Purchasing Managers Index Data |WORK| Download
Pamela Olivares
ISM, SIPMM, and S&P separately compile purchasing managers' index (PMI) surveys on a monthly basis by polling businesses which represent the makeup of the respective business sector. ISM's surveys cover all NAICS categories. SIPMM survey covers all manufacturing sectors.[9][10][11] The S&P survey covers private sector companies, but not the public sector.
ISM, SIPMM, and Markit purchasing managers indices include additional sub indices for manufacturing surveys such as new orders, employment, exports, stocks of raw materials and finished goods, prices of inputs and finished goods.[17]
The data for the index are collected through a survey of 400 purchasing managers in the manufacturing sector on five different fields, namely, new orders from customers, speed of supplier deliveries, inventories, order backlogs and employment level. Respondents can report either better, same or worse business conditions than previous months.[20] For all these fields the percentage of respondents that reported better conditions than the previous months is calculated. The five percentages are multiplied by a weighting factor (the factors adding to 1) and are added.[17]
Purchasing managers form a near ideal survey sample base, having access to information often denied to many other managers. Due to the nature of their job function, it is important that purchasing managers are among the first to know when trading conditions, and therefore company performance, change for the better or worse. Markit therefore uses such executives to produce data on business conditions.[17]
In each country, a panel of purchasing managers is carefully selected by Markit, designed to accurately represent the true structure of the chosen sector of the economy as determined by official data. Generally, value added data are used at two-digit SIC level, with a further breakdown by company size analysis where possible. The survey panels therefore replicate the actual economy in miniature. A weighting system is also incorporated into the survey database that weights each response by company size and the relative importance of the sector in which that company operates.[17]
Similar purchasing managers indices are published by the Ifo Institute for Economic Research in Germany, the Bank of Japan in Japan (Tankan), the Caixin China PMI published by Markit and the Swedish PMI run by private bank Swedbank.[21]
The PRIX index uses a diffusion index methodology based on that of PMIs. However, rather than drawing on purchasing managers, it uses country analysts based in the world's 20 largest oil exporting countries to forecast political events that may affect global oil exports. The PRIX index is updated quarterly and published for free on the internet.[31]
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.1
Purchasing managers' indices (PMIs) are monthly economic surveys of companies in which senior managers overseeing operations answer questions on business activity and its recent trends. The questions cover output, employment, new orders, prices, costs and other aspects of business activity. Due to their timeliness and breadth of coverage, PMIs are among the business surveys most closely watched by analysts and commentators. PMIs also add power to forecasting models and are being used to derive real-time estimates ("nowcasts") of GDP.2 In early 2018, PMIs came under the spotlight as they started to foreshadow weaker export orders and industrial output growth well before a slowdown in global economic activity became more visible in hard data during the first half of 2019.
As business activity indicators, PMIs have several advantages over traditional statistical data such as industrial production, retail sales, or exports and imports. One is their timeliness: PMI readings are released immediately after the end of the reference month.5 By comparison, industrial production data are published in many cases five to seven weeks after the end of a reference month, which can be problematic for assessments of conjunctural developments and decision-making in real time. Another advantage is the breadth of PMIs' coverage. By surveying managers who order intermediate products, decide on inventory levels or set prices, PMIs should accurately capture the vagaries of business conditions. This is especially the case when the surveyed firms are engaged in international trade and are thus exposed to shifts in global conditions. Moreover, by putting the same (or a very similar) set of questions to companies around the world, PMI surveys provide a data set that is comparable across countries and sectors. Such standardisation and comparability are not always guaranteed between national statistical surveys.
PMIs show the direction of change in business conditions, but say little about the drivers of that change. One possible source of such information is comments that purchasing managers give to explain or add nuance to their responses. However, these comments are anecdotal and cannot be easily structured for empirical research.
More informative are the correlations between the PMIs and other high-frequency data, notably financial variables. One reason is that these variables tend to reflect the financing conditions faced by the respondent firms; this information is, in turn, likely to affect purchasing managers' responses to questions about economic activity, both present and future. Likewise, financial variables tend to reflect current economic activity and, as forward-looking variables, the economic outlook too. Business sentiment plays a key role in both respects.
Before we suggest possible reasons for the empirical association between the dollar and PMIs, we examine more systematically how correlations between financial variables and PMIs show up in basic in-sample forecasting exercises. In particular, we ask how well current month (eg August) PMIs can be nowcast by relying on financial market information available up to the point the survey is conducted (ie until mid-August). In other words, we assume that business conditions reported at mid-month relative to the previous mid-month partly reflect the influence of financial variables on purchasing managers' decisions over that period (Graph 3).7
Taken together, these findings suggest that the links between the financial and real variables operate through both shifts in broad macroeconomic sentiment and global financing conditions. The higher explanatory power and the forward-looking nature of equity prices point to the former. Yet the significance of the dollar index and corporate bond spreads might also point more directly to a channel operating through shifts in global financing conditions. As noted above, purchasing managers are likely to internalise these shifts when making input and output decisions at the firm level, which then aggregate into GDP outcomes.15
The Purchasing Manager's Index (PMI) Survey targets purchasing managers in the West Michigan area. Data is collected from business representatives from the region's major industrial manufacturers, distributors, and industrial service organizations. Analysts and economists use the PMI to evaluate economic trends in sales, employment, and inflation.
The manufacturing purchasing managers' index (PMI), which measures the activity of managers in the manufacturing sector, added 1 point to 48.9, up from 47.9 last month, according to flash estimates by the financial services company.
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