Purchasing Managers Index

National Bureau of Statistics of China 2023-06-13 15:34 Print| Large| Medium| Small

1. Explanatory Notes


Purchasing Managers Index PMI is an index summarized and compiled through the results of the monthly survey of enterprises purchasing managers. It covers every links of the enterprises including purchasing production logistics and so on. It is one of the leading indexes which was commonly adopted by international society to monitor the macroeconomic trends and played an important role in forecasting and monitoring. The Composite PMI Output Index belonging to the PMI indicator system is a composite index reflecting the changes in the output in current period of the entire industry manufacturing and non-manufacturing industries. If PMI above 50 percent it reflects the overall economy is expanding if less than 50 percent it reflects the overall economy is in recession.


2. Statistical Coverage


The survey involves 31 divisions of manufacturing industry in the “Industrial Classification for National Economic Activities” GB/T4754-2017), and 3200 samples as well as 43 divisions of non-manufacturing industry and 4300 samples.


3. Survey Methods


PPS Probability Proportional to Size sampling method was adopted in purchasing managers’ survey. Using the divisions of the manufacturing or non-manufacturing industry as the selecting strata the sample size of each division is proportional to its proportion of the value-added of the division to the total value-added of the manufacturing or non-manufacturing industry. Within the stratum the samples are selected according to the probabilities proportional to their principal business revenues of the enterprises.


The survey was organized and conducted by staff members of survey offices monthly through Online Reporting System of NBS by sending survey questionnaires to the purchasing managers of the selected enterprises.


4. Calculation Methods


1 Calculation Methods of Sub-indexes. The indicator system of manufacturing purchasing managers’ survey covers 13 sub-indexes such as production new orders new export orders existing orders finished goods inventory purchase import purchase price producer price raw materials inventory employment supplier’s delivery time production and business activities expectation. The indicator system of non-manufacturing purchasing managers’ survey covers 10 sub-indexes such as business activities new orders new export orders existing orders inventory input price sales price employment supplier’s delivery time and business activities expectation. Sub-indexes adopt diffusion index calculation method i.e. percentage of positive answers in number of enterprises plus half of the percentage in the same answers. Due to the lack of synthesis of non-manufacturing integrated PMI index the international society often used business activity index to reflect the overall changes in non-manufacturing economic development.


2 Calculation Methods of Manufacturing PMI. Manufacturing PMI was calculated according to five diffusion indexes group indexes and their weights. 5 group indexes and their weights are determined in accordance with their leading impact on the economy. Specifically new orders index weighted 30 percent production index weighted 25 percent employment index weighted 20 percent supplier delivery time index weighted 15 percent raw materials inventory index weighted 10 percent. Of which the supplier delivery time index is a converse index and contrary calculation is needed when combines it into PMI.


3 Calculation Methods of Composite PMI Output Index. Composite PMI Output Index was calculated by weighted summation of the manufacturing output index and non-manufacturing business activity index. Their weights are determined by the proportion manufacturing and non-manufacturing industries in GDP.


5. Seasonal adjustment


The purchasing managers’ survey is a monthly survey the data of the survey fluctuates very much for the influences of seasonal factors. The released PMI composite index and sub-indexes are seasonally adjusted data.