from opinions to facts…links between short-term business statistics and business and consumer...

8/9/2019 From opinions to factsLinks between short-term business statistics and business and consumer opinion surveys

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Statistics

in focus

INDUSTRY, TRADE

AND SERVICES

15/2005

Author

Isabelle REMOND-TIEDREZ

ContentsLinks between the evolution of

STS data and data derived

from business and consumer

opinion surveys ........................ 2

Industrial indicators..................4

Construction indicators ...........8

Retail trade indicators.............. 9

From opinions to facts

Links between short-term business statistics and business

and consumer opinion surveys

This publication provides details of a study conducted on monthly short-termbusiness statistics (STS) and business and consumer opinion survey data (asreleased by the European Commission's Directorate-General of Economicand Financial Affairs). Business and consumer opinion surveys are usuallyconducted on the basis of a panel or representative sample of businessleaders from industrial, construction, retail trade and services sectors. Thesesurveys provide results in the form of a balance of opinions, with respect torecently observed developments and future expectations in areas such asproduction, employment, sales and prices. The balance of replies is measured

by the difference between the percentage of positive and negative answers toeach question. Such surveys provide an important indication as to the likelyevolution of business activity (upward, downward, no change), withinformation being collected in a rapid manner. While these surveys do notgenerally provide information on the level of production, sales, prices oremployment, information on expectations can be suitable for monitoring andforecasting business cycles.

The objective of this study was to look for any relationship that may existbetween quantitative data (available from the STS data set) and qualitativedata (collected by business and consumer opinion surveys). As business andconsumer opinion survey data are available within a relatively shorttimeframe, and almost always before quantitative, official statistics, policymakers and strategists are increasingly aware of the potential of this data toanalyse economic perspectives. Indeed, timeliness is an important dimensionwith respect to the quality of statistical information and business andconsumer opinion survey data provides almost real-time data.

The graph below shows, for the EU-25, the relationship between the keymacro-economic indicator of constant price GDP and the economic sentimentindicator (ESI), which is composed of the industrial, construction, retail trade,services and consumer confidence indicators. When looking at quarter onquarter growth rates of GDP and the economic sentiment indicator there wasa correlation coefficient of 0.8. These initial results led on to a sectoralexamination at a more detailed level.

Figure 1: Developments for the economic sentiment indicator and GDP, EU-25

Manuscript completed on: 4.04.2005ISSN 1561-4840Catalogue number: KS-NP-05-015-EN-N

European Communities, 2005

90

100

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120

04-95 10-96 04-98 10-99 04-01 10-02 04-04 -0.75

0.00

0.75

1.50

ESI (index, 100 = long-term average sentiment, left-hand scale)

Constant price GDP (3-month moving average, q/q-1, %, right-hand scale)


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2 Statistics in focus Industry, trade and services 15/2005

Links between the evolution of STS data and data derived frombusiness and consumer opinion surveys

Table 1 lists, by broad economicsector, the indicators used in thisstudy from both short-term businessstatistics (STS) and business andconsumer opinion surveys. Normallyit was possible to select for eachSTS indicator a direct counterpartfrom the business and consumeropinion surveys, or alternatively anindicator where it was thought thereshould be links (such as the indexfor new orders and productionexpectations from the businessopinion survey). However, for someSTS indicators there was no directlycomparable indicator available in the

opinion survey; for these cases STSdata was compared with compositebusiness or consumer confidenceindicators. Time-series were soshort for services that this area wasnot analysed. Hence, the analysispresented focuses on industry,construction and retail trade.

The balance of respondents replyingto opinion survey questions might beused to try to forecast the evolution

of short-term business statistics, ifsome form of relationship can beestablished between business andconsumer opinion survey data andSTS data, such that econometricmodels can be built to predict theevolution of STS.

As such, the rapid release ofbusiness and consumer opinionsurvey data may provide advancewarning of turning points for leadingeconomic indicators that are used totrack business cycles, such as GDP,industrial output or deflated turnoverfor retail trade. The delays inpublishing STS data can range(according to the indicator beingstudied) from just over one monthafter the reference period (outputprices) to around three months afterthe reference period (some labourinput and construction indicators).The most frequently used series

from the STS data set, the index ofindustrial production, is normallypublished between 45 and 50 daysafter the reference period for theEU-25 and euro-zone aggregates. Incontrast, business and consumeropinion survey data are publishedmore rapidly. Indeed, the release ofinformation from this source for EUaggregates and for all of theMember States is normally madethe last working day of the reference

month.

One critique often made of businessand consumer opinion survey datais that respondents do not answerthe questions in relation to the timehorizons requested. For example,when asked about future productionexpectations for the next three-month period, respondents are likelyto place more emphasis on whatthey believe will happen during thenext month. This is perhaps notsurprising, given that respondentsare more likely to have informationfor the immediate period upon whichto base their judgements. Indeed,the measurement of future

expectations could be considered asconjecture, which, to a large degree,is based upon knowledge of thepresent. Such a critique should notnecessarily pose a problem whentrying to use business andconsumer opinion survey data toforecast the future evolution ofshort-term business statistics, aslong as the behaviour ofrespondents remains consistentover time.

Table 1: Possible correspondence between STS indicators and business and consumer opinion survey indicators

STS indicators Business and consumer survey indicators

Industry (excluding construction)

Production index Industrial confidence indicator

Production index Production expectations for the months ahead (over the next three months)

New orders index Production expectations for the months ahead (over the next three months)

New orders index Orders expectations for the months ahead (over the next three months)

Number of persons employed Employment expectations for the months ahead (over the next three months)

Total producer price index Selling price expectations for the months ahead (over the next three months)

Construction

Production index Construction confidence indicator

Number of persons employed Employment expectations for the months ahead (over the next three months)

Price indices for new residential buildings Price expectations for the months ahead (over the next three months)

Retail trade

Turnover/deflated turnover Retail confidence indicator

Turnover/deflated turnover Consumer confidence indicator

Turnover/deflated turnover Expected business situation (sales) (over the next three months)Number of persons employed Expected total employment (over the next three months)


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15/2005 Industry, trade and services Statistics in focus 3

Links between the evolution of STS data and data derived frombusiness and consumer opinion surveys (continued)

A similar critique is that respondentsdo not answer specifically in relationto each indicator, but instead tend tobase their judgements on a widerange of information. Hence,respondents may well considerother economic factors such asinterest rates, movements inexchange rates, the cost of inputs ordomestic and international politicalevents before pronouncing theirexpectations for a range ofindicators. Once more, thesemeasurement difficulties are not inthemselves a problem when lookingat the use of survey information to

predict the future behaviour of STSdata, as long as the relationshipsthat are observed are consistentover time.

A related point is that respondentsto business and consumer opinionsurveys are often found to provideover-pessimistic answers. Indeed,the balance of productionexpectations from the businessopinion survey often falls at a rapid

pace when the STS index ofproduction remains stable (seeFigure 2 below). This too should notpose a problem to analysts, as suchbias can be built into models.

When asked if a variable has goneup (favourable change), remainedstable (unchanged) or fallen(unfavourable change), respondentsinterpret the situation in differentways. For example, when asked fortheir expectations for production,respondents may be faced with whatcould be considered as fairly largeincreases (say 1 % to 5 %difference) and yet still reply that thesituation was unchanged. Anotherrespondent could consider that anincrease of less than 1 % wasimportant enough to warrantreplying that there was a favourable,

positive change.

Some other points also need to beconsidered in terms of potentialmeasurement difficulties. Forexample, analysts need to takeaccount of the different units that areused for the two data sources. Whilebusiness and consumer opinionsurvey data are expressed as abalance of positive to negativeanswers, short-term business

statistics are provided in the form ofan index (which is given in relationto a base year, currently 2000).

Figure 2 shows data for the EU-25aggregate for three series: theindices of industrial production andnew orders (as provided by STS);and the balance of productionexpectations from the business andconsumer opinion survey. The latterof these series has been plottedusing a different scale for the y-axis.

Before continuing the analysis it isimportant to look at the differentnature of the two types of indicator.Each confidence indicator iscalculated as the arithmetic averageof the balances (seasonally

adjusted) of the answers to specificquestions chosen among the full setof questions of each survey. Theseindicators are constrained betweenthe extremes of all respondentsreplying positively or negatively. TheSTS indicators are not constrainedin the same way, having anarbitrarily fixed point as the baseperiod (currently the year2000=100), a theoretical minimumof 0 (as none of the indicators

analysed in this publication can benegative) and no theoreticalmaximum value.

Figure 2: Developments for production expectations and the index of production, industry, EU-25

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01-90 01-91 01-92 01-93 01-94 01-95 01-96 01-97 01-98 01-99 01-00 01-01 01-02 01-03 01-04

75

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105

115

125

Production expectations (balance, left-hand scale) Production index (2000=100, right-hand scale)

New orders (2000=100, right-hand scale)


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Industrial indicators

Identification of turning points

(peaks and trough)

Using month on month growth ratesfor the index of production andpercentage point differences for thebalance of production expectations,similarities were found in thedevelopment of both series. Theseries were examined to determinewhether or not it was possible toobserve turning points in STS seriesand to match these with turningpoints in business opinion surveys.Figures 3a and 3b provide anexample, showing the original seriesand six-month moving averages that

were used to help delimit theeconomic phases (time spansbetween peaks and troughs), shownas vertical lines in the graphs.During the period 1996-2004,turning points for the balance ofproduction expectations tended tolead the production index by 0 to 3months. It is important to note that

this delay in the observation ofturning points for the index ofproduction may result fromdifferences in the seasonaladjustment methods that areemployed for the two indicators(TRAMO/SEATS is used for theindex of production, while DAINTIESis used for the business andconsumer survey data).

Growth rates for industrial

production and new orders follow

closely the evolution of

production expectations

Figure 2 shows the relationship

between the index of production andthe balance of productionexpectations. As such, theinvestigation of possible linksbetween the series moved on tostudy other possible relationships, inparticular by looking at the linkbetween growth rates for theindustrial production index and the

balance of production expectations.Figure 4 shows that there was acloser relation between productionexpectations and the annual growthrates of the production index, asmeasured by the change betweenone month and the same month ofthe previous year (t/t-12).

This suggests that respondents tothe business survey might not make judgements of future expectationscompared with the present, butinstead compared with pastperformance over a longer period.These initial observations wereanalysed across the Member States

and the results confirmed that inmost cases there was a close linkbetween production expectationsand growth rates for the index ofproduction based upon acomparison with the same month ofthe previous year (t/t-12). Figure 5displays this relationship, with datafor the four largest Member States.

Figure 3b: Developments for the balance of production expectations, industry, EU-25

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01-96 01-97 01-98 01-99 01-00 01-01 01-02 01-03 01-04

-6-4-202468

Production expectations (balance, left-hand scale) Index of production (t/t-12, %, right-hand scale)

-1.5

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01-96 01-97 01-98 01-99 01-00 01-01 01-02 01-03 01-04

Month on month growth rate Moving average

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-3.0

0.0

3.0

6.0

01-96 01-97 01-98 01-99 01-00 01-01 01-02 01-03 01-04Change in production expectations (percentage points) Moving average

Figure 3a: Developments for the index of production, industry, EU-25

Figure 4: Developments for production expectations and growth rates for the index of production, total industry, EU-25


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Industrial indicators (continued)

The United KingdomFrance

Figure 5: Developments for production expectations and growth rates for the index of production, total industry,the four largest Member States

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01-95 01-97 01-99 01-01 01-03

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Prod. expectations (balance, left-hand scale)

Index of production (t/t-12, %, right-hand scale)

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Germany

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10

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Assessment of order-book levels (balance, left-hand scale)Production expectations (balance, left-hand scale)

Index of new orders (3-month moving average, t/t-12, %, right-hand scale)Figure 6: Developments for the assessment of order-book levels and growth rates for the index of new orders,

industry, euro-zone

Italy


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Subsequently, an analysis wasmade across the Member States tofind the peak-correlation coefficientbetween business opinion surveydata and growth rates for the indexof production. Growth rates for theindex of production were calculatedfor 24 different periods ranging fromt+6/t to t/t-18. Table 2 shows theresults which confirm that thehighest correlation pairings wereusually obtained for growth ratescalculated upon the basis of acomparison between t/t-11 and t/t-16. Cyprus (t/t-1) and Estonia (t/t-7)were the only exceptions to reportpeak-correlation coefficients for

growth rates that were based uponmore recent periods. For the EU-25,the highest peak-correlationcoefficient was obtained betweenproduction expectations and growthrates of the production index basedupon a comparison with 11 monthsbeforehand (t/t-11), which stood at0.91.

Having analysed the variations incorrelation coefficients according todifferent growth rates for the indices,the next step involved testingvarious leads and lags to see ifthese could be used to increase thecorrelation coefficients.

As a first step, leads and lags of thegrowth rates for t/t-1 and t/t-12 wereanalysed. The introduction of leadsand lags did little to improve thecorrelations for the t/t-1 growthrates, where the highest correlationwith production expectations wasrecorded with a lag of 2, 3 or 4months for the growth rates of the

production index, with coefficients of0.31. For the t/t-12 growth rates, thehighest coefficient was recordedwith a lead of 1 month for the growthrates, meaning that, in effect, therewere 11 months between the tworeference periods. The highestcorrelation coefficient, using thismeasure, was 0.91 for the EU-25.

Turning to the indices themselves,the correlation coefficient betweenthe index of production for totalindustry and productionexpectations was 0.30 for the EU-25, while the introduction of a fourmonth lag for the index of productionresulted in the highest correlation-pairing of 0.38. A similar analysiswas carried out for new orders forthe euro-zone (where a longer time-series existed) and this showed thatthe index of new orders had acorrelation coefficient of 0.14 withproduction expectations. Theintroduction of a three or four monthlead for new orders resulted in this

coefficient rising to 0.20. As such,lagging or leading indices resulted inonly modest improvements in termsof the results achieved, andcorrelation coefficients remainedwell below those recorded betweenthe t/t-12 growth rates for indices ofproduction and productionexpectations.

The results of analysis carried outon new orders confirm to a large

degree the findings for industrialproduction, insofar as highercorrelation coefficients wererecorded between business opinionsurvey data and growth rates for theindex of new orders based upon acomparison with the same month ofa year before. The correlationcoefficient for the EU-25 was 0.73between production expectationsand t/t-12 growth rates for neworders, and 0.78 for the euro-zone.

In relation to the assessment ofexport orders from the businessopinion survey, t/t-12 growth ratesfor the index of new orders to exportmarkets recorded a correlationcoefficient of 0.86 for the EU-25,while the coefficient between theassessment of total new orders fromthe business opinion survey andt/t-12 growth rates for the index oftotal new orders, again for theEU-25, was 0.83.

Table 2: Peak-correlation coefficients between production expectations and aselection of growth rates for the index of production, industry

Highest correlation Period

EU-25 0.91 t-11Euro-zone 0.88 t-11; t-13; t-14; t-15BE 0.55 t-14CZ 0.48 t-11DK 0.47 t-15; t-16DE 0.85 t-15EE 0.62 t-7EL 0.43 t-11ES 0.68 t-13FR 0.75 t-13; t-15: t-17IE 0.54 t-11; t-14IT 0.75 t-11; t-14CY 0.18 t-1LV 0.67 t-17

LT 0.78 t-16LU 0.43 t-16HU 0.75 t-17NL 0.54 t-13; t-14; t-17AT 0.72 t-13PL 0.77 t-17PT 0.31 t-16; t-17SI 0.73 t-15SK 0.61 t-13FI 0.65 t-14SE 0.59 t-11; t-15UK 0.53 t-11


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Growth rates for industrial output

prices follow the evolution of

price expectations

The next step involved analysing theinitial findings to see if similar resultscould be obtained for other indices.The correlation coefficient for theEU-25 between the gross index ofdomestic output prices andexpected prices from the businessopinion survey was found to benegative (-0.25, 1991-2004).

To explore further, growth rates fort/t-1 and t/t-12 were calculated forthe index of domestic output prices

and correlation coefficients werecomputed with respect to thebalance of expected prices. Thehighest correlation for the EU-25(0.85) was again recorded betweenthe business opinion survey dataand growth rates of indices basedupon a comparison with the samemonth of the previous year - Figure 7shows the close relationshipbetween the two series. The resultsfor the EU-25 were confirmed when

looking at the data by MemberState. For the period 1991 onwards,correlation coefficients of 0.77 and0.79 were recorded for Germanyand Italy (the two countries with thelongest time-series available).

while growth rates for

industrial employment lag

employment expectations

For industrial employment thenature of the results was largelyrepeated. Figure 8 shows a time-series for employment expectationsfrom the business opinion surveyand growth rates for the index ofemployment for total industry basedupon a comparison with the samemonth of a year before (t/t-12). Notethat the graph is presented for theeuro-zone, as a longer time-serieswas available for this aggregate.

One feature of Figure 8 is that theseries for employment expectationsappears to lead that for the growthrates of the employment index. Anexplanation of this pattern could bethat the question for employmentclearly asks respondents to assessthe future development ofemployment over the next threemonths and hence for a given periodrespondents are providinginformation on the likely situation in

three months time, as witnessed inthe index of employment whenofficial STS data is released.

Another possible explanation is thatemployment markets are inflexible.

Hence, if economic circumstanceschange for the better (or worse) it islikely that a relatively long period oftime will pass before employers feelcompounded to react or are able toreact to the changes that areobserved. Given this inflexibility,employers' decisions on whether tohire or fire are often postponed andare only acted upon once economicdevelopments become so clear thatthey eventually have to take adecision. Hence, despite the factthat business opinion surveys mayindicate a significant change inemployment expectations, it may beseveral months before employers

follow their feelings, once furtherconfirmation of the economicsituation has been provided. As aresult, growth rates for the index ofemployment could lag employmentexpectations by several months.

Tests on peak-correlation coefficientpairings showed that the highestcorrelation was obtained whenemployment expectations had athree month lead on the growth

rates for the index of employment.When this was taken into account,the correlation coefficient betweenthe two series for the euro-zone (forwhich a longer time-series wasavailable) rose to 0.95.

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Employment expectations (balance, left-hand scale) Index of employment (t/t-12, %, right-hand scale)

Figure 8: Developments for employment expectations and growth rates for the index of employment, industry, euro-zone

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Selling price expectations (balance, left-hand scale) Growth rate: index of output prices (t/t-12, %, right-hand scale)

Figure 7:Developments for price expectations and growth rates for the index of output prices, industry, EU-25


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Construction indicators

Link between STS indicators and

construction confidence most

evident for indices

Output in the construction sector is,in part, driven by household demandand interest rates. The decision toundertake civil engineering projectscan also lead to a significantincrease in demand (the timing ofwhich may be unrelated to economiccycles). The business cycle for theconstruction sector is only indirectlyrelated to foreign competition andexternal shocks.

The highest correlation coefficients

for the construction sector werereported for the indices ofproduction and employment, whencompared with the constructionconfidence index and employmentexpectations indicator. The STSdata for prices and new orderswithin the construction sector did not

show signs of a relationship with thedata from the business opinionsurvey.

Contrary to the results obtained forthe industrial economy, the highestcorrelation coefficients between theindex of production and theconstruction confidence indicatorwere obtained when analysing theindices from STS and not rates ofchange. Construction confidence isa composite indicator: the arithmeticmean of the balance of replies toquestions on construction orderbooks and employmentexpectations. Figure 9 shows the

EU-25 series for the index ofproduction for construction and theconstruction confidence indicator,where a correlation coefficient of0.67 was recorded. A correlationcoefficient of 0.66 was recorded forFrance between 1995 and 2004,while that for Germany was 0.14.

However, for the period 1998-2004,the coefficient for Germany rose to0.72.

Over the period 1995-2004, EU-25correlation coefficients were higherwhen comparing employmentexpectations (see Figure 10) withthe indices of employment (0.75)than they were when comparing withgrowth rates from the same monthof a year before (0.59). Across thelarger Member States, the resultswere less conclusive, as the highestcorrelation coefficients betweenemployment expectations and theindex of employment were recorded

for France and Spain (0.55 and0.43), although, during the period1998-2004 the German correlationcoefficient was 0.72.

Figure 10: Developments for employment expectations and the index of employment for construction, EU-25

Figure 9: Developments for construction confidence and the index of production for construction, EU-25

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01-95 01-96 01-97 01-98 01-99 01-00 01-01 01-02 01-03 01-04

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Construction confidence indicator (balance, left-hand scale) Production index (2000=100, right-hand scale)

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Employment expectations (balance, left-hand scale) Employment index (2000=100, right-hand scale)


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Retail trade indicators

Consumers (as opposed to

businesses) appear more adept at

foreseeing the evolution of retail

trade turnover

The evolution of deflated turnover inthe retail trade sector displays a lesscyclical pattern than many of theother indicators presented so far.This may well be due to sustainedhousehold consumption in many ofthe Member States during recentyears. This may be expected tosome degree, as demand for somenon-durable items remains fairlyconstant over time, no matter whatthe economic conditions (basic

foodstuffs, for example). However,the increase in consumer debt in anumber of Member States alsosuggests that even in times ofeconomic downturn or stagnationmany consumers continued tospend.

There are also likely to be otherfactors that drive the evolution ofretail sales so that they do notnecessarily follow the general

economic cycle. For example, coldweather could lead to an increase inthe sale of heating products.

For the retail trade sector, the mainindicators used for the investigationwere turnover and employment. Aswith the results for the industrialsector, the highest correlationcoefficients were obtained whencomparing the results of business

and consumer opinion surveys withgrowth rates based upon STSindices, as calculated on the basisof a comparison with the samemonth of a year before.

The highest correlation coefficientfor the EU-25 (0.64) was recordedwhen comparing the t/t-12 growthrates for deflated turnover withconsumer confidence. Figure 11shows the relationship betweenthese two series during the period1996-2004. For the largest MemberStates, similar results to thoseobtained for the EU-25 aggregatewere recorded. For example, the

correlation coefficient for Germanywas 0.52, closely followed byFrance (0.51).

Looking at the other series from thebusiness and consumer opinionsurveys, there was little evidence ofa relationship between the index ofdeflated turnover from STS andeither the business confidenceindicator for retail trade or businessexpectations for future sales in retail

trade. The EU-25 businessconfidence indicator for retail tradehad a correlation coefficient of 0.25when compared with growth ratesfor the index of deflated turnover(t/t-12), while the correlationcoefficient between expected salesand t/t-12 growth rates for the indexof deflated turnover was 0.16.Correlation coefficients betweenexpected sales or business

confidence and the indices ofdeflated turnover themselves (asopposed to the growth rates) wereeven lower, as were correlationswith the turnover indices (non-deflated).

At a country level, the resultsreported for the EU-25 were notconsistently reproduced. Forexample, both business confidenceand expected sales were morecorrelated with the t/t-12 growthrates for deflated turnover than theywere with consumer confidence inSpain and the United Kingdomduring the period 1999-2004.

When comparing the developmentof employment expectations and theindex of employment (for indices,t/t-1 and t/t-12 growth rates) therewas little evidence of any linkbetween these series for the EU-25during the period 1996-2004. Thiswas confirmed by the fact that thehighest correlation coefficient (0.08)was recorded between employmentexpectations and t/t-12 growth rates

for the index of employment. Of thelargest EU Member States, onlyGermany and Spain had lengthytime-series available and theirresults confirmed the patternsobserved for the EU-25, namely,that no clear relationship could bedrawn.

Figure 11: Developments for consumer confidence and growth rates for the index of deflated turnover,retail trade, EU-25

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Consumer confidence indicator (balance, left-hand scale)Turnover index (3-month moving average, t/t-12, %, right-hand scale)Deflated turnover index (3-month moving average, t/t-12, %, right-hand scale)


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ESSENTIAL INFORMATION METHODOLOGICAL NOTES

The data used in this publicationwere extracted from Commissiondatabases during December 2004.

STS INDICATORS

The legal basis for the collection ofshort-term business statistics (STS)is Council Regulation No 1165/98 of19 May 1998.

Wherever possible seasonallyadjusted series were used toperform the analyses. The mainexception to this rule was for theoutput price index, where only a

gross series is available.The production index is animportant business cycle indicatorwhich shows the monthly activity ofthe industrial sector, one of the mostvolatile components of the economy.As specified in the STS Regulation,and in line with traditional practice inbusiness statistics, the productionindex should show the evolution ofvalue added at factor cost, atconstant prices. Value added at

factor cost can be calculated fromturnover (excluding VAT), pluscapitalised production, plus otheroperating income, plus or minus thechanges in stocks, minus thepurchases of goods and services,minus other taxes on products andtaxes linked to production.

The new orders index is defined asthe value of the contract linking aproducer and a third party with

respect to future deliveries by theproducer of the goods and services.New orders include all duties andtaxes on the goods or services thatwill be invoiced by the unit with theexception of the VAT and othersimilar deductible taxes directlylinked to turnover. All other charges(transport, packaging, etc.) that arepassed on to the customer are alsoincluded. Orders that are passed onto sub-contractors are included.

The output price index (orproducer price index) showsmonthly price changes in theindustrial sector, which can be an

indicator of inflationary pressurebefore it reaches the consumer. Allprice-determining characteristics ofthe products should be taken intoaccount, including quantity of unitssold, transport provided, rebates,service conditions, guaranteeconditions and destination.

The index of the number ofpersons employed monitors thedevelopment of total employment.

This indicator may be approximatedby the number of employees. Thenumber of persons employed isdefined as the total number ofpersons working in an observationunit (inclusive of working proprietors,partners working regularly in the unitand unpaid family workers), as wellas persons who work outside theunit who belong to it and are paid byit (e.g. sales representatives,delivery personnel, repair andmaintenance teams).

The objective of the volume ofsales index is to show the quantityof goods sold in the retail tradesector. It is an indicator for finaldomestic demand and providesinformation about consumerconfidence. The volume of salesrepresents the value of turnover inconstant prices and as such it is aquantity index. It can be calculatedas turnover at current prices,

deflated by the deflator of sales, oras a quantity index derived directlyfrom the quantity of goods sold.Turnover comprises the totalsinvoiced by the observation unitduring the reference period. Itincludes all duties and taxes on thegoods or services invoiced by theunit with the exception of the VATinvoiced by the unit vis--vis itscustomer and other similardeductible taxes directly linked toturnover.

For more information onmethodology for STS indicators, see'Methodology of short-term businessstatistics', available at:

http://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.html

BUSINESS AND CONSUMER

CONFIDENCE INDICATORS

Business and consumer opinionsurveys are compiled in accordancewith the framework of the JointHarmonised EU Programme. Theframework provides for thecollection of information in the

following fields: the industrial, retailtrade, building and services sectors,as well as information pertaining toinvestment decisions and consumerconfidence.

Currently, more than 110 000 unitsand almost 33 000 consumers aresurveyed every month across theEU-25. The sample for industryincludes more than 35 000 units thatare surveyed every month. Thesample size for services is more

than 28 000 units, while for retailtrade and construction sample sizesconsist of more than 23 000 and20 000 units respectively.

The main users of survey results arethe respondents themselves, asthey may obtain detailed surveyresults broken down by sector ofactivity. These results providevaluable information on businessconditions both within the activities

of the enterprise itself and withinother areas of the economy (such asupstream and downstreammarkets). Economic and financialanalysts have also becomeimportant users of this information,as the data are available rapidly andhence some of the series mayprovide advance warning ofchanges in the direction of economicactivity.
http://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.htmlhttp://forum.europa.eu.int/irc/dsis/bmethods/info/data/new/embs/embs_en.html


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ESSENTIAL INFORMATION METHODOLOGICAL NOTES ( continued)

Data cover all 25 Member States ofthe European Union as well as twoof the candidate countries (Bulgariaand Romania). The figures from the

survey are presented as seasonallyadjusted balances, which aredefined as the difference (inpercentage point terms) between allpositive and negative answers. Thedata are only seasonally adjustedonce at least 36 monthly or 12quarterly observations are available,and so for some of the new MemberStates the data are still provided ingross form.

Business and consumer opinionsurveys are qualitative economicsurveys that are intended for short-term economic analysis. Whileconventional econometric models ofthe economy perform reasonablywell when the economy is within aperiod of stable growth, theirperformance is not so good forsignalling changes of direction orturning points in economic cycles.

The range of information covered by

business and consumer opinionsurveys often goes beyond thetraditional variables that arecollected for conventionalquantitative analysis through thedevelopment of official statistics.Qualitative information may becollected for variables that aredifficult or impossible to measure byconventional methods, for example,capacity utilisation, productionbottlenecks, plans and expectations

for the immediate future andmanagers' views of the overalleconomic situation.

There is an increasing interest in theuse of business and consumeropinion surveys for predictingturning points and these series are

often viewed as an essential tool forcomplementing quantitativestatistical surveys. Business andconsumer opinion surveys provide arapid means of compiling simplestatistics with results becomingavailable within a short period oftime, and almost always beforeofficial statistics.

The indicator of productionexpectations for industry is the

difference (in percentage points oftotal answers) between positive andnegative options for the question'How do you expect your productionto develop over the next threemonths?'

The indicator on the assessment oforder books for industry is thedifference (in percentage points oftotal answers) between positive andnegative options for the question 'Doyou consider your current overall

order books to be? (above normal,normal for the season, belownormal).'

The indicator ofprice expectationsfor industry is the difference (inpercentage points of total answers)between positive and negativeoptions for the question 'How do youexpect your selling prices to changeover the next 3 months?'

The indicator of employmentexpectations for industry is thedifference (in percentage points oftotal answers) between positive and

negative options for the question'How do you expect your firms totalemployment to change over the next3 months?'

The construction confidenceindicator is the arithmetic averageof the balances (in percentage pointterms) of the answers to thequestions on the order book andemployment expectations within theconstruction sector; balances are

seasonally adjusted.The consumer confidenceindicator is the arithmetic averageof the balances (in percentage pointterms) of the answers to thequestions on the financial situationof households, the generaleconomic situation, unemploymentexpectations (with inverted sign) andsavings. All of these points aresurveyed in relation to expectationsover the next 12 month period;

balances are seasonally adjusted.

More information can be obtainedfrom the DG ECFIN web-site, at thefollowing address:http://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htm
http://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htmhttp://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htmhttp://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htmhttp://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htmhttp://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htmhttp://europa.eu.int/comm/economy_finance/indicators/businessandconsumersurveys_en.htm


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Further information: Reference publications

Title Quarterly panorama of European business statistics

Subscription number VPA000 Price EUR100

Databases

EUROSTAT Website/Industry, trade and services/Industry, trade and services - horizontal view/Short-termBusiness Statistics - Monthly and Quarterly (Industry, Construction, Retail Trade and Other Services)

EUROSTAT Website/General and regional statistics/European and national short term indicators/Business andconsumer surveys(Source: DG ECFIN)

Journalists can contact the media support service:

Bech Building Office A4/017 L-2920 Luxembourg Tel. (352) 4301 33408 Fax (352) 4301 35349

E-mail: [email protected]

European Statistical Data Support:

Eurostat set up with the members of the European statistical system a network of support centres, which will exist innearly all Member States as well as in some EFTA countries.

Their mission is to provide help and guidance to Internet users of European statistical data.

The complete details concerning this support network can be found on our Internet site: www.europa.eu.int/comm/eurostat/

A list of worldwide sales outlets is available at the:Office for Official Publications of the European Communities.2, rue Mercier L-2985 LuxembourgURL: http://publications.eu.intE-mail: [email protected]

BELGIEN/BELGIQUE/BELGI - DANMARK - DEUTSCHLAND - EESTI ELLDA - ESPAA - FRANCE - IRELAND -ITALIA - KYPROS/KIBRIS LUXEMBOURG - MAGYARORSZG MALTA - NEDERLAND - STERREICH - POLSKA -PORTUGAL - SLOVENIJA - SLOVENSKO - SUOMI/FINLAND - SVERIGE - UNITED KINGDOM - BALGARIJA -HRVATSKA - SLAND NORGE - SCHWEIZ/SUISSE/SVIZZERA - AUSTRALIA - BRASIL - CANADA - EGYPT -MALAYSIA - MXICO - SOUTH KOREA - SRI LANKA - T'AI-WAN - UNITED STATES OF AMERICA

ORIGINAL TEXT: English
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