287415
/en/energi-og-industri/statistikker/kbar/kvartal
287415
statistikk
2017-10-20T08:00:00.000Z
Energy and manufacturing;National accounts and business cycles
en
kbar, Business tendency survey for manufacturing, mining and quarrying, actual and expected development, production, employment, new orders, market prices, resource shortage, bottlenecks, capacity utilisation, industrial confidence indicatorBusiness cycles , Manufacturing, mining and quarrying , National accounts and business cycles, Energy and manufacturing
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Business tendency survey for manufacturing, mining and quarrying

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Key figures

2.3

Industrial confidence indicator for 3rd quarter 2017

Manufacturing. Selected indicators
2nd quarter 20173rd quarter 2017
1Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance.
2A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same). The diffusion index has a turning point at 50. An index value above 50 indicates growth in the variable, and opposite for a value below 50. The diffusion index is presented as smoothed seasonally adjusted figures.
Confidence Indicator. Seasonally adjusted.13.72.3
 
Changes from previous quarter2
Total volume of production49.650.7
Average employment47.549.5
New orders received from home markets50.351.0
New orders received from export markets49.850.5
 
Expected changes in next quarter. Diffusion indices2
Total volume of production54.354.9
Average employment47.247.6
New orders received from home markets54.954.6
New orders received from export markets53.453.6

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Table 1 
Manufacturing, Mining and Quarrying. Tendencies. Diffusion index. Smoothed seasonally adjusted

Manufacturing, Mining and Quarrying. Tendencies. Diffusion index. Smoothed seasonally adjusted12
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2The diffusion index has a turning point at 50. A common way of interpreting an index value of 50 is to say that half the respondents has had an increase while the other a fall. An increasing index at or above 50 indicates that the growthrate is increasing, while a falling index above 50 indicates a falling rate of growth. Opposite for an index below 50.
Changes from previous quarter
Total volume of production47.247.348.649.750.8
Average capacity utilisation47.047.048.750.151.1
Average employment42.142.945.247.749.5
New orders received from home markets47.449.150.450.250.9
New orders received from export markets43.745.647.949.750.5
Total stock of orders44.145.848.449.449.4
Prices on products at home markets50.049.950.751.852.5
Prices on products at export markets48.148.150.151.651.4
 
Expected changes in next quarter
Total volume of production51.152.153.454.555.0
Average capacity utilisation51.852.052.553.854.6
Average employment43.144.546.247.447.5
New orders received from home markets51.952.953.954.855.0
New orders received from export markets49.551.752.853.553.7
Total stock of orders49.351.252.954.154.2
Prices on products at home markets51.251.952.954.155.7
Prices on products at export markets47.648.950.852.252.8

Table 2 
Manufacturing, Mining and Quarrying. Judgements and composite indicators. Smoothed seasonally adjusted

Manufacturing, Mining and Quarrying. Judgements and composite indicators. Smoothed seasonally adjusted
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent. See also table 10.
3Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance. See also table 9.
Diffusion indices1
Stocks of orders compared to current level of production30.430.731.933.434.6
Stocks of orders for export36.536.538.139.639.9
Inventories of own products ment for sale49.548.949.049.849.4
Does the enterprise consider changes in the plans for gross capital investments49.350.151.552.953.5
General judgement of the outlook for the enterprise in next quarter52.753.854.655.255.3
 
Composite indicators
The utilisation of capacity at current level of production in per cent77.277.177.277.777.9
Number of working months covered by stock of orders, weighted average3.94.04.04.14.2
Indicator on resource shortage217.517.718.519.519.9
Confidence Indicator3-40243

Table 3 
Manufacturing, Mining and Quarrying. Limiting factors for production. Smoothed seasonally adjusted. Per cent.

Manufacturing, Mining and Quarrying. Limiting factors for production. Smoothed seasonally adjusted. Per cent.1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1The results are percentages estimated for important limiting factors for production in current quarter or expected limiting factors for next quarter.
Limiting factors in current quarter
Demand and competition (total)7171706866
Demand from home markets3030313131
Demand from export markets1818171616
Competition at the home market1213131212
Competition in the EU market66555
Competition when exporting to other countries44333
Capasity of the unit65666
Supply of labour22333
The supply of raw materials and/or electric power33344
Other factors32233
No special factors1515151616
 
Limiting factors expected for next quarter
Demand and competition (total)7170696868
Demand from home markets3131303030
Demand from export markets1818171717
Competition at the home market1212121213
Competition in the EU market66655
Competition when exporting to other countries44433
Capasity of the unit44555
Supply of labour23333
The supply of raw materials and/or electric power33333
Other factors22233
No special factors1717171717

Table 4 
Manufacturing. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted

Manufacturing. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2Composite indicators are not precented as diffusionindices, but in per cent, number of months and balance
3Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent. See also table 10.
4Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance. See also table 9.
Changes from previous quarter
Total volume of production47.147.248.449.650.7
Average capacity utilisation46.946.848.449.750.9
Average employment42.142.845.047.549.5
New orders received from home markets47.349.150.450.351.0
New orders received from export markets43.745.548.049.850.5
Total stock of orders43.745.548.349.349.6
Prices on products at home markets49.849.850.651.652.4
Prices on products at export markets47.847.849.851.451.2
 
Judgements of the current situation by end of quarter
Stocks of orders compared to current level of production30.030.331.533.134.3
Inventories of own products ment for sale49.648.849.049.949.6
Does the enterprise consider changes in the plans for gross capital investments49.350.151.552.853.5
General judgement of the outlook for the enterprise in next quarter52.653.754.455.155.4
 
Expected changes in next quarter
Total volume of production50.952.053.354.354.9
Average capacity utilisation51.651.952.553.754.5
Average employment43.044.446.047.247.6
New orders received from home markets51.852.953.954.954.6
New orders received from export markets49.051.052.553.453.6
Total stock of orders49.351.052.753.954.1
Prices on products at home markets51.151.852.854.155.6
Prices on products at export markets47.148.350.351.952.5
 
Composite indicators2
The utilisation of capacity at current level of production in per cent77.076.877.177.677.8
Number of working months covered by stock of orders, weighted average3.94.04.04.14.1
Indicator on resource shortage317.117.318.219.419.8
Demand and competition as limiting factors for production in current quarter, per cent7171706867
Confidence Indicator4-50142

Table 5 
Intermediate goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted

Intermediate goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2Composite indicators are not precented as diffusionindices, but in per cent, number of months and balance
3Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent. See also table 10.
4Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance. See also table 9.
Changes from previous quarter
Total volume of production52.252.554.554.954.9
Average capacity utilisation52.054.256.055.153.7
Average employment48.950.252.753.853.6
New orders received from home markets51.853.554.254.355.4
New orders received from export markets48.449.251.251.751.0
Total stock of orders50.852.453.853.753.8
Prices on products at home markets50.351.153.355.456.3
Prices on products at export markets49.050.755.258.255.2
 
Judgements of the current situation by end of quarter
Stocks of orders compared to current level of production34.335.836.336.637.5
Inventories of own products ment for sale47.746.648.350.549.6
Does the enterprise consider changes in the plans for gross capital investments51.352.454.255.555.0
General judgement of the outlook for the enterprise in next quarter56.758.458.157.457.7
 
Expected changes in next quarter
Total volume of production55.357.758.958.758.3
Average capacity utilisation55.756.456.756.856.7
Average employment49.751.351.551.250.1
New orders received from home markets57.057.958.158.457.4
New orders received from export markets53.555.855.656.556.8
Total stock of orders57.059.660.260.258.9
Prices on products at home markets52.053.755.757.458.0
Prices on products at export markets49.652.054.556.256.0
 
Composite indicators2
The utilisation of capacity at current level of production in per cent80.080.681.080.780.2
Number of working months covered by stock of orders, weighted average3.13.33.33.33.3
Indicator on resource shortage323.523.924.925.725.8
Demand and competition as limiting factors for production in current quarter, per cent6666656362
Confidence Indicator43111087

Table 6 
Capital goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted

Capital goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2Composite indicators are not precented as diffusionindices, but in per cent, number of months and balance
3Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent. See also table 10.
4Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance. See also table 9.
Changes from previous quarter
Total volume of production38.438.541.545.248.6
Average capacity utilisation38.038.642.046.349.6
Average employment31.132.437.042.646.7
New orders received from home markets39.442.646.148.349.2
New orders received from export markets33.735.037.942.444.6
Total stock of orders31.735.141.045.246.8
Prices on products at home markets42.343.044.846.146.5
Prices on products at export markets40.340.441.542.843.8
 
Judgements of the current situation by end of quarter
Stocks of orders compared to current level of production21.223.626.429.030.3
Inventories of own products ment for sale48.947.947.648.749.3
Does the enterprise consider changes in the plans for gross capital investments43.845.547.649.651.0
General judgement of the outlook for the enterprise in next quarter45.447.550.453.655.7
 
Expected changes in next quarter
Total volume of production42.243.548.052.053.6
Average capacity utilisation43.244.148.152.353.8
Average employment34.036.542.346.346.5
New orders received from home markets44.446.851.053.753.8
New orders received from export markets41.544.247.851.052.4
Total stock of orders38.540.944.848.550.7
Prices on products at home markets44.747.148.849.650.6
Prices on products at export markets40.242.045.047.148.5
 
Composite indicators2
The utilisation of capacity at current level of production in per cent76.175.676.077.278.1
Number of working months covered by stock of orders, weighted average5.85.96.06.16.1
Indicator on resource shortage312.013.014.717.218.5
Demand and competition as limiting factors for production in current quarter, per cent8281787574
Confidence Indicator4-17-13-501

Table 7 
Consumer goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted

Consumer goods. Tendencies, judgements and composite indicators. Diffusion index. Smoothed seasonally adjusted1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
2Composite indicators are not precented as diffusionindices, but in per cent, number of months and balance
3Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent. See also table 10.
4Industrial confidence indicator is the average of the answers (balances) to the questions on production expectations, total stock of orders and inventories of own products ment for sale (the latter with inverted sign). The indicator is presented as seasonally adjusted balance. See also table 9.
Changes from previous quarter
Total volume of production53.451.750.448.648.2
Average capacity utilisation53.251.850.348.648.8
Average employment46.446.047.348.449.4
New orders received from home markets52.551.249.748.748.9
New orders received from export markets53.153.654.655.455.8
Total stock of orders53.552.851.550.049.2
Prices on products at home markets57.655.754.854.554.6
Prices on products at export markets59.455.554.555.054.4
 
Judgements of the current situation by end of quarter
Stocks of orders compared to current level of production38.136.335.535.936.5
Inventories of own products ment for sale53.152.150.950.150.1
Does the enterprise consider changes in the plans for gross capital investments52.151.952.153.154.5
General judgement of the outlook for the enterprise in next quarter57.156.654.753.252.9
 
Expected changes in next quarter
Total volume of production56.554.552.752.853.9
Average capacity utilisation57.856.152.952.153.0
Average employment47.346.945.645.646.3
New orders received from home markets56.354.952.552.853.7
New orders received from export markets58.058.856.052.851.8
Total stock of orders57.155.753.352.953.9
Prices on products at home markets57.055.755.256.157.6
Prices on products at export markets56.555.553.953.253.3
 
Composite indicators2
The utilisation of capacity at current level of production in per cent76.075.975.375.175.1
Number of working months covered by stock of orders, weighted average2.72.83.03.03.0
Indicator on resource shortage318.717.216.316.316.2
Demand and competition as limiting factors for production in current quarter, per cent6061646463
Confidence Indicator443032

Table 8 
Manufacturing. Industrial Confidence Indicator. Balances

Manufacturing. Industrial Confidence Indicator. Balances12
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1Industrial confidence indicator is the average of the answers (balances) to the questions on expected volume of production, total stock of orders and inventories of own products ment for sale (the latter with inverted sign)
2The balance (net figure) is defined as the difference between the percentage shares for the extreme response alternatives (Greater - Smaller)
Seasonally adjusted
Confidence Indicator-50142
 
Unadjusted
Confidence Indicator-3-3164
Expected volume of production1-4111210
Inventories of own products ment for sale-2-631-4
Total stock of orders-13-12-56-3

Table 9 
Manufacturing. Indicator on resource shortage. Smoothed seasonally adjusted

Manufacturing. Indicator on resource shortage. Smoothed seasonally adjusted1
3rd quarter 20164th quarter 20161st quarter 20172nd quarter 20173rd quarter 2017
1Indicator on resource shortage is the sum of percentages for those who have pointed out that lack of qualified labour and raw materials/electric power limits production, plus the percentage of establishments with capacity utilisation above 95 per cent.
A+B+C Indicator of resource shortage1717181920
A Supply of labour, per cent22333
B Supply of raw mat electric power, per cent33344
C Units having full capacity, per cent1212121213

Table 10 
Actual and expected changes in total production, by division and main industrial groupings. Diffusion index. Unadjusted figures

Actual and expected changes in total production, by division and main industrial groupings. Diffusion index. Unadjusted figures1
Changes from previous quarterExpected changes in next quarter
3rd quarter 20163rd quarter 20173rd quarter 20163rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
Manufacturing, mining and quarrying44.148.150.755.0
 
Manufacturing44.147.950.655.0
Food, beverages and tobacco56.547.963.959.2
Food products58.749.165.057.9
Textiles, wearing apparel, leather50.351.132.255.1
Wood and wood products59.858.155.252.6
Paper and paper products68.636.851.740.9
Printing, reproduction37.053.662.563.9
Refined petro., chemicals, pharmac.42.654.460.555.4
Basic chemicals43.655.062.954.0
Rubber, plastic and mineral prod.49.953.449.757.8
Basic metals43.349.536.948.4
Non-ferrous metals49.547.537.446.7
Fabricated metal products48.050.751.760.3
Computer and electrical equipment34.238.540.245.6
Machinery and equipment24.444.735.753.1
Ships, boats and oil platforms29.538.742.145.7
Transport equipment n.e.c58.662.455.853.0
Repair, installation of machinery38.048.443.653.9
Furniture and manufacturing n.e.c.35.438.957.759.8
 
Main industrial groupings:
Intermediate goods49.852.150.453.0
Capital goods33.344.942.953.6
Consumer goods51.847.460.359.1

Table 11 
Actual and expected changes in employment, by division and main industrial groupings. Diffusion index. Unadjusted figures

Actual and expected changes in employment, by division and main industrial groupings. Diffusion index. Unadjusted figures1
Changes from previous quarterExpected changes in next quarter
3rd quarter 20163rd quarter 20173rd quarter 20163rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
Manufacturing, mining and quarrying42.450.342.246.9
 
Manufacturing42.450.442.147.0
Food, beverages and tobacco52.550.350.947.2
Food products53.550.151.047.0
Textiles, wearing apparel, leather45.557.738.049.8
Wood and wood products64.557.849.445.6
Paper and paper products51.548.445.747.2
Printing, reproduction36.745.234.649.0
Refined petro., chemicals, pharmac.58.153.049.451.8
Basic chemicals51.147.350.346.0
Rubber, plastic and mineral prod.50.253.542.648.7
Basic metals57.350.649.645.8
Non-ferrous metals62.551.852.444.5
Fabricated metal products45.958.147.152.8
Computer and electrical equipment27.845.941.251.0
Machinery and equipment24.743.830.639.9
Ships, boats and oil platforms20.349.421.436.4
Transport equipment n.e.c46.748.135.850.7
Repair, installation of machinery31.644.935.746.2
Furniture and manufacturing n.e.c.34.145.846.750.0
 
Main industrial groupings:
Intermediate goods50.454.148.248.6
Capital goods30.146.532.744.2
Consumer goods48.750.447.647.9

Table 12 
Actual and expected changes in new orders from home market, by division and main industrial groupings. Diffusion index. Unadjusted figures

Actual and expected changes in new orders from home market, by division and main industrial groupings. Diffusion index. Unadjusted figures1
Changes from previous quarterExpected changes in next quarter
3rd quarter 20163rd quarter 20173rd quarter 20163rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
Manufacturing, mining and quarrying45.450.151.053.4
 
Manufacturing45.250.251.253.7
Food, beverages and tobacco56.751.464.260.4
Food products59.751.662.960.1
Textiles, wearing apparel, leather59.149.637.156.7
Wood and wood products59.857.849.750.4
Paper and paper products64.350.062.154.4
Printing, reproduction33.550.762.558.3
Refined petro., chemicals, pharmac.44.753.251.846.1
Basic chemicals39.354.254.842.7
Rubber, plastic and mineral prod.50.751.252.453.7
Basic metals48.850.546.638.0
Non-ferrous metals51.549.750.032.5
Fabricated metal products53.856.453.458.5
Computer and electrical equipment21.939.134.942.3
Machinery and equipment37.243.135.253.2
Ships, boats and oil platforms29.445.844.246.0
Transport equipment n.e.c48.167.955.751.8
Repair, installation of machinery35.450.648.951.4
Furniture and manufacturing n.e.c.39.744.659.863.6
 
Main industrial groupings:
Intermediate goods49.654.749.449.1
Capital goods35.845.944.252.1
Consumer goods52.550.261.259.5

Table 13 
Actual and expected changes in new orders from the export market, by division and main industrial groupings. Diffusion index. Unadjusted figures

Actual and expected changes in new orders from the export market, by division and main industrial groupings. Diffusion index. Unadjusted figures1
Changes from previous quarterExpected changes in next quarter
3rd quarter 20163rd quarter 20173rd quarter 20163rd quarter 2017
1A diffusion index is compiled using the estimated percentages on "ups" and "same" according to the formula: (ups + 0,5 * same) after adjustments for non-response.
Manufacturing, mining and quarrying39.548.848.853.3
 
Manufacturing38.848.648.553.5
Food, beverages and tobacco58.459.957.055.5
Food products56.561.257.756.0
Textiles, wearing apparel, leather67.452.862.248.3
Wood and wood products63.944.648.848.8
Paper and paper products61.045.829.545.8
Printing, reproduction67.162.355.850.0
Refined petro., chemicals, pharmac.51.657.258.858.6
Basic chemicals37.752.064.355.0
Rubber, plastic and mineral prod.35.254.063.357.3
Basic metals48.651.239.548.2
Non-ferrous metals46.448.834.846.5
Fabricated metal products36.440.552.262.0
Computer and electrical equipment24.135.044.850.5
Machinery and equipment30.253.041.361.1
Ships, boats and oil platforms15.430.834.842.9
Transport equipment n.e.c48.465.255.650.0
Repair, installation of machinery31.741.642.648.5
Furniture and manufacturing n.e.c.25.453.063.844.3
 
Main industrial groupings:
Intermediate goods46.148.451.154.8
Capital goods25.943.041.152.8
Consumer goods54.457.559.851.8

About the statistics

The statistics provide current data on the business cycle for manufacturing, mining and quarrying by collecting business leaders’ assessments of the economic situation and the short-term outlook.

Definitions

Definitions of the main concepts and variables

Local unit (establishment) : An enterprise or part of an enterprise that is located in one particular place and can be identified geographically.

Enterprise : The smallest combination of legal units that is an organisational unit producing goods or services and that benefits from a certain degree of autonomy in decision making.

Branch unit : Unit, which comprises all establishments within an enterprise belonging to the same 3-digit industry group (SIC2007).

IDUN : Statistics Norway's electronic system for reporting data via the Internet.

NACE : Standard for industrial classification used by EUROSTAT based on the UN's international standard for industrial classification, ISIC Rev. 3.

Unadjusted figures : Raw data figures with primary information from the respondent.

Seasonally-adjusted figures : Time series for which calendar and seasonal effects have been removed. X12-ARIMA is used to calculate these figures.

Trend series : Time series for which calendar and seasonal effects together with the irregular component have been removed. The trend in a time series reflects the long-term tendency that influences the series and has a fairly smooth and monotonic character. The trend series are calculated in connection with the decomposition of the time series for the unadjusted figures in X12-ARIMA.

Response distribution : Employment weighted shares in percentages for valid response alternatives for a single question. For questions like «total level of production» the response alternatives are greater , unchanged and smaller respectively. The response distribution may be expressed in the following way:

(1) G + U + S = 100

where

G = Percentage that has replied: Greater

U = Percentage that has replied: Unchanged

S = Percentage that has replied: Smaller

Net figures : Defined as the difference between the percentage shares for the extreme response alternatives. For questions like «total level of production» the extreme response alternatives are greater and smaller respectively. The Net figure, N, is defined as:

(2) N = G - S

The net figure, as an indicator of the development in the variable, is often assigned turning point characteristics. A net figure greater then zero indicates that the growth rate of the variable is positive. A positive net figure, but reduced from one quarter to the next, indicates that the growth rate is still positive but reduced. The opposite applies for a negative net figure.

Diffusion index : Defined as the estimated positive percentages (greater) plus half of the neutral answers (unchanged). For questions like «total level of production» the diffusion index, D, is compiled as:

(3) D = G + 0.5 x U

The diffusion index has a simple intuitive approach as it compiles the respondents answering greater seen in association with half the share of respondents answering unchanged. The simplicity lies in the fact that the indicator builds on the assumption that half of the respondents answering unchanged in practice have experienced a growth in the variable, while the other half have experienced a decline. The diffusion index has 100 as the maximum value when all active respondents choose the response alternative greater. The minimum value is equal to 0 when all choose smaller. The index normally fluctuates around 50, which is also the turning point value. Below are some interpretations for the diffusion index as described in the literature:

  • If the D value is greater than 50 it indicates that the growth rate of the variable is positive, and the opposite for a value below 50.
  • If the D value rises from a level below to a level above 50, the growth rate of the variable has turned from negative to positive.
  • If the D value is greater than 50 and increasing it indicates that the growth rate is increasing, while a falling index from above 50 indicates a falling rate of growth, but still positive. The opposite is the case for an index below 50.

Industrial Confidence Indicator (ICI) : The ICI is calculated on the basis of the net figures from three questions in the Business Tendency Survey:

  • Actual development in total stock of orders compared with the previous quarter (X)
  • Expected development in the level of production in the forthcoming quarter compared with the present quarter (Y)
  • Assessment of stock of own products intended for sale (Z)

The ICI is the arithmetic average of the net figures (Z with inverted sign). Further, the trend is identified by the seasonal adjustment of the ICI. The Norwegian ICI is harmonised with the ICI defined by EUROSTAT, and the composition is described in detail in Economic Paper number 151, see DG ECFIN (2001). The ICI is supposed to be a leading indicator for the production in manufacturing industries whereby increases in production expectations indicate directly increases in the forthcoming level of output, increases in the total stock of orders indicate an increased level of production due to the fulfilment of the received orders, and finally, increases in stocks indicate slow sales and reduced activity.

(5) ICI = (X + Y - Z)/3

Standard classifications

The survey is classified according to the Standard Industrial Classification 2007 (SIC2007). This is a Norwegian adaptation of Eurostat’s industry classification, NACE Rev. 2. SIC2007 forms the basis for classifying units according to principal activity in the Central Register of Establishments and Enterprises. The use of common standards is essential in order to enable the comparison and analysis of statistical data at an international level and over time.

The survey is also classified according to EUROSTAT's end-use categories (Main Industrial Groupings, MIG). The end-use categories (MIGs) are based on the 3-digit level industrial groupings in SIC2007. Five end-use categories are included in the survey:

MIG code

Description

E1

Intermediate goods

E2

Capital goods

E3

Consumer durables

E4

Consumer non-durables

E5

Consumer goods (E3+E4)

   

The following table summarises the most important industries included in the different end-use categories:

MIG

Main industries included

Intermediate goods

Wood and wood products, Paper and paper products, Basic chemicals, Rubber and plastics products, Non-metallic mineral products, Basic metals

Capital goods

Machinery and equipment, Building of ships, boats and oil platforms, Repair and installation of machinery

Consumer durables

Manufacture of furniture

Consumer non-durables

Food products, Printing and reproduction, Basic pharmaceuticals

Consumer goods (E3+E4)

Manufacture of furniture, Food products, Printing and reproduction, Basic pharmaceuticals

   

For a complete description of industries covered in each MIG, see Commission regulation (EC) No 656/2007 .

The objective of this classification is to provide an activity breakdown of NACE, which is more detailed. The classification of the different units is based on the application of the produced products. It should be noted that the MIGs are not comparable in size, in particular the consumer durables heading is smaller than the others.

Administrative information

Name and topic

Name: Business tendency survey for manufacturing, mining and quarrying
Topic: Energy and manufacturing

Next release

Responsible division

Division for Manufacturing and R&D statistics

Regional level

National level only

Frequency and timeliness

Published about one month after the end of the quarter

International reporting

Time series are reported to the OECD on a quarterly basis

Microdata

Non-revised and revised micro data are stored in accordance with Statistics Norway's guidelines for storing computer files.

Background

Background and purpose

The survey maps out business leaders’ evaluations of the economic situation and the outlook for a fixed set of indicators. Even if the survey does not give precise measures of economic variables, this kind of business survey helps to monitor the economic trend in present time and in the short-term outlook.

The survey was established in 1973 and put into operation on a regular basis from the first quarter of 1974. In 1995, a major review of the survey was conducted. The review was especially concerned with a modernisation of the bottleneck questions and related response alternatives i.e. factors delimiting the production activity. A second review of the survey was conducted in 2011. Some questions concerning delivery time and inventories were replaced by other ones concerning input factor prices, profitability and factors delimiting gross capital investments.

As from the first quarter 2009, all results will refer to SIC2007 (see paragraph 4.2). The historical series are recalculated according to this version of SIC, and results for the business tendency survey dating back to 1990 are available in the StatBank database. Historical series based on SIC2002 (see paragraph 6.1) also remain available for the period 1988 to 2008.

The survey is wholly financed by government appropriations.

Users and applications

The users of the business tendency survey are found within the financial sector, the macro economic analytic environment, media and public institutions (the Ministry of Finance and Norges Bank among others). The results are mainly used for monitoring the economic performance during a business cycle, for analyses and for predicting the short-term development.

Equal treatment of users

No external users have access to the statistics and analyses before they are published and accessible simultaneously for all users on ssb.no at 8 am. Prior to this, a minimum of three months' advance notice is given inthe Statistics Release Calendar.

Coherence with other statistics

The survey is one of many indicators that form a basis for monitoring the performance of the economy during a business cycle. A collection of business cycle indicators is available in the theme page Economic indicators and Key Economic Figures. The survey does not, however, have a direct connection with other statistics.

Legal authority

The Statistics Act of 16 June 1989 , § 2-1 (voluntary)

EEA reference

Not relevant

Production

Population

The population covers all branch units in mining and quarrying (SN05, SN07-08, SN09.9) and manufacturing (10-33), see Standard Industrial Classification 2007 (SIC2007) . The Central Register of Establishments and Enterprises (CRE) defines the population, and the branch unit is the unit for analysis in the survey. The branch unit comprises all establishments within an enterprise belonging to the same 3-digit industry group. See paragraph 4.1 for a complete definition of establishment, branch unit and enterprise.

Data sources and sampling

The survey uses data collected by questionnaires from the units included in the sample, in addition to information from the CRE. The CRE is Statistics Norway's own register of all legal units and establishments in the private and public sectors in Norway. Employment data from the annual Manufacturing statistics are also used in the estimation process.

The gross sample includes about 800 units and represents about 3.5 per cent of the total population of branch units. The sample units cover about 40 per cent of the total level of employment for the industries covered by the survey. The sample includes all branch units with 300 employees or more (panel). The remaining units are drawn by methods based on stratification and optimal allocation with probability proportional to the size of the unit measured by the number of employees. The sample does not include establishments with fewer than 10 employees.

Collection of data, editing and estimations

The survey is based on data collected by questionnaire. The questionnaires are returned electronically via Altinn. The questionnaire is released around the 10th in the last month of each quarter. The deadline for returning the questionnaire is the last day of the month. Units registered with an e-mail address in Altinn are notified by e-mail when the questionnaire is available on the Internet.

The largest of the establishments within the branch unit is used as the reporting unit. For practical reasons, some enterprises prefer to report from the head office. The person responsible for filling in the questionnaire should be the leader of the unit or a member of the management staff. Establishments that fail to return the questionnaire receive a reminder within a few days of the deadline. A new deadline of 12 days is set.

The questionnaires are optically read or downloaded from the Internet, and the data are automatically checked for duplicates. Questionnaires edited close to the release day, and faxes, are manually registered. When data from the questionnaires are loaded to the production database, they are controlled for logical errors, such as multiple response alternatives chosen where this is not valid. Revision on aggregated level is done by assessing the development over time, and unacceptable series lead to further revision of the data. Results and tendencies are also compared with other relevant quantitative statistics.

Employment weighted results (response distribution) are calculated for each question. The sample units are classified in different strata depending on the number of employees in the branch unit and in which industry they belong to (3-digit NACE). For each question by stratum a response distribution is estimated using employment data as weights. The response for each branch unit is given a weight equal to the number of employees. For aggregation to the industrial group level and totals, the stratum results carry a weight equal to the stratum population employment.

Time series sometimes contain significant seasonal variations that make it difficult to interpret the development from one period to another. To facilitate the interpretation of such time series, the figures are seasonally adjusted. For more information on seasonal adjustment, see Seasonal adjustment: general information .

Seasonal adjustment

In the Business Tendency Survey, seasonally adjusted figures and trend figures are calculated with X12-ARIMA for most of the questions. Only the trend figures are released, together with the unadjusted figures. For survey specific documentation of seasonal adjustment practices, see About sesaonal adjustment .

Confidentiality

Confidential micro data : According to § 2-4 of the Statistics Act, collected data are subject to secrecy and must be kept or destroyed in a secure manner. Any use of the data must be in accordance with the rules set out by the Data Inspectorate.

Time series that are not to be published : The publication of data is subject to the provisions in § 2-6 of the Statistics Act. The main rule is that data should not be published if they can be traced back to the respondent, i.e. figures for which less than three respondents make up the foundation for a cell in the table, figures where one respondent represents more than 90 per cent of the total value or figures where two respondents represent at least 95 per cent of the total value. In the business tendency survey this is the case for divisions 05, 12 and 19 (SIC2007), and for a number of other more detailed levels of aggregation. As a main rule, all series that are not published are considered confidential.

Unpublished data : Revised data that are not published are subject to secrecy. This means that they are unavailable without specific approval.

Comparability over time and space

As from the first quarter 2009, SIC2002 has been replaced by SIC 2007 (see paragraph 2.1). The historical series based on this new version of SIC have been recalculated back to 1990. For the years 1990 to 2003 a macro-approach is used for back-casting the time series. For the years 2004 - 2008 the survey is recalculated by a detailed re-working of individual data (micro-approaches). Users of the data must ensure they use results based on the same version of SIC when making comparisons over time. Historical series based on SIC2002 remain available in the StatBank database under Completed time series. However, as from the first quarter 2009, only series based on SIC2007 will be continued.

Accuracy and reliability

Sources of error and uncertainty

Measurement errors are caused by the questionnaire or the respondent’s internal systems for obtaining the data. Sources of measurement errors may be ambiguous guidelines or the respondent’s insufficient accounting systems. In the Business Tendency Survey, errors in reported answers may originate from misunderstandings of the definition of the main variables used in the survey. Unambiguous guidelines and definitions are therefore emphasised.

Processing errors can occur when Statistics Norway processes the data. Typical examples are misinterpretations of the answers on the questionnaires &– for example that a chosen response alternative is not registered. Paper questionnaires are optically read with automatic verification and transfer to an electronic medium. The current techniques for optical reading are of a high quality, and few errors are found in this phase of the production. The introduction of Altinn has also helped reduce such errors, as data from electronic questionnaires are loaded directly into the system. Questionnaires that are not verified by optical reading are processed manually. Thus there is room for human error, but because the proportion of manually registered questionnaires is very small this type of error seldom occurs.

After data has been loaded into the production database, in the revision process, there will be occurrences of multiple response alternatives where this is not valid. When this occurs the answer must be evaluated and a response alternative must be chosen as the valid one. These corrections are based on assumed logical coherences with other questions in the same questionnaire or by the use of response alternatives from previous questionnaires for the same respondent. This assessment can cause processing errors when the response alternative registered is not what the respondent had in mind. However, the number of occurrences of multiple response alternatives is very small, and this kind of error does not exist in the electronic questionnaire. In this questionnaire it is not possible to choose more than the valid number of response alternatives.

Errors of non-response refer to errors that either occur due to unit non-response or item non-response. Unit non-response occurs when the respondent has not returned the questionnaire, while item non-response occurs when at least one of the questions in the questionnaire is not answered.

Unit non-response for the survey is around 7 per cent when final production file is ready. Critical units, i.e. units that have a considerable impact on the results at a detailed level aggregation (2-digit NACE), are contacted by telephone. Calculations of the effect of missing units have been carried out (see Documents 2004/3 ), and no systematic skewness has been uncovered. Unit non-response is considered to be neutral, and is covered indirectly in the aggregation when inflating to population level.

Item non-response (single questions not answered in the questionnaire) is coded automatically as response alternative non-response and is not normally imputed.

Sampling errors refer to uncertainty that occurs when figures are produced based on a sample survey as opposed to a full count. The sample variance equals the expected deviation between a sample survey and a full count. In the business bendency survey the sample represents 3.5 per cent of the branch units in the population and covers about 40 per cent of the population’s total employment rate. In order to ensure a high degree of relevance at the lowest cost possible, great effort is put into including all large units in the population in the sample. The effect of sampling errors occurring in the population estimate is calculated, and the results are published in Documents 2004/10 .

Units in the sample that close down can be a source of skewness if the proportion of units closing down in the sample deviates from the population. The business tendency survey is mainly based on a fixed sample (panel). Periodic updates of the sample ensure that the structure of the sample is in accordance with the population.

Coverage errors refer to errors in registers that define the population. As a result, units may be incorrectly included in or excluded from the population. Other problems are related to delays in the update of the registers and units that are incorrectly classified. From experience a limited share of the population units are incorrectly classified. This is usually due to misleading or insufficient information at a certain time. Calculations of the size and significance of such errors have not been carried out. However, such errors are not considered to be greater than for other quantitative short-term statistics. Industry classification for the sample units is revised annually in the first quarter to ensure correct classification in accordance with the CRE.

Modelling errors are first and foremost related to problems with the seasonal adjustment of time series. Such problems are caused by deviations from the conditions that form the basis for the model used. Typical problems are related to movable public holidays such as Christmas and Easter. However, such problems are considered greater for surveys published on a monthly basis. X12-ARIMA generates a number of indicators that are used to evaluate the quality of the seasonal adjustment. The quality of the seasonally-adjusted time series is also evaluated by the inspection of figures that generate seasonally-adjusted and unadjusted series.

Revision

Not relevant

About seasonal adjustment

General information on seasonal adjustment

What is seasonal adjustment?

Monthly and quarterly time series are often characterised by considerable seasonal variations, which might complicate their interpretation. Such time series are therefore subjected to a process of seasonal adjustment in order to remove the effects of these seasonal fluctuations. Once data have been adjusted for seasonal effects by X-12-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.

For more information on seasonal adjustment: metadata on methods: seasonal adjustment

Why seasonally adjust these statistics?

Why do we seasonally adjust the business tendency survey?

The business tendency survey is part of a system of short term statistics to monitor the economy. The primary goal of the survey is to provide current data on the development in the business cycle for manufacturing, mining and quarrying. The survey does not give precise measures of economic variables, but it still provides useful information on the current situation and the short-term outlook.

The level of activity within manufacturing, mining and quarrying will vary throughout the year because of public holidays etc. Some industries also experience fluctuations due to a change of seasons. An example is the demand for and production of certain food products which depend on whether it is summer or winter. This kind of effects will influence the reported data for a number of indicators in the business tendency survey and make it difficult to compare the results from quarter to quarter.

The business tendency survey is subjected to a process of seasonal adjustment in order to remove the effects of seasonal fluctuations. In this way we are able to analyse the underlying development in the business cycle. It is mainly the smoothed seasonally adjusted time series (trend) that are released and analysed.

Time series that are seasonally adjusted

The business tendency survey publishes 220 seasonally adjusted time series which covers a wide range of indicators on the development within manufacturing, mining and quarrying and EUROSTAT's end-use categories (Main Industrial Groupings, MIG).

 

 

 

Pre-treatment

Pre-treatment routines/schemes

Pre-treatment is an adjustment for variations caused by calendar effects and outliers.

No pre-treatment is performed.

Calendar adjustment

Calendar adjustment involves adjusting for the effects of working days/trading days and for moving holidays. Working days/trading days are adjustment for both the number of working days/trading days and for that the composition of days can vary from one month to another.

No calendar adjustment is performed.

Methods for trading/working day adjustment

No adjustment for trading/working day is performed.

Correction for moving holidays

No correction for moving holidays is performed.

National and EU/euro area calendars

Calendar adjustment is not required.

Treatment of outliers

Outliers, or extreme values, are abnormal values of the series.

No pre-treatment of extreme values. 

Model selection

Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log transformed or not.

Model selection is performed manually based on statistical tests.

Comments: (0,1,1) (0,1,1) or the "Airline model" is selected manually for all the time series.

Decomposition scheme

The composition scheme specifies how the various components - basically trend-cycle, seasonal and irregular - combine to form the original series. The most frequently used decomposition schemes are the multiplicative, additive or log additive.  

Manual decomposition scheme selection after graphical inspection of the series.

Comment: Log additive method is in use for some of the time series.

Seasonal adjustment

Choice of seasonal adjustment approach

X-12-ARIMA

Consistency between raw and seasonally adjusted data

In some series, consistency between raw and seasonally adjusted series is imposed.

Do not apply any constraint.

Consistency between aggregate/definition of seasonally adjusted data

In some series, consistency between seasonally adjusted totals and the aggregate is imposed. For some series there is also a special relationship between the different series, e.g. GDP which equals production minus intermediate consumption.

Do not apply any constraint.

Direct versus indirect approach

Direct seasonal adjustment is performed if all series, including aggregates, are seasonally adjusted on an individual basis. Indirect seasonal adjustment is performed if the seasonally adjusted estimate for a time series is derived by combining the estimates for two or more directly adjusted series.

The unadjusted data are aggregated, and direct seasonal adjustment is performed on aggregates and components using the same approach and software. Any discrepancies across the aggregation structure are not removed.

Horizon for estimating the model and the correction factors

When performing seasonal adjustment on time series, it is possible to choose the number of observations to be used when estimating the model and the correction factors. Correction factors are the factors used in the pre-treatment and seasonal adjustment of the time series.

The whole time series is used to estimate the model and the correction factors.

Audit procedures

General revision policy

Seasonally adjusted data may change due to a revision of the unadjusted (raw) data or the addition of new data. Such changes are called revisions, and there are several ways to deal with the problem of revisions when publishing the seasonally adjusted statistics.

Seasonally adjusted data are revised in accordance with a well-defined and publicly available revision policy and release calendar.

Concurrent versus current adjustment

The model, filters, outliers and regression parameters are re-identified and re-estimated continuously as new or revised data become available.

Horizon for published revisions

The revision period for the seasonally adjusted results is limited to 3-4 years prior to the revision period of the unadjusted data, while older data are frozen.

Comment: The revision period for the seasonally adjusted figures is 4 years when new data are added. The whole time series may be revised when implementing new or improved methods.

Quality of seasonal adjustment

Evaluation of seasonally adjustment data

Continuous/periodical evaluation using standard measures proposed by different seasonal adjustment tools.

Quality measures for seasonal adjustment

For most of the series, a selected set of diagnostics and graphical facilities for bulk treatment of data is used.

A table containing selected quality indicators for the seasonal adjustment is available here.

For more information on the quality indicators in the table see: metadata on methods: seasonal adjustment

Special cases

Seasonal adjustment of short time series

All series are sufficiently long to perform an optimal seasonal adjustment.

Treatment of problematic series

All problematic series are treated in a special way.

Posting procedures

Data availability

Unadjusted data, seasonally adjusted data and smoothed seasonally adjusted data are available.

Comments: Only unadjusted data are released for lower aggregates within manufacturing.

Press releases

In addition to raw data, at least one of the following series is released: Calendar adjusted, seasonally adjusted, smoothed seasonally adjusted (trend).

 

Relevant documentation

Contact