the forecasts relative to the benchmark models. This finding highlights the usefulness of such indicators for short-term forecasting.

A PMI-based real GDP tracker for the euro area

ECB /Journal of Business Cycle Research | By Gabe de Bondt

Real-time evidence for the euro area shows that a tracker for real GDP growth using only the Purchasing Managers' Index (PMI) composite output is of similar accuracy for the final GDP release as the first GDP release. No signs of instability—except during the 2008/09 crisis—in this tracking performance are found. This is surprising given the small size of the underlying PMI panel. From a closer look at what is driving this outstanding track record, seven conclusions emerge: (i) the level of and change in the PMI composite output explain one-third of the GDP revisions; (ii) later available information is more accurate; (iii) services are key; (iv) firm size breakdown is valuable; (v) export status breakdown creates only noise; (vi) aggregated euro area PMI track record is not consistently related to a particular country; (vii) take firm defaults into account during very bad times. These findings imply that PMI surveys are not only valuable for analysts and policymakers as a timely and reliable GDP tracker, but also for statisticians to potentially improve the accuracy of the first preliminary flash estimate of euro area real GDP.

Nowcasting Europe

S&P Global | By Paul Smith

In this research paper we build on our previous nowcasting work with Purchasing Managers' Index® (PMI®) data by introducing two dynamic factor models that can be used to provide judgement-free estimates of underlying changes in gross domestic product (GDP) for the eurozone and the United Kingdom.

A Multi-Country Approach to Forecasting Output Growth Using PMIs*

Federal Reserve Bank of Dallas | by Chudik, A, V Grossman and M Pesaran

We investigate the value of the information content of Purchasing Managers Indices (PMIs) for forecasting global (48 countries) growth and compare forecasts from AugGVAR models with a number of data-rich forecasting methods, including Lasso, Ridge, partial least squares, and factor-based methods. It is found that (a) regardless of the forecasting methods considered, PMIs are useful for nowcasting, but their value-added diminishes quite rapidly with the forecast horizon, and (b) AugGVAR forecasts do as well as other data-rich forecasting techniques for short horizons and tend to do better for longer forecast horizons.

A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP

ECB | By Bańbura, M and G Rünstler

We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information beyond the monthly real activity measures for the GDP forecasts. However, this is discovered only, if their more timely publication is properly taken into account. Differences in publication lags play a very important role and should be considered in forecast evaluation.

The PMI: A Predictive Power for Economic Growth?

Blominvest Bank | By Marwan Mikhael

The substantial delay in publishing national accounts (namely the Gross Domestic Product, GDP) and thus economic growth (g) in developed and developing countries cripples financiers' and statesmen's ability to take critical, timely monetary policy, fiscal policy, and investment -decisions. This market gap is partially corrected with delayed GDP data, knowing that GDP has been the primary macroeconomic measure to assess the health of an economy. However, a modern yardstick, known as the Purchasing Managers' Index (PMI), also emerged as a leading indicator to forecast economic (GDP) growth. Such a finding may improve quantitative assessments of any economy's health and facilitate the international comparison of related data. Yet, historically, academic scholars have recorded controversial input on how much the GDP measure is representative and accurate in capturing the health of an economy.

Nowcasting Quarterly GDP Dynamics In The Euro Area - The Role Of Sentiment Indicators

University of Łódź | by Pawel Gajewski

The paper compares the most closely watched sentiment indicators with respect to their ability to nowcast quarterly GDP dynamics in the Euro Area and its biggest economies. We analyze cross-correlations and out-of-sample forecast errors generated from equations estimated by rolling regressions in a fixed-length window. The results show that models employing PMI Composite perform best in the cases of the Euro Area, Germany, France, and Italy, whilst Spanish GDP dynamics are best nowcasted using ESI-based models. PMI-based models generate the most accurate nowcasts at the beginning of the quarter, as well as during periods of high volatility of GDP growth rates.

Nowcasting real economic activity in the euro area: Assessing the impact of qualitative surveys

National Bank of Belgium | By Raïsa Basselier, David de Antonio Liedo and Geert Langenus

This paper analyses the contribution of survey data, in particular various sentiment indicators, to nowcasts of quarterly euro area GDP. It uses a genuine real-time dataset that is constructed from original press releases in order to transform the actual data flow into an interpretable flow of news. The latter is defined as the difference between the released values and the prediction of a mixed frequency dynamic factor model.

Nowcasting European GDP during an economic shock

S&P Global | By Joe Hayes and Paul Smith

Since last July, we have been utilising a technique called 'dynamic factor' modelling to provide high-frequency estimates of current quarter GDP, leaning heavily on the signals provided by our PMI data.

However, in the face of recent events, we've found these models have been a little slow to react to sudden changes in economic conditions, particularly in the face of unforeseen shocks. We noted that, in these instances, reverting to more simplistic model specifications is likely to yield more reliable indications of current economic activity.

Nowcasting South Africa: Utilising PMI and official data to provide early estimates of GDP

S&P Global | By David Owen and Paul Smith

In this research paper, we build on our previous nowcasting work with Purchasing Managers' Index (PMI) data by introducing a new model to provide early estimates of gross domestic product in South Africa. The nowcast model draws on both PMI and non-PMI data sources, taking advantage of the timely release of PMI survey data to provide GDP nowcasts well in advance of official numbers.

PMI and GDP revisions

How the US-Eurozone growth differential gets revised away

Unicredit | By Daniel Vernazza

We find that US GDP growth tends to be revised down and Euro area growth revised up from the initial estimates. The effect is significant: since 1999, the annual average growth differential between the US and Euro area is subsequently halved between the first estimate and the near-final estimate. After further adjusting for population growth, the growth differential between the US and Euro area almost disappears. We also find that both in the Euro area and the US, GDP revisions are pro-cyclical - that is, they are revised up in good times and down in bad times. Moreover, the initial estimates tend to lag the "true" business cycle revealed in mature estimates, meaning the initial estimates are slow to identify turning points. Finally, business surveys such as the PMIs have predictive power for GDP revisions, meaning they are a better guide to the mature - rather than the initial - estimates of growth.

Extracting a better signal from uncertain data

Bank of England | By Alastair Cunningham and Christopher Jeffery

Most macroeconomic data are uncertain — they are estimates rather than perfect measures. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in light of new information or methodological advances. While revisions should move estimates closer to the 'truth', the potential for early estimates to be revised poses challenges for forecasting and economic analysis. Over the past few years, Bank staff have undertaken a range of research into how best to deal with the ensuing uncertainty. The results of that research have been used for some time as part of the toolkit available to staff when briefing the Monetary Policy Committee. This article describes some further developments in that research effort aimed at refining the staff's toolkit.

PMI and financial conditions

Financial conditions and purchasing managers' indices: exploring the links

BIS | By Burcu Erik, et al.

Purchasing managers' indices (PMIs) have found a place in global conjunctural analysis and quarterly GDP nowcasting, serving as reliable concurrent indicators of real economic activity. They also closely mirror changes in equity prices and corporate bond spreads. More surprisingly, PMIs react to changes in the dollar index and do so in a way that runs counter to a trade competitiveness explanation. We show that the financial variables help predict PMIs and explain a significant proportion of their variation. The two seem to be linked through shifts in macroeconomic sentiment and global financing conditions.

Estimating short-term FX equilibria using PMIs

S&P Global | By Joe Hayes

New research aims to demonstrate how timely PMI survey data can enhance short-term equilibrium exchange rate estimation by quantifying changes in macroeconomic trends between countries as they happen, and then feeding these into short-term equilibrium exchange rate estimations. We find that PMI data play a statistically significant role in capturing changes in the economic fundamentals that can affect short-term exchange rate valuations. Our short-term equilibrium exchange rate model provides estimates of a currency pair's "fair value", based on the short-term changes in economic and financial market fundamentals in one country, relative to another.

PMI data and investment strategy

PMI™ as a tool for equity portfolio adjustments

S&P Global | By Paul Smith

This paper provides another fruitful avenue for the applicability of PMI data. We conduct a simulation exercise whereby we split investment capital of $10,000 into two separate Exchange Traded Funds (ETFs) which respectively provide direct exposure to equities in both developed and emerging markets. We then use monthly changes in aggregated PMI numbers as a guide to adjust and facilitate changes in exposure to these developed and emerging markets ETFs over a period stretching back over a decade.

New case studies in active PMI™ investment strategies in Japan and the US

S&P Global | By Paul Smith

We present ideas on how to derive signals from national sector PMI data and use these in active equity investment strategies for both Japan and the US. Results are positive, with signals from the PMI data generating excess returns compared to a naïve benchmark strategy in a coherent and consistent fashion.

PMI™ as a tool for sector rotation investment strategies

S&P Global | By Joe Hayes

In this paper, we introduce a new method to demonstrate how an active rules-based approach, based on "investment factors", can generate excess returns for equity market investors across different time horizons.

For this exercise, we use S&P Global Sector PMI data, which provides insight into business conditions in over 30 sectors with granularity down to three distinct tiers. Using 16 sectors and mapping them to the appropriate index within the MSCI universe, we establish a sector rotation model which uses signals identified from the Global Sector PMI to direct a hypothetical long-only portfolio. We find that, over both a five- and ten-year investment horizon, our approach generated sizeable excess returns over the benchmark MSCI World Index.

Using SP Global PMI survey data as an indicator corporate earnings

S&P Global | By Chris Williamson

PMI survey data produced around the world by S&P Global have an unrivalled reputation for providing advance insights into changing economic conditions, being widely used to anticipate changes in official macroeconomic data such as GDP, industrial production, inflation and employment. However, the surveys can also provide valuable, unique guidance on corporate earnings trends, as illustrated by the following case study from the United States.

PMI versus other business surveys

IHS Markit versus ISM Manufacturing PMI

Macroeconomic Advisors by IHS Markit | By Ben Herzon, Joel Prakken

Both IHS Markit and the Institute for Supply Management (ISM) compute composite indexes covering the US manufacturing sector. Both are weighted up from component diffusion indexes measuring five economic concepts: manufacturing output, new orders, employment, supplier delivery times, and inventories. Both sets of diffusion indexes are survey-based measures in which respondents are queried about the current month's activity relative to one month prior.

Until recently, the two manufacturing composite indexes tracked each other quite closely. But beginning in early 2017, the ISM index moved sharply and persistently above the IHS Markit index. This has presented a conundrum for analysts who rely on these indexes as indicators of the health of the manufacturing sector: which one is providing a better signal?

In this note, we investigate whether either index has recently become "disconnected" from the underlying economic concepts. We present evidence supporting the view that the ISM PMI has, and the IHS Markit PMI has not, suggesting the latter is providing a better signal.

Surveys and economic modeling

The University of Pennsylvania Models for High-Frequency Macroeconomic Modeling

University of Pennsylvania | By Lawrence R. Klein, Suleyman Ozmucur

Forecasting economic activity requires the use of all available information. However, data are collected at different frequencies. For example, stock prices are available instantaneously (real-time), but industrial production data are available monthly, at best. This necessitates building models which utilize data at different frequencies.

Purchasing Managers' Index™ (PMI^®) data are compiled by S&P Global 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.

Learn more about PMI data

Request a demo

This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.