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The enterprises are numbered 1 - 11 and the reporting units belonging to enterprise 1 are numbered 1.1, 1.2 and 1.3, those belonging to enterprise 2 are numbered 2.1 and 2.2. etc.
The reporting units belonging to the same enterprise all have the same sampling probability as the enterprise to which they belong.
Therefore the contents of column 8 is the same for all reporting units belonging to the same enterprise and identical with column 4 for that enterprise.
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On the other hand, reporting units belonging to the same enterprise might belong to different industries and size groups.
Examples of this are included in the list.
42 Table 3.
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List of enterprises and report units with data for numerical illustration of two weighting and estimation methods in BT-surveys Enterprises No Industry Size group Sampling Probability Reporting units Industry No Size group Sampling Probability Col 1 Col 2 1 A Col 3 Col 4 1 1/1 2 A 1 1/1 A A B B B B B B B 4 5 6 7 8 9 10 11 2 2 1 1 2 2 2 1/10 1/10 1/3 1/3 1/6 1/6 1/6 2 1/6 2 1/6 Col 5 Col 6 1.1 1.2 1.3 2.1 2.2 2.3 3.1 4.1 4.2 5.1 6.1 6.2 7.1 8.1 9.1 9.2 9.3 10.1 10.2 11.1 A A B A B A A A B B B A B B B A A A B B Col 7 Col 8 1 2 1 2 1 2 2 2 2 1 1 1 2 2 2 2 2 2 2 2 1/1 1/1 1/1 1/1 1/1 1/1 1/10 1/10 1/10 1/3 1/3 1/3 1/6 1/6 1/6 1/6 1/6 1/6 1/6 1/6 Weight (Number of employees) Col 9 600 100 300 160 250 140 70 60 50 1000 400 400 5 30 140 20 10 40 80 170 Response question Q to Col 10 + 1 0 − 1 0 + 1 − 1 − 1 − 1 + 1 − 1 0 − 1 0 + 1 + 1 0 − 1 − 1 − 1 + 1 43 General method 147.
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Balances (B) are calculated as follows.
Report unit no.
Response Sampling probability Table 4.
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Calculating the balance for industry A (Ba ) Response adjusted to universe level Weight Weight adjusted to universe level Adjustment factor to universe level [xik] Col 1 Col 2 [fi] Col 3 1/1 +1 1.1 1/1 0 1.2 1/1 0 2.1 − 1 1/1 2.3 − 1 1/10 3.1 − 1 1/10 4.1 − 1 1/3 6.2 1/6 0 9.2 − 1 1/6 9.3 − 1 1/6 10.1 • • SUM • • • • = Irrelevant information [1/fi] Col 4 (1/Col 3) 1 1 1 1 10 10 3 6 6 6 44 [xik × 1/fi] Col 5 (Col 2* Col 4) + 1 0 0 − 1 − 10 − 10 − 3 0 − 6 − 6 − 35 [wik] Col 6 [1/fi × wik] Col 7 (Col 4*Col 6) 600 600 100 100 160 160 140 140 70 700 60 600 400 1200 20 120 10 60 40 240 1600 3920 Weighted response at universe level [1/fi × xik] × wik Col 8 (Col 5* Col 6) 600 0 0 − 140 − 700 − 600 −1200 0 − 60 −1200 − 3300 148.
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From the SUM row the balance for industry A is calculated as the quotient of column 8 / column 7 which amounts to -3300 / 3920 = - 0.84 Expressed in percentage points this gives the balance − 84.
The number of reporting units adjusted to universe level being 44, the unweighted balance is the quotient of column 5 / column 4 which amounts to -35 / 44 = - 0.80 or, in percentage points, − 80.
149.
Repeating the calculations for industry B we get the information recorded in Table 5.
150.
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150.
From the SUM row in Table 5 the balance for industry B is calculated as the quotient of column 8 / column 7 which amounts to − 990 / 7800 = − 0,13.
Expressed in percentage points this gives the balance − 13.
The unweighted balance is derived from the SUM row as the quotient of column 5 / column 4 which amounts to + 19 / 48 = + 0,40 or in percentage points + 40.
44 Table 5.
Calculation of balances for industry B, (Bb) Report unit no.
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Response Sampling probability Col 1 [xik] Col 2 [fi] Col 3 − 1 1/1 1.3 1/1 + 1 2.2 1/10 + 1 4.2 − 1 1/3 5.1 1/3 0 6.1 1/6 0 7.1 1/6 + 1 8.1 1/6 + 1 9.1 − 1 1/6 10.2 1/6 11.1 + 1 • • SUM + 4 • • = Irrelevant information Adjustment factor to universe level [1/fi] Col 4 (1/Col 3) Response adjusted to universe level × 1/fi] [xik Col 5 (Col 2* Col 4) 1 1 10 3 3 6 6 6 6 6 48 − 1 + 1 + 10 − 3 0 0 + 6 + 6 − 6 + 6 + 19 Weight [wik] Col 6 300 250 50 1000 400 5 30 140 80 170 2425 Weight adjusted to universe level × wik] [1/fi Col 7 (Col 4*Col 6) 300 250 500 3000 1200 30 180 840 480 1020 7800 Weighted response at universe level × xik] × wik [1/fi Col 8 (Col 5* Col 6) − 300 250 500 − 3000 0 0 180 840 − 480 1020 − 990 151.
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For calculating the balance for industry A and B combined, equation (9) is used.
In our numerical example the value added data in Table 2 (4.000 mln $ for industry A and 16.000 miln $ for industry B) are used as weights.
In the formula numerical values are used as follows: wk for industry A = 4.000 Bk for industry A = − 84 wk for industry B = 16.000 Bk for industry B = − 13 Consequently: k w∑ = 4.000 + 16.000 = 20.000 and k 152.
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Applying the same calculation method and industry weights to the unweighted balances we get B = [4000× (− 80) + 16.000× ( + 40)] / 20.000 = [− 320.000 + 640.000] : 20.000 = + 16 Simplified method 153.
Estimates from the sample of the total number of reporting units in each industry/size group of + )* ksN ( , = ksN ( )* and − ksN ( )* in formula the universe responding (+), (=) and (-) respectively - labelled (11) - are computed as follows using the data recorded in Table 3.
45 Table 6.
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Calculation of balances by the simplified weighting method Report unit no Industry Size group Response Sampling probability [xik] Col 4 Col 1 Col 2 Col 3 1 + 1 2 0 1 − 1 2 0 1 + 1 2 − 1 2 − 1 2 − 1 2 + 1 1 − 1 1 0 1 − 1 2 0 2 + 1 2 + 1 2 0 2 − 1 2 − 1 2 − 1 2 + 1 •• •• •• = Irrelevant information A 1.1 A 1.2 B 1.3 A 2.1 B 2.2 A 2.3 A 3.1 A 4.1 B 4.2 B 5.1 B 6.1 A 6.2 B 7.1 B 8.1 B 9.1 A 9.2 A 9.3 A 10.1 B 10.2 11.1 B SUM •• [fi] Col 5 1/1 1/1 1/1 1/1 1/1 1/1 1/10 1/10 1/10 1/3 1/3 1/3 1/6 1/6 1/6 1/6 1/6 1/6 1/6 1/6 •• Adjustment factor to universe level [1/fi] Col 6 (1/Col 4) 1 1 1 1 1 1 10 10 10 3 3 3 6 6 6 6 6 6 6 6 93 Response adjusted to universe level × 1/fi] [xik Col 7 Industry A Size group 1 Industry A Size group 2 IndustryB Size group 1 Industry B Size group 2 N*ks Col 8 N*ks Col 9 N*ks Col 10 N*ks Col 11 + 1 0 - 1 0 + 1 - 1 - 10 - 10 + 10 - 3 0 - 3 0 + 6 + 6 0 - 6 - 6 - 6 + 6 •• 1 3 1 1 3 3 1 1 1 10 10 6 6 6 4 41 8 10 6 6 6 6 6 40 154. up to the SUM for columns 8 to 11 in Table 6.
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Table 7 is derived from Table 6.
The frequencies in absolute numbers presented in Table 7 add Table 7.
Distribution within report strata of responses to question Q adjusted to universe level .
Absolute frequencies.
SUM OF RESPONSES REPORT UNIT STRATUM Industry A, Size group 1 Size group 2 Industry B, Size group 1 Size group 2 (+) 1 0 1 28 (=) 0 8 3 6 (−) 3 33 4 6 SUM 4 41 8 40 155.
The absolute numbers in this table are converted to percentages as shown in Table 8.
46 Table 8.
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46 Table 8.
Distribution within report strata of responses to question Q adjusted to universe level.
Percentage frequencies SUM OF RESPONSES REPORT UNIT STRATUM (+) (=) Industry A, Size group 1 Size group 2 Industry B, Size group 1 Size group 2 25 0 13 70 0 20 37 15 (−) 75 80 50 15 SUM 100 100 100 100 BALANCE [(+) - (−)] − 50 − 60 − 37 + 55 The figures in the cells of the columns (+), (=) and (−) are the Aks values according to formula 156.
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(11) above expressed as percentages and the figures in the cells of column BALANCE are the Bks values in formula (12).
Applying formula (11) for estimating the balances for our two industries and using the numerical data presented in Table 2 we get the information recorded in Table 9.
Table 9.
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Table 9.
Aggregation of size groups to industries and industries to industry aggregates INDUSTRY SIZE GROUP wks A A A B B B A + B 1 2 Total 1 2 Total TOTAL 2000 2500 4500 5000 3000 8000 12500 VALUE ADDED 4000 mln $ 16000 mln $ 20000 mln $ Bks Bk BV − 50 − 60 − 56 (1) − 37 + 55 − 3 (1) − 14 (2) (1) The balances by industry (Bk) have been computed by applying formula (12) above to the numerical data in the table.
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Thus: For industry A we get Bk = [2000× (−50) + 2500× (−60)] / 4500 = − 56 For industry B we get Bk = [5000× (−37) + 3000× (+55)] / 8000 = − 3 (2) The balance for aggregates of industries - i.e.
industry A plus industry B - is computed applying formula (9) above to the numerical data in the table as follows: B = [4000× (−56 ) + 16000× (−3)] / 20000 = − 14 157.
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In this simplified numerical example, the three different procedures – size-weighted general method, general method without size-weights and the simplified method – give very different results.
Using real-life data, the usual finding is that the choice of weighting procedure has a limited effect on the results.
Recommended weighting and estimation procedure 158.
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The recommended approach is to use reliable external information to come as close as possible to the correct weighting of size groups and industries for reporting units.
When this condition is fulfilled a mix between the simplified and general method should be used.
The general method is used to estimate the response distribution at the report stratum level and from there on external information is used as indicated in Table 2.
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In this manner the error due to estimating the importance of different size groups and of different industries is reduced.
47 6.
PUBLICATION OF RESULTS Introduction 159.
The quality of a statistical output has several dimensions.
Reliability and timeliness are the two that come immediately to mind but they are by no means the only ones.
This Chapter deals with three other key aspects of statistical quality: − Transparency.
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Are users sufficiently informed about the sources of the data and the methods used to edit and process them?
Methodological information – metadata – is considered in the first part of this Chapter.
− Interpretability.
Are users able to interpret the data easily and correctly?
The next part considers the information needs of different users and how these can be met.
− Accessibility.
Can users easily find the information they need?
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Can users easily find the information they need?
The final part of the Chapter offers guidance on dissemination of business tendency survey results.
Information on the methodology (meta-data) 160.
Users should be provided with sufficient information about the overall quality of the survey to enable them to draw accurate inferences from the data.
Users may also need to determine whether the results of surveys conducted in different countries are comparable.
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In many cases, this information is provided in the survey report at least once a year, usually in the report for surveys conducted in January or for the first quarter.
It is standard practice to include the questionnaire used for the survey and the instructions to respondents.
In addition the following points should be covered.
The frame 161.
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The frame 161.
Information about the coverage of the survey should be provided in terms of: − what types of enterprises are covered; − estimates of the extent of possible under–coverage e.g.
late up-date of new enterprises, poor coverage of small firms, enterprises excluded because of misclassification.
− estimates of the extent of possible over–coverage e.g.
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extinct enterprises remaining in the frame, enterprises wrongly included because of faulty classification; − age of the frame and how often is it updated.
49 The units 162.
Information about the units should include details on: − what are the response units i.e.
what kind of unit is the questionnaire sent to; − what are the reporting unit i.e.
the unit for which data are collected - enterprise, kind of activity unit, local unit or establishment.
The sample 163.
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The sample 163.
Information should be given on the sampling method: − random or purposive selection; − simple or stratified selection; − if stratified selection is used, what are the criteria for stratification: − kind of activity; − size in terms of employment, turnover, etc.
; − updating of sample: − − fixed panel; fixed panel but with new enterprises introduced at regular intervals; − entire sample renewed at regular intervals.
Weighting 164.
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Weighting 164.
Methods for estimating universe totals from the sample need to be explained: − at the lowest aggregation level (the individual stratum); − for higher aggregation levels (industries, industry groups, grand total).
Data collection methods 165.
A description of the data collection method should be provided e.g.
mail, telephone interview, personal interview, e-mail return, etc.
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When several methods have been used, the approximate proportion of replies received with the different methods should be indicated 50 Treatment of non–response Information on the extent of non–response should be provided by size groups according to the 166. appropriate measures M1–M3 (see Chapter 4).
Information is also required on the procedures used to deal with non-response.
For example: − substitution (enterprises who have replied have been included as substitutes for non– responding enterprises).
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In this case the method for selecting substitutes should be explained; − imputation (a completed questionnaire has been constructed).
In this case the method of imputation should be explained; − assumption that non–responding enterprises are a random sample of enterprises in the survey; − other methods, details of which need to be specified.
Precision 167.
The margins of error due to the use of a sample instead of complete enumeration should also be explained.
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Ideally, estimates of the variance and 95% confidence interval should be given for the total and the main kind of activity groups.
These measures are only relevant when random sampling has been used.
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Comparability 168. comparisons of data between: Information provided should include descriptions of survey comparability with regard to − consecutive surveys, especially between the last quarter/month one year and the first in the following year, since this is when changes to questionnaires or survey methods are most often introduced; − business tendency survey data and related quantitative statistics.
169. between the survey and the harmonised system.
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169. between the survey and the harmonised system.
This Handbook recommends that there should also be a brief discussion of the differences Policy for release of data 170.
The first of the United Nations Fundamental Principles of Official Statistics specifies that all users must be accorded access to official statistics on an impartial basis25.
This implies that official 25.
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This implies that official 25.
The first of the “ten commandments” of the Fundamental Principles of Official Statistics states that: “Official statistics provide an indispensable element in the information system of a democratic demographic, social and environmental situation.
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To this end, official statistics that meet the test of practical utility are to be compiled and made available on an impartial basis by official statistical agencies to honour citizens’ entitlement to public information.” The principles can be viewed on the UNECE Website: http://www.unece.org/stats/documents/fund.principles/efund.pdf 51 statistics should be released simultaneously to all users.
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If there are some privileged users who are given prior knowledge of the results before they are released to the general public, this should be explained together with the reasons for making the exception.
Supervision of "outsources" 171.
If the survey is partly or wholly “outsourced” – for example if the field interviews or the data editing has been outsourced to specialised companies or other government departments – details should be given of the control procedures out in place by the survey owners.
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Needs of different users 172. different kinds of users of business tendency survey data.
Users and potential users are: In considering what data to present and how it should be presented, it is helpful to consider the − Respondents to the survey; − Senior business executives; − Parliamentarians; − Senior civil servants responsible for government policy; − Senior personal in banks and financial institutions; − Economists, researchers and analysts in general; − The press and other media.
173.
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173.
The potential users listed above do not all need the same type of information.
In general they can be divided into two categories: those who intend to analyse the statistics in detail and those who simply want to know the main results.
The first category – “analysts” for short – includes economists, researchers, other analysts and the respondents to the survey.
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The second category may be labelled “executives” and consists of senior business executives, politicians, senior civil servants responsible for government policy, senior personal in banks and financial institutions, and the press and other media.
“Executives” probably make up the majority of business tendency survey data users.
Analysts Analysts are people who are have the time and knowledge to study the survey results in detail.
174.
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174.
They may work for statistical institutes, economic research institutes and companies that have their own in-house research department.
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The main requirements for analysts are: − − to have access to the data quickly after publication; to have the figures clearly printed and laid out; 52 − − − to have concise, easily absorbed, methodological information and a telephone number or address to write to with queries and to have access to the more detailed methodological information as described above; to receive historical data for a few years back so they do not have to waste time looking through too many back issues of the survey reports; to have any breaks in the series properly dealt with and noted, with at least one period on both the old and the new base; − and, when revisions are made, to have access to the full run of revised data.
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175.
Survey respondents are a particularly important group among the analysts since they need to be motivated to continue filling in the questionnaires.
In order to provide incentives for enterprises to participate in the surveys, many agencies conducting business surveys provide their regular respondents with special services in order to persuade participants to remain in the sample.
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These services include: − − forecasts for the respondent’s kind of activity based on the survey series alone or in combination with quantitative statistical series; forecasts for the respondent’s potential customers so as to provide information on incoming orders; − disequilibrium analysis on branch level: this approach focus on the micro data from the surveys and has the advantage that both cyclical and structural phenomena can be analysed at the same time.
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Executives Analysts are a minority, though an important one, of all users.
Executives are a much greater 176. potential user group.
Executives do not want to look at the results as such, but want to know what the results mean.
They need their information “pre-digested”.
If the agency conducting the business surveys does not publish the results in a way that appeals to executives, the majority of potential users will never know about the survey.
177.
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177.
The results for executives should be presented in a way that makes it easy for them to absorb the material and encourage them to read it.
They do not have time to read everything and will select only that which seems important.
They will hardly look at statistical tables.
Statistical tables should be included in the presentation as they add credibility to the analysis, but they should play a relatively minor role or be put in an annex.
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The main requirements for a report for executives may by summarised in the following points: − − − the main part of the report should be devoted to text; the main results should be presented in a simple way and give a good overview of the main developments.
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The presentation could focus on the results based on confidence indicators for broad sectors of the economy; it should be brief, two or three pages of text with a few graphs (business survey data are particularly suitable for graphical presentation); 53 − one or two pages of statistical tables attached in annex; − it will need to explain why the survey results can be important guides to economic activity as well as reflecting the views of the business community, and any relevant technical points.
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(This is most important in the early days of the survey).
Dissemination of survey results 178. for presenting business tendency survey data to different users: Three main types of reports, on paper or electronic, form the ideal basis for a publication strategy − press release; − publication for analysts; − reports for respondents.
179. detail in what follows.
The main focus and content of these reports are summarised in Table 2 and explained in more 180.
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The press release should be very short - one or two pages maximum.
Only the main features should be covered in the text.
The press notice will also include methodological information dealing with the number of respondents and coverage of the survey in terms of employment, value added, sales or turnover.
A table summarising key indicators and a graph showing the overall development of one or two main indicator could also be included.
A telephone contact number should be given.
181.
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A telephone contact number should be given.
181.
The report for analysts should contain a complete presentation of the survey results.
This will include an overview of the main results and main features by sectors, regions etc.
The text should be complemented with graphs and tables of key results.
This report should contain detailed results with full data presentation in tables for all variables by sectors, regions etc.
and covering a reasonable period of past data.
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and covering a reasonable period of past data.
These tables could show quarterly or annual averages of data for a longer period of years so that the analysts can easily compare current results with past trends.
The methodological description should be rather extensive and give more technical and detailed 182. information.
The previous section in this Chapter describes the kind of methodological information that is required.
This information will usually be updated once a year.
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The report for respondents to the survey should include the same information as the one 183. prepared for analysts.
In addition, it could contain enterprise-specific information, if such information is available.
For example it could include sectoral and branch forecasts for key sectors of interest to particular enterprises in a particular industry.
Specific forecast for individual enterprises participating in the survey could also be prepared on request.
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54 Table 2. Business survey reports for different users Reports/users Focus of information Content Press release Main features Text, survey characteristics Analysts Overview Main features by sectors Respondents Overview Main features by sectors Enterprise specific information Text, graphs, tables Detailed data Survey characteristics Interpretation of results Methodolgical information Text, graphs, tables Detailed data Special tabulations Survey characteristics Interpretation of results Methodological information 184.
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Production of three different reports for each survey may be beyond the means of many agencies carrying out business tendency surveys.
In this case, the second publication could serve both analysts and survey respondents, with the latter also being offered, on demand, a limited range of tabulations giving information specific to the responding enterprise.
55 56 7.
USE OF RESULTS Interpretation of survey data 185.
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USE OF RESULTS Interpretation of survey data 185.
Interpretation of business tendency survey data is complicated by the subjective nature of the replies and, in particular by the rather vague way in which many questions are phrased.
For example a question such as, Do you consider that the present business situation of your company is: good ( ), satisfactory ( ), bad ( )?
will almost certainly be interpreted in different ways by different respondents.
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Perhaps this could be solved by giving a set of detailed instructions to the respondents, but asking them to refer to these instructions will increase the reporting burden and there is no guarantee that respondent will in fact bother to do so.
Some agencies that carry out business tendency surveys have made special enquiries about how respondents have interpreted the questions.
The paragraphs below describe some of the findings of these studies.26 A “normal" situation 186.
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In assessing order books and inventories, respondents are often asked to compare current levels with a normal situation.
Some respondents may define normality by reference to the companies’ plans or budget projections, but most will refer to average levels over some past period – the last year or two for example.
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This means that the judgement on what is normal will change over time, so that when demand is rising/falling the judgement of what is a normal level of inventories or order books will also rise/fall.
Reference period for questions 187.
Survey questions asking for an appreciation of past and future changes usually specify a previous or future period for comparison.
In the standardised questionnaires in Annex A, “three or four months” is suggested as the reference period.
188.
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188.
In formulating their replies, respondents may refer to other reference periods in the past and in the future.
The appreciation of past changes may for example be answered with reference to the corresponding period of the previous year as a way of excluding seasonal problems, and not with reference to the period specified in the questionnaire.
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Questions concerning future changes on the other hand, may be answered with a shorter time horizon than requested due to problems in estimating the variable too far in the future.
In general this will not cause problems in interpreting the data provided the behaviour of respondents does not change over time.
If the answering practices remain stable over time the balances will still give valid information on changes.
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26 .
Mr Sudir Junankar, formerly responsible for the business tendency survey carried out by the Confederation of British Industries has reported on studies of respondent behaviour at joint OECD-EU seminars.
57 Capacity utilisation Capacity utilisation may be assessed by reference to physical capacity alone – buildings, plant, 189. machinery, vehicles etc.
– and this appears to the commonest practice among respondents.
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Some respondents, however, will take account of other factors such as access to financial capital and, particularly, the supply of labour.
Again this should not affect the validity of the results so far as changes over time are concerned provided that respondent behaviour is stable.
However, survey data on the actual levels of capacity utilisation will represent some unknown mixture of capital and labour utilisation.
Business situation 190.
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Business situation 190.
Assessments of the future business situation – is it expected to improve or worsen in the near future – are widely-used statistics from business tendency surveys so it is important to know what factors respondents have in mind in answering this question.
For business tendency surveys in industry, the most important factor is usually the level of future demand as measured by order books and future production.
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Other factors include expectations about interest rates, movements of exchange rates and political events in the home country and in export markets.
“Bias” in responses “Bias” in the form of over-optimism or over-pessimism by respondents is occasionally observed 191. and must be taken into account in the interpretation of the results.
For example, respondents tend consistently to report that their order books are lower than “normal”.
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This is illustrated in Chart 1 where the average of the balance relating to order books, reported in a Swedish survey, is below zero over several years – clearly an impossible occurrence.
The same chart shows that Swedish respondents tend consistently to report that their stocks are higher than “normal”.
Swedish respondents are systematically pessimistic in answering both questions, but the situation may be different in other countries.
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192. between the balance and its long-term average rather than the gap between the balance and the zero level.
This type of consistent over-optimism or over-pessimism can be corrected by comparing the gap 58 Chart 1.
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Orderbooks and Stocks of Finished Goods e c n a a B l 60 40 20 0 -20 -40 -60 -80 Orders Stocks 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 Source: Business Survey in Industry, Sweden, OECD Main Economic Indicators Comparing business tendency survey data with quantitative statistics 193.
Comparisons of business tendency survey series with conventional quantitative series provide an external consistency test.
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Such comparisons, however, are complicated by the fact that conventional statistical series are expressed in value or volume terms, while business surveys use ordinal scales for most variables – commonly a three point scale.
A crucial issue in this context is whether the balances derived from business tendency surveys refer to trend deviations or to changes in the levels of related quantitative series.
194.
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194.
For questions asking whether present levels of activity are above normal, normal or below normal, the balance series constructed from the replies can be regarded as representing a trend deviation.
For questions asking for a judgement on present or future changes or trends in comparison to past or present periods, the balance series corresponds to changes in levels.
Survey series in level form 195.
The first category of survey questions i.e.
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The first category of survey questions i.e.
an assessment of the present level of activity, is illustrated in Chart 2 by a balance series on stocks of finished goods.
Data are from the Business Conditions Survey carried out by Statistics Canada.
The survey series is compared with the quarterly changes in the corresponding quantitative series on finished goods stocks (top panel)) and the same quantitative series in de-trended form is shown in the bottom panel of the chart.
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The correlation between the balance series and the quarterly changes in the quantitative series has a correlation coefficient (r) of 0.45 while the correlation between the balance series and the de-trended quantitative series has a correlation coefficient of 0.87.
These results show that survey series in level form are more compatible with related quantitative series in de-trended form.
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59 Survey series in tendency form As regards survey questions asking for judgements on present or future changes, a common 196. difficulty is that respondents may not actually use the reference period specified in the questionnaire in answering the question.
As a result, when a quantitative series is converted to monthly or quarterly changes it may not correspond with the reference period actually used by respondents answering questions about present or future changes.
197.
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197.
The importance of the reference period is illustrated in Chart 3 which compares a balance series on new orders with a related quantitative series.
The data are from the Business Tendency Survey carried out by the ifo Institut für Wirtschaftsforschung in Germany.
The survey series on new orders which supposedly measures the direction of change over one month is compared with the changes over one month and over 12 months in a quantitative series on new orders (top and bottom panel in Chart 3).
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The balance series shows a correlation of 0.25 against the one month change in the quantitative new orders series and a correlation of 0.76 compared to the 12 months change in the quantitative series.
These results indicate that the balance series reflects changes over longer periods than the one month as requested in the survey.
Business surveys and cyclical analysis 198.
The statistical series derived from business surveys are particularly suitable for business cycle monitoring and forecasting.
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The cyclical profiles of the series are in many cases easier to detect because they contain no trend and the series reflect assessments and expectations by businessmen, which make them very suitable as leading indicators.
Because of this, business tendency survey series are extensively used in cyclical analysis and in particular for constructing composite indicators that either lead or coincide with the business cycle.
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Composite indicators based on business survey information are included in many reports on business tendency surveys or they are used by analysts to calculate such indicators.
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199. depending on the kind of information requested in the survey: It is convenient to distinguish two types of indicators, which may be labelled internal or external − an indicator is referred to as internal if the survey information refers to judgements or assessments about variables concerning the respondents own company; − an indicator is referred to as external if the survey information refers to matters that are external to the reporting enterprise, such as the general economic situation in the country or in a particular industrial sector.
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60 Volume of finished goods Quarterly changes Chart 2 8 6 4 2 0 -2 -4 -6 1976Q2 1977Q2 1978Q2 1979Q2 1980Q2 1981Q2 1982Q2 1983Q2 1984Q2 1985Q2 1986Q2 1987Q2 1988Q2 1989Q2 1990Q2 Survey data: finished goods stocks Balance 50 40 30 20 10 0 -10 1976Q2 1977Q2 1978Q2 1979Q2 1980Q2 1981Q2 1.2 1.15 1.1 1.05 1 0.95 0.9 0.85 1982Q2 Volum e of finished goods stocks 1983Q2 1984Q2 1985Q2 Detrended 1986Q2 1987Q2 1988Q2 1989Q2 1990Q2 1976M 3 1977M 3 1978M 3 1979M 3 1980M3 1981M 3 1982M 3 1983M3 1984M 3 1985M 3 1986M3 1987M 3 1988M 3 1989M3 1990M 3 61 Volume of new orders Monthly changes 1979M1 1981M1 1983M1 1985M1 1987M1 1989M1 1991M1 1993M1 Survey data: New orders Balance Chart 3 10 8 6 4 2 0 -2 -4 -6 -8 -10 1977M1 30 20 10 0 -10 -20 -30 -40 1977M1 1979M1 1981M1 1983M1 1985M1 1987M1 1989M1 1991M1 1993M1 Volume of new orders Change over same month previous year 15 10 5 0 -5 -10 -15 -20 1977M1 1979M1 1981M1 983M1 1985M1 1987M1 1989M1 1991M1 1993M1 62 200.
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External-type questions are asked in the industry surveys in Australia, New Zealand, France and Italy.
This Handbook, however, recommends that business tendency survey questionnaires should be focussed on questions where the respondent may be expected to have particularly good knowledge – i.e.
questions that are internal rather than external to the respondent’s company.
Only internal-type indicators are discussed in what follows.
Confidence indicators based on a single survey question 201.
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Answers to questions on the general business situation will usually be based on a combination of factors such as the respondents' appraisals about order books and expected new orders, as well as expectations about interest rates, exchange rates and political developments.
Questions of this type are included in many business tendency surveys and are also in the standard questionnaires contained in Annex A.
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Balances from these questions are often referred to as confidence indicators and may be used as leading indicators for predicting short-term economic developments.
Composite confidence indicators 202.
Rather than using answers to a single question, a set of survey variables can be combined into a single composite confidence indicator, which summarises economic agents’ assessments and expectations of the general economic situation.
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The following paragraphs describe composite indicators that have been found useful in several countries by analysts at the European Commission and the OECD.
They are given only as examples since other combinations may perform better for particular countries or over particular time periods.
The balances are averaged by taking means as indicated below.
The questions are taken from the standard questionnaires in Annex A.
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Industry 203. the industry survey relating to: The industrial confidence indicator (ICI) is an average of the balances to the three questions in − Question 2: production, future tendency (PE) − Question 3: total order books (OB) − Question 5: stocks of finished goods (ST) (inverted) − ICI = (PE + OB – ST)/3 Construction 204. the construction survey relating to: The construction confidence indicator (CCI) is an average of the balances to the two questions in − Question 3: total order books (OB) − Question 8: employment, future tendency (EE) − CCI = (OB + EE)/2 63 Retail trade 205. the retail trade survey relating to: The retail trade confidence indicator (RCI) is an average of the balances to the three questions in − Question 1: business situation , present (BS) − Question 2: business situation, future tendency (BF) − Question 6: stocks (inverted) (ST) − RCI = (BS + BF – ST)/3 Services 206. the survey relating to: The confidence indicator for services (SCI) is an average of the balance to the three questions in − Question 4 : employment, future tendency (EE) − Question 6: business situation, present (BS) − Question 7: business situation, future tendency (BF) − SCI= (EE + BS + BF)/3 Cyclical indicator systems Introduction 207.
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Confidence indicators of the kind discussed above are simple to calculate and have proved useful in many countries for monitoring the current economic situation and predicting likely changes in the short- term.
However business tendency survey data can also be combined with quantitative statistics to obtain a more structured cyclical indicator system such as the OECD “System of Composite Leading Indicators”.
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These are published for most OECD Member countries in the monthly publication Main Economic Indicators and in the OECD's half-yearly report on member countries' economies, the Economic Outlook.
208.
Economic development in market economies is characterised by a succession of cycles with alternating phases of expansions and contractions in economic activity.
The cycle may be defined by reference to the absolute level of economic activity.
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A downturn occurs when economic activity falls in absolute terms and an upturn occurs when it begins to increase in absolute terms.
This can be described as the classical definition of a cycle.
The alternative is to define cycles in terms of growth rates.
A downturn occurs when the growth of economic activity falls below the long-term trend and an upturn occurs when the growth rate rises above it.
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Growth cycle contractions/expansions include slowdowns/pick-ups as well as absolute declines/increases in activity, whereas classical cycle contractions/expansions include only absolute declines/increases.
In common with most other indicator systems, the OECD leading indicator system measures growth cycles.
64 209.
Leading, or “cyclical” indicator systems are constructed around a reference series i.e.
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a target series which reflects overall economic activity and whose cyclical development it is intended to predict.
The reference series is used to establish the “timing classification” of statistical indicators into leading, coincident or lagging indicators.
Of the three, there is most interest in leading indicators.
A single variable such as total industrial production27 or GDP is used as reference series in most 210. cyclical indicator systems.
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GDP is the best measure of overall economic activity but changes in industrial production are highly correlated with GDP and are used as the reference series in many indicator systems because it is usually available on a monthly basis and becomes available soon after the reference period.
However, a set of coincident indicators combined into a composite indicator is an alternative way to define a reference series.
211.
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211.
Once a set of cyclical indicators has been selected they are combined them into a single composite indicator.
This is done in order to reduce the risk of false signals, and to provide a cyclical indicator with better forecasting and tracking qualities than any of its individual components.
The reason why a group of indicators combined into a composite indicator should be more reliable over a period of time than any of its individual components is related to the nature and causes of business cycles.
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Each cycle has its unique characteristics as well as features in common with other cycles.
But no single cause explains the cyclical fluctuation over a period of time in overall activity.
The performance of individual indicators will then depend on the causes behind a specific cycle.
Some indicators will perform better in one cycle and less well in a different cycle.
It is therefore necessary to have signals for the many possible causes of cyclical changes.
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Advantages of business tendency survey series for cyclical indicator systems The statistical series derived from business surveys are particularly suitable for business cycle 212. monitoring and forecasting.
In particular, their ability to predict the cycle’s turning point makes them very suitable as leading indicators and the construction of leading indicators is the main objective of a cyclical indicator system.
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213. following criteria28: Statistical series are normally selected for inclusion in a cyclical indicator system if they meet the − Relevance: There must be an economic rational for expecting a leading relationship.
− Cyclical behaviour: The length and consistency of lead is obviously important as is cyclical conformity (general fit), the absence of extra or missing cycles and the smoothness of the series over time.
27.
28 .
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27.
28 .
In almost industrialised countries, industry accounts for much less than half of GDP.
However, many activities within the services sector, which now dominates GDP in most OECD countries, are closely linked with industrial output – transport, trade, business and financial services for example.
Indices of industrial production are closely correlated with movements in GDP in most countries.
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The United States Conference Board uses an expanded set of criteria in selecting data series for its composite indicators.
These are: conformity to the business cycle; consistency of timing; economic significance; statistical adequacy; smoothness; and currency (being up-to-date).
See The Conference Board (ed.
), Business Cycle Indicators Handbook, (p.14), New York 2001.
The three criteria offered here cover these six criteria in shortened form.
65 − Practical considerations.
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65 − Practical considerations.
These include the frequency of publication (at least quarterly and preferably monthly), no large revisions, timeliness of publication, and availability of a long time series with no breaks.
214.
In terms of relevance, the business surveys score well as they include variables which measure the early stages of production (e.g.
new orders, order books), respond rapidly to changes in economic activity (e.g.
stocks) and measure expectations (e.g.
future production tendency).
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| 124 |
future production tendency).
215.
The cyclical profiles of business tendency survey series are usually easy to detect because they contain no trend.
This is a big advantage if the indicator system is designed to detect growth cycles measured in terms of deviations from long term trend.
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As explained earlier, while conventional statistics are expressed in values and volumes, business tendency surveys use ordinal scales for most variables - (usually a three point scale (up/same/down) - and this makes them very sensitive to cyclical developments.
In addition, business tendency survey variables related to judgements and expectations register a change in the cycle earlier than corresponding quantitative statistical series.
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This is because judgements and expectations lead to plans and only after these plans have been implemented will they be picked up by conventional statistical surveys.
Business tendency survey series are also relatively smooth compared with quantitative statistics.
216.
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216.
This is partly explained by the fact that business tendency survey series are less sensitive to disruptive events such as changes in holidays or plant shutdown schedules and unusual weather conditions that will affect quantitative statistics, particularly if they are monthly.
217.
Another advantage is that business tendency survey data are all available from a single source (the agency conducting the business tendency survey) and are all published at the same time.
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This means that a composite indicator that includes several business tendency survey series will always be calculated with a high number of components available and so will be less subject to later revisions.
(Most leading indicators are published as soon as a certain percentage of their components become available and are later revised when the missing components become available.)
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Finally, business tendency surveys collect information on variables which are difficult or 218. impossible to measure by conventional methods such as capacity utilisation, production bottlenecks and the overall economic situation.
These variables are highly relevant in forecasting cyclical turning points.
Types of series used in international indicator systems 219.
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| 70 |
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