2015.11.20 Barbieri Structural Business Statistics

Analyse de l’entreprise et de la performance

régionale basée sur les statistiques

structurelles sur les entreprises

Giovanni A. Barbieri (Istat)

Le système de statistiques territoriales au service de la conception et la mise en œuvre

de politiques de développement local et régional en Tunisie

Tunis, 19-20 novembre 2015

Summary

Structural Business Statistics (SBS)

Why collect SBS?

Acquisition of data and transmission of results

The Italian experience: Frame-SBS

General remarks: pros and cons of Frame-SBS

Frame-SBS and regional SBS statistics

Analyse de l’entreprise et performance régionaleGiovanni A. Barbieri – Tunis, 19-20 novembre 2015

2

Structural Business Statistics

[1] Structural business statistics (SBS) describe the structure, conduct and

performance of businesses across the European Union (EU)

Legal basis: Originally: Council Regulation 0058/1997 (and later amendments) on structural business

statistics

Many revisions and amendments over time to the SBS Regulation: Parliament and Council Regulation 0295/2008 (“recasting”)

Definitions, breakdowns, deadlines for data delivery, and various quality aspects are specified in implementing regulations

A new regulation in the works: Frame Regulation on Integrating Business Statistics (FRIBS)

SBS cover industry, construction, distributive trades and services (according to the NACE activity classification)

The main indicators within SBS are generally collected and presented as monetary values, or as counts (for example, numbers of enterprises or persons employed)

Breakdown: By sector (at a very deep detail, i.e. several hundred economic activities)

By size of enterprises

By region

3 Analyse de l’entreprise et performance régionaleGiovanni A. Barbieri – Tunis, 19-20 novembre 2015

Structural Business Statistics

[2] Coverage:

SBS cover the ‘business economy’ (NACE Rev. 2 Sections B to N and Division 95) which includes: Industry

Construction

Distributive trades

Services

Financial services (NACE Rev. 2 Section K) are generally kept separate

SBS do not cover agriculture, forestry and fishing, nor public administration and (largely) non-market services such as education and health

Modules: A horizontal module (Annex I), including a limited set of basic statistics for all market activities

Seven sector-specific annexes cover a more extended list of sector-specific characteristics: industry (Annex II), distributive trades (Annex III), construction (Annex IV), insurance services (Annex V), credit institutions (Annex VI), pension funds (Annex VII) and business services (Annex VIII)

Annex IX covers business demography statistics for all market activities

Size classes: A limited set of the standard SBS variables (i.e. number of enterprises, turnover, persons employed and

value added) available, at the three-digit (group) level of the NACE classification, by size class: Micro enterprises: with less than 10 persons employed

Small enterprises: with 10 to 49 persons employed

Medium-sized enterprises: with 50 to 249 persons employed

Large enterprises: with 250 or more persons employed

Actually, the European Commission Recommendation (2003/361/EC), adopted on 6 May 2003, classifies SMEs according to their number of persons employed, annual turnover, and independence


Main variables and indicators

SBS contain a comprehensive set of basic variables describing business demography and employment characteristics, as well as monetary variables (mainly concerning operating income and expenditure, or investment)

In addition, a set of derived indicators has been compiled: for example, ratios of monetary characteristics or per head values

Main variables and indicators: Number of enterprises

Local units

Turnover

Value added at factor cost

Total purchases of goods and services

Gross investment in tangible goods

Number of persons employed

Employee

Personnel costs

Apparent labour productivity

Wage-adjusted labour productivity ratio

Gross operating surplus

Gross operating rate


Why collect SBS?

SBS may be used to answer such questions as: How much wealth is created in an activity and how many persons are employed?

Is there a shift from the industrial sector to the services sector and in which specific activities is this trend most notable?

Which countries are relatively specialised in the manufacture of a particular activity – for example, the manufacture of aerospace equipment?

How productive is a particular activity, such as the chemicals sector, and how does it fare in terms of its operating profitability?

Very often, at present, aggregate answers are not enough!

Monitoring policies such as: Creating a favourable environment for business

Fostering higher productivity, economic growth, jobs and wealth

Reducing administrative burdens

Stimulating innovation

Encouraging sustainable production

Ensuring the smooth functioning of the market

Promoting SMEs’ growth


Acquisition of data

Member States may acquire the necessary data using a combination of different sources: compulsory surveys

other sources equivalent as regards accuracy and quality

statistical estimation procedures

administrative data sources and administrative data

Quality evaluation

Comparability

Use of electronic data transmission and automatic data-processing


SBS by region

SBS may be broken down by NUTS region

SBS are based upon data for enterprises or parts of enterprises, such as local units which are often used for regional SBS data

An enterprise can carry out one or more activities at one or more locations and may comprise one or more legal units

When an enterprise is active in more than one economic activity, then the value added and turnover that it generates, the persons it employs, and the values of all other variables will be classified under the enterprise’s principal activity; the principal activity is normally the one that generates the largest amount of value added

This is a problem in the estimate of regional SBS!


Transmission of results

The results are to be transmitted within 18 months of the end of the calendar year of the reference period: The results for the statistics are to be broken down to the NACE

Rev. 2 4-digit level (class)

Some results are also to be broken down into size classes and to NACE Rev. 2 3-digit level (group)

The results for the regional statistics are to be broken down to the NACE Rev. 2 2-digit level (division) and level 2 of NUTS

Data are transmitted, in a standard format, for the following annexes: Industry

Construction

Distributive trades

Services


The Italian experience: the

move to Frame-SBS Traditionally, Italian SBS data have been compiled by combining the estimates from

2 surveys: PMI: a sample survey on small and medium-sized enterprises with less than 100 persons

employed

SCI: a census survey on enterprises with 100 persons employed and more

Both surveys use administrative sources to integrate total non-responses

Starting from SBS2012 Istat has combined administrative sources with survey data aiming at reducing the sampling error and at improving data quality: the project is called Frame-SBS

Components: For the structural variables (number of persons employed, number of employees,

economic activity, administrative region): business register of active enterprises (Asia)

For the main economic variables (turnover, purchases of goods and services, value added, personnel costs, etc.): exhaustive administrative sources

For the other economic variables, not available from administrative sources: estimation from PMI survey data by using either weighted regression estimators or calibration (e.g. investments)

For all variables for the enterprises with 100 persons employed and more: data from SCI census survey


The components: Frame

Microdata from administrative sources

4,3 million enterprises with less than 100 persons employed

15 main economic variables (Turnover, Total purchases of goods and services, Personnel costs, Wages and salaries, Value-added at factorcost, Gross operating surplus, Number of persons employed, Numberof employees …)


Source Enterprises Value added Persons

employed

Total 100.0 100.0 100.0

P&L accounts 16.2 53.8 38.2

«Sector studies» 67.3 36.6 49.9

Tax declarations 12.3 3.1 5.9

Other tax records 1.8 4.4 3.3

No fonte amministrativa 2.5 2.1 2,7

The components: the

surveys Sample survey PMI2012 (enterprises with less than 100 persons employed):

Sample: 100,005 enterprises

Integration of total non-responses using P&L accounts and “sector studies”

Number of enterprises used in the estimation process (respondents + integrated

units): 77,8% of the theoretical sample

Number of variables in the questionnaire: around 200

Number of released variables: around 70

Number of SBS variables: around 40

Census survey SCI2012 (enterprises with 100 persons employed and more):

10,554 enterprises

Integration of total non-responses using P&L accounts and IRAP (other tax records)

Number of variables in the questionnaire: around 300

Number of released variables: around 70

Number of SBS variables: around 40


General remarks

The administrative sources have been analysed in terms of both coverage of the SBS

target population as listed in the Business Register, and available variables

A comparative analysis of the variables observed in each administrative source and in the

PMI survey has led to the integrated use of the relevant administrative sources according

to a specific “hierarchy”

Such hierarchy is based on how the variable definitions are close to the SBS ones and on

the reliability of the sources themselves (stability, availability, completeness…)

Target variables not available in the administrative sources estimated through massive

imputation, using a mixed approach, depending on the coverage rate of the target

variables to be estimated: Classical predictive model-based approaches have been used for estimating high coverage variables

Models based on PMI data have been adopted for estimating the remaining variables

In this way a multidimensional micro data matrix has been built (FrameSBS), containing

the Business Register variables and the economic variables for all the SBS population

units


Main features

The Frame-Sbs dataset is an array of firm-level structural and

economic information for each of the over 4 million Italian

enterprises, aligned with the Business Register

Variables are obtained as the mere sum of every single firm’s

corresponding variable:

Thus the sum of all firms’ value added gives the total official value added

of the whole business system gives the official value added of the total

business system

In the traditional sample survey procedure, variables are obtained

multiplying a sampled value by a final weight, obtaining results valid only

for programmed domains


Pros and cons

Pros: Improvement of the overall consistency and quality of

business statistics (and national accounts estimates)

Longitudinal evaluation of the performance of single production units, allowing to explore firm- and sector-level dynamics

Integration with other surveys (thanks to its exhaustive nature)

Production of very detailed estimates

More statistical analyses and indicators

Better statistical representation of some industries

Reduction of the statistical burden on enterprises

More domains in dissemination


Pros and cons

Cons and constraints: Methodological constraints: significance of

model-based estimates for specific variables in

small domains

Confidentiality issues

Dependence on administrative sources:

Timeliness of production and transmission

Normative changes affect availability and continuity


Regional analysis: current

situation The SBS Regulation 295/2008 provide the legal basis

for the annual collection of regional SBS (not regional business demography statistics!) Regional statistics are compiled for wages and salaries and the

number of persons employed

They are provided for NACE divisions and for NUTS level 2 regions

The statistical unit used for regional SBS is generally the local unit, which is an enterprise or part of an enterprise situated in a geographically identified place

Local units are usually classified under NACE according to their main activity


Regional analysis: perspectives

after Frame-SBS KAU and LKAU

The kind of activity unit (KAU) groups all the parts of an enterprise contributing to the performance of an activity at class level (4- digits) of NACE Rev. 1 and corresponds to one or more operational subdivisions of the enterprise

The enterprise's information system must be capable of indicating or calculating for each KAU at least the production value, intermediate consumption, manpower costs, the operating surplus and employment and gross fixed capital formation

The local unit is an enterprise or part thereof (e.g. a workshop, factory, warehouse, office, mine or depot) situated in a geographically identified place

At or from this place economic activity is carried out for which – save for certain exceptions – one or more persons work (even if only part-time) for one and the same enterprise

The local kind-of activity unit (local KAU) is the part of a KAU which corresponds to a local unit

The Frame-SBS makes it possible to build aggregates by adding-up microdata at the enterprise level, with maximum geographical detail

The only limits are quality and confidentiality

The move to local unit questions the economic meaning of aggregates


Data & Analytics

2015.11.20 Barbieri Structural Business Statistics