3. Method

For parts of the Supply and Use Tables (SUT), Sector Accounts (SA) and Labour Accounts (LA), new methods and software were developed to construct the time series. These methods, which are in line with the previously established guiding principles, are explained below. There are many similarities between the methods used to produce the time series for each of the three systems. Section 3.1, on the methodology behind the SUT series, offers the most detailed explanation, as much of this also applies to the other systems. Sections 3.2 (Sector Accounts) and 3.3 (Labour Accounts) focus mainly on system-specific details.

3.1 Methodology for Supply and Use Tables (SUT)

A high level of aggregation was used in compiling the SUT annual series. This has resulted in a limited set of figures on industries, expenditure and product groups, in which the desired publication variables have been established. No revised Input-Output Tables (IOT) were created for the 1995-2020 time series. Moreover, product group-specific information is not available for all series. These tables are available for the 2021 revision year and beyond, however.

In the 2021 revision year, adjustments were made for almost all industries and expenditure categories. In areas where the adjustments were limited, the figures from the previous revision year, 2015, were assumed to be correct, and the adjustments were gradually backcast to this previous base year. Larger adjustments were backcast to the 2010 reporting year, the revision year before 2015. Thus, an explicit decision was made to make as few changes as possible to previous years, unless the previous estimate contained serious omissions that needed to be corrected. The same principles were applied to the SA and LA as well.

The larger the adjustment for the 2021 revision year, the greater the changes to the developments in the time series. For the SUT, a conscious choice was made to attribute the adjustment in value growth to volume growth, which means that the pre-revision prices determined the post-revision prices. This was done because pricing data is based on directly observed data sources, while volume figures (also in the regular estimates) are derived from value and price trends. Only for parts of the economy where volume developments were considered to be of higher quality than price developments (as in the case of some adjustments to the data on insurance companies) have price developments been adjusted.

Exactly how the adjustments for the 2021 revision year have been backcast in the time series varies by industry and final expenditure category. First, the adjustments for the 2021 revision year were looked at by industry or expenditure category. Subsequently, it was determined whether additional information was available on the size of the adjustments in the other years of the time series. Finally, the adjustments for the other years were determined, with the smaller revisions again tapering to zero in 2015 and the larger ones in 2010.

Updates to the national accounts time series are never made in isolation. For example, the adjustments to output and consumption of hospitality services must match. In addition, adjustments in one system, such as the SUT, need to be coordinated with adjustments to the other systems, such as the SA. In aligning these changes, the SA figures always follow the output and income generation data from the SUT (except for government estimates).

Ideally, adjustments in the revision year gradually become smaller further back in the time series, to ensure that the overall economic picture does not change too radically. The economic pattern before the revision is therefore very similar to the economic pattern after the revision. This is also included as one of the guiding principles in the methodology, and it is clearly visible in the graphical representations of the various economic aggregates before and after revision (see Section 4).

Below, the method for creating the SUT time series is set out in several steps.

3.1.1 Time series layers

The adjustment from the 2021 reporting year to the 2021 revision year can generally be divided into two parts: a part that can mostly be backcast using the old figures, and a part for which this is not the case, because the old figures are not representative of the phenomenon that has been adjusted. Adjustments of the latter type are also called time series layers.

The exact characteristics of a time series layer are determined in a revision project. For this revision, time series layers were created in response to a number of GNI action items (globalisation, spreads, health care costs), adjustments made for several large multinational companies, illegal activities and the transfer of social workshops and job pools to general government (see the revision publication for more information on the GNI action items and the other adjustments).

When using a time series layer, the impact of specific revision projects on the previous years is determined separately based on the available information. Some of the time series layers extend back to 1995, the beginning of the time series. This information was first incorporated into the time series before the rest of the time series was backcast using algorithms. Revision projects and time series layers were also used to create the time series for the SA and LA systems (see sections 3.2 and 3.3).

3.1.2 Backcasting adjustments

This section offers a detailed description of the backward adjustments to the production and expenditure GDP approaches.

Production approach to GDP:

1) The total output by branch of industry in current prices and the underlying commodity groups were backcast using the following formula:

A) If the recalibration for the 2021 revision year was less than or equal to 4 percent, the difference was backcast to the 2015 revision year.

B) If the recalibration was greater than 4 percent, the difference was backcast to the 2010 revision year.

The backcasting method used was relatively linear: the backcasting rate decreases each year by a fixed difference (linear) and is multiplied by the initial value (relative). The table below illustrates the backcasting process using sample figures. The pre-revision series is in the ‘initial’ column. For 2021, the revision adjustment (recalibration) is 100, which is less than 4 percent of the total. This means that the recalibration has been backcast to the previous revision in 2015. If the adjustment had been 300, the recalibration would have been backcast to the 2010 revision.

2) Output by product group was also backcast using the formula in step 1. Differences between total output and the sum of all product groups were adjusted in the product group with the highest output. These differences arose because the backcasting periods for the product groups and the total were not always the same.

3) The total value added was backcast using the same formula as in step 1. As a result, the backcasting period for total value added is always equal to that of total output.

4) The intermediate consumption time series was calculated as total output minus total value added.

5) Intermediate consumption by product group was also backcast using the formula in step 1. Differences between total intermediate consumption and the sum of all product groups were adjusted in the product group with the highest intermediate consumption.

6) The outcomes in the previous year’s prices (the constant prices) were calculated as follows: the values per product group in current prices were deflated based on the existing pre-revision price indices. Total output and total intermediate consumption, both in constant prices, were calculated by adding up the product groups in constant prices. Value added in constant prices was calculated as output minus intermediate consumption.

Expenditure approach to GDP:

7) The imports of goods at current prices time series was calculated in the same way as the output time series (see step 1), meaning that total imports of goods was backcast in a relatively linear fashion. The same applies to imports by product group. The difference between total imports and the sum of the different product groups was then adjusted in the product group with the highest imports.

8) The trade balance of goods was backcast in a relatively linear fashion.

9) The total exports time series was calculated as a residual of the trade balance and total imports.

10) Exports by product group were calculated using the same method used for output (see step 1). Differences between total exports and the product groups were adjusted in the product group with the highest exports.

11) Steps 7 to 10 were also carried out to produce the service imports and exports time series.

12) The time series for consumption by government, households, and non-profit institutions serving households (NPISHs) and the time series for investment were calculated in the same way as the one for output (see step 1).

13) The vast majority of the inventory adjustments relate only to the 2021 reporting year and therefore have no impact on the time series. Adjustments were made to the time series only for a very limited proportion. The remaining absolute differences between pre- and post-revision changes in inventories and valuables were backcast linearly. The absolute differences were used because these series can be either positive or negative; using the absolute mutations yielded results closer to the original pattern.

14) All values in the previous year’s prices (constant prices) for expenditure were calculated in the same way as in step 6. The totals of expenditure in constant prices are always the sum of the product groups.

3.1.3 Automated integration

After going through the above steps, the remaining integration differences between supply of and demand for goods were generally found to be limited. In most cases, the time series layers were consistent (with supply equal to demand), and due to the high level of aggregation of the product groups, lower-level supply and demand differences often cancelled each other out. As a result, the remaining integration differences could easily be resolved using automated procedures, preserving existing mutations as much as possible. A number of preconditions had to be met for this. For example, supply of and demand for goods had to be identical, and data from the Tax and Customs Administration on product and non-product taxes and subsidies were used exogenously, as well as LA data on employee remuneration.

In addition to the annual time series, revised SUT quarterly time series have also been published. These were created using an automated calculation procedure. The old quarters have been reconciled to the new yearly totals, while the old quarter-on-quarter developments have been kept intact as much as possible. Where necessary, additional information on adjustments in the time series before 2021 has also been added (through the use of time series layers), such as for the time series on employee remuneration and taxes. The quarterly series have been used as input for the seasonally adjusted GDP and underlying series figures (see Annex A), and also as input for the SA (see Section 3.2) including the Government Accounts.

3.2 Methodology for Sector Accounts (SA)

The methodology for estimating the SA time series is essentially the same as that described above for the SUT. One important difference, however, is that parts of the non-financial accounts and the financial accounts and balance sheets are revised annually, including a full reconciliation of the time series.

The inputs to the time series are (a) the pre-revision figures from 1995 to 2021, including those revised annually after the 2015 benchmark revision, (b) the outcomes of the various revision projects and (c) the final results of the revision of the 2021 benchmark reporting year. The outcomes of the revision projects were largely added to the pre-revision figures as time series layers, which sometimes go as far back as 1995, as with the SUT. The remaining difference with the 2021 post-revision figures was, with some exceptions, linearly backcast to the previous 2015 revision. This yielded other developments and levels. The exact methodology differs for each activity/transaction, and the resulting time series were integrated after backcasting.

3.2.1 Non-financial transactions

For the transactions that also appear in the SUT, the figures from the revised SUT time series were used. The information by branch of industry has been attributed to sectors (the grouping of (parts of) industries by institutional sectors) using dual classification. For the other transactions, such as interest and dividend flows, the recalibration was backcast linearly.

3.2.2 Financial accounts and balance sheets

A similar strategy was used for the financial accounts and balance sheets. The aim here was to achieve optimal alignment with the final pre-revision balance sheet for the 2015 reporting year (plus the layers added in step 1) by gradually reducing the difference in the balance sheet to zero in 2015 (or further back in time in some cases). The choice was made to channel the adjustments largely through financial transactions (and partly through price and exchange rate movements). After that, the integration software ensured an integrated and consistent system.

Because government finance is part of the SA, it also went through the above procedure for compiling the revised time series.

3.3 Methodology for Labour Accounts (LA)

The pre-revision LA time series also served as the basis for the revised time series for 1995-2021. To arrive at a revised time series, several layers were added to this series, as with the SUT and SA. Broadly speaking, the following procedure was followed:

• Time series revisions based on several revision projects were added to the pre-revision time series for wages and social security contributions as time series layers.
• Then, to fully align the time series for wages and social security contributions with the 2021 revision year estimates, the remaining differences were also gradually backcast using a recalibration.
• In addition, the new LA time series for wages and social security contributions were aligned with those for the public sector, the Sector Accounts (SA) and the Supply and Use Tables (SUT).
• In conjunction with the revision of the wages and social security contributions figures, labour volume data was also revised; this includes data on jobs, labour years, hours worked and employed persons.
• To compile quarterly series on wages, social security contributions and labour volumes, the pre-revision quarterly patterns were superimposed on the post-revision annual totals (after some changes).

3.3.1 Employee wages and social security contributions

As mentioned, the pre-revision time series served as the basis for the employee remuneration and social security charges borne by employers time series. First, time series layers from various revision projects were added to this. Examples of important revision projects include the reconciliation of severance and transition payments with the observation from policy records of the Employee Insurance Agency (UWV), the recalibration of wages in kind (wages in the form of goods or services, such as the private use of a company car), and the revision of pension contributions, whereby the totals of De Nederlandsche Bank (DNB) are now used for both employee and employer contributions. For each project, an assessment was made to determine how many years back corrections were needed, as well as the size of these corrections per year. For example, the revision project on severance and transition payments took into account recent changes in laws and regulations.

Then, to fully align the time series for wages and social security contributions with the new 2021 revision year estimates, the remaining differences were backcast using a recalibration. These remaining differences for the most part consisted of changes in the enterprise population by branch of industry, and of a smaller other residual difference. The changes in the enterprise population were partly due to different estimates for undeclared work/the illegal economy; the optimal backcasting method for these figures was determined by branch of industry on a year-by-year basis. The General Business Register’s (ABR) new classifications for business units also played a role in the changes in the enterprise population. These changes were the result of confrontations with other sources, such as De Nederlandsche Bank’s population of financial institutions. They were gradually backcast to 1995, with the compounded macro-level impact kept at zero for each year, as shifts between industries should not result in macro-level differences.

The final residual differences for wages and social security contributions necessary to achieve alignment with the 2021 post-revision estimate were also backcast to 1995. Here, value indices for wages and social security contributions were used for each branch of industry to index the calculated residual difference for 2021 back in time.

3.3.2 Labour volume

Labour volume includes jobs, labour years, hours worked and employed persons (employees and the self-employed). Analogous to the method for wages and social security contributions, the time series were calculated based on the pre-revision figures, to which layers were added. Apart from the new estimates for undeclared work/the illegal economy, the separate revision projects had no effect on labour volume. However, the same recalibration made for wages and social security contributions, due to population changes and the remaining residual difference, was also made for labour volumes. In doing so, the same changes per branch of industry and period were used as for wages and social security contributions, so as not to distort the relationships between labour volumes and remuneration for different groups.

For the self-employed, additional hours worked and labour years were revised due to the revision of the Labour Force Survey (EBB) in 2021. Changes in the EBB questions led to a slightly higher average number of hours worked per self-employed person. The fact that respondents were asked to fill in the EBB twice allowed the trend break in 2021 to be quantified and backcast to 1995 with fixed percentages for each subgroup.

3.3.3 Quarterly series

The pre-revision quarterly patterns served as a basis to compile quarterly series on wages, social security contributions and labour volumes. After some changes to the patterns for wages and social security contributions due to new insights, these quarterly patterns were superimposed on the post-revision annual totals by branch of industry.

3.3.4 Aligning time series with other systems

Total social security contributions for the Netherlands and wages and labour volumes for the public sector were aligned with government statistics. Wages, social security contributions and labour volumes were also aligned with the SA. In the LA, pension contributions, which are part of wages and social security contributions, were specifically adjusted in line with the SA to fully match DNB data. Finally, as usual, the data for employee remuneration from the LA was used for the SUT, after a confrontation and some adjustments to the figures.