National accounts

National Accounts Institute

Benchmark revision 2019 Overview of the main methodological changes

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Table of contents

1 Introduction 5

2 Revisions – production approach 62.1 Company administrators 62.2 Dwelling services 7

2.2.1 Production of housing services by households 72.2.2 Intermediate consumption relating to housing services 8

2.3 Insurance and pension funds 92.3.1 Life insurance 92.3.2 Pension funds 9

2.4 Health and welfare 102.4.1 Hospital services 102.4.2 Child minders 102.4.3 Adapted work enterprises 10

2.5 Research and development 112.6 "Market/non-market" test 122.7 Production of electricity by households 142.8 Financial intermediation services indirectly measured (FISIM) 152.9 Taxes less subsidies on production and imports 16

3 Revisions – expenditure approach 173.1 Imports and exports by non-residents 173.2 Gross fixed capital formation 193.3 Imports and exports 20

3.3.1 Imports and exports by non-residents 203.3.2 CIF/FOB adjustment 213.3.3 Other changes 22

4 Revisions – deflators 23

5 Revisions – property income and other transfers 245.1 Interest income 245.2 Dividends 255.3 Reinvested earnings from foreign direct investment 265.4 Collective investment fund income 285.5 Transfers for cross-border workers 295.6 Cross-border pension funds 30

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6 Revisions – labour market 316.1 Employment 316.2 Compensation of employees 326.3 Volume of work 33

7 Revisions – general government 347.1 Changes with an impact on the balance and/or debt 34

7.1.1 Green certificates 347.1.2 Social Maribel – local government 407.1.3 Health care expenditure by NIHDI 40

7.2 Changes having an impact on the level of revenue and expenditure 41(but not on the balance)

7.2.1 VAT on electronic services (2015-2018 transition period) 417.2.2 Social Maribel 417.2.3 Consolidation of Infrabel 427.2.4 Pension fund-related transactions 427.2.5 Sales of trees by local governments 42

7.3 Changes having an impact on the breakdown of revenue and expenditure (but not on their level) 43

7.3.1 VAT due but not recoverable as a result of bankruptcies 437.3.2 Payroll tax due but not recoverable as a result of bankruptcies 437.3.3 Social contributions due but not recoverable as a result of bankruptcies 447.3.4 Other changes 44

8 Quantified impact of the revisions 458.1 Reference year 2015 468.2 Long series 1995-2017 49

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Benchmark revision 2019

Overview of the main methodological changes

1. Introduction

In line with the Eurostat recommendations, Belgium – like most European countries – conducted a benchmark revision of its national accounts in 2019. In principle, such a revision takes place every five years and is among the normal procedures for improving statistics.

Benchmark revisions are more important than routine revisions. They enable new data sources and methods to be incorporated into the compilation estimates used for establishing the national accounts. Their inclusion generally helps maintain or even improve the quality of the statistics produced. Benchmark revisions also provide an opportunity to enhance the relevance of statistics by including new economic phenomena. For instance, this latest revision has improved the measurement of internet sales, introduced an estimate of electricity production by households, and developed an accounting method for recording green certificates. Moreover, another guiding principle of this revision has been to improve consistency between the national accounts and other macroeconomic statistics, notably balance of payments and financial accounts data.

As far as possible and in order to ensure the temporal uniformity of the series, revisions need to be made from 1995 onwards1. In cases where it proved impossible to go right back to 1995 owing to the lack of relevant data, the year 2009 was chosen as the base year from which the revisions were made.

The changes to sources and methods obviously had an impact on the key national accounts aggregate – gross domestic product (GDP) – but they also affected many other economic indicators calculated on the basis of the accounts.

The main revision points are documented in detail below. Chapter 2 gives details of the revisions which affect the valuation of GDP according to the production approach. Chapter 3 discusses the revisions according to the expenditure approach. It should be noted that GDP may also have been influenced by the revisions concerning the compilation of the general government accounts, described in chapter 7. In that chapter a distinction is made between revisions which affect the deficit and the debt and those which have no impact on them.

The revisions mentioned in chapters 2 and 3 are made at current prices. The estimate of real GDP is also affected by revisions to the deflators, which are mentioned in chapter 4. Chapter 5 focuses on revisions which affect the measurement of gross national income (GNI), while chapter 6 deals with labour market statistics. Finally, the quantified impact of the revisions is set out in detail at the end of this publication (chapter 8).

1 For more information on the national accounts revision policy, see https://www.nbb.be/doc/dq/e_method/methodcn_en_201709.pdf

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2. Revisions – production approach

2.1 Company administrators

Impact on GDP 1995 2005 2015 2016 2017EUR millions +802 +1 310 +1 792 +1 998 +2 044% of GDP +0.4 % +0.4 % +0.4 % +0.5 % +0.5 %

In the national accounts, non-salaried company administrators are regarded as self-employed persons classified under NACE code 70.2 (management consultancy activities) in the household sector. A director’s remuneration received from the business is regarded as the value of the director’s production. The expenses incurred in producing that output are regarded as intermediate consumption.

Administrators’ production is estimated primarily on the basis of the income declared for personal income tax under “company director’s remuneration”. In the course of the revision, the population of administrators used in the national accounts was redefined in order to improve consistency with the basic data on personal income tax. A supplementary estimate was also made in order to include the remuneration and expenses of administrators of associations or companies without legal personality and/or those not subject to corporation tax.

Apart from the revision of the population of administrators, the method of estimating production based on personal income tax was also modified. More specifically, the personal income tax headings covering pay components were eliminated from the current estimation formula in order to prevent any double counting with the wage bill. Furthermore, the personal income tax headings covering benefits in kind were added since the ESA 2010 recommends taking account of both benefits in kind and cash benefits. In the national accounts these benefits in kind are assessed at their real value according to a “price x quantity” approach. The price is based on the average value of similar expenditure by a Belgian household in Belgium for each benefit in kind. The quantity of benefits in kind was inferred from information in the tax database 281.20, used as the source of information for the heading “company director’s remuneration” under personal income tax.

In order to assess the intermediate consumption of administrators, a supplementary estimate was made in addition to professional expenses for declarants who do not record their actual expenses under personal income tax. This is a flat rate estimate based on the declared turnover.

To ensure that benefits in kind are treated consistently according to the production and expenditure approaches, final consumption was calculated for all types of benefits granted to company administrators. The intermediate consumption of non-financial corporations was also increased to take account of benefits in kind which are not included in the company accounts.

As well as taking account of final consumption relating to all types of benefits, the new method includes an estimate of the export of administrators’ services based on personal income tax data. The export of such services is not in fact recorded according to the ordinary methods of estimating imports and exports of services1.

The changes mentioned above have a significant positive impact on the value added of the household sector during the period 1995-2017. The revisions to household consumption and exports of services have a more modest upward impact.

1 The ordinary methods of estimating imports and exports of services are based on the data from surveys sent out to entities subject to VAT. A director (a natural person) is not subject to VAT so that administrators’ exports will not be included under the normal procedures.

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2.2 Dwelling services

Impact on GDP 1995 2005 2015 2016 2017EUR millions -1 461 -1 909 +799 +760 +1 354% of GDP -0.7 % -0.6 % +0.2 % +0.2 % +0.3 %

2.2.1 Production of housing services by households

DIn the national accounts, the production of housing services comprises not only services produced by rented dwellings but also those provided by owner-occupied dwellings. Production is measured by the value of the rents. It is recorded as the provision of services by the owner and as consumption by the tenant (final consumption in the case of a household and intermediate consumption in the case of a business). If a household owns the housing which it occupies, the national accounts record both the production of housing services and final consumption for that household.

The production of housing services is estimated according to a "price x quantity" approach, i.e. a method which combines an estimate of the quantity of housing with actual rents. The “quantity” component is based on observations of the housing stock derived from the ten-year censuses. The “price” component is based on observed monthly rents. As the rental data are generally derived from surveys, the estimate is based on an extrapolation method which applies the sample of observed rents in general to all housing with similar characteristics.

During the 2019 benchmark revision, the "price x quantity" method was adapted in numerous respects. The main change concerns the introduction of the results of the SILC ("Statistics on Income and Living Conditions") survey, available from 2004 onwards. This survey, conducted under the auspices of the EU, includes a section on housing and a question on the monthly rents that tenant households pay for their housing. The introduction of the results of this survey was accompanied by a new method of stratification conforming to the Eurostat recommendations. This new method of stratifying the housing stock makes it possible to modulate rents according to both the municipality where the housing is located and the type of housing. As regards housing locations, the total of 589 municipalities was divided into six strata, taking account of two criteria: property prices in the municipality and population density. As regards the type of housing, five strata were defined: detached house, semi-detached or terraced house, small apartment, medium-sized apartment and large apartment. Altogether, the method is therefore based on the identification of 30 housing strata.

The same stratification was used to deal with the data on the number of housing units derived from the five-yearly censuses, which therefore form the base years. Between two censuses and after the latest available census the number of housing units per stratum has to be interpolated or extrapolated. For that purpose, data from the land registry were preferred to the data on housing starts which had previously been used. Another adjustment concerning the housing stock involves the elimination of rented housing owned by companies or NPIs. In that case, the production of housing services is estimated elsewhere and it is necessary to avoid double counting.

Other changes were made. The production of housing services relating to second homes was revised: both the number of second homes in Belgium and the associated rents underwent revision. A reasonable assumption concerning the rate of occupation of this type of property was also introduced.

For the first time, an estimate was formulated for rents relating to garages on separate land parcels. It is based on the land registry data available from 2005 onwards combined with an assumption concerning monthly garage rents.

For the purposes of the national accounts, figures were retropolated on the basis of historical series in order to present consistent time series from 1995 onwards.

The changes made led to a downward revision of the level of production of housing services at the start of the period and an upward revision at the end of the period. This is because the SILC data now being used result in downward revision of the value of rents at the start of the period, but also indicate stronger average annual rent

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increases. Owing to this steeper rise, the initial negative revision fades away and becomes positive from 2012 onwards.

2.2.2 Intermediate consumption relating to housing services

In order to estimate intermediate consumption relating to housing services produced by households, the relevant headings in the 2012 Household Budget Survey (HBS) are first identified. Expenditure typically borne by owners is allocated to intermediate consumption, while that specific to tenants is recorded under final consumption, and expenditure which cannot be attributed solely to either party is divided between the two aggregates. Average household expenditure is then treated in the same way as the other HBS headings in the national accounts (i.e. multiplied by the number of households and adjusted to take account of collective households and expenditure of residents incurred abroad).

An adjustment used to be made to the figure thus obtained in order to eliminate intermediate consumption relating to social housing, which has to be imputed to the owners – the social housing associations – and not to households. In the benchmark revision, this adjustment was abolished because it was unnecessary in view of the method described above, which automatically excluded any expenditure by social housing companies from the household account.

Similarly, the services produced by branch 64922 "Provision of mortgage credit" were hitherto considered as being entirely consumed by households; however, the fees relating to mortgage loans granted to individuals should not be classed as final consumption but as intermediate consumption because they are consumed by the owners. Under the current revision, these fees are all allocated to intermediate consumption.

These two adjustments both imply an upward revision to intermediate consumption relating to housing services produced by households.

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2.3 Insurance and pension funds

Impact on GDP 1995 2005 2015 2016 2017EUR millions +343 -172 +1 812 +88 +648% of GDP +0.2 % +0.1 % +0.4 % +0.0 % +0.1 %

2.3.1 Life insurance

The ESA 2010 defines the method of calculating the output of life insurance as follows: Premiums earned, Plus premium supplementsLess benefits dueLess increases (plus decreases) in technical reserves.

The ESA 2010 also specifies that the formula for estimating output described above should only take account of the impact of transactions, excluding revaluations and other volume changes, on the change in the technical reserves.

The analysis showed that insurance company allocations to the supplementary life insurance reserve (also known as the "flashing-light reserve") - to be established by insurance companies where the guaranteed interest rate on premiums exceeds the threshold statutory threshold – had hitherto been wrongly included in the sequence for estimating the value of the service produced. In fact, the impact of these allocations on the change in the life insurance technical reserves should be seen as the result of revaluations and not transactions within the meaning of the ESA 2010. Consequently, these flashing-light reserves should not be taken into account and were excluded from the estimate.

This revision led to a substantial revaluation of the value of the life insurance service output, particularly from 2013 to 2015, years in which the allocations to the supplementary life insurance reserve imposed by the regulations were very considerable, against the backdrop of low interest rates.

This revision considerably reduces the volatility of the value of life insurance output over the period 2012-2016.

2.3.2 Pension funds

The pension fund sub-sector S.129 consists exclusively of institutions for occupational retirement provision (IORPs) incorporated under Belgian law.

The output of services by this sub-sector was previously estimated by the method applicable to life insurance (see equation above, point 2.3.1).

Use of this formula means that life insurance output can be estimated in the absence of explicit invoicing. It is based on the fact that the amount of the life insurance premium is set by the insurer with the aim of making a margin which can be retained as remuneration for its intermediation service.

Although this method may correspond to insurance company practice, it takes no account of the activities of an institution for occupational retirement provision, as the latter does not derive any profit from the amounts allocated by the employer setting it up.

Consequently, the output of sub-sector S.129 is now estimated by an approach based on the sum of the costs in accordance with the ESA 2010 recommendations for the treatment of pension schemes managed by a separate fund but set up by an employer.

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2.4 Health and welfare

Impact on GDP 1995 2005 2015 2016 2017EUR millions -210 -316 -463 -675 -677% of GDP -0.1 % -0.1 % -0.1 % -0.2 % -0.2 %

2.4.1 Hospital services

According to the ESA 2010 rules, the amount of government aid for servicing hospitals’ investment debt recorded in their turnover must be excluded when calculating value added. That amount had not previously been excluded, but the exclusion has now been effected since 1995.

By the same reasoning, subsidies received by hospitals must be excluded from the value of their output and recorded as production subsidies. Revision of these subsidies resulted in an adjustment to hospitals’ output and hence to their value added. On the one hand, the social Maribel subsidy was reassessed1, while a new subsidy concerning the financing of nurses’ retirement was taken into account from 2006.

Altogether, the revision points presented above led to a downward revision of the value added of hospitals over the period 1995-2017.

2.4.2 Child minders

The method of estimating the output of services by self-employed child minders was revised. Under the "price x quantity" approach used, improvements were made to the "price" data for the country’s three Communities and to the "quantity" data for the Flemish Community. The price data were adjusted upwards to take account of the government subsidies. The estimate of quantities in the Flemish Community was revised downwards to reflect more accurately the actual occupancy rate. These adjustments led to an upward revision of the output of services by child minders.

In addition, a downward adjustment was made in order to exclude the output of approved minders overseen by a private agency already recorded in the non-financial corporations sector. Since the elimination of this double counting exceeded the revision of the output of self-employed child minders, the overall result was a downward revision of output in the branch comprising social work activities without accommodation. However, the amounts involved are much smaller than those referred to in point 2.4.1.

2.4.3 Adapted work enterprises

The value added of adapted work enterprises (AWEs) was revised with effect from base year 2009 by incorporating data from the annual accounts filed and by improving the extrapolation methods used in the absence of accounts or in cases where the accounts are filed in the simplified format. The survey on the breakdown of the activities of the AWEs was also relaunched in 2017. The new results of this survey were used from 2015 onwards in order to allocate the value added of the AWEs to the branches of activity corresponding to their main activity. The impact of these revisions on the value added of the AWEs is marginal.

1 The breakdown of subsidies between branches of activity was revised on the basis of detailed data collected from a few large funds which manage the social Maribel subsidies.

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2.5 Research and development

Impact on GDP 1995 2005 2015 2016 2017EUR millions -785 -58 -296 -845 -126% of GDP -0.4 % 0.0 % -0.1 % -0.2 % 0.0 %

Since the switch to the ESA 2010, R&D expenditure has been recorded as gross fixed capital formation (GFCF), i.e. investment. In Belgium, the Federal Scientific Policy (Belspo) organises the collection of data on R&D expenditure, distinguishing between in-house R&D expenditure and external R&D expenditure. The former generates either R&D output for own final use (P.12) or R&D output for sale to a third party (P.11). Purchases of R&D by a third party come under external R&D expenditure.

The new treatment of R&D expenditure according to the ESA 2010 has had the effect of increasing the value added of units incurring R&D expenditure, but the mechanisms differ between market and non-market entities and depending on whether the R&D takes place for own use or forms the subject of a transaction between production units.

� Since value added is obtained by deducting intermediate consumption from output, the reclassification of intermediate consumption expenditure as investment results in an increase in value added. This mechanism applies in the case of the purchase by a market or non-market unit of an R&D product or service provided by an external entity.

� In the case of own account R&D activities, the effect of an increase in the value added of the production unit also applies: in market enterprises, expenditure incurred in connection with R&D (wages, miscellaneous purchases, etc.) for own final use is recorded directly as gross fixed capital formation. The output of non-market units is conventionally calculated as the sum of their production costs, including the consumption of fixed capital. The consumption of fixed capital – which is increased following the capitalisation of the R&D expenditure – is the factor that increases the value added of non-market units.

R&D output is estimated with the aid of a satellite R&D account whose starting point is in-house R&D expenditure. This satellite account can be used to estimate domestic R&D output but does not allow that output to be broken down into market production and own account production. One of the major changes introduced by the benchmark revision means that market production of R&D and production of R&D for own final use are now estimated with the aid of data directly available in the Belspo R&D survey, as in-house expenditure on R&D is available by funding source. It is therefore possible to identify the proportion of this internal R&D expenditure generating R&D sales (funding of expenditure by other units) and the proportion capitalised within the business. Before this revision, R&D output was broken down on the basis of various administrative sources (annual accounts, business structure survey), often leading to inconsistent results.

A second revision point concerns net purchases of R&D. The R&D produced by a unit active in a specific branch of activity may be purchased and capitalised by a unit active in another branch of activity. The branch in which the R&D is produced therefore need not be the same as the one in which it is capitalised. Consequently, the estimation of gross fixed capital formation of R&D must take account of purchases and sales between branches of activity. Before the revision, net purchases of R&D were estimated by means of matrices constructed on the basis of funding sources for in-house R&D expenditure and were only available by sector/branch, so that it was not possible to estimate R&D investment per company, in contrast to all the other R&D output aggregates. The revision means that net purchases of R&D are now estimated at company level. On the basis of in-house R&D expenditure by funding source and external R&D expenditure it is in fact possible to estimate R&D sales and purchases respectively at microeconomic level. Taking account of the scope of the Belspo survey, which focuses primarily on in-house R&D expenditure1, R&D sales generally exceed R&D purchases (at the level of the Belgian economy).

1 The R&D survey covers units which incur in-house R&D expenditure. The units polled are then asked to report any external R&D expenditure as well, constituting purchases of R&D. Units which only purchase R&D (with no in-house R&D expenditure) are therefore not polled, so that R&D purchases are underestimated.

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The units’ purchases of R&D were then adjusted upwards so that net R&D purchases are zero at the level of the Belgian economy, as the amount of sales must equal the amount of purchases.

A third revision point concerns market production of R&D in branch of activity 72 (scientific R&D). After comparison of the information sources it emerged that, according to the estimation framework hitherto used, less than 50% of the total output of branch of activity 72 comprises R&D products, principally at the level of market production. Under the revision, with effect from 2009 a series of firms whose R&D is not their main activity were reclassified outside branch of activity 72. Part of the residual difference between market production of R&D estimated with the aid of the satellite R&D accounts and item 70 in the annual accounts (turnover) was imputed to the units for which R&D expenditure is underestimated in the Belspo survey. Following revision, the market production of R&D in branch of activity 72 represents around 80% of the total output of the branch (taking all products together).

Finally, for two large firms in the pharmaceutical industry (branch of activity 21), investment in R&D – previously estimated on the basis of their annual accounts – is now estimated according to the data derived from the satellite R&D accounts with retroactive effect from 2006 for one firm and from 2009 for the other.

The incorporation of all these changes in the national accounts had a negative impact overall on the value added of the R&D branch and hence on GDP.

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2.6 "Market/non-market" test

Impact on GDP 1995 2005 2015 2016 2017EUR millions 0 0 -466 -446 -297% of GDP 0.0 % 0.0 % -0.1 % -0.1 % -0.1 %

This revision point concerns implementation of the "market/non-market" test specified by the ESA 2010 for the classification of private non-profit institutions (NPIs)1. This test involves calculating the ratio between the NPI’s income from sales and its production costs: if that ratio is less than 50 %, the NPI is deemed to be non-market and is classified in the sector for NPIs serving households(S.15). If the opposite applies, it is regarded as market and classified in the sector for non-financial corporations (S.11) or financial corporations (S.12). To ensure that classifications are stable, assignment to a sector has to be confirmed for at least three consecutive years before a change in the sectoral classification of an NPI can be considered.

In the past, most NPIs were classified in the non-financial or financial corporations sector (S.11 or S.12 respectively) or in the sector for NPIs serving households (S.15), depending on the nature of their activities, since there was insufficient accounting information available, making it impractical to apply the quantitative test to determine whether the units in question were market or non-market.

Changes to the law gradually led to an increase in the number of NPIs required to file their annual accounts at Belgium’s Central Balance Sheet Office. However, the information gathered depends on the size of the NPI: "full-format" accounts for very large NPIs and "abbreviated" accounts for large NPIs.

Since 2009, many NPIs have also responded to a very detailed survey (the Statbel structure survey), thus extending the quantitative data on their activities. The benchmark revision provided an opportunity to make maximum use of all the information now available.

Where the information is not sufficiently detailed, i.e. if an NPI has not taken part in the survey, has not filed full annual accounts, or has not completed the optional sections in filing abbreviated annual accounts, the sectoral classification depends on the unit’s activity, as in the past.

Implementation of the quantitative test from 2009 led to reclassification of around 12% of private NPIs: 6 % were transferred to the non-market sector and 6 % to the market sector. The impact on the overall population of enterprises is therefore limited. Conversely, the transfer of units between branches of activity may be more evident.

Sectoral reclassifications influence the estimate of GDP because the ESA 2010 specifies different rules for the methods of assessing value added, depending on whether a unit is deemed to be market or non-market; in the case of non-market units, the cost method has to be applied. However, as NPIs are relatively small units, application of the quantitative test has a fairly marginal – and generally negative - impact on GDP.

1 Public NPIs are not covered by section 2.6, even though they are also subject to a market/non-market test enabling them to be classified in the general government sector or in the corporations sector. For more details on general government, see chapter 7.

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2.7 Production of electricity by households

Impact on GDP 1995 2005 2015 2016 2017EUR millions 0 0 +557 +549 +535% of GDP 0.0 % 0.0 % +0.1 % +0.1 % +0.1 %

As part of the 2019 benchmark revision, the production of electricity by households was included in the national accounts. This electricity production used to be marginal but began to increase significantly from 2009, notably as a result of government incentives.

Households consume directly some of the electricity that they produce, and if they produce more than they consume they feed the surplus electricity into the public network. A reverse electricity meter records the corresponding value for the households. Analysis of the available data reveals that – up to now – households produce their electricity almost exclusively by means of photovoltaic panels.

The value of the electricity production is determined partly by the quantity and price of the electricity produced and partly by the production subsidies that households receive from the government.

In the past, the three Regions granted substantial subsidies for the production of renewable energy, which includes the electricity generated by solar panels. In many cases, the subsidy was based on the capacity – the installed power – of the photovoltaic installation. The installed capacity was used to indicate the approximate quantity, to which an adjustment coefficient was applied to take account of the efficiency–related difference between the installed capacity and the power actually produced.

The price of the electricity produced corresponds to the energy component of the price paid by a consumer household. As electricity producers, households do not set the prices; it therefore seemed appropriate to assess the price of the electricity that they supply to the electricity grid via the energy component of the overall electricity price for the average end user.

Subsidies paid to households by the distribution network operators were added in order to supplement the estimate of production.

The intermediate consumption relating to the production of electricity by households was then estimated. It corresponds to the cost of maintaining and cleaning the installations, and the "prosumer"-tariff in Flanders. That tariff comprises a payment introduced in 2015 for use of the distribution network. The rationale is that owners of (small) solar panel installations use the distribution network both to feed in the surplus electricity that they produce and to draw electricity from the grid when they are not producing it themselves.

It should be remembered that installations for the production of electricity by households – essentially solar panels – are recorded as investment in housing. That was already the case before the present revision.

As electricity producers, households created around € 600 million in annual value added - namely the difference between production and intermediate consumption - in 2012-2017.

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2.8 Financial intermediation services indirectly measured (FISIM)

Impact on GDP 1995 2005 2015 2016 2017EUR millions 0 0 +796 +1 250 +1 473% of GDP 0.0 % 0.0 % +0.2 % +0.3 % +0.3 %

Financial intermediation services indirectly measured (FISIM) represent the proportion of financial intermediaries’ services not explicitly invoiced to customers. For these services, financial intermediaries obtain remuneration by applying an interest rate margin to their customers’ deposits and to the loans that they grant. These services are recorded as production in the national accounts (or as imports if the producing financial intermediary is based abroad). They are then either consumed by the various resident institutional sectors in the form of intermediate or final consumption, or exported.

The assessment of FISIM according to both the production and the expenditure approach is directly linked to the estimate of interest received and paid by the various institutional sectors. For the purpose of creating the interest matrix, that expenditure was adjusted in a number of respects (see point 5.1), leading to a revision of the FISIM calculated on the basis of the matrix. This had little effect on domestic production of financial services indirectly measured. Conversely, imports of FISIM were revised. The breakdown between FISIM consumers according to whether they are non-resident (exports) or resident (in the form of intermediate and final consumption) was also reassessed; taking account of the revision of intermediate consumption, this affected GDP from 2009 onwards.

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2.9 Taxes less subsidies on production and imports

Impact on GDP 1995 2005 2015 2016 2017EUR millions +160 +223 +1 160 +2 181 +2 556% of GDP +0.1 % +0.1 % +0.3 % +0.5 % +0.6 %

A first revision item concerns taxes on products (D.21), which were adjusted to take account of VAT due but not received in order to comply with the Eurostat recommendations whereby that VAT must be included in the estimate of GDP (see point 7.3.1).

A second type of adjustment concerns taxes less subsidies on production (D.29-D.39), where revisions may indirectly influence the assessment of value added, and hence GDP.

In this connection, the breakdown of these net taxes between domestic institutional sectors and branches of activity was refined on the basis of detailed data obtained from the government.

That breakdown was also adjusted following the sectoral reclassification of NPIs (see point 2.6 above). In the case of non-market NPIs, value added is calculated by the cost method which includes taxes less subsidies on products. The revision of those taxes therefore also influenced the estimate of the value added of NPIs serving households (sector S.15).

In addition, subsidies on production attributed to the general government sector were revised upwards following the inclusion of the social Maribel employment subsidies attributed to units in the sector (see point 7.1.2). It had not previously been possible to distinguish between those subsidies and the ones granted to companies. The production, and hence the value added, of the general government sector was therefore revised downwards by use of the cost method.

Comparison of the new estimates of taxes and subsidies on production with the data in the annual accounts of businesses also triggered revisions of the value added of non-financial corporations.

Altogether, these adjustments implied an upward revision of GDP.

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3. Revisions – expenditure approach

3.1 Household final consumption expenditure

Impact on GDP 1995 2005 2015 2016 2017EUR millions -1 659 -2 048 +4 661 +4 396 +6 425

- on-line purchases 0 0 +1 901 +2 163 +2 835

- dwelling services -2 203 -2 947 -403 -238 +338

- financial and insurance services +637 +125 +2 146 +1 042 +1 892

- administrators’ benefits in kind +102 +166 +455 +490 +517

- correspondence between HBS and NACE codes 0 0 -230 +402 +323

- cross-border expenditure +194 -6 +114 +28 -175

- other -390 -614 +678 +510 +694

% of GDP -0.8 % -0.7 % +1.1 % +1.0 % +1.5 %

Two types of revision affected private consumption: (a) those concerning the direct estimate of household final consumption, and (b) those resulting from revisions according to the production approach (see chapter 2). This section only gives details of revisions concerning the direct estimate of consumption.

A first important revision concerns on-line purchases. The estimate of these purchases was refined by means of detailed bank card and/or credit card payment statistics. This new source can be used to distinguish between on-site and on-line purchases, and to ascertain whether a business or personal payment card was used. This implies a more accurate estimate of foreign on-line purchases by resident households. According to the Eurostat recommendations, on-line purchases made by residents via a foreign website and delivered in Belgium are recorded both as domestic consumption expenditure and as an import of goods. This new estimate was introduced in household final consumption expenditure and imports with effect from 2011.

This adjustment is an example of a methodological revision designed to accurately reflect economic phenomena which are gaining ground. Household expenditure was thus increased by around € 2.8 billion in 2017. The impact is particularly significant for expenditure on clothing and footwear (COICOP 03), and expenditure relating to leisure and culture (COICOP 09).

There was no revision of estimates of on-line purchases by resident households via a Belgian website. According to the existing method, these purchases are implicitly estimated on the basis of the turnover figures declared for VAT.

A second revision specific to the estimate relates to intermediate and final consumption concerning the maintenance and repair of housing (included under "dwelling services" in the table above). According to the ESA 2010, an owner-occupier’s expenditure on the decoration, maintenance and repair of the home, being expenditure not normally borne by a tenant, should be excluded from final consumption and classed as intermediate consumption in calculating the production of housing services. Conversely, expenditure typically borne by a tenant should be recorded as household final consumption. For information, major repairs (renovation) are recorded as investment expenditure.

On the basis of the information in the Household Budget Survey (HBS), the treatment of expenditure on the maintenance and repair of housing was revised, leading to a downward revision of household final consumption.

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The third revision point concerns the expenditure of Belgian residents abroad and of non-residents in Belgium (cross-border expenditure). There are two aspects to this revision.

� The balance of payments data on travel were revised to include the statistics on payment by bank card and/or credit card. These balance of payments data are themselves used in the national accounts to estimate expenditure by residents abroad (P.33) and expenditure by non-residents in Belgium (P.34). The new balance of payments data are available from base year 2015. For the purposes of the national accounts, figures were retropolated on the basis of historical series for the period 1995-2014. The incorporation of new balance of payments data has an upward impact on both the level of consumption expenditure by residents abroad and the level of expenditure by non-residents in Belgium.

� The method of identifying the imported intermediate consumption of tour operators was revised. Tour operators sell an "all-inclusive" service, the total value of which – i.e. the operator’s margin plus hotel and transport costs – is equal to the tour operator’s production. That production is attributed entirely to domestic household final consumption. Intermediate consumption comprising the value of imported services (hotels and transport) is also recorded in the tour operators branch. In the balance of payments, those service imports are recorded under "Travel" but should not be included in the final consumption of residents abroad (and vice versa in regard to exported services). Residents’ final consumption abroad should therefore be adjusted in that respect. That adjustment was already made in the past, but the new estimation method is based on a more refined definition of the production and intermediate consumption of tour operators. The revision of the intermediate consumption of tour operators has an upward impact on both the final consumption of residents abroad and that of non-residents in Belgium.

Overall, the final consumption of residents abroad and that of non-residents in Belgium were revised downwards. The net impact on household final consumption expenditure at national level, and hence on GDP, is smaller and the sign is variable, as shown in the table above.

A fourth revision point concerns improving the link between NACE codes and expenditure categories. The estimate of household final consumption is based largely on the results of the household budget survey. A new base year is introduced periodically to determine the level of expenditure per category. For intermediate years, the figures are interpolated, usually on the basis of the change in the turnover figures declared for VAT for activities whose NACE code corresponds to the expenditure categories in question. On the occasion of the benchmark revision, the appropriateness of the relevant NACE codes per expenditure category was reviewed and improved where necessary.

Finally, some revision points in the production approach affect the estimate of household final consumption expenditure. That applies to: – financial services (including FISIM) and insurance services; – housing services; – benefits in kind of self-employed company administrators; – own account electricity production; – health and welfare services; – certain market production of general government and non-profit institutions serving households.

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3.2 Gross fixed capital formation

Impact on GDP 1995 2005 2015 2016 2017EUR millions -453 -331 +709 +772 +16% of GDP -0.2 % -0.1 % +0.2 % +0.2 % +0.0 %

There are four types of revision in the estimate of gross fixed capital formation: (a) revisions arising from adjustments in the general government accounts; (b) adjustments to the estimate of R&D; (c) revisions to the method of recording registration fees, and (d) revisions to the assessment of SME investments.

A first revision point concerns adjustments in the general government accounts. Minor adjustments were made to public investments over the period as a whole. From 2014 onwards, those adjustments became more significant owing to the reclassification of Infrabel in the general government sector (see point 7.2.3).

A second revision concerns the new methodology relating to R&D, which has a direct influence on gross fixed capital formation for all sectors (see point 2.5).

A third revision point concerns the way in which registration fees and the associated notary costs are recorded in the national accounts. According to the ESA 2010, the cost of transferring the ownership of land and buildings should be regarded as gross fixed capital formation. Registration fees are due on transactions concerning undeveloped land and buildings on the secondary market. Previously, these costs were estimated by means of an allocation key based on the known total amount according to the general government accounts. The associated notary costs were estimated on the basis of a ratio. The total estimated costs were included in gross fixed capital formation in housing (AN.111) in the household sector (S.14).

Since detailed information on registration fees relating to the sale of real estate is now available in the general government accounts, it is no longer necessary to rely on assumptions. The new method uses the amount recorded in the general government accounts concerning transactions relating to land and buildings. In addition, the ratios used to estimate notary costs are produced in more detail, namely by Region. Finally, the costs are apportioned between investment in "housing (AN.111)" and in "other buildings and civil engineering (AN.112)" via an allocation key based on secondary market transactions. That results in a more accurate allocation of registration fees per sector and per asset.

The fourth point concerns the change in the method of assessing SME investments, which was harmonised with the method used for large firms from 2009. In the past, SME investments were valued on the basis of the annual accounts, if available, or otherwise by using data reported to the VAT authority. From now on, the annual accounts of SMEs will be used as such to estimate investments only if the financial year corresponds to the calendar year and/or if no restructuring is in progress. That information will be checked on the basis of heading 8299 in the company accounts, which reflects depreciation acquired from third parties. If the SME is in one of the situations mentioned above, the investment will be estimated on the basis of data reported for VAT. In the absence of VAT data, the annual accounts adjusted to allow for item 8299 will be used.

Finally, other revision points influence gross investment. More specifically, the "market/non-market" test (mentioned in point 2.6) and the resulting new sectoral classification affect the breakdown of investments by sector. In addition, a number of adjustments were made to the most recent years in order to enhance consistency with the balance of payments data.

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3.3 Imports and exports

3.3.1 Imports and exports by non-residents

Impact on GDP 1995 2005 2015 2016 2017EUR millions 0 0 -2 892 -3 994 -4 685% of GDP 0.0 % 0.0 % -0.7 % -0.9 % -1.1 %

On the occasion of the benchmark revision, the method of calculating imports and exports of goods by non-residents was changed in order to conform to the recommendations made by Eurostat in its publication Manual on foreign trade reported by non-residents. Previously, imports and exports by non-residents according to the national concept were based respectively on total sales and purchases appearing in the VAT supplier database, but these imports and exports are now determined on the basis of sales and purchases effected solely with resident counterparties appearing in those records. This method avoids creating an unjustified increase in trade flows as a result of recording transactions between non-residents on the Belgian territory.

Since the VAT supplier database does not make a distinction between transactions in goods and transactions in services, it could be that the goods account includes service components, possibly resulting in double counting with transactions in the services account. To avoid that risk it was decided that the definition of the national concept for non-residents should be further restricted to purchases effected with resident counterparties operating in the goods sector.

In contrast to past practice, non cross-border transactions in goods between non-residents and residents are now also included in import and export flows. Indeed, the concept of transfer of ownership applies in national accounts. This means that goods which do not cross the border but involve a transfer of ownership must be included in imports and exports of goods1. For that purpose, a distinction is made between non-residents who already declare foreign trade in goods and non-residents who do not. For the first group, cross-border transactions are calculated as the difference between the amounts entered under the Community concept and those entered in the VAT supplier database, if the latter source indicates higher amounts. If the data in the VAT supplier database show a smaller amount than the figure estimated on the basis of the Community concept, it is assumed that there are no transactions without a cross-border dimension. For the group of non-residents who do not declare foreign trade in goods, the estimate is based on the VAT supplier database according to the estimation method used to define the national concept in foreign trade in goods.

While non cross-border transactions in goods between non-residents and residents are now included, temporary inward and outward transactions in goods which do not imply any transfer of ownership are excluded from the estimate.

The above changes were applied from base year 2015 in the balance of payments and in the national accounts so that, from a methodological point of view, those statistics are entirely comparable from that year onwards2. For the period 2009-2014, the changes were only retropolated in the national accounts.

These adjustments have a negative impact on net imports and exports of goods over the period 2009-2017.

1 This contrasts with the foreign trade statistics, where imports and exports are defined solely on the basis of cross-border movements of goods.2 The recalculation of the national concept in the case of non-residents was also introduced in the statistics on foreign trade in goods with effect from 2015. The other

revision points only affect the balance of payments and the national accounts.

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3.3.2 CIF/FOB adjustment

Impact on GDP 1995 2005 2015 2016 2017EUR millions 0 0 -472 -514 -513% of GDP 0.0 % 0.0 % -0.1 % -0.1 % -0.1 %

To comply with the ESA 2010 stipulations, imports of goods broken down by product in the supply and use table have to be assessed according to their "cost-insurance-freight" (CIF) value, while exports of goods have to be assessed according to their "free on board" (FOB) value. However, total goods imports have to be assessed at their FOB value, entailing the introduction of a CIF/FOB adjustment. In practice, import and export data underwent three transformations:

a) Conversion of current imports (respectively exports) per product from the invoiced value to the CIF value(respectively the FOB value);

b) Estimation of the CIF/FOB adjustment for total goods imports (transport and insurance costs betweenthe exporting and importing countries being deducted from imports of goods; this corresponds to all thecosts incurred in transit through intermediate countries);

c) Breakdown of the CIF/FOB adjustment into a part attributable to residents (cross-entry in exports ofservices (P.62) by way of negative adjustment) and a part attributable to non-residents (cross-entry inimports of services (P.72) by way of positive adjustment).

a) Imports and exports of goods according to the national concept (derived from foreign trade) were notpreviously calculated at their CIF and FOB values except in the case of trade with non-EU countries; tradewith EU countries was estimated on the basis of the invoiced value. Conversely, imports and exports of goodsaccording to the Community concept, from and to EU countries, are estimated at their CIF and FOB values.This information, available per product and per partner country, was therefore used to convert imports andexports to the national concept.

b) Current information sources (customs documents, Intrastat declarations, balance of payments surveys, ESE[business structure survey], etc.) do not contain data permitting the conversion of total goods imports from theCIF value to the FOB value, i.e. the CIF/FOB adjustment. That is why the CIF/FOB percentage was definedusing reference data obtained from comparable small open economies. That percentage takes account of theshare of neighbouring countries in total imports, as no CIF/FOB adjustment should be made in that respectand neighbouring countries represent a very high proportion of total goods imports in Belgium.

c) The cross-entry of the CIF/FOB adjustment for imports and exports of services is likewise based on dataderived from benchmark countries.

The said changes were implemented in the balance of payments and in the national accounts with effect from 2015 so that those two sets of statistics are methodologically comparable from that year onwards. For the period 2009-2014, the changes were only retropolated in the national accounts.

The CIF/FOB adjustment itself has no impact on the balance of total imports and exports of goods and services. It merely implies a transfer of the net balance from goods to services, as transport and insurance costs are now eliminated from trade in goods (positive impact on the net balance of goods) and added to trade in services (negative impact on the net balance of services).

Nevertheless, the conversion of imports and exports of goods from the invoiced value to the CIF value and the FOB value respectively has a negative impact on the net balance of goods (and therefore also on the total balance P.6-P.7).

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3.3.3 Other changes

Impact on GDP 1995 2005 2015 2016 2017EUR millions +774 +1 095 +3 410 +4 004 +6 305% of GDP +0.4 % +0.4 % +0.8 % +0.9 % +1.4 %

Apart from the new estimates concerning exports and imports by non-residents and the CIF/FOB adjustment, other revisions affect the trade balance.

For instance, net exports of financial intermediation services indirectly measured (FISIM) were revised following the general revision of the interest matrix (see point 2.8).

Exports of services were recorded at the level of services relating to self-employed administrators resident in Belgium but pursuing activities abroad (see point 2.1).

The introduction of a new method of estimating travel-related exports and imports in the balance of payments, and the inclusion of internet purchases from non-resident counterparties, both on the basis of data derived from debit card and credit card payments (see point 3.1), have a significant impact on the net balance of goods and services in recent years.

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4. Revisions – deflators

Growth in volume of value added is calculated using the double deflation method. Recommended by Eurostat in the framework of ESA2010, this method involves calculating value added in volume terms by measuring the difference between output and intermediate consumption, both expressed in volume terms, rather than deflating directly value added at current prices. In this respect, separate deflators – for output and intermediate consumption – need to be determined, in order to adjust the changes in value for price effects, and individually for each branch of activity. These deflators per branch are obtained by weighting the prices of various products by the share they account for, respectively, in output and in intermediate consumption. On the output side of the equation, information on prices corresponds to Statbel’s industrial producer price indices (PPI); in the case of intermediate consumption, import prices of goods are used alongside industrial producer prices. As for the weighting system, this is derived from detailed supply-use tables.

As part of this latest benchmark revision, a benchmarking exercise was carried out to compare changes in producer prices and output deflators in Belgium and the neighbouring countries, following which the deflators have been adjusted in 11 industrial branches and in six market services branches, since 1995. In industry, the corrections consisted of bringing the output deflators more closely into line with the producer price of the flagship product of each of the branches, while taking account of their individual degree of uniformity. The intermediate consumption deflators were then adapted, under reasonable assumptions about the stability of production processes. The adjustments made in the market services sectors have largely arisen from one-off corrections of trends deemed to be abnormal in Belgium in relation to changes recorded in the neighbouring countries. Moreover, the deflator for the human health (health care) branch of activity has been recalculated over the entire period.

The table below gives the names of the various branches for which the deflators have been adjusted.

C10-12 Manufacture of food products, beverages and tobacco products

C13-15 Manufacture of textiles, wearing apparel and leather

C17 Manufacture of paper and paper products

C18 Printing and reproduction of recorded media

C19 Manufacture of coke and refining

C20 Chemicals industry

C24 Metallurgy

C25 Manufacture of fabricated metal products, except machinert and equipment

C26 Manufacture of computer, electronic and optical products

C29 Manufacture of motor vehicles, trailers and semi-trailers

C30 Manufacture of other transport equipment

G46 Wholesale trade

G47 Retail trade

M73 Advertising and market research

N79 Travel agency, tour operator, reservation services and related activities

Q86 Human health activities

R93 Sports activities and amusement and recreation activities

S95 Repair of computers and personal and household goods

Given the weighting of the branches where the adjustments have been made, the total deflator for industry has been revised upwards; its annual average growth over the period 1995-2015 is now zero (0.0%), compared with -0.5% previously. In market services, the annual average growth of the deflator has been revised downwards, from 1.9% to 1.7%, over the period 1995-2015. In the health care sector, annual average growth of the deflator has been revised downwards, from 2.9 % to 2.1%. Overall, the revisions made to the industry and services deflators have nevertheless had only a limited impact on the value added deflator for the whole of the economy, the average growth of which over the period 1995-2015 has remained unchanged, at around 1.5%.

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5. Revisions – property income and other transfers

There is no impact on GDP from the revision points covered in this chapter 5. However, these points may have some impact on uses et resources of the institutional sectors, and also their net lending/borrowing. Since transactions in question concern income transiting between Belgium and the rest of the world, there may also be some impact on the measurement of gross national income (GNI).

5.1 Interest income

Impact on GNI 1995 2005 2015 2016 2017EUR millions 0 0 +1 015 +274 -690% of GNI 0.0 % 0.0 % +0.2 % +0.1 % -0.2 %

The estimate of interest income paid and received for each institutional sector has not been subject to any change in methodology as such.

As a general rule, interest flows are estimated by combining financial stocks with interest rates, while taking account of certain constraints where direct data on these flows are known. All calculations and balancing are done in an interest matrix that enables interest flows between each institutional sector to be estimated.

Firstly, the interest rates used in the compilation of the matrix were revised.

Secondly, the choce of interest rates used for counterpart sectors for general government assets and liabilities has been refined. The use of these new rates produces results that are more consistent with the constraints imposed by total interest paid and received by general government. This enhances the interest matrix’s balancing procedure and thus guarantees better quality results for all institutional sectors.

Thirdly, as part of the harmonisation of national financial accounts and the international investment position, outstanding financial assets and liabilities of the rest of the world sector have been revised, leading to revisions of financial stocks taken into account in calculating the matrix.

Lastly, the interest payments of certain institutional sectors that act as constraints in the matrix in calculations have been revised over a longer period. This is the case for certain financial sub-sectors and for general government.

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5.2 Dividends

Impact on GNI 1995 2005 2015 2016 2017EUR millions 0 0 -343 +212 -71% of GNI 0.0 % 0.0 % -0 .1 % +0.0 % -0.1 %

Flows of dividends between the different institutional sectors, and consequently the dividend matrix1, have been revised for the period 2009-2017 owing to : (a) the process of harmonisation with balance of payments data which has been extended to the period 2009-2013 ; (b) changes in methodology spanning the whole period.

a) First of all, two methodological revisions, which had already been incorporated into the statistics from 2014 on as part of the process of harmonisation with the balance of payments, have been extended to cover the period 2009-2013:

� dividends paid are no longer calculated on a prorata basis when the annual accounts have not been closed on 31 December of the calendar year. From now on, they are fully recorded in the period during which the general meeting of shareholders approved the annual accounts and proposed to pay out a dividend. Furthermore, dividends received from foreign direct investment enterprises are calculated using another heading taken from the balance of payments survey on direct investment flows (F13FDI), that is more appropriate for recording dividends received by Belgian institutional units;

� dividends paid and received from portfolio investment have been aligned on the new outstanding amounts of Belgium’s International Investment Position (IIP). Moreover, the third-party holdings (TPH) concept2 has been introduced into the IIP for portfolio investment, and dividends have been calculated and incoporated for these new assets.

b) In addition, changes in methodology have been incorporated into the estimation of dividends received by domestic financial and non-financial sectors. For certain financial sub-sectors, like banks and insurance companies, dividends received are calculated on the basis of exhaustive data. However, for the other financial sub-sectors and the non-financial sector, dividends received are calculated from the total financial income per enterprise to which ratios are applied. These ratios have been revised from 2009 on the basis of survey data, information on corporate (financial) assets and qualitative checks carried out on the annual reports of companies. In addition, the definition of super dividends3 has also been widened to all financial sub-sectors. Up until now, only full-format annual accounts of financial and non-financial corporations had been analysed. Thanks to this extension, super dividends can from now on also be recorded for banks and insurance companies. Lastly, dividends generated by unobserved activities have also been revised following the revision of wages for undeclared work (see point 6.2). These dividends are considered to be fully distributed to the household sector.

1 The dividend matrix lists all flows of dividends between the different institutional sectors (corporations, general government, households, non-profit institutions serving households, and the rest of the world). In the dividend matrix, all dividends received or paid out between the different institutional sectors are cross-matched. Since estimation methods and sources vary from one sector to another, the matrix is not balanced at the point when all flows are initially entered. The household sector is given the balance of all inward and outward flows and, for this reason, constitutes the balancing item in the matrix.

2 TPHs cover other portfolio investment made by non-financial corporations and households in securities issued by non-residents and held outside Belgium but still within the euro area. For further information on all the changes made to the IIP: https://www.nbb.be/doc/dq/f_method/iip201709_f.pdf

3 Super dividends are extraordinary dividends, that are large relative to companies’ recent levels of dividends and earnings (ESA 2010, § 4.55). These super dividends are calculated on the basis of withdrawals of equity capital and/or on the reserves that a company makes when allocating profits. In the case of enterprises falling within the scope of the government sector, specific rules imposed by ESA 2010 and by the Manual on Government Deficit and Debt apply.

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5.3 Reinvested earnings from foreign direct investment

Impact on GNI 1995 2005 2015 2016 2017EUR millions 0 0 +6 985 +3 060 -114% of GNI 0.0 % 0.0 % +1.7 % +0.7 % 0.0 %

Up until now, only income derived from directly owned enterprises had been recorded. From now on, income derived from indirectly owned enterprises are also taken into account.

According to the ESA 2010 methodology, profits actually paid out as well as reinvested earnings must be booked as income. Distributed profits or dividends are recorded under the variable D.421 and reinvested earnings under the variable D.43. Reinvested earnings are derived from two concepts, namely the operating surplus of the company less dividends paid. In Belgium, it is the Current Operating Profit (COP) concept that is used as a proxy for the operating surplus, with the company’s profit (or loss) after tax being adjusted for extraordinary income and expenses. The COP concept had already been applied before this benchmark revision, since 2013, and is now extended to 2009 in this publication1. The definition has been harmonised with the Balance of Payments’ COP definition and is used to calculate the operating results of Belgian and foreign direct and indirect investment firms.

In order to be considered as a direct investment firm, the direct investor must have control over at least 10% of the shares or voting rights. This foreign direct investment relationship may itself be either direct or arise from an ownership chain. Participations can also be indirectly held: these are stakes through which a Belgian or a foreign parent company has indirect control over a firm through one or more subsidiaries. However, up until now, only directly held investment firms fell within the population of foreign direct investors (FDI). These indirect relationships had been left out of the calculation of reinvested earnings, even though they can have a significant impact on Belgium’s income balance vis-à-vis the rest of the world.

These indirect participations have thus been analysed with the help of the FDI database of the NBB’s External Statistics Service, which conducts several surveys on direct investment firms. The annual accounts (individual and consolidated) have also been analysed in order to obtain a complete overview of the participations (direct and indirect) of multinationals established in Belgium. The analysis was carried out on 60 multinational groups for the years 2009-2017.

Two methodologies have been developed for the recording of indirect participations in Belgium's reinvested earnings (D.43):

� For multinational companies with headquarters located in Belgium, the consolidated financial business accounts of the Belgian groups, which are filed with the Bank's Central Balance Sheet Office, are now used to calculate profits at group level. By combining the individual financial statements of the Belgian parent company and the ones of its subsidiaries, the foreign share in the total group profit is determined. By applying this accounting consolidation method (ACM), reinvested earnings are therefore calculated at the level of the entire group and no longer at the level of individual entities. So, it is a top-down approach in which the group’s total profits are divided between Belgian and foreign entities. Given the complexity and scale of some groups, the consolidated annual accounts are the best source for deriving the group’s total profits. The structure of the group is charted using the list of participations available through the annual accounts of the Belgian group members and through the FDI surveys. This enables a distinction to be made between domestic and foreign flows. The ACM method is currently applied to 12 Belgian multinationals.

� In the case of multinational groups with participations in Belgium but whose head office is located abroad, the statistical consolidation method (SCM) is used. Like in the first method, the entire group structure is identified on the basis of the FDI surveys and individual annual accounts. However, in contrast to the

1 The harmonised definition of COP has been applied to the calculation of reinvested earnings from 2013 on since the 2016 publication.

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accounting method, the statistical method actually calculates the COPC and D.43 for each entity of the group. These flows are then aggregated along the investment chain in proportion to the direct investment percentage. In other words, the statistical method follows a bottom-up approach whereby all Belgian and foreign profits are ultimately aggregated at the level of the Belgian or foreign parent company. This method is currently used for foreign multinationals with Belgian subsidiaries and for some smaller Belgian multinationals for which we have reliable FDI survey data. In cooperation with the External Statistics Service, efforts are being made to obtain more precise and better quality information on the indirectly held foreign enterprises for the 12 Belgian multinationals currently covered by the accounting approach. This will allow a full transition to the Statistical Consolidation Method (SCM).

The integration of these indirect participations has a significant impact on the reinvested earnings (D.43) of Belgium, on both the uses and the resources side. The integration of foreign indirect participations of Belgian multinationals may lead to a significant increase or decrease in the flow of reinvested earnings, depending on the profits or losses of these foreign subsidiaries. The same goes for foreign multinationals with participating stakes in Belgium. Retained profits (losses) from Belgian indirect participations of foreign groups are transferred to the foreign parent company, thereby increasing (decreasing) the reinvested earnings payable. In addition, the new calculation method ensures that the reinvested earnings received by Belgian "intermediate companies" are passed on to the foreign parent company. Such transfer entities are set up by a foreign parent company for the purpose of placing certain foreign subsidiaries with the Belgian holding company. If, for example, a foreign parent owns a Belgian holding company with a few fully-owned foreign subsidiaries, the reinvested earnings received on these foreign subsidiaries are fully transferred abroad, so that they have no impact whatsoever on the Belgian income balance1. Previously, each investment relationship was recorded separately, so that the profits or losses of such relationships remained with the Belgian intermediate holding company. As Belgium has many of these holding structures, the new methodology has a significant impact on reinvested earnings and the income balance vis-à-vis the rest of the world.

1 Reinvested earnings transit in proportion to the foreign parent company’s controlling percentage stake in the Belgian intermediate company. If the controlling percentage is as much as 100 %, any reinvested earnings received are therefore returned in full to the rest of the world.

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5.4 Collective investment fund income

Impact on GNI 1995 2005 2015 2016 2017EUR millions 0 0 +2 -242 -277% of GNI 0.0 % 0.0 % +0.0 % -0.1 % -0.1 %

According to the ESA 2010 methodology, all collective investment fund income (regardless of its nature, interest or dividends) has to be recorded as if it had been directly and fully redistributed to shareholders, under a single heading for property income D.443 "investment income attributable to collective investment fund shareholders". This heading nevertheless makes a distinction between income that is actually distributed (dividends) and income that is capitalised (retained earnings) :

� dividends attributable to collective investment fund shareholders (D.4431); � retained earnings attributable to collective investment fund shareholders (D.4432).

It has been possible to improve the breakdown between distributed (D.4431) and capitalised (D.4432) income by using detailed data from the Central Security Data Base (CSDB) set up by the European Central Bank and backed up by data from the Balance of Payments’ Processor for Investment Series Management (PRISM) since 2013. The information contained in these databases effectively enables investment funds to be classified by type (distribution or capitalisation) and by type of fund shareholders (institutional sectors). By cross-matching this information, it has been possible to calculate a specific distribution/capitalisation ratio for each holding sector.

The total amounts to which the new allocation keys have been applied have been only marginally revised, except or the most recent years covered by routine revisions.

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5.5 Transfers for cross-border workers

Impact on GNI 1995 2005 2015 2016 2017EUR millions +95 +220 +409 +452 +652% of GNI +0.0 % +0.1 % +2.0 % +0.9 % -0.1 %

According to ESA 2010, local staff working for foreign embassies or for international institutions are considered to be cross-border workers.

Compensation of employees for local staff working for Belgian embassies abroad has been added to the salaries of incoming cross-border workers. The figures have been provided by the FPS Foreign Affairs. Salaries of outgoing cross-border workers have been supplemented by remuneration of staff resident in Belgium and working for foreign embassies. These amounts have been estimated on the basis of data coming from the National Social Security Office. Also, salaries of staff working for other international organisations than the European institutions and NATO/SHAPE have been estimated and added to the existing amounts.

Furthermore, tax and social security benefits respectively paid and received from abroad have been estimated for cross-border workers employed in the neighbouring countries (Germany, France, the Netherlands and Luxembourg). The amounts have been calculated from information extracted from these four countries’ national accounts or their balance of payments.

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5.6 Cross-border pension funds

Impact on GNI 1995 2005 2015 2016 2017EUR millions 0 0 0 -12 -18% of GNI 0,0% 0,0% 0,0% -0,0% -0,0%

Since 2016, the national accounts have been recording additional transfers from pension funds established in Belgium to non-resident affiliates. Some big international groups have actually set up pension funds in Belgium and transferred pension entitlements of workers from non-resident companies into them.

The following transactions have consequently been recorded in the national accounts:

� investment income payable on pension entitlements paid by resident pension funds to the rest of the world; � net social contributions paid by the rest of the world to the resident pension funds sector; � social benefits paid by these pension funds to the rest of the world; � an adjustment for changes in the rest of the world’s (household) pension entitlements on resident pension

funds.

These amounts are derived from the profit and loss accounts and balance sheets of cross-border pension funds established in Belgium.

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6. Revisions – labour market

6.1 Employment

Impact on salaried employment 1995 2005 2015 2016 2017Thousands of persons +0,9 +18,0 +15,5 +15,2 +27,3Percentage of salaried employment +0.0 % +0.5 % +0.4 % +0.4 % +0.7 %

Domestic employment

In the national accounts, national employment is obtained by combining domestic employment with cross-border workers. Domestic employment is itself the combination of salaried employment with self-employment. The final estimate for a given year is mainly based on administrative data from the NSSO, for those with employee status, and from the National Institute for the Social Security of the Self-employed (NISSE) for the self-employed. As a person can only be counted once, corrections have to be applied so as to avoid double-counting of workers who have both employee and self-employed status.

Corrections for double-counting have been made based on information extracted from the Labour Market and Social Protection datawarehouse run by the Crossroads Bank for Social Security (CBSS). To refine these corrections, more precise and detailed information has been obtained from the Crossroads Bank and has been be used for the benchmark revision. This new data has made it possible to adjust salaried employment in the branch of activity corresponding to the worker’s extra activity.

In accordance with the ESA 2010 requirements, salaried employment estimated on the basis of administrative sources has to be expanded by an estimate of the number of people working in the black market. This correction had already been made in the accounts published up until now, but as part of the benchmark revision, its estimation method has been revised since 2002 following the reassessment of income from undeclared work (see point 6.2).

Moreover, according to ESA 2010, national diplomatic staff posted abroad must be included in domestic salaried employment. This category of staff from Belgian embassies abroad is not included in the administrative sources used. But the benchmark revision featured in this publication has made it possible to incorporate these workers in the salaried employment estimates. The data used for this correction come from the FPS Foreign Affairs.

Lastly, the breakdown of salaried employment between the different institutional sectors has been adapted to take account of reclassifications of units in one or another sector. The most striking example is Infrabel’s reclassification under the general government sector from 2014 onwards (see point 7.2.3).

National employment

According to ESA 2010, local staff working for foreign embassies or for international institutions are considered to be cross-border workers.

As part of the benchmark revision, local staff working for Belgian embassies abroad has been added to incoming cross-border workers. This correction is made on the basis of figures provided by the FPS Foreign Affairs. Likewise, the number of outgoing cross-border workers have been supplemented by local staff working for foreign embassies in Belgium, in turn determined on the basis of data available from the NSSO. This data comes on top of the information already taken into account concerning the number of workers domiciled in countries bordering Belgium and working here (incoming cross-border workers) and the number of workers domiciled in Belgium and working in these same bordering countries (outgoing cross-border workers), as well as staff employed in international institutions established in Belgium’s geographic area. For this last group of workers, preference has been given to a new source of informations from the year 2016 onwards, namely data collected by the Institut Bruxellois de Statistique et d’Analyse (IBSA).

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6.2 Compensation of employees

Impact on the wage bill 1995 2005 2015 2016 2017EUR millions 0 +1 132 +1 568 +1 721 +2 226Percentages of the wage bill 0.0 % +0.7 % +0.8 % +0.8 % +1.0 %

Compensation of employees is mainly estimated on the basis of administratives sources, namely NSSO statistics and companies’ social balance sheets. Additional corrections are made so as to arrive at an exhaustive estimate of salaried workers’ remuneration, in line with the requirements of ESA 2010.

An initial correction aims to refine the estimate of remuneration for undeclared work in the private sector. The black economy is not covered by the administrative sources since it stems from hidden business activities or those conducted by undeclared businesses. With the changeover to ESA 2010 in 2014, new coefficients of increase for the black economy had been determined for value added with no corresponding repercussions for the estimates of undeclared wages (and employment).

The new method for estimating this black market remuneration is based on the coefficients defined for value added, while taking account of the fact that, by the very definition of undeclared work, no employer contributions, nor any payroll tax are levied. It implies an upward revision of compensation of employees, and more particularly of its “gross wages and salaries”component since 2002, for the private sector, especially in the construction, catering and wholesale, retail trade and repair branches.

Moreover, the breakdown of remuneration by branch of activity and by institutional sector has been adapted to changes in the classification of certain units, like the reclassification of Infrabel in the general government sector as of 2014 (see point 7.2.3) or the new institutional classification of private non-profit institutions (NPIs) (see point 2.6).

Lastly, the breakdown of compensation of employees between its different components (and more particularly between gross wages and social security contributions) has also been adjusted on the basis of new information about employers’ actual social contributions since 1995 (general government data), as well as employers’ imputed social contributions since 2009 for the economy as a whole (four-yearly labour costs survey dating from 2016). The share of social security contributions in compensation of employees has thus revised downwards since 2010.

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6.3 Volume of work

Impact on the volume of work 1995 2005 2015 2016 2017Millions of hours nd +80.5 +157.0 +152.5 +180.2Percentage of volume of work nd +1.2 % +2.2 % +2.1 % +2.5 %

Employees

The volume of work for employees was revised given the different revisions introduced in the employment (see section 6.1) and in the average number of hours worked by employee.

The estimation method of the volume of work of employees is not revised as such, but this benchmark revision provided an opportunity to reassess the average number of hours worked per employee per quarter. This revaluation is carried out mainly at two levels. On the one hand, as regards administrative data from the NSSO, the data relating to the number of full-time and part-time employees used to estimate the average number of hours worked for these categories of workers are now expressed as a quarterly average rather than at the end of the quarter. On the other hand, as regards the level of detail of the calculations for the public sector, given that, for the estimation of hours worked by employees in this sector, the data used to derive average hours per employee are not exhaustive (provincial and local government not being covered), the average hours per quarter are derived from the data available for the general government sector as a whole and no longer by general government sub-sector.

Self-employed

The estimation of the volume of work of the self-employed is characterised by the use of an indirect method based on the information available through the labour force survey. Thanks to this survey it is possible to estimate multiplying coefficients in order to derive the average number of hours worked by the self-employed from the average number of hours worked by employees.

The present revision gave an opportunity to re-evaluate the survey data, in particular by exploiting the detailed information collected through this survey. This re-evaluation implies a revision of the series of multipliers by branch of activity, which are now established by A38 categories and therefore at a more aggregated level than before the revision. This improves the quality of these coefficients.

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7. Revisions – general government

7.1 Changes with an impact on the balance and/or debt

7.1.1 Green certificates

Since 2002, the federal government and the three Regions have put in place a number of mechanisms designed to encourage production of renewable energy. On the one hand, certain green electricity generators receive green certificates (GC) for their production and, on the other hand, electricity suppliers are required to surrender GC allowances. In this way, a green certificate market is created, because under this obligation, electricity suppliers need to buy GCs from green electricity generators at a market price1. This system makes green electricity production more profitable.

In the green certificate mechanism, almost no cash flows transit through general government accounts. Electricity suppliers buy GCs from green electricity generators and try to pass the resultant costs on to their clients. The green certificate mechanism was nevertheless set up by law or by government Decree setting the minimum amounts involved, the duration involved and the obligations of the various parties. An important aspect of the system is compulsory redistribution, which ESA 2010 considers to be a typical government function. The green certificate mechanism is similar to a system where the public authorities themselves would subsidise green electricity generators and would levy taxes on electricity suppliers.

In some cases, the public authorities guarantee to green electricity producers a minimum price for their certificates. In practice, these minimum prices are actually guaranteed by a public services provider appointed by the government. In practice, this is the transmission or distribution system operator. The operator is obliged to buy back the green certificates at the garanteed minimum price, although it can pass on all the associated costs to its customers through its transmission or distribution fees.

To better reflect economic reality, this benchmark revision shows the full extent of the role of public institutions in the existing mechanisms by rerouting transactions and recording them in the general government accounts under subsidies and tax flows2. It has been established that the public services provider was working exclusively on behalf of the public authorities, so the transactions it has carried out are only booked in the accounts of these public authorities.

A simplified explanation of the rerouting of various flows in the general government accounts is given below.

Grants attributed to green power generators are considered as subsidies on products in ESA 2010 (D.31), as they relate to an amount per unit produced. They are recorded in the accounts at the time of production and their value corresponds to the market price of green certificates in force when they were granted.

Electricity suppliers must surrender a GC quota in proportion to the green power that they have supplied over a given period. To the extent that a link is established with the electricity supplied during a given period, the "Taxes on products, except VAT and import taxes" heading in ESA 2010 (D.214) will be used. This tax must be recorded in the accounts at the time of production, which in this case means when the electricity is supplied. To facilitate incorporation into the general government accounts, the value of the tax per GC has been equated to the average value of subsidies granted per GC.

The fact that the subsidy and the tax are booked at different times influences the general government overall balance. This time lag means that, in ESA 2010, a financial liability is recorded under the "Other accounts payable" item (F.89) on their balance sheet and a financial claim is booked under the "Other accounts receivable" item (F.89) on the balance sheet of the counterparties concerned. As the tax per GC had been equated to the average subsidy

1 Under the federal system, which grants certificates for offshore wind power production, electricity suppliers are not obliged to surrender an allocated quota. The certificates can only be sold to the transmission system operator at a fixed price.

2 This revision is based on the principle set out in ESA 2010 whereby transactions can be rearranged "in order to bring out the underlying economic relationships more clearly" (ESA 2010, § 1.72 and 1.73). In particular, they may be rerouted, or in other words reorganised, to emphasise the role of public institutions in a mechanism, for example.

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recorded per GC, the system nevertheless turns out to be neutral for the general government overall balance in the long term. This self-evident since there is no cash flow passing through government. Nor is there any impact on the gross consolidated debt (Maastricht definition) because the other accounts payable are not part of it.

Schematisch kunnen de transacties worden uitgesplitst als volgt: ◦ Period T: green power producers generate electricity and in exchange receive 100 GC each worth €70. The

subsidy granted (€7 000 ) is booked in the general government accounts and the green energy producers’ accounts at the time the green power is generated. There has not yet been any cash transaction, so that the public authorities record a liability in their balance sheet corresponding to the amount the producers have to receive. The general government overall balance is negative as a result of the subsidy being granted.

◦ Period T+1 : the green power producers sell their 100 GC to the suppliers for the price of € 70. A cash flow is recorded between the suppliers and electricity producers, removing the green power producers’ financial claim as well as the outstanding amount on the liabilities side for the general government. However, the tax is not yet due, so the purchase of the green certificates by the electricity suppliers is regarded as an advance payment to the government on the future collection of the tax. The recordings mentioned here are all of a financial nature and have no impact on the general government net lending/net borrowing.

◦ Period T+2 : the suppliers deliver the electricity for which they have to give back a quota of 100 GC to the energy regulator. The tax is presumed to have been determined at the time the electricity was supplied. The booking of the tax in the accounts implies deleting the general government’s and the electricity suppliers’ other accounts payable/receivable.

The total impact on the general government overall balance remains neutral over these different periods.

Green electricity producers General government

Expenditure Revenue

Assets Liabilities

Subsidy = +7000 Subsidy= +7000

Revenue

Assets Liabilities

Subsidy receivable= +7000

Subsidy receivable= +7000

Balance = 7000 Balance = -7000

Expenditure

General government Electricity suppliers

Expenditure Revenue

Assets Liabilities

Tax = +7000 Tax = +7000

Expenditure Revenue

Assets Liabilities

Tax pre payment = -7000 Tax pre payment = -7000

Balance = +7000 Balance = -7000

Green electricity producers General government

Expenditure Revenue

Assets Liabilities

Cash flow = +7000

Subsidy receivable = -7000

Subsidy payable = -7000

Tax pre-payment = +7000

Expenditure Revenue

Assets Liabilities

Expenditure Revenue

Assets Liabilities

Electricity suppliers

Cash flow = -7000

Tax pre-payment= +7000

Balance = 0 Balance = 0 Balance = 0

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Activating the role of the public services provider makes the accounting more complicated. Since the latter works on behalf of the government, transactions are only recorded in the general government accounts. If this services provider buys a green certificate at a minimum price, in the accounts, that means that payment of the subsidy comes directly from the government. For that, it obtains from the public services provider funding comparable to a loan, as it does not result from a distributive transaction between these parties, which therefore influences the government debt.

The public services providers are able to pass on their costs in full by applying a surcharge to their transmission or distribution fees. This surcharge is recorded in the general government accounts as a tax on production.

7.1.1.1 GREEN CERTIFICATES IN THE WALLOON REGION

Since 2003, the Walloon Region has been issuing green certificates to certain producers in proportion to their output volume and electricity suppliers have to give back a set quota of certificates each quarter. Some producers are guaranteed a minimum price of € 65 euros per certificate under a public service obligation. This task has been entrusted to the operator of the Belgian high-voltage grid. The public services provider takes the purchased green certificates off the market and in principle does not resell them. The costs associated with the public service obligation are passed on through the transmission fees.

Since 2010, the figures for subsidies granted have grown considerably; and as electricity suppliers’ quota obligations have not kept up the same pace, a surplus of green certificates has emerged on the market. The role of the public services provider has been strengthened as from 2013, sharply pushing up funding from transmission fees. In a bid to limit this effect, from 2015, the Walloon Region set up funding schemes that had the effect of taking part of the green certificates held by the transmission system operator off the market temporarily. So, these certificates do not have to be financed immediately through transmission fees. Three operations of this type have been carried out. In 2015, Solar Chest, an entity falling under the general government sector, conducted a carry trade: a loan of €275 million was contracted to buy back green certificates from Elia. A second so-called ‘temporization operation’ mobilised the funds available in public institutions to acquire green certificates. In 2018, a securitisation transaction was planned for 2019, under which green certificates have been bought back from Elia. But the compensation by means of the surcharge on transmission fees has been spread out over a longer period.

CHART A OVERVIEW OF THE IMPACT OF WALLOON GREEN CERTIFICATES ON THE GENERAL GOVERNMENT ACCOUNTS (€ millions)

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-200

-100

0

100

200

300

400

500

600

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

0

100

200

300

400

500

600

700

800

Impact on the balance

Outstanding liabilities

Tax via surrendered quotas

Tax on the transmission fees

Subsidy

Additional public debt

Already included in general government debt

Source: NAI.

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These transactions have affected the Walloon general government debt, either directly or indirectly.

Since 2014, the Solwatt system described above has been replaced by the Qualiwatt system in which GC for new facilities are replaced by investment aid, granted by the distribution system operators. This investment aid is not coupled to actual production of the plants. This expenditure is also financed by a surcharge on transmission fees. The flows caused by this system are smaller, but they are also rerouted into the general government accounts. At the moment, the investment aid is regarded as tax received.

TABLE A INVESTMENT AID RECORDED IN THE ACCOUNTS UNDER THE QUALIWATT SYSTEM (€ millions)

2014 2015 2016 2017 2018Investment aid 0.8 3.7 7.2 10.7 14.5

Source: NAI.

7.1.1.2 GREEN CERTIFICATES IN THE FLEMISH REGION

In the Flemish Region, green electricity producers have since 2002 received GC in proportion to their production volume and electricity suppliers have to surrender, by 31 March, a given quota of GC depending on the electricity they have actually delivered during the course of the previous year1. Depending on the installation year and the type of electricity production different minimum prices are guaranteed to certain producers via a public service obligation. This task has been entrusted to the distribution system operators. The allowances bought by the DSOs are not withdrawn from the market altogether as they are re-sold. The distribution system operators recover the difference between the minimum price and the sales price by applying a surcharge to their distribution fees. Between 2016 and 2018, the Flemish Community introduced an additional tax on energy enabling allowances to be taken off the market and cancelled. This tax, as well as the expenditure it helped to finance had already been incorporated into the Flemish general government accounts.

Between 2009 and 2012, the subsidies granted have tripled. Since 2013, their level has remained stable. Taxes on electricity suppliers and consumers have not risen to the same extent. The result is a considerable surplus of certificates. The Flemish public authorities have urged the system operators to keep a large part of them, which has pushed the public debt up. The introduction in 2016 of the energy tax has made it possible to take surplus green certificates off the market and reduce the general government debt.

1 In the Flemish Region, besides the GC system, there is also a separate mechanism for cogeneration certificates. The figures given in this part refer to the total for the two systems.

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Since 2003, besides the GC system, the Flemish government has required the distribution system operators to give grants to households making energy-saving investment (replacement of windows, insulation, etc.). These grants have in large part been financed by the distribution fee, but in recent years, they have also been funded directly from the budget. Like the GC, these flows have been fully incoporated into the Flemish general government accounts under the benchmark revision.

TABLE B INVESTMENT AID GRANTED BY DISTRIBUTION SYSTEM OPERATORS AND MEANS OF FUNDING(€ millions)

Investment aid Funded by the distribution fee Funded via the Flemish budget2003 8.8 8.82004 13.2 13.22005 15.3 15.32006 12.7 12.72007 25.4 25.42008 40.6 40.62009 54.1 54.12010 53.9 51.5 2.42011 64.7 57.8 6.92012 77.4 42.9 34.62013 128.6 70.2 58.42014 80.3 23.7 56.62015 103.3 101.6 1.82016 102.8 100.9 1.9

2017 90.6 84.9 5.72018 65.8 3.9 61.9

Source: NAI.

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-400

-200

0

200

400

600

800

1000

1200

1400

1600

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-200

0

200

400

600

800

1000

1200

Funding by energy tax

Tax via surrendered quotas

Tax on distribution fees

Subsidy

Extra public debtImpact on the balance

Outstanding liabilities

Source: NAI.

CHART B OVERVIEW OF THE IMPACT OF FLEMISH GREEN CERTIFICATES ON THE GENERAL GOVERNMENT ACCOUNTS (€ millions)

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7.1.1.3 GREEN CERTIFICATES IN THE BRUSSELS-CAPITAL REGION

In the Brussels-Capital Region, green power producers have received green certificates since 2005 in proportion to their production volume. By 31 March, electricity suppliers have to surrender a fixed quota of GC, depending on how much electricity that they have actally delivered during the previous year. The minimum price system has never been applicable in the Brussels-Capital Region, because there has been no surplus supply on the market.

As the role of the public services provider was never activated, there has been no impact on the public debt. Only additional financial liabilities under Other accounts payable (F.89) are recorded.

7.1.1.4 GREEN CERTIFICATES FOR THE FEDERAL GOVERNMENT

The federal government grants green certificates for offshore electricity production. These rights do not have to be surrendered by the electricity suppliers and so there is no market for these certificates. Offshore producers receive green certificates and sell them on at a given minimum price to the high-tension network operator, which removes the green certificates rights and passes on the costs in its transmission fees.

The extra impact on the public debt is very small because no limit has been set for any repercussions on the transmission fees. In most years, net pre-funding is recorded for the public services supplier.

CHART C OVERVIEW OF THE IMPACT OF BRUSSELS GC ON THE GENERAL GOVERNMENT ACCOUNTS(€ millions)

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-10

0

10

20

30

40

50

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-6

-4

-2

0

2

4

6

Outstanding liabilities

Tax via surrendered quotas

Subsidy

Impact on the balance

Source: NAI.

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7.1.2 Social Maribel – local government

In the past, there were no details at all available to identify the the share of Social Maribel subsidies that went into local government (S.1313). Almost all these wage subsidies were recorded as being intended for the non-financial corporations sector (S.11). As part of the benchmark revision, the NAI received the list of beneficiaries of these subsidies. These details showed higher-than-predicted Social Maribel subsidies for local government (S.1313). As for the total level of Social Maribel subsidies paid by social security funds (S.1314), nothing changes; only the counterparties of the transaction are changed: more subsidies for local government and less subsidies for non-financial corporations. As the transfers from higher authorities determine the revenue recorded for local government, the Social Maribel subsidies they received increase and their overall balance has improved.

7.1.3 Health care expenditure by NIHDI

In the case of social benefits for health care payable by the National Institute for Health and Disability Insurance (NIHDI or INAMI-RIZIV), the expenses recorded in the NIHDI’s public accounts have been replaced by the expenses corresponding to the services rendered, which are only available in t+25 months and are not accounting data, but only statistical data. This correction had already been applied in the last few years’ accounts. It has now been extended to cover the whole period starting from 1995.

CHART D OVERVIEW OF THE IMPACT OF OF THE FEDERAL GC SYSTEM ON THE GENERAL GOVERNMENT ACCOUNTS

(€ millions)

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

-50

0

50

100

150

200

250

300

350

Tax on transmission fee

Subsidy

Balance

Source: NAI.

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7.2 Changes having an impact on the level of revenue and expenditure (but not on the balance)

7.2.1 VAT on electronic services (2015-2018 transition period)

This revision point concerns the inclusion of a Mini One Stop Shop (MOSS) for VAT, in force since 1 January 2015.

Up to and including 31 December 2014, EU suppliers of electronic services, telecommunications services, as well as radio and television broadcasting services declared and paid VAT in their country of residence.

As of 1 January 2015, companies have to pay VAT in the Member State where the customer is resident. This means that a supplier has to pay VAT in each Member State where its customers are established, regardless of where the service provider is resident. The targeted services are those provided to final consumers, that is, private individuals, public services, municipalities and others exempt from VAT1.

The objective of this Directive is to bring treatment of VAT on these services into line with one of the main principles of VAT whereby, as a consumer tax, the revenue must accrue to the Member State in which the goods or services are consumed. Up until the end of 2014, deliveries from EU-based firms to final consumers were taxed in the supplier’s country. In other words, for deliveries made to final consumers, firms established in Member States applying lower VAT rates had a competitive advantage over firms established in other Member States.

In practice, companies do not send the VAT proceeds to each country concerned, but continue to pay VAT through a "one-stop shop", which channels the proceeds of the tax between countries.

A transitional period from 2015 to 2018 was arranged, during which the country where the one-stop shop was located could keep a fraction of the VAT levied over this period. This degressive system was wound up at the end of 2018.

It was agreed that the retained part of the VAT on e-services (during the 2015-2018 transition period) should be recorded as a VAT receipt and also as expenditure under "Current international cooperation" (D.74) in the beneficiary country and as revenue under "Current international cooperation" (D.74) in the host country. This method of recording has a limited upward impact on GDP and GNI.

7.2.2 Social Maribel

The objective of Social Maribel is to promote employment, especially in the non-market sector, by creating extra jobs. In reality, this is an employment subsidy that is unusual in that it is partly financed by a refund of employers’ contributions, that is paid back by the NSSO into the sectoral Maribel Funds. The establishment of the first Social Maribel Plan dates back to 1997.

In theory, on top of the structural reduction, each employer falling within the scope of the scheme has the right to a flat-rate refund from NSSO contributions for each worker who works at least one part-time job over a quarter. Unlike other reductions in contributions, the Social Maribel reduction is not granted directly to employers, but is transferred by the NSSO to the different Social Maribel funds. These are referred to as allocations made by the NSSO into the sectoral Maribel Funds.

All employers in sectors concerned by Social Maribel may request funding for one or more additional jobs, but it is the Management Committee of each Maribel Fund that then decides to grant certain companies a financial allowance for new job creations under the conditions and procedures stipulated by the Fund in question. So, this is effectively an indirect and conditional reduction in social contributions since the employer does not benefit directly and systematically from this intervention.

1 This change is the result of amendments made to the rules governing the place of supply of services in the EU VAT system adopted in 2008 as part of the "VAT package" (Council Directive 2008/8/EC of 12 February 2008 amending Directive 2006/112/EC as regards the place of supply of services).

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Besides the financing by means of employers’ social security contributions, the Maribel Funds have received resources through Fiscal Maribel since 2002. This is a part of payroll tax allocated to the scheme. This system does not apply to sheltered workshops or to the government. However, in these two cases, there is some form of compensation via a withdrawal on the global management of social security (Fiscal Maribel for the public sector).

In the national accounts, for compensation of employees (D.1), employers’ social security contributions under Social Maribel are recorded correctly in employers’ actual social contributions (D.121), given that these flat-rate reductions are not treated as structural reductions in employers’ contributions. The amounts that employers benefit from are recorded as expenditure on other subsidies on production (D.39).

The Central Economic Council (CEC) obtained from the NSSO detailed figures for Social Maribel and reached the conclusion that the subsidy under Social Maribel for the economy as a whole calculated by the National Accounts Institute (NAI) on the basis of aggregate data received from FPS Social Security contained a number of elements that were either recorded twice, or should not have been there. Corrections have been applied, wherever necessary.

7.2.3 Consolidation of Infrabel

In September 2018, the NAI decided to consolidate Infrabel in the general government sector as from the year 2014.

In order to limit any inconvenience for users of national accounts data following the re-sectorisation of Infrabel, a choice had been made to not initially make all the changes for the different series of revenue and expenditure in the general government non-financial accounts, but to incorporate them fully, on a net basis, into other capital transfers payable to non-financial corporations. In this way, the general government overall balance was as accurate as possible, but the main economic aggregates (GDP, compensation of employees, etc.) were not affected by these changes. It should also be pointed out that public-debt-related recordings had been made in the general government financial accounts, while those concerning financial assets had only been partially made.

The opportunity of the 2019 benchmark revision has been used to correctly insert the changes related to the reclassification of Infrabel over the period 2014-2018 into the full sequence of national accounts.

7.2.4 Pension fund-related transactions

As a reminder, pension funds managing the statutory pensions of officials from units belonging to the general government sector (S.13) are also included in the delineation of general government (S.13). The pension funds concerned are: VRT pensioenfonds and Provincie Oost-Vlaanderen pensioenfonds.

With the switchover to ESA 2010, the following transactions: Households’ social contribution supplements (D.614), Investment income attributable to insurance policy-holders (D.441), Social insurance scheme service charges (D.61SC) and Payments for non-market output (P.131), had not been recorded correctly. Following Eurostat’s recommendations, the amounts in question have been adjusted.

7.2.5 Sales of trees by local governments

Production of standing timber is treated as an increase in stocks en cours during the production process (while the trees are growing), generating a net operating surplus. The sale of trees is thus recorded as a stock decrease.

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7.3 Changes having an impact on the breakdown of revenue and expenditure (but not on their level)

7.3.1 VAT due but not recoverable as a result of bankruptcies

Previously, VAT revenue had been estimated using method b) set out in paragraph 4.27 of ESA 2010: if cash receipts are used as the source, they shall be time-adjusted so that the sums in question are attributed to the period when the activity took place to generate the tax liability. This adjustment is based on the average time difference between the activity and cash tax receipt. In practice, this means that VAT cash receipts had been recorded under the so-called month-on-month transactionalised cash basis method.

Eurostat’s GNI expert group reached the conclusion that the value of VAT due but not recoverable following bankruptcies should be included in the estimate of GDP, which effectively boiled down to imposing method a) of paragraph 4.27 of ESA 2010 and the option of cancellation through a capital transfer: if assessments and declarations are used as the source, the amounts shall be adjusted by a coefficient reflecting assessed and declared amounts never collected. An alternative treatment is that a capital transfer (D.995), as described in point (j) of paragraph 4.165, to the relevant sectors is recorded equal to the same adjustment.

In accordance with paragraphs 4.27 and 4.165, point j) of ESA 2010 and upon recommendation of the GNI expert group, it follows that, if assessments and declarations are used as the source so as to reflect due and declared amounts that are never collected, the amount in question is also recorded as a capital transfer (D.995) to the debtor sectors concerned.

In practice, it has not been possible to reconcile declarations and cash receipts for VAT: it is the transactionalised cash sum that has been increased by an estimate of VAT revenue not collected as a result of bankruptcies, with the estimate being cancelled out simultaneously in the accounts sequence via the recording of a negative capital transfer receivable in accordance with the ESA 2010 transmission programme.

7.3.2 Payroll tax due but not recoverable as a result of bankruptcies

Likewise, payroll tax revenue had been estimated using method b) set out in paragraph 4.82 of ESA 2010: if cash receipts are used as the source, they are time-adjusted so that the sums in question are attributed to the period when the activity, transactions or other events took place to generate the tax liability (or when the amount of tax was determined, in the case of some income taxes). This adjustment is based on the average time difference between the activities, transactions or other events (or the determination of the amount of tax) and cash tax receipt. In practice, this means that payroll tax cash receipts had been recorded under the so-called month-on-month transactionalised cash basis method.

Paragraph 4.82 of ESA 2010 states that: "When retained at source by an employer, current taxes on income, wealth, etc. are included in wages and salaries even if the employer did not pass them on to the general government. The households sector is shown as paying the full amount to the general government sector. The amounts actually unpaid are neutralised under D.995 as a capital transfer from general government to the employers' sectors".

To comply with the stipulations of ESA 2010 and not over-estimate households’ disposable income, an estimate of payroll tax revenue due but not recoverable following bankruptcies has been added to the transactionalised cash sum, with the estimate being cancelled out simultaneously in the accounts sequence via the recording of a negative capital transfer receipt in accordance with the ESA 2010 transmission programme.

7.3.3 Social contributions due but not recoverable as a result of bankruptcies

Up until now, revenue from social security contributions had been estimated using method a) set out in paragraph 4.95 of ESA 2010: If assessments and declarations are used as the source, the amounts are adjusted with the help of a coefficient enabling account to be taken of amounts that have been assessed and declared but never collected.

44

Paragraph 4.95 of ESA 2010 states that: "When retained at source by the employer, social contributions payable to the general government sector are included in wages and salaries irrespective of whether the employer passed them to the general government. The household sector is then shown as paying the full amount to the general government sector. The amounts actually unpaid are neutralised under D.995 as a capital transfer from general government to the employers' sectors."

To comply with the stipulations of ESA 2010 and not over-estimate households’ disposable income, method a) of paragraph 4.95 of ESA 2010 and the option of cancellation through a capital transfer have now been chosen: An alternative solution would be to record a capital transfer to the relevant sectors equal to the same adjustment.

7.3.4 Other changes

The benchmark revision 2019 has served as an opportunity to correct the economic nature of certain transactions: for instance, the breakdown of recurrent expenditure for education in the Flemish Community between remunerations and current purchases of goods and services has been revised for certain years, expenditure by the NIHDI (INAMI) relating to payroll harmonisation and final salaries of staff employed in residential care and nursing homes/old people’s homes have been reclassified from social benefits in kind to wage subsidies, etc. In addition, transactions in products between municipalities and the inter-municipal waste management companies have been consolidated because they more closely resemble transfers between governments than sales as they do not meet the qualitative criterion (not obtained via public tenders).

45

46

8. Quantified impact of the revisions

8.1 Reference year 2015

TABLEAU 1 EFFET DES RÉVISIONS SUR LE PIB (OPTIQUE DE LA PRODUCTION)(2015, en millions d’euros, prix courants)

en niveau en % du PIB avant révision

Administrateurs de sociétés +1 792 +0,4 %

Services de logement +799 +0,2 %

Services d'assurance +1 812 +0,4 %

Services hospitaliers -467 -0,1 %

R&D -296 -0,1 %

Test marchand/non marchand -466 -0,1 %

Production d’électricité par les ménages +557 +0,1 %

SIFIM +796 +0,2 %

Reclassement sectoriel d'Infrabel +619 +0,2 %

Autres révisions de la valeur ajoutée -614 -0,1 %

Impôts moins subventions sur la production et les importations +1 160 +0,3 %

Total +5 691 +1,4 %

Source : ICN.

TABLEAU 2 RÉVISION DE LA VALEUR AJOUTÉE BRUTE DES SECTEURS INSTITUTIONNELS(2015, en millions d’euros, prix courants)

Révision Part dans le PIB

Avant révision

(sept. 2018)

en niveau en % de l’agrégat

avant révision

Après révision

(sept. 2019)

Avant révision

(sept. 2018)

Aprèsrévision

(sept. 2019)

Sociétés non financières (S.11) 227 656 -2 342 -1,0 % 225 315 55,4 % 54,1 %

Sociétés financières (S.12) 22 653 +1 544 +6,8 % 24 197 5,5 % 5,8 %

Administrations publiques (S.13) 59 762 +1 456 +2,4 % 61 218 14,5 % 14,7 %

Ménages (S.14) 54 528 +4 701 +8,6 % 59 229 13,3 % 14,2 %

Institutions sans but lucratif au service des ménages (S.15) 3 508 -164 -4,7 % 3 344 0,9 % 0,8 %

Ensemble des secteurs institutionnels 368 107 +5 195 +1,4 % 373 302 89,6 % 89,6 %

Impôts sur les produits moins subventions sur les produits 42 904 +496 +1,2 % 43 400 10,4 % 10,4 %

Produit intérieur brut 411 010 +5 691 +1,4 % 416 701 100,0 % 100,0 %

Source : ICN.

47

TABLEAU 3 RÉVISION DE LA VALEUR AJOUTÉE BRUTE PAR BRANCHE D’ACTIVITÉ (2015, en millions d’euros, prix courants)

Révision Part dans le PIB

Avant révision

(sept. 2018)en niveau

en % de l’agrégat

avant révision

Après révision

(sept. 2019)

Avant révision

(sept. 2018)

Aprèsrévision

(sept. 2019

Agriculture, sylviculture et pêche 2 873 -12 -0,4 % 2 860 0,8 % 0,8 %

Industrie manufacturière, industries extractives et autres 61 584 +1 086 +1,8 % 62 671 16,7 % 16,8 %

Construction 19 682 -388 -2,0 % 19 294 5,3 % 5,2 %

Commerce de gros et de détail, transports, hôtels et restaurants 72 429 +457 +0,6 % 72 886 19,7 % 19,5 %

Information et communication 15 196 +118 +0,8 % 15 314 4,1 % 4,1 %

Activités financières et d’assurance 22 168 +1 523 +6,9 % 23 690 6,0 % 6,3 %

Activités immobilières 31 892 +1 930 +6,1 % 33 821 8,7 % 9,1 %

Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien

52 097 +2 127 +4,1 % 54 224 14,2 % 14,5 %

Administration publique, défense, enseignement, santé humaine et action sociale

81 861 -966 -1,2 % 80 895 22,2 % 21,7 %

Autres activités de services 8 326 -679 -8,2 % 7 647 2,3 % 2,0 %

Total 368 107 +5 195 +1,4 % 373 302 100,0 % 100,0 %

Source : ICN.

TABLEAU 4 RÉVISION DES AGRÉGATS DANS L’OPTIQUE DES DÉPENSES(2015, en millions d’euros, prix courants)

Révision Part dans le PIB

Avant révision (sept. 2018) en niveau

en % de l’agrégat avant

révision

Après révision (sept. 2019)

Avant révision (sept. 2018)

Après révision (sept. 2019)

Produit intérieur brut 411 010 +5 691 +1,4 % 416 701 100,0 % 100,0 %

Dépenses de consommation finale 308 073 +4 262 +1,4 % 312 335 75,0 % 75,0 %

Ménages 204 866 +4 661 +2,3 % 209 527 49,8 % 50,3 %

Administrations publiques 98 051 +354 +0,4 % 98 404 23,9 % 23,6 %

ISBL au service des ménages 5 156 -753 -14,6 % 4 403 1,3 % 1,1 %

Formation brute de capital fixe 94 980 +709 +0,7 % 95 689 23,1 % 23,0 %

Ménages 23 363 -952 -4,1 % 22 411 5,7 % 5,4 %

Sociétés 61 666 +889 +1,4 % 62 555 15,0 % 15,0 %

Administrations publiques 9 459 +928 +9,8 % 10 388 2,3 % 2,5 %

ISBL au service des ménages 492 -156 -31,7 % 336 0,1 % 0,1 %

Exportations nettes de biens et services 5 864 +45 +0,8 % 5 909 1,4 % 1,4 %

Exportations 332 094 -7 878 -2,4 % 324 216 80,8 % 77,8 %

Importations 326 230 -7 923 -2,4 % 318 307 79,4 % 76,4 %

Variations de stocks 2 094 +676 +32,3 % 2 769 0,5 % 0,7 %

Source : ICN.

48

TABLEAU 6 RÉVISION DES SOLDES DES SECTEURS INSTITUTIONNELS(2015, prix courants)

Avant révision (sept. 2018) Révision Après révision

(sept. 2019)

en millions d’euros

Ensemble des sociétés 5 209 +5 421 10 630

Sociétés non financières -1 414 +4 948 3 534

Sociétés financières 6 623 +474 7 097

Administrations publiques -10 076 +18 -10 058

Ménages 1 666 +3 470 5 136

Institutions sans but lucratif au service des ménages 119 -5 114

Ensemble des secteurs institutionnels -3 081 +8 904 5 823

en p.c. du PIB

Ensemble des sociétés 1,3 +1,3 2,6

Sociétés non financières -0,3 +1,2 0,8

Sociétés financières 1,6 +0,1 1,7

Administrations publiques -2,5 0,0 -2,4

Ménages 0,4 +0,8 1,2

Institutions sans but lucratif au service des ménages 0,0 0,0 0,0

Ensemble des secteurs institutionnels -0,7 +2,1 1,4

Source : ICN.

TABLEAU 5 RÉVISION DES AGRÉGATS DANS L’OPTIQUE DES REVENUS(2015, en millions d’euros, prix courants)

Révision Part dans le PIB

Avant révision

(sept. 2018)

en niveau en % de l’agrégat avant révision

Après révision

(sept. 2019)

Avant révision

(sept. 2018)

Après révision

(sept. 2019)

Produit intérieur brut 411 010 +5 691 +1,4 % 416 701 100,0 % 100,0 %

Rémunérations des salariés 206 560 +1 568 +0,8 % 208 128 50,3 % 49,9 %

Impôts moins subventions sur la production et les importations 39 705 +418 +1,1 % 40 123 9,7 % 9,6 %

Excédent brut d'exploitation et revenu mixte brut 164 745 +3 705 +2,2 % 168 451 40,1 % 40,4 %

Source : ICN.

49

TABLEAU 8 RÉVISION DE L’EMPLOI INTÉRIEUR(2015, milliers de personnes)

Révision

Avant révision (sept. 2018) en niveau en % de l’agrégat

avant révisionAprès révision

(sept. 2019)

Emploi salarié 3 835,6 +15,5 +0,4 % 3 851,1

Agriculture, sylviculture et pêche 22,7 +0,3 +1,3 % 23,0

Industrie manufacturière, industries extractives et autres 526,0 +1,6 +0,3 % 527,6

Construction 201,2 +5,0 +2,5 % 206,2

Services (marchands) 2 275,1 +5,4 +0,2 % 2 280,5

Services publics 810,5 +3,3 +0,4 % 813,8

Emploi indépendant 765,1 +1,2 +0,2 % 766,3

Total emploi 4 600,7 +16,7 +0,4 % 4 617,4

Source : ICN.

TABLEAU 7 RÉVISION DU REVENU NATIONAL BRUT(2015, en millions d’euros, prix courants)

Révision

Avant révision (sept. 2018) en niveau en % de l’agrégat

avant révisionAprès révision

(sept. 2019)

Produit intérieur brut 411 010 +5 691 +1,4 % 416 701

Solde des revenus primaires avec le reste du monde -2 234 +8 131 -364,0 % 5 897

Rémunérations nettes1 des salariés 5 899 +409 +6,9 % 6 308

Impôts versés nets des subventions reçues -907 -7 +0,7 % -913

Revenus nets1 de la propriété -7 226 +7 729 -107,0 % 503

Revenu national brut 408 777 +13 822 +3,4 % 422 599

Source : ICN.1 Le terme "net" signifie qu’il s’agit de la différence entre les revenus qui sont reçus du reste du monde et ceux qui sont versés au reste du monde.

50

TABL

EAU

9

INC

IDEN

CE

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 S

UR

LE

PIB

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

PIB

à p

rix c

oura

nts

(mill

ions

d'e

uros

)Av

ant r

évis

ion

211

616

215

942

225

969

234

490

244

226

258

222

265

788

275

065

282

637

298

711

311

481

Aprè

s ré

visi

on21

0 48

921

4 28

722

4 10

223

2 62

424

2 30

825

6 37

626

4 33

527

3 25

628

1 20

029

6 82

031

0 03

8

Écar

t-1

127

-1 6

55-1

867

-1 8

66-1

918

-1 8

46-1

453

-1 8

09-1

436

-1 8

91-1

443

Cro

issa

nce

du P

IB e

n va

leur

(pou

rcen

tage

s)A v

ant r

évis

ion

2,0

4,6

3,8

4,2

5,7

2,9

3,5

2,8

5,7

4,3

Aprè

s ré

visi

on1,

84,

63,

84,

25,

83,

13,

42,

95,

64,

5

Écar

t-0

,2-0

,10,

00,

00,

10,

2-0

,10,

2-0

,10,

2

PIB

en

volu

me

(mill

ions

d'e

uros

1 )Av

ant r

évis

ion

288

250

292

843

303

709

309

708

320

744

332

399

335

096

341

063

343

704

356

197

363

657

Aprè

s ré

visi

on28

6 26

329

0 04

630

1 04

930

6 95

531

7 83

032

9 64

233

3 26

733

8 95

634

2 47

435

4 70

436

2 94

0

Écar

t-1

988

-2 7

98-2

660

-2 7

53-2

914

-2 7

56-1

829

-2 1

07-1

230

-1 4

93-7

17

Cro

issa

nce

du P

IB e

n vo

lum

e (p

ourc

enta

ges)

Avan

t rév

isio

n1,

63,

72,

03,

63,

60,

81,

80,

83,

62,

1Ap

rès

révi

sion

1,3

3,8

2,0

3,5

3,7

1,1

1,7

1,0

3,6

2,3

Éc

art

-0,3

0,1

0,0

0,0

0,1

0,3

-0,1

0,3

-0,1

0,2

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

PIB

à p

rix c

oura

nts

(mill

ions

d'e

uros

)Av

ant r

évis

ion

326

662

344

713

354

066

348

781

365

101

379

106

387

500

392

340

400

087

411

010

424

660

439

052

Aprè

s ré

visi

on32

5 15

234

3 61

935

1 74

334

6 47

336

3 14

037

5 96

838

6 17

539

2 88

040

3 00

341

6 70

143

0 37

244

6 36

5

Écar

t-1

511

-1 0

94-2

323

-2 3

08-1

960

-3 1

38-1

325

+540

+2 9

17+5

691

+5 7

12+7

313

Cro

issa

nce

du P

IB e

n va

leur

(pou

rcen

tage

s)Av

ant r

évis

ion

4,9

5,5

2,7

-1,5

4,7

3,8

2,2

1,2

2,0

2,7

3,3

3,4

Aprè

s ré

visi

on4,

95,

72,

4-1

,54,

83,

52,

71,

72,

63,

43,

33,

7

Écar

t0,

00,

2-0

,30,

00,

1-0

,30,

50,

50,

60,

70,

00,

3

PIB

en

volu

me

(mill

ions

d'e

uros

1 )Av

ant r

évis

ion

372

770

385

627

388

647

379

890

390

315

397

334

398

267

399

067

404

074

411

010

417

129

424

190

Aprè

s ré

visi

on37

2 20

338

5 88

938

7 61

337

9 78

139

0 65

939

7 27

840

0 21

540

2 05

340

8 40

041

6 70

142

2 99

843

1 30

7

Écar

t-5

67+2

61-1

034

-110

+343

-56

+1 9

48+2

986

+4 3

26+5

691

+5 8

69+7

116

Cro

issa

nce

du P

IB e

n vo

lum

e (p

ourc

enta

ges)

Avan

t rév

isio

n2,

53,

40,

8-2

,32,

71,

80,

20,

21,

31,

71,

51,

7Ap

rès

révi

sion

2,6

3,7

0,4

-2,0

2,9

1,7

0,7

0,5

1,6

2,0

1,5

2,0

Éc

art

0,0

0,2

-0,3

0,2

0,1

-0,1

0,5

0,3

0,3

0,3

0,0

0,3

Sour

ce : I

CN

.1

Euro

s ch

aîné

s - A

nnée

de

réfe

renc

e 20

15.

8.2 Long series 1995-2017

51

TABL

EAU

10

INC

IDEN

CE

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 S

ELO

N L

ES T

RO

IS O

PTIQ

UES

DU

PIB

(prix

cou

rant

s, m

illio

ns d

’eur

os)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Opt

ique

de

la p

rodu

ctio

n

Prod

uctio

n-9

98-1

552

-1 5

50-1

582

-1 5

15-1

172

-1 1

51-1

081

-1 3

04-1

653

-691

C

onso

mm

atio

n in

term

édia

ire (-

)28

926

635

744

145

069

264

394

964

354

697

5

Vale

ur a

jout

ée, é

cono

mie

tota

le-1

287

-1 8

18-1

908

-2 0

23-1

965

-1 8

64-1

794

-2 0

30-1

947

-2 1

99-1

666

Im

pôts

net

s de

s su

bven

tions

sur

les

prod

uits

160

163

4115

747

1834

122

151

130

822

3

PI

B-1

127

-1 6

55-1

867

-1 8

66-1

918

-1 8

46-1

453

-1 8

09-1

436

-1 8

91-1

443

Opt

ique

des

dép

ense

s

Con

som

mat

ion

final

e de

s ad

min

istra

tions

pub

lique

s11

510

247

165

242

40-2

1721

252

64-3

62

Con

som

mat

ion

final

e de

s m

énag

es e

t des

ISBL

au

serv

ice

des

mén

ages

-1 6

98-2

009

-2 4

70-2

160

-1 9

72-1

987

-1 7

65-1

972

-1 8

44-2

522

-2 0

58

Inve

stis

sem

ents

des

soc

iété

s7

-59

-9-2

1-2

319

117

935

252

564

448

4

Inve

stis

sem

ents

des

adm

inis

tratio

ns p

ubliq

ues

-185

-201

-241

-244

-261

-172

-186

-191

-202

-218

-223

In

vest

isse

men

ts d

es m

énag

es e

t des

ISBL

au

serv

ice

des

mén

ages

-275

-337

-376

-507

-373

-391

-385

-439

-463

-504

-593

Va

riatio

ns d

e st

ocks

135

153

221

196

164

-65

174

131

133

163

213

Ex

porta

tions

net

tes

de b

iens

et s

ervi

ces

774

696

961

705

305

537

746

9936

348

11

095

PI

B-1

127

-1 6

55-1

867

-1 8

66-1

918

-1 8

46-1

454

-1 8

09-1

436

-1 8

91-1

443

Opt

ique

des

reve

nus

R

émun

érat

ions

des

sal

arié

s1

10

01

4245

1 07

21

101

1 11

71

132

Im

pôts

net

s de

s su

bven

tions

sur

la p

rodu

ctio

n et

les

impo

rtatio

ns30

931

419

531

520

818

250

338

762

939

218

6

Excé

dent

bru

t d'e

xplo

itatio

n et

reve

nu m

ixte

bru

t-1

436

-1 9

70-2

063

-2 1

81-2

127

-2 0

70-2

001

-3 2

69-3

167

-3 4

00-2

761

PI

B-1

127

-1 6

55-1

867

-1 8

66-1

918

-1 8

46-1

453

-1 8

09-1

436

-1 8

91-1

443

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Opt

ique

de

la p

rodu

ctio

n

Prod

uctio

n-1

233

-570

-1 8

10-3

986

-1 7

59-2

5588

4-2

001

481

4 77

31

005

58

Con

som

mat

ion

inte

rméd

iaire

(-)

570

801

1 21

4-9

0242

73

279

2 51

4-2

92-1

037

-422

-3 8

92-6

200

Va

leur

ajo

utée

, éco

nom

ie to

tale

-1 8

03-1

371

-3 0

25-3

084

-2 1

87-3

534

-1 6

3092

2 51

85

195

4 89

76

258

Im

pôts

net

s de

s su

bven

tions

sur

les

prod

uits

293

277

702

1 00

652

479

070

11

089

1 18

21

160

2 18

12

556

PI

B-1

511

-1 0

94-2

323

-2 0

78-1

662

-2 7

44-9

291

181

3 69

96

355

7 07

78

813

Opt

ique

des

dép

ense

s

Con

som

mat

ion

final

e de

s ad

min

istra

tions

pub

lique

s-1

79-1

35-1

3137

184

291

-157

-567

315

354

648

773

C

onso

mm

atio

n fin

ale

des

mén

ages

et d

es IS

BL a

u se

rvic

e de

s m

énag

es-2

216

-2 2

74-2

973

-3 5

53-2

901

-2 2

86-5

881

725

2 05

33

908

3 68

65

678

In

vest

isse

men

ts d

es s

ocié

tés

464

720

792

1 06

31

593

1 98

31

842

984

-435

889

1 08

662

9

Inve

stis

sem

ents

des

adm

inis

tratio

ns p

ubliq

ues

-206

-213

-242

-231

-246

-280

-51

-114

961

928

1 05

194

8

Inve

stis

sem

ents

des

mén

ages

et d

es IS

BL a

u se

rvic

e de

s m

énag

es-6

60-5

63-6

03-6

70-6

70-8

00-7

90-7

00-7

80-1

108

-1 3

66-1

561

Va

riatio

ns d

e st

ocks

322

323

180

1 10

245

728

856

695

139

676

1 11

1-2

61

Expo

rtatio

ns n

ette

s de

bie

ns e

t ser

vice

s96

51

048

653

-55

-378

-2 3

34-2

147

-1 7

3876

345

-504

1 10

7

PI

B-1

511

-1 0

94-2

323

-2 3

08-1

960

-3 1

38-1

325

540

2 91

75

691

5 71

27

313

Opt

ique

des

reve

nus

R

émun

érat

ions

des

sal

arié

s1

153

1 21

01

267

1 28

21

482

1 54

51

501

1 33

41

323

1 56

81

721

2 22

6

Impô

ts n

ets

des

subv

entio

ns s

ur la

pro

duct

ion

et le

s im

porta

tions

210

185

638

869

369

604

468

486

444

418

968

1 14

2

Excé

dent

bru

t d'e

xplo

itatio

n et

reve

nu m

ixte

bru

t-2

874

-2 4

89-4

228

-4 4

60-3

812

-5 2

87-3

294

-1 2

801

150

3 70

53

024

3 94

5

PI

B-1

511

-1 0

94-2

323

-2 3

08-1

960

-3 1

38-1

325

540

2 91

75

691

5 71

27

313

Sour

ce : I

CN

.

52

TABL

EAU

11

PRIN

CIP

AUX

ÉLÉM

ENTS

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 -

OPT

IQU

E D

E LA

PR

OD

UC

TIO

N(p

rix c

oura

nts,

mill

ions

d’e

uros

)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Adm

inis

trate

urs

de s

ocié

tés

802

802

802

943

1 15

393

81

009

1 06

11

080

1 19

61

310

Serv

ices

de

loge

men

t-1

462

-1 6

04-1

764

-1 8

84-1

998

-2 1

51-2

125

-2 2

75-2

373

-2 4

86-1

909

Serv

ices

d'a

ssur

ance

343

-38

107

5815

824

-46

-65

-305

-85

-172

Serv

ices

hos

pita

liers

-229

-234

-234

-243

-258

-269

-300

-317

-309

-316

-327

R&D

-785

-767

-805

-900

-968

-203

-261

-378

52-7

4-5

8Te

st m

arch

and/

non

mar

chan

d0

00

00

00

00

00

Prod

uctio

n d'

élec

trici

té p

ar le

s m

énag

es0

00

00

00

00

00

SIFI

M0

00

00

00

00

00

Rec

lass

emen

t sec

torie

l d'In

frabe

l0

00

00

00

00

00

Autre

s ré

visi

ons

de la

val

eur a

jout

ée1

4424

-14

3-5

3-2

02-7

1-5

6-9

3-4

34-5

11

Vale

ur a

jout

ée, é

cono

mie

tota

le-1

287

-1 8

18-1

908

-2 0

23-1

965

-1 8

64-1

794

-2 0

30-1

947

-2 1

99-1

666

Impô

ts m

oins

sub

vent

ions

sur

la p

rodu

ctio

n et

les

impo

rtatio

ns16

016

341

157

4718

341

221

511

308

223

PIB

-1 1

27-1

655

-1 8

67-1

866

-1 9

18-1

846

-1 4

53-1

809

-1 4

36-1

891

-1 4

43

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Adm

inis

trate

urs

de s

ocié

tés

1 37

41

557

1 46

51

515

1 49

31

465

1 48

71

635

1 76

01

792

1 99

82

044

Serv

ices

de

loge

men

t-1

812

-1 9

23-2

175

-2 1

20-1

551

-462

621

1 16

872

279

976

01

354

Serv

ices

d'a

ssur

ance

6018

6-3

75-5

327

3-7

54-3

5073

91

174

1 81

288

648

Serv

ices

hos

pita

liers

-398

-453

-525

-459

-383

-433

-482

-501

-556

-467

-689

-687

R&D

-722

-191

-1 1

64-1

96-9

920

8-4

840

43-2

96-8

45-1

26Te

st m

arch

and/

non

mar

chan

d0

00

-420

-393

-487

-124

-431

-859

-466

-446

-297

Prod

uctio

n d'

élec

trici

té p

ar le

s m

énag

es0

00

8924

240

257

760

463

455

754

953

5SI

FIM

00

04

-767

-2 2

99-2

185

-1 4

5417

679

61

250

1 47

3R

ecla

ssem

ent s

ecto

riel d

'Infra

bel

00

00

00

00

507

619

587

637

Autre

s ré

visi

ons

de la

val

eur a

jout

ée1

-305

-546

-251

-1 6

75-1

299

-1 5

68-1

521

-2 3

49-1

866

-614

280

-824

Vale

ur a

jout

ée, é

cono

mie

tota

le-1

803

-1 3

71-3

025

-3 3

14-2

485

-3 9

28-2

026

-549

1 73

54

532

3 53

14

758

Impô

ts m

oins

sub

vent

ions

sur

la p

rodu

ctio

n et

les

impo

rtatio

ns29

327

770

21

006

524

790

701

1 08

91

182

1 16

02

181

2 55

6

PIB

-1 5

11-1

094

-2 3

23-2

308

-1 9

60-3

138

-1 3

2554

02

917

5 69

15

712

7 31

3

Sour

ce : I

CN

.1

Y co

mpr

is l’

équi

libra

ge q

ui p

erm

et d

’ass

urer

la c

ohér

ence

ent

re le

s op

tique

s du

PIB

.

53

TABL

EAU

12

INC

IDEN

CE

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 S

UR

LE

RN

B(p

rix c

oura

nts,

mill

ions

d’e

uros

)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

PIB

-1 1

27-1

655

-1 8

67-1

866

-1 9

18-1

846

-1 4

53-1

809

-1 4

36-1

891

-1 4

43

Sold

e de

s re

venu

s pr

ilmai

res

avec

le re

ste

du m

onde

9510

110

310

611

111

612

114

915

616

622

0

Rém

unér

atio

ns d

es s

alar

iés

9510

110

310

611

111

612

114

915

616

622

0

Impô

ts s

ur la

pro

duct

ion

et le

s im

porta

tions

00

00

00

00

00

0

Subv

entio

ns0

00

00

00

00

00

R

even

us d

e la

pro

prié

té0

00

00

00

00

00

Inté

rêts

00

00

00

00

00

0

Rev

enus

dis

tribu

és d

es s

ocié

tés

00

00

00

00

00

0

Bén

éfic

es ré

inve

stis

d'in

vest

isse

men

ts d

irect

s ét

rang

ers

00

00

00

00

00

0

Aut

res

reve

nus

d'in

vest

isse

men

ts0

00

00

00

00

00

RN

B-1

031

-1 5

55-1

764

-1 7

59-1

808

-1 7

30-1

333

-1 6

61-1

280

-1 7

25-1

224

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

PIB

-1 5

11-1

094

-2 3

23-2

308

-1 9

60-3

138

-1 3

2554

02

917

5 69

15

712

7 31

3

Sold

e de

s re

venu

s pr

ilmai

res

avec

le re

ste

du m

onde

244

257

255

6 01

3-5

934

-3 2

21-5

213

210

5 69

58

131

3 65

9-4

81

Rém

unér

atio

ns d

es s

alar

iés

244

257

255

310

348

349

378

372

419

409

452

652

Im

pôts

sur

la p

rodu

ctio

n et

les

impo

rtatio

ns0

00

00

00

00

-7-9

-22

Su

bven

tions

00

00

00

020

00

00

R

even

us d

e la

pro

prié

té0

00

5 70

3-6

282

-3 5

70-9

002

818

5 27

67

729

3 21

6-1

112

Inté

rêts

00

02

747

-358

91

614

81

015

274

-690

Rev

enus

dis

tribu

és d

es s

ocié

tés

00

0-7

46-3

078

-4 0

55-2

706

-4 1

2554

-343

212

-71

Bén

éfic

es ré

inve

stis

d'in

vest

isse

men

ts d

irect

s ét

rang

ers

00

06

480

-3 9

5289

41

983

5 33

55

105

6 98

53

060

-114

Aut

res

reve

nus

d'in

vest

isse

men

ts0

00

-33

1-5

0-1

86-7

109

72-3

30-2

37

RN

B-1

266

-837

-2 0

683

705

-7 8

94-6

360

-1 8

473

751

8 61

213

822

9 37

16

832

Sour

ce : I

CN

.

54

TABL

EAU

13

INC

IDEN

CE

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 S

UR

LE

DÉF

ICIT

PU

BLIC

(mill

ions

d’e

uros

, sau

f men

tion

cont

raire

)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Sold

e de

fina

ncem

ent a

vant

révi

sion

(mar

s 20

19)

-9 4

08-8

489

-4 8

02-2

223

-1 3

45-1

8645

712

5-4

977

-469

-8 6

01Po

urce

ntag

e du

PIB

-4,4

-3,9

-2,1

-0,9

-0,6

-0,1

0,2

0,0

-1,8

-0,2

-2,8

Rév

isio

n du

sol

de-8

1-8

7-1

9-1

61-2

26-1

815

9-2

44-2

65-2

4018

3

C

ertif

icat

s ve

rts0

00

00

00

-3-2

19

14

Po

uvoi

r féd

éral

00

00

00

00

00

0

C

omm

unau

té fl

aman

de0

00

00

00

-3-9

87

Rég

ion

de B

ruxe

lles-

capi

tale

00

00

00

00

00

0

R

égio

n w

allo

nne

00

00

00

00

-12

17

M

arib

el s

ocia

l

Po

uvoi

rs lo

caux

00

00

5031

3737

3738

74

Pr

esta

tions

soc

iale

s en

nat

ure

Soin

s de

san

té IN

AMI

-84

-89

-21

-159

-276

-126

147

-254

-249

-202

192

Au

tres

(révi

sion

s co

uran

tes)

22

2-2

177

-25

-25

-32

-85

-97

Sold

e de

fina

ncem

ent a

près

révi

sion

(sep

tem

bre

2019

)-9

490

-857

7-4

821

-238

4-1

571

-203

615

-119

-524

2-7

08-8

418

Pour

cent

age

du P

IB-4

,5-4

,0-2

,2-1

,0-0

,6-0

,10,

20,

0-1

,9-0

,2-2

,7

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Sold

e de

fina

ncem

ent a

vant

révi

sion

(mar

s 20

19)

716

226

-3 9

06-1

8 77

5-1

4 60

9-1

5 89

9-1

6 40

9-1

2 28

1-1

2 39

7-9

819

-10

225

-3 6

44Po

urce

ntag

e du

PIB

0,2

0,1

-1,1

-5,4

-4,0

-4,2

-4,2

-3,1

-3,1

-2,4

-2,4

-0,8

Rév

isio

n du

sol

de63

353

-42

-235

-381

-267

-13

83-2

3848

485

C

ertif

icat

s ve

rts-3

2-4

2-1

6-1

35-2

60-3

06-4

07-1

66-7

0-2

7358

345

Pouv

oir f

édér

al0

03

2-3

-17

-11

133

10-1

411

Com

mun

auté

flam

ande

-13

-10

-9-1

26-1

53-1

59-2

18-1

60-1

06-1

8511

931

0

R

égio

n de

Bru

xelle

s-ca

pita

le-1

10

00

-11

0-2

-18

-2

R

égio

n w

allo

nne

-18

-33

-11

-10

-104

-129

-179

-65

-97

-56

26

M

arib

el s

ocia

l

Po

uvoi

rs lo

caux

7590

8789

9612

815

215

415

431

3132

Pr

esta

tions

soc

iale

s en

nat

ure

Soin

s de

san

té IN

AMI

-150

-183

-293

-193

-180

-197

-13

-82

-66

111

00

Au

tres

(révi

sion

s co

uran

tes)

170

138

275

197

108

-61

8165

-108

-41

107

Sold

e de

fina

ncem

ent a

près

révi

sion

(sep

tem

bre

2019

)77

922

8-3

853

-188

17-1

4844

-162

80-1

6677

-122

95-1

2315

-100

58-1

0177

-315

9Po

urce

ntag

e du

PIB

0,2

0,1

-1,1

-5,4

-4,1

-4,3

-4,3

-3,1

-3,1

-2,4

-2,4

-0,7

Sour

ce : I

CN

.

55

TABL

EAU

14

INC

IDEN

CE

DE

LA R

ÉVIS

ION

OC

CAS

ION

NEL

LE D

E 20

19 S

UR

LA

DET

TE P

UBL

IQU

E(m

illio

ns d

’eur

os, s

auf m

entio

n co

ntra

ire)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Det

te p

ubliq

ue a

vant

révi

sion

(mar

s 20

19)

276

253

276

348

278

406

277

158

279

434

280

866

285

966

288

024

285

784

288

327

294

901

Pour

cent

age

du P

IB13

0,5

128,

012

3,2

118,

211

4,4

108,

810

7,6

104,

710

1,1

96,5

94,7

Rév

isio

n de

la d

ette

pub

lique

110

106

101

9697

9490

8783

9275

C

ertif

icat

s ve

rts0

00

00

00

00

00

Pouv

oir f

édér

al0

00

00

00

00

00

Com

mun

auté

flam

ande

00

00

00

00

00

0

R

égio

n de

Bru

xelle

s-ca

pita

le0

00

00

00

00

00

Rég

ion

wal

lonn

e0

00

00

00

00

00

Au

tres

révi

sion

s11

010

610

196

9794

9087

8392

75

Det

te p

ubliq

ue a

près

révi

sion

(sep

tem

bre

2019

)27

6 36

327

6 45

427

8 50

727

7 25

527

9 53

128

0 96

028

6 05

528

8 11

128

5 86

728

8 41

929

4 97

5Po

urce

ntag

e du

PIB

131,

312

9,0

124,

311

9,2

115,

410

9,6

108,

210

5,4

101,

797

,295

,1

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Det

te p

ubliq

ue a

vant

révi

sion

(mar

s 20

19)

297

424

299

997

327

620

347

165

364

078

388

935

404

289

413

730

430

186

437

176

450

545

454

112

Pour

cent

age

du P

IB91

,087

,092

,599

,599

,710

2,6

104,

310

5,5

107,

510

6,4

106,

110

3,4

Rév

isio

n de

la d

ette

pub

lique

7167

6358

5417

246

370

297

410

5785

118

1

C

ertif

icat

s ve

rts0

00

00

122

418

663

743

888

707

33

Po

uvoi

r féd

éral

00

00

015

2626

00

00

Com

mun

auté

flam

ande

00

00

010

635

057

565

588

165

533

Rég

ion

de B

ruxe

lles-

capi

tale

00

00

00

00

00

00

Rég

ion

wal

lonn

e0

00

00

142

6388

852

0

Au

tres

révi

sion

s71

6763

5854

4944

3923

116

914

414

8

Det

te p

ubliq

ue a

près

révi

sion

(sep

tem

bre

2019

)29

7 49

530

0 06

432

7 68

334

7 22

436

4 13

238

9 10

740

4 75

241

4 43

243

1 15

943

8 23

345

1 39

645

4 29

3Po

urce

ntag

e du

PIB

91,5

87,3

93,2

100,

210

0,3

103,

510

4,8

105,

510

7,0

105,

210

4,9

101,

8

Sour

ce : I

CN

.

56

Les graphiques 1 à 4 illustrent l’incidence de la révision sur le niveau du PIB et suivant les trois optiques (production, dépenses, revenus). L’incidence est exprimée à prix courants, en pourcentage du PIB tel qu’il était mesuré dans la dernière édition des comptes annuels (septembre 2018).

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

Total

Prix courants Taux de croissance annuel moyen du PIB (1995-2017)

3,39 %

3,49 %

En volume

Avant révision

Après révision

1,78 %

1,89 %

Taux de croissance annuel moyen du PIB (1995-2017)

Avant révision

Après révision

Impôts moins subventions sur la production et les importations

Autres révisions de la valeur ajoutée

Test marchand/non marchand

R&D

Services hospitaliers

Production d'électricité par les ménages

Reclassement sectoriel d'Infrabel

Administrateurs de sociétés

Services d'assurance

SIFIMServices de logement

Source : ICN.

GRAPHIQUE 1 INCIDENCE DES PRINCIPAUX ÉLÉMENTS DE RÉVISION SUR LE NIVEAU DU PIB – OPTIQUE DE LA PRODUCTION(pourcentages du PIB, prix courants)

Source : ICN.

SociŽtŽs non Þnancières

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

SociŽtŽs Þnanci es

Administrations publiques

M ages

Total

ISBL au service des m ages

Imp s sur les produits moins subventions sur les produits

GRAPHIQUE 2 DÉCOMPOSITION DE LA RÉVISION DU NIVEAU DU PIB - VALEUR AJOUTÉE DES SECTEURS INSTITUTIONNELS(pourcentages du PIB, prix courants)

57

Investissements des ménages et des ISBL au service des ménages

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

DŽpense de consommation Þnale des mŽnages et des ISBL au service des mŽnages

Investissements des sociétés

Investissements des administrations publiques

Variations de stocks

DŽpense de consommation Þnale des administrations publiques

Exportations nettes de biens et services

Total

Source : ICN.

GRAPHIQUE 3 DÉCOMPOSITION DE LA RÉVISION DU NIVEAU DU PIB - OPTIQUE DES DÉPENSES(pourcentages du PIB, prix courants)

Source : ICN.

GRAPHIQUE 4 DÉCOMPOSITION DE LA RÉVISION DU NIVEAU DU PIB - OPTIQUE DES REVENUS(pourcentages du PIB, prix courants)

R un ations des salari

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

Imp s moins subventions sur la production et les importations

Exc ent brut d'exploitation et revenu mixte brut

Total

58

Les graphiques 5 à 8 illustrent quelques agrégats-clés des comptes nationaux avant et après la révision occasionnelle.

Écart

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017-3%

-2%

-1%

0%

1%

2%

3%

4%

PIB avant révision PIB après révision

Source : ICN.

GRAPHIQUE 5 TAUX DE CROISSANCE DU PIB EN VOLUME AVANT ET APRÈS RÉVISION

Source : ICN.

GRAPHIQUE 6 TAUX DE CROISSANCE DU REVENU NATIONAL BRUT (RNB) À PRIX COURANTS AVANT ET APRÈS RÉVISION

RNB avant r ision

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017-4%

-2%

0%

2%

4%

6%

8%

RNB apr r ision É

59

Source : ICN.1 Y compris les ISBL au service des ménages.2 En pourcentage du revenu disponible.3 Sociétés non financières et sociétés financières.4 En pourcentage de la valeur ajoutée.

GRAPHIQUE 7 AGRÉGATS-CLÉS DES COMPTES DES SECTEURS AVANT ET APRÈS RÉVISION

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

10%

12%

14%

16%

18%

20%

22%

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

6%

7%

8%

9%

10%

11%

12%

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

33%

35%

37%

39%

41%

43%

45%

Après révisionAvant révision

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

18%

19%

20%

21%

22%

23%

24%

25%

26%

27%

Taux d'épargne et taux d'investissement des ménages¹

Taux d'investissement4Taux de marge4

Taux d'épargne² Taux d'investissement²

Taux de marge et taux d'investissement des sociétés³

60

Source : ICN.1 Sociétés non financières et sociétés financières.

GRAPHIQUE 8 SOLDE DE FINANCEMENT DES SECTEURS INSTITUTIONNELS AVANT ET APRÈS RÉVISION (pourcentages du PIB)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

-6%

-5%

-4%

-3%

-2%

-1%

0%

1%19

9519

9619

9719

9819

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

17

0%

1%

2%

3%

4%

5%

6%

7%

8%

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

7%

Solde de Þnancement des sociŽtŽs¹

Avant r ision Apr r ision

Solde de Þnancement des administrations publiques

Solde de Þnancement des mŽnages et des ISBL au service des mŽnages

Solde de Þnancement de l'ensemble de l'Žconomie

61

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More informations

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© Illustrations: National Bank of Belgium

Layout: NBB General Statistics Cover: NBB AG — Prepress & Image

Published in September 2015

Editor

Rudi AcxHead of the General Statistics Department

National Bank of Belgium Limited Liability company RLP Brussels — Company’s number: 0203.201.340 Registered office: boulevard de Berlaimont 14 — BE-1000 Brussels www.nbb.be