Instituto Brasileiro de Geografia e Estatística

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Monthly Survey of Industrial Employment and Wages

Methodological Notes

In December of 2001, IBGE started to publish the indicators for the industrial workplace (their series started in December of 2000) resulting from the Monthly Survey of Industrial Employment and Wages (PIMES). That survey replaces the Monthly Industrial Survey – General Data, which was published for the last time in June of 2001.

The conception of PIMES is part of the Program for the Economic Statistics Update, started by IBGE in 1994. That program has the purpose of producing updated statistics by increasing their efficiency as to quality, time and cost.

The purpose of the indicators presented herein is to show the evolvement, in a short term, of some variables relative to the industrial labor market in national and regional perspectives. Thus, the results encompass 18 (eighteen) industrial sectors, and, regionally, the following States and Major Regions: Pernambuco; Ceará; Bahia; Espírito Santo; Minas Gerais; Rio de Janeiro; São Paulo; Paraná; Santa Catarina and Rio Grande do Sul; North and Central-West Regions; Northeast Region ; Southeast Region; and South Region.

The industrial activities in PIMES correspond to the descriptions of the National Classification of Economic Activities (CNAE) as in the chart below:

PIMES description CNAE categories
Mining and Quarrying Industry 10 – Mining of Coal
11 – Extraction of Petroleum and Service Activities incidental to oil extraction
13 – Mining of Metal Ores
14 – Other Mining and Quarrying
Food and Beverages 15 – Manufacture of Food Products and Beverages
Tobacco 16 – Manufacture of Tobacco Products
Textiles 17 – Manufacture of Textiles
Apparel 18 – Manufacture of Apparel and Accessories
Footwear and Leather 19 – Tanning and dressing of Leather and Manufacture of Leather Products, Luggage and Footwear
Wood 20 – Manufacture of Wood Products
Paper and Publishing and Printing 21 – Manufacture of Pulp, Paper and Paper Products
22 – Publishing, Printing and Reproduction of Recorded Media
Coke, Petroleum Refining, Nuclear Fuel and Alcohol 23 – Manufacture of Coke, Refined Petroleum Products, Nuclear Fuel and Alcohol
Chemical Products 24 – Manufacture of Chemical Product
Rubber and Plastic Products 25 – Manufacture of Plastic and Rubber Products
Non-metallic Mineral Products 26 – Manufacture of Non-metallic Mineral Products
PIMES description CNAE categories
Basic Metals 27 – Basic Metals
Fabricated Metal Products, except machinery and equipment 28 – Manufacture of Fabricated Metal Products, except machinery and equipment
Machinery and Equipment, except electrical, electronic, precision and communication equipment 29 – Manufacture of Machinery and Equipment
30 – Manufacture of Office Machinery and Computer Equipment
Electronic, Electrical, Precision and Communication Machinery and Apparatus 31 – Manufacture of Electrical Machinery and Apparatus
32 – Manufacture of Electronic Material and Communication Equipment and Apparatus
33 – Manufacture of Medical and Optical Instruments, Industrial Process Control Equipment, Watches and Clocks
Manufacture of Transportation Means 34 – Manufacture and Assembly of Motor Vehicles, Trailers and Bodies
35 – Manufacture of Other Transport Equipment
Other Manufacturing 36 – Manufacture of Furniture and Miscellaneous Manufacturing
37 – Recycling

The survey sample is generated by the Basic Selection Inventory (CBS) and referenced by the Central Register of Enterprises of IBGE (CEMPRE) — which systematically gathers information from the Annual Inventory of Social Information (RAIS), the General Registry of Employed and Unemployed Persons (CAGED) and the structural surveys from IBGE. It was obtained by means of the probability sampling technique, in which the selection unit is the Local Industrial Productive Unit.

The Local Units (LUs) are selected by means of the CBS, and the Inventory of Survey Respondents is generated. The LUs must correspond to the addresses where the industrial enterprises operate. Those enterprises, in turn, must predominantly generate industrial production, classified under the C and D sections of CNAE, and present at least 5 salaried employed persons. Then, a stratified sample is designed by using the simple random sampling technique, with no replacement. Following that reasoning, the total investigation universe is estimated.

PIMES investigates the following variables in about 5 500 (five thousand and five hundred) industrial plants: Salaried Employed Personnel, Hirings, Separations, Number of Hours Paid and Value of Payroll . The indicators for that last variable are presented in nominal (current values) and real (deflated by the Extended National Consumer Price Index - IPCA) terms. In order to see the definitions of the variables, click here .

The PIMES series started in December of 2000, and the published indicators were the following:

•  Monthly Fixed-Base Index : that index compares data from the reference month with data from the base month (January of 2001);

•  Month/Month Index (Seasonally Adjusted): that index is published only for salaried employed personnel, number of hours paid and real value of the payroll, in a national level, for overall industry, mining and quarrying industry and manufacturing industry. It compares the seasonally adjusted data from the reference month with the data from the immediately previous month;

•  Monthly Index : that index compares data from the reference month with the data from the same month a year ago;

•  Accumulated Index: that index compares the accumulated data in the year, from January to the reference month, with the data from the same period a year ago;

•  Accumulated Index 12 Months : that index compares the data accumulated in the last 12 reference months with the data from the 12 immediately previous months; and

•  Other Indexes : for example, the seasonally unadjusted Month/Month index can be obtained from the Monthly Fixed-Base Index or from SIDRA, the statistical database available on www.ibge.gov.br .

The seasonal adjustment – for salaried employed personnel, number of hours paid and real value of the payroll, in a national level, for overall industry, mining and quarrying industry and manufacturing industry – was obtained by means of the X-12 ARIMA method. Click here for more details on the adopted procedures.

The indexes herein presented are preliminary. They can be altered in case respondents change their historical data and in case those data impact the indexes published in the reference year (N year) and in the immediately previous year (N-1 year). The indexes become definite only from the N-2 year on.

Further information on methodological procedures can be obtained in the Coordination of Industry (COIND), at 500/4th floor República do Chile Ave., Zip Code 20031-170, Rio de Janeiro or by the telephones (21) 2142-0067 and 2142-4513. Specific inquiries can be sent to ibge@ibge.gov.br .


Table 1 – Salaried Employed Personnel

Statistics Overall Industry Manufacturing Industry Quarrying and Mining Industry
Sample cut-off (period) 2000.12 to 2007.12 2000.12 to 2007.12 2000.12 to 2007.12
Series Structure Multiplicative Multiplicative Multiplicative
Leap Year No No No
ARIMA Model (010)(011) (010)(011) (211)(011)
RegARIMA Associated with the Model Yes Yes Yes
Prediction 12 months ahead 12 months ahead 12 months ahead
FED8 77.96 77.95 4.77
FMD8 2.42 2.50 0.51
Diagnosis Identifiable Seasonality Present (ISP) Identifiable Seasonality Present (ISP) Identifiable Seasonality Present (ISP)
Seasonal Filter 3X5 3X5 3X5
Trend Filter MMH9 MMH9 MMH13
M1 to M11 M1 to M11 < 1 M1 to M11 < 1 M1, M4, M8, M10, M11 > 1
Q 0.21 0.23 0.93
Diagnosis for Seasonality
Diagnosis for TDs (Trading Days), Easter and Carnival		 Adjust for Seasonality Adjust for Seasonality Adjust for Seasonality
F 2.B: Relative contributions from each component of the original series to the variance of the monthly change (for the three first months)

Overall Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 4.31 10.17 85.52 0 0
2 1.51 1459 83.89 0 0
3 0.66 21.95 77.40 0 0
Manufacturing Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 4.15 67.15 28.70 0 0
2 1.43 75.34 23.23 0 0
3 0.64 81.84 17.52 0 0
Quarrying and Mining Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 40.45 12.13 47.42 0 0
2 31.30 28.92 39.78 0 0
3 18.00 38.96 43.04 0 0
(*) Adjustment Preliminary Coefficients (LS, AO, Calendar, etc.)


Table 2 – Number of Hours Paid

Statistics Overall Industry Manufacturing Industry Quarrying and Mining Industry
Sample cut-off (period) 2000.12 to 2007.12 2000.12 to 2007.12 2000.12 to 2007.12
Series Structure Multiplicative Multiplicative Additive
Leap Year No No No
ARIMA Model (211)(011) (211)(011) (211)(011)
RegARIMA Associated with the Model Yes Yes Yes
Prediction 12 months ahead 12 months ahead 12 months ahead
FED8 156.07 157.06 15.06
FMD8 0.97 0.89 1.97
Diagnosis Identifiable Seasonality Present (ISP) Identifiable Seasonality Present (ISP) Identifiable Seasonality Present (ISP)
Seasonal Filter 3X5 3X5 3X5
Trend Filter MMH13 MMH13 MMH13
M1 to M11 M1 to M11 < 1 M1 to M11 < 1 M10, M11 > 1
Q 0.25 0.25 0.64
Diagnosis for Seasonality
Diagnosis for TDs (Trading Days), Easter and Carnival 		Adjust for Seasonality
 Adjust for Seasonality
 Adjust for Seasonality
F 2.B: Relative contributions from each component of the original series to the variance of the monthly change (for the three first months)

Overall Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 4.18 1.52 94.30 0 0
2 2.55 3.06 94.39 0 0
3 1.15 5.00 93.86 0 0
Manufacturing Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 4.21 1.53 94.26 0 0
2 2.56 3.09 94.35 0 0
3 1.15 5.03 93.83 0 0
Quarrying and Mining Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 15.78 5.79 78.43 0 0
2 13.28 14.26 72.46 0 0
3 9.37 23.40 67.23 0 0
(*) Adjustment Preliminary Coefficients (LS, AO, Calendar, etc.)


Table 3 – Real Payroll

Statistics Overall Industry Manufacturing Industry Quarrying and Mining Industry
Sample cut-off (period) 2000.12 to 2007.12 2000.12 to 2007.12 2000.12 to 2007.12
Series Structure Multiplicative Multiplicative Multiplicative
Leap Year No No No
ARIMA Model (210) (011) (210) (011) (210) (011)
RegARIMA Associated with the Model Yes Yes Yes
Prediction 12 months ahead 12 months ahead 12 months ahead
FED8 547.96 607.95 26.11
FMD8 0.82 0.71 0.55
Diagnosis Identifiable Seasonality Present (ISP) ) Identifiable Seasonality Present (ISP) Identifiable Seasonality Present (ISP)
Seasonal Filter 3X9 3 X 5 3 X 5
Trend Filter MMH13 MMH13 MMH13
M1 to M11 M1 to M11 < 1 M1 to M11 < 1 M1 to M11 < 1
Q 0.18 0.19 0.47
Diagnosis for Seasonality
Diagnosis for TDs (Trading Days), Easter and Carnival		 Adjust for Seasonality Adjust for Carnival and Easter [1] Adjust for Seasonality
 Adjust for Seasonality
Adjust for Carnival
F 2.B: Relative contributions from each component of the original series to the variance of the monthly change (for the three first months)

Overall Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 2.08 0.56 97.14 0 0
2 1.14 1.17 97.57 0 0
3 0.81 2.04 97.07 0 0
Manufacturing Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 1.12 0.51 98.37 0 0
2 0.50 1.06 98.45 0 0
3 0.45 1.88 97.67 0 0
Quarrying and Mining Industry
Months Irregular Trend Seasonal A2(*) Calendar, Easter and Carnival
1 10.01 1.47 68.19 20.33 0
2 5.67 3.46 81.97 8.90 0
3 2.69 4.43 84.23 8.65 0
(*) Adjustment Preliminary Coefficients (LS, AO, Calendar, etc.)
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