Unit for Satellite Accounts

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Social Accounting Matrix- Portugal

• Unit for Satellite Accounts
• National Accounts Department
• Statistics Portugal

Geneva, Switzerland 6-7-8 October 2008

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Contents

1. General overview of a SAM (NAM)
2. Labour-oriented SAM (expansion of a NAM)
3. Portuguese SAM (NAM)
4. Main uses of a SAM (some results)

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1. General overview

• Purpose provide an overview of a SAM
  labour-oriented and to show the possible types of
  indicators that can be derived.
• A Social Accounting Matrix (SAM) consists in a
  framework that integrates National Accounts and
  Social Statistics in a coherent, complete and
  consistent way. It also shows the circular flow
  of income within the economy
• the goods and services account
• the production account
• the generation of income account
• the primary and secondary distribution account
• the use of income account
• the capital account
• The financial account and
• The rest of the world account.

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1. General overview

• Types of SAM
• Environment-oriented
• Labour-oriented
• Investment oriented
• also combinations.
• The SAM that will be dealt with is
  labour-oriented one and its compilation is
  described in the Handbook on SAMs. Statistics
  Portugal compiles SAMs labour-oriented on a
  mandatory way.

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General overview
Social Accounting Matrix (SAM)
National Accounts
Labour Accounts
National Accounting Matrix (NAM)
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General overview

• The matrix format, in a NAM and a SAM has the
  advantage of (I)
• Provide a general overview of the economy -all
  the tables are in the same format (a single entry
  describes simultaneously a use and a resource).
  Possibility to expand cells to distinguish
  sub-accounts according to the purpose of analysis
  and also to aggregate or subdivide groups of
  units in a NAM

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General overview

• The matrix format, in a NAM and a SAM has the
  advantage of (II)
• At a meso-level shows interrelations among
  various different economic flows
• from whom to whom - in each sub-matrix it is
  possible to identify the paying/receiving units
  to aggregate or subdivide groups of units in a
  NAM. In these matrices not only it is possible to
  know the totals receivable/payable but also whos
  paying to whom and whos receiving from whom

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General overview

• The matrix format, in a NAM and a SAM has the
  advantage of (III)
• Possible to use different classifications from
  cell to cell and different levels of aggregation
  for each account. Possibility of creating and
  introducing dummy accounts whenever data to
  breakdown a given transaction are not available.
  These dummy accounts show in the row the total
  paid by each sector and in the column the total
  received by each sector

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General overview

• SAMs can be compiled in one of two ways (I)
• On a bottom-up approach compilation results from
  the aggregation of micro data. Using National
  Accounts in a matrix format and the monetary data
  of labour accounts related to the type of labour
  are integrated in the SAM. If labour accounts are
  not available it is necessary to compile labour
  data for SAM. Physical data are also available in
  the same detail.

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General overview

• SAMs can be compiled in one of two ways (II)
• On a top-down approach compilation results from
  the breakdown of the macro data in order to fill
  in the SAM requirements.
• The Portuguese SAM is compiled on a top-down
  approach, by 17 industries, where employment of
  the National Accounts is broken-down by gender
  and education level and households are split into
  households group according to the main source of
  income.

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General overview

• The compilation of a NAM (National Accounting
  Matrix) requires a supply-use table and
  institutional sector accounts.
• For completeness reasons it is useful to have for
  each account within the NAM, tables sector by
  sector, for each transaction in addition to the
  supply and uses table.

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Table sector by sector From whom to whom
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1. Labour-oriented SAM, expansion of a NAM

• A NAM represents the entire economy, the complete
  sequence of economic accounts but is limited by
  to its scope and doesnt show all the dimensions.
  
• A SAM provides extra-dimensions to the NAM,
  according to the purpose of analysis
• Extra-dimensions result from the breakdowns of
  the sub- matrices of the NAM, detailing the
  actors or the nature of some monetary flows
• Portuguese SAM ? Labour-oriented SAM
• Purpose capture different kind of labour and
  its relationship with income distribution and
  use.
• Focus remunerations of labour as input factor
  in the process of production Compensations of
  employees and Mixed Income.

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1. Labour-oriented SAM, expansion of a NAM

• Possible dimensions of a Labour-oriented SAM
• Type of labour
• status in employment employee or self-employed
• gender
• educational level
• age group
• categories of professions,
• Households groups - as labour suppliers and
  income receivers
• main source of income
• dimension of the household
• income class, .
• These dimensions provide information on the kind
  of labour
• its contribution to the generation of Value Added
  in each industry.
• its relation with the income distribution and use.

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1. Labour-oriented SAM, expansion of a NAM

The economic accounts integrating
Employment Generation of Income Account Labour
demand Shows how primary income is generated as
the result of the participation in the process of
production. includes Compensations of
employees and Mixed Income, by type of
labour Allocation of primary Income Account
Labour supply shows how income is distributed
according to the ownership of assets (financials
and tangible non-produced assets) are made
available for production. includes

Compensations of
Employees and Mixed Income by

• Type of labour
• Households group

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1. Labour-oriented SAM, expansion of a NAM

Contribution of employment by industry in the NAM
Generation of income(value added categories)   Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries)   Total
Generation of income(value added categories)   Agriculture, forestry, fishing(NACE A/B) Mining, quarrying, manufacturing, electricity, gas and water supply(NACE C/D/E) Construction(NACE F) Trade, repair, hotels and restaurants, transport, storage and communication(NACE G/H/I) Financial intermediation, real estate, renting and business activities(NACE J/K) Public administration and defence, education, health and social work, services n.e.c. (NACE L/M/N/O/P) FISIM Total
  codes 2a 2b 2c 2d 2e 2f 2g 2h
Compensations 3a 667 9.465 2.646 8.412 4.306 13.934 0 39.431
Mixed Income 3b 2.867 751 1.529 3.479 1.135 1.222 0 10.982
Net operating surplus 3c 85 4.500 187 3.621 3.343 -147 0 11.589
Other taxes less subsidies on production 3d -173 -40 -25 -122 -17 -65 0 -443
FISIM 3e 0 0 0 0 0 0 -3.770 -3.770
Total 3f 3.446 14.676 4.337 15.390 8.767 14.944 -3.770 57.789
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and in a SAM
Generation of income(value added categories) Generation of income(value added categories) Generation of income(value added categories)   Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries) Production (NACE-rev. 1 Industries)   Total
Generation of income(value added categories) Generation of income(value added categories) Generation of income(value added categories)   NACE A/B NACE C/D/E NACE F NACE G/H/I NACE J/K NACE L/M/N/O/P FISIM Total
      codes 2a 2b 2c 2d 2e 2f 2g 2h
Compensations Male Primary/lower secondary (ISCED 1-2) 3a-1 467 4.202 2.112 3.967 917 2.259   13.924
Compensations Male Upper or post secondary (ISCED 3-4) 3a-2 20 846 201 947 1.075 1.252   4.342
Compensations Male Tertiary (ISCED 5-6) 3a-3 4 841 164 481 936 3.683   6.109
Compensations Female ISCED 1-2 3a-4 158 2.955 28 1.932 475 2.869   8.417
Compensations Female ISCED 3-4 3a-5 16 435 101 756 602 1.724   3.634
Compensations Female ISCED 5-6 3a-6 2 187 41 328 301 2.147   3.006
Mixed Income Male ISCED 1-2 3b-1 1.536 460 1.434 1.959 298 315   6.002
Mixed Income Male ISCED 3-4 3b-2 27 79 45 295 262 106   814
Mixed Income Male ISCED 5-6 3b-3 2 36 44 106 328 149   664
Mixed Income Female ISCED 1-2 3b-4 1.293 151 5 971 82 374   2.875
Mixed Income Female ISCED 3-4 3b-5 8 19 0 125 63 167   382
Mixed Income Female ISCED 5-6 3b-6 1 7 0 24 102 111   245
Net operating surplus Net operating surplus Net operating surplus 3c 85 4.500 187 3.621 3.343 -147   11.589
Other taxes less subsidies on production Other taxes less subsidies on production Other taxes less subsidies on production 3d -173 -40 -25 -122 -17 -65   -443
FISIM FISIM FISIM -3.770 -3.770
Total Total Total 3f 3.446 14.676 4.337 15.390 8.767 14.944 -3.770 57.789
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1. Labour oriented SAM, expansion of a NAM

Compensations of employees of Households for
providing labour to the economy, in a NAM
Allocation of primary income (Institutional sectors)   Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Total
Allocation of primary income (Institutional sectors)   Compensations Mixed Income Net operating surplus Other taxes less subsidies on production FISIM Total
  codes 3a 3b 3c 3d 3e 3f
Non-financial corporations 4a     10.097   10.097
Financial corporations 4b     1.324   -3770 -2.447
General government 4c     -76 10.473   10.398
Households 4d 39.489 10.982 449     50.919
Non-profit institutions serving households 4e     -205     -205
Total 4f 39.489 10.982 11.589 10.473 -3.770 68.762
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in a SAM
Allocation of primary income (Institutional sectors) Allocation of primary income (Institutional sectors)   Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories) Generation of income (value added categories)   Total
Allocation of primary income (Institutional sectors) Allocation of primary income (Institutional sectors)   Compensations Compensations Compensations Compensations Compensations Compensations Mixed Income Mixed Income Mixed Income Mixed Income Mixed Income Mixed Income Net operating surplus Taxes less subsidies on production FISIM Total
Allocation of primary income (Institutional sectors) Allocation of primary income (Institutional sectors)   Male Male Male Female Female Female Male Male Male Female Female Female Net operating surplus Taxes less subsidies on production FISIM Total
Allocation of primary income (Institutional sectors) Allocation of primary income (Institutional sectors)   ISCED 1-2 ISCED 3-4 ISCED 5-6 ISCED 1-2 ISCED 3-4 ISCED 5-6 Net operating surplus Taxes less subsidies on production FISIM Total
    cod 3a-1 3a-2 3a-3 3a-4 3a-5 3a-6 3b-1 3b-2 3b-3 3b-4 3b-5 3b-6 3c 3d 3e 3f
Non-financial corporations Non-financial corporations 4a                         10.097   10.097
Financial corporations Financial corporations 4b                         1.324   -3770 -2.447
General government General government 4c                         -76 10.473   10.398
Households classified by main source of income Wages and salaries 4d-1 13.463 4.100 6.003 7.599 3.253 2.848 1.031 297 271 926 220 155 260     40.426
Households classified by main source of income Mixed income (including property income) 4d-2 235 127 38 515 274 97 4.649 560 268 1.676 298 35 117     8.888
Households classified by main source of income Income in connection with old age (retirement) 4d-3 121 79 17 166 80 66 84 66 13 196 39 4 58     987
Households classified by main source of income Other transfers income (including other households) 4d-4 96 48 45 159 45 13 71 33 8 73 12 0 15     618
Non-profit institutions serving households Non-profit institutions serving households 4e                         -205     -205
Total Total 4f 13.916 4.354 6.103 8.438 3.652 3.025 5.835 955 559 2.871 569 194 11.589 10.473 -3.770 68.762
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1. Portuguese SAM

Classifications in the pilot-SAM
NAM/SAM (ESA95 transactions)

• Input labour
• status
• employees
• self-employed
• gender
• educational level
• lower (ISCED 1-2)
• medium (ISCED 3-4)
• higher (ISCED 5-6)
• Households
• Wages and salaries (S143)
• Mixed income including property
• income (S141S142 S1441)
• Income with connection with old
• age (S1442)
• Other transfers income (including
• other households)
• (S1443 and S145)

• Industries a minimum of 6
• industries according to NACE
• Products a minimum of 6 products
• according to CPA.
• Institutional sectors according to
• ESA95. A minimum of 3 sectors
• (corporations general government
• and households including NPISH).
• Financial transactions

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1. Portuguese SAM -Demand side of the labour market

• Estimation of compensations of employees-demand
  side
• In the generation of income account,
  compensations are broken-down by type of labour,
  by gender and education level. Compensations of
  employees are estimated with the same procedures
  used in the National Accounts and respective data
  sources.
• Also Labour input (persons, jobs) is broken-down
  by type of labour.
• Data sources
  
  Administrative data source Quadros de Pessoal -
  structures
• Ministry of Labour and Social Security
• Every enterprise with at least on employed
  person answers it
• Labour Force Survey (LFS) - structures
• National Accounts - totals

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1. Portuguese SAM-Demand side of the labour market

Methodology - Part 1 1st Step Values of
earnings by gender, level of education and
activity branch from Quadros de Pessoal. (matrix
W) 2nd Step

Values were adjusted in order to incorporate
the employer's actual and imputed social
contributions. Wijg Wijl x (1 tisc tasc),
i refers to the type of labour and j to the
branch
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1. Portuguese SAM-Demand side of the labour market

Each estimate was also adjusted to an annual
scale Wijga 14 Wijg 3rd step
Determination of the matrix of hours worked in
each branch, by gender and education level,
available by the same source Quadros de Pessoal.
This matrix, with the general element Hij, was
also scaled to an annual basis. 4th step
Determination of the average hourly
earnings cij (Wij / Hij)
5th step Determination of the relevant matrix
of hours worked using the data from Labour Force
Survey hijw
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1. Portuguese SAM-Demand side of the labour market

First estimates of compensations
Average hourly earnings x Actual hours worked
Matrix C
cij cij x hijw

• Methodology - Part 2
• Reconciliation with NA data through the RAS
  method,
• taking into account two constraints
• NA figures of compensations by industry
• Weights of each kind of labour in the total
  compensations obtained from the matrix C of the
  first estimates.
• For Mixed Income, the same data sources and
  methodology was adopted. It was admitted that the
  hourly earnings of self-employed were the same as
  those of the employees.

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1. Portuguese SAM-Supply side of the labour market

• Estimation of compensation
• Compensations were previously broken-down by type
  of labour. For the allocation of the primary
  income account, compensations and mixed income
  are further broken-down by type of recipient
  household group according to the main source of
  income.
• Compensations are estimated through the use of
  the National Accounts procedures and respective
  data sources.
• Data sources
• Household Budget Survey (HBS) structures
• National Accounts (NA) - totals

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1. Portuguese SAM-Supply side of the labour market

1st step From HBS a matrix of compensations by
type household (rows), gender and education level
and productive branch (columns), matrix R
2nd step
The
last row of the above table - row R.j matches
the matrix of compensation associated with the
demand side of labour (industry x type of labour,
matrix Cij), that has already been reconciled
with NA data. Matrix Cij will be considered as
constraint for matrix R.
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1. Portuguese SAM-Supply side of the labour market

3rd step From matrix R, the share of
compensations by type household for a certain
branch / type of labour can be found. Matrix Rw
of relative weights of each cell of R in the
total of the respective column. The sum of each
column of matrix Rw is 1. The generic element
rwij rij / R.j
4th step There are NA values (matrix C) and the
HBS structure (matrix Rw) to respect. Each value
of matrix C, cij, is broken-down through the
structure of households of matrix Rw. The result
is a matrix R1 with dimension 4x(6x17) compatible
with NA. The last row of R1 is now identical to
matrix C.

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1. Portuguese SAM Supply
   side of the labour market

5th step Being the objective to have a matrix
of compensations of employees by type of labour
and type of household, the values of different
branches must be aggregated, as if only one
industry was considered. The resulting matrix,
let us call C, has a dimension 4 households
groups (in row) x 6 types of labour (in column).

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1. Main uses

1. Productivity growth of labour input (requires SAM
   at constant prices)
2. Employment growth
3. Composition of labour among industries in terms
   of status, gender, educational level
4. Gender cost of labour differential among
   industries and countries that compile SAM
5. SAM time series analysis of impacts and changes
   in the structures of labour (in composition and
   industries)

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1. Main uses Direct indicators Compensations
   by gender

2.
1.
3.
Between 2000 and 2003 Compensations by gender present a structural behaviour On average, 39 of the compensations referred to women and 61 to men Compensations for women had a higher nominal growth rate

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• Main uses Direct indicators
• Jobs by gender

2.
1.
3.
Between 2000 and 2003 Compensations of women, on average, represent 39, but women occupy, on average, 47 of jobs Womens compensations had a higher growth rate

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1. Main uses Direct indicators Compensations
   by level of education

2.
1.
Between 2000 and 2003 Compensations by level of education present a structural behaviour. On average, 67 of the compensations referred to lower level of education, 28 to medium and 17 to the higher level. Compensations of the higher and medium levels of education grow more than the lower level.
3.

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1. Main uses Direct indicators Jobs by level
   of education

2.
1.
3.
Between 2000 and 2003 Compensations of the highest educ. level represent on average 26 but Only 12 of jobs, on average The number of jobs of the higher and medium levels of education grow more than the lower level,

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1. Main uses Direct indicators Compensations
   by gender and level of education

The split of compensations of employees by gender
changes according to the level of
education Women have a higher percentage within
the medium and higher levels of education, in
relation to the differential men vs women.

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1. Main uses Direct indicators Yearly average
   compensations by gender and level of education

For the same education level, womens yearly
average compensations are lower than
mens. Average compensations of employees for
women of the highest level are closer with those
of men corresponding to the immediate lower level
of education (medium) and those of women for the
medium are closer with those of men for the
lowest.

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• Main uses Direct indicators
• Average compensations by industry

gender
and level of education

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1. Main uses Direct indicators Average
   compensations in Manufacturing (2000-2003)

• Manufacturing is an example of industry with
  predominance of compensations generated by
• lower education jobs
• men jobs

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1. Main uses Direct indicators Average
   jobs in Manufacturing (2000-2003)

• Manufacturing is an example of industry with
  predominance of
• lower education jobs
• men jobs

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1. Main uses Direct indicators Average
   compensations in Education (2000-2003)

• Education is an example of industry with
  predominance of compensations generated by
• higher education jobs
• women jobs

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1. Main uses Direct indicators Average
   jobs in Education (2000-2003)

• Education is an example of industry with
  predominance of
• higher education jobs
• women jobs

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1. Main uses

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