1. 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

2. 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 régionale
Giovanni A. Barbieri – Tunis, 19-20 novembre 2015
2

3. 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
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4. 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
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Giovanni A. Barbieri – Tunis, 19-20 novembre 2015

5. 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
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6. 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
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7. 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
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8. 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!
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9. 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
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10. 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
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11. 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 factor
cost, Gross operating surplus, Number of persons employed, Number
of employees …)
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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

12. 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
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13. 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
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14. 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
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15. 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
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16. 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
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17. 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
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18. 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
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