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Unit for Satellite AccountsNational Accounts
DepartmentStatistics Portugal
« Geneva, Switzerland
6-7-8 October 2008 «
Social Accounting Matrix- Portugal
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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 SAM’s. Statistics Portugal compiles SAM’s labour-oriented on a mandatory way.
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1. General overview
Social AccountingMatrix(SAM)
National Accounts
Labour AccountsNational AccountingMatrix(NAM)
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Table 1.1 : Aggregate National Accounts M atrix, Europeland
ACCOUNT 1, Goods and 2. Production 3. Generation 4. Allocation of 5. Secondary distri-6. Use of dispo- 7. Capital 8. Gross fixed 9. Financial 10. Rest of the world, 11. Rest of the world,12,TOTAL
services of income primary income bution of income sable income capital formation current capital
Classifications product industries primary input institutional institutional institutional institutional industries financial
groups categories sectors sectors sectors sectors assets
1. Goods and product Trade and Intermediate Final consumption Changes in Gross fixed Exports of goods
services groups transport consumption expenditure inventories capital formation and services
margins
0 1 904 1 371 38 376 536 4 225
2. Production industries Output
(basic prices)
3 595 3 595
3. Generation primary input NET VALUE Compensation of
of income categories ADDED employees from
(basic prices) the ROW
1 469 6 1 475
4. Allocation institutional Taxes less GENERATED Property income Property income and
of primary sectors subsidies on INCOME, NET taxes less subsidies
income products (basic prices) on production from
the ROW
133 1 473 341 66 2 013
5. Secondary institutional NATIONAL Current Current transfers
distribution sectors INCOME, NET transfers from the rest
of income of the world
1 633 1 096 10 2 739
6. Use of institutional DISPOSABLE Adjustment for the Adjustment for the
disposable sectors INCOME, NET change in net equity change in net equity of
income of households on pen- households on pension
sion funds reserves funds reserves from ROW
1604 11 0 1615
7. Capital insttutional SAVING, NET Capital transfers+I32 Net incurrence Capital transfers
sectors of liabilities from the ROW
233 68 603 1 905
8. Gross fixed industries Consumption Net fixed capital
capital of fixed capital formation
formation 222 154 376
9. Financial financial Net acquisitions of NET LENDING
assets financial assets OF THE ROW
641 -38 603
10. Rest of the world, Imports of Compensation Property income Current Adjustment for the
current goods and of employees and taxes less transfers change in net equity
services to the ROW subsidies on pro- to the ROW equity of households
(c.i.f.) duction to the on pension funds re-
ROW serves to the ROW
497 2 39 39 0 577
11. Rest of the world, Capital transfers CURRENT
capital to the ROW EXTERNAL
BALANCE
4 -41 -37
12. TOTAL 4 225 3 595 1 475 2 013 2 739 1 615 905 376 603 577 -37
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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;
1. General overview
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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 who’s paying to whom and who’s receiving from whom;
1. General overview
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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;
1. General overview
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SAM’s 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.
1. General overview
11
SAM’s 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.
1. General overview
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• 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.
1. General overview
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Sectors a b c d e f Totala. Non-financial
Corporations (a,a) (a,b) (a,c) (a,d) (a,e) (a,f)A
(Resources)
b. Financial Corporations (b,a) (b,b) (b,c) (b,d) (b,e) (b,f)B
(Resources)
c. General Government (c,a) (c,b) (c,c) (c,d) (c,e) (c,f)C
(Resources)
d. Households (d,a) (d,b) (d,c) (d,d) (d,e) (d,f)D
(Resources)
e. NPISH (e,a) (e,b) (e,c) (e,d) (e,e) (e,f)E
(Resources)
f. Rest of the World (f,a) (f,b) (f,c) (f,d) (f,e)F
(Resources)
TotalA
(Uses)B
(Uses)C
(Uses)D
(Uses)E
(Uses)F
(Uses)Total economy
Table sector by sectorFrom “whom to whom”
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• A NAM represents the entire economy, the complete sequence of economic accounts but is limited by to its scope and doesn’t 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.
2.Labour-oriented SAM, expansion of a NAM
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Possible dimensions of a Labour-oriented SAM:
1. Type of labour: status in employment: employee or self-
employed; gender; educational level; age group; categories of professions, …
2. 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.
2.Labour-oriented SAM, expansion of a NAM
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The economic accounts integrating Employment:
Generation of Income Account: Labour demandShows 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:
2.Labour-oriented SAM, expansion of a NAM
• Type of labour
• Households group
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Generation of income
(value added categories)
Production (NACE-rev. 1 Industries) Total
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
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 10.982Net operating surplus
3c
85 4.500 187 3.621 3.343 -147 0 11.589Other 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
Total3f 3.446 14.676 4.337 15.390 8.767 14.944 -3.770
57.789
Contribution of employment by industry in the NAM
2.Labour-oriented SAM, expansion of a NAM
Generation of income(value added categories)
Production (NACE-rev. 1 Industries)
TotalNACE A/B
NACE C/D/E NACE F NACE G/H/I NACE J/KNACE
L/M/N/O/PFISIM
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
Upper or post secondary (ISCED 3-4)
3a-2 20 846 201 947 1.075 1.252 4.342
Tertiary (ISCED 5-6)
3a-3 4 841 164 481 936 3.683 6.109
FemaleISCED 1-2 3a-4 158 2.955 28 1.932 475 2.869 8.417
ISCED 3-4 3a-5 16 435 101 756 602 1.724 3.634
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
ISCED 3-4 3b-2 27 79 45 295 262 106 814
ISCED 5-6 3b-3 2 36 44 106 328 149 664
Female
ISCED 1-2 3b-4 1.293 151 5 971 82 374 2.875
ISCED 3-4 3b-5 8 19 0 125 63 167 382
ISCED 5-6 3b-6 1 7 0 24 102 111 245 Net operating surplus 3c 85 4.500 187 3.621 3.343 -147 11.589
Other taxes less subsidies on production 3d -173 -40 -25 -122 -17 -65 -443
FISIM -3.770 -3.770
Total 3f 3.446 14.676 4.337 15.390 8.767 14.944 -3.770 57.789
… and in a SAM
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Allocation of primary income
(Institutional sectors)
Generation of income (value added categories)
TotalCompensations
Mixed Income
Net operating surplus
Other taxes less subsidies on production
FISIM
codes3a 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
Compensations of employees of Households for providing labour to the economy, in a NAM …
2.Labour oriented SAM, expansion of a NAM
Allocation of primary income
(Institutional sectors)
Generation of income (value added categories) Total
Compensations Mixed Income Net operating surplus
Taxes less
subsidies on
production
FISIM
Male Female Male FemaleISCED
1-2ISCED
3-4ISCED
5-6ISCED
1-2ISCED
3-4ISCED
5-6
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 4a 10.097 10.097
Financial corporations 4b 1.324 -3770 -2.447
General government 4c -76 10.473 10.398 Ho
useh
old
s classified b
y main
sou
rce of in
com
e
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 Mixed income
(including property income)
4d-2
235 127 38 515 274 97 4.649 560 268 1.676 298 35 117 8.888
Income in connection with old age (retirement)
4d-3
121 79 17 166 80 66 84 66 13 196 39 4 58 987
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
4e -205 -205
Total 4f 13.916 4.354 6.103 8.438 3.652 3.025 5.83
5 955 559 2.871 569 194 11.589 10.473 -3.770 68.762
… in a SAM
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Classifications in the pilot-SAM:
NAM/SAM(ESA95 transactions)
Industries: a minimum of 6industries according to NACE
Products: a minimum of 6 productsaccording to CPA.
Institutional sectors: according to ESA95. A minimum of 3 sectors(corporations; general governmentand households including NPISH). Financial transactions
Input labour: status:
employeesself-employed
gendereducational level
lower (ISCED 1-2)medium (ISCED 3-4)higher (ISCED 5-6)
Households:Wages and salaries (S143)Mixed income including property
income (S141+S142; S1441)Income with connection with old age (S1442)Other transfers income (including
other households) (S1443 and S145)
3.Portuguese SAM
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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
3.Portuguese SAM -Demand side of the labour market
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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 = Wij
l * x (1+ tisc+ tasc),
i refers to the type of labour and j to the branch
Activity branches A B . . . P Q TOTAL
Type of labour 1 2 . . . . . . 17 TOTALG1 - MG1 - F C21 C22 Cij C2.
G2 - MG2 - FG3 - MG3 - FTOTAL C.2 C.j
3.Portuguese SAM-Demand side of the labour market
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Each estimate was also adjusted to an annual scale:
Wijga = 14 * Wij
g
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: hij
w
3.Portuguese SAM-Demand side of the labour market
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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.
= Average hourly earnings x Actual hours worked
cij = cij x hijw
First estimates of
compensations Matrix C
3.Portuguese SAM-Demand side of the labour market
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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
3.Portuguese SAM-Supply side of the labour market
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1st step
From HBS a matrix of compensations by type household (rows), gender and education level and productive branch (columns), matrix R:
QG1-M G1-F … G3-F … …
R .1
R .2
R .3
R .4
R .1 R .2 R .j R .17
Total
TotalHou
seho
ld
subs
ecto
r
S1442S1443+S145
AActivity branchesType of labour
S143S141+S142+S1441
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.
3.Portuguese SAM-Supply side of the labour market
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«
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.
3.Portuguese SAM-Supply side of the labour market
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«
«
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).
3.Portuguese SAM Supply side of the labour market
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«4.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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Average percentage of compensations by gender (2000-2003)
39%
61%
Men
Women
Total compensations by gender
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
2000 2001 2002 2003
mill
ion
eu
ros
Women
Men
Growth rate of total compensations by gender
0,0
2,5
5,0
7,5
10,0
2001 2002 2003
%
Men
Women
Between 2000 and 2003:
1. Compensations by gender present a structural behaviour
2. On average, 39% of the compensations referred to women and 61% to men
3. Compensations for women had a higher nominal growth rate
4.Main uses: Direct indicators Compensations by gender
1.
3.
2.
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«
«
Average percentage of compensations by gender (2000-2003)
39%
61%
Men
Women
Between 2000 and 2003:
1. Compensations of women, on average, represent 39%, but
2. women occupy, on average, 47% of jobs
3. Women’s compensations had a higher growth rate
Average jobs by gender (2000-2003)
53%
47%
Men
Women
4. Main uses: Direct indicators
Jobs by gender1.
3.
2.
Growth rate of jobs by gender
-2,5
0,0
2,5
5,0
2001 2002 2003
%
Men
Women
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«
«
Between 2000 and 2003:
1. Compensations by level of education present a structural behaviour.
2. On average, 67% of the compensations referred to lower level of education, 28% to medium and 17% to the higher level.
3. Compensations of the higher and medium levels of education grow more than the lower level.
Total compensations by educational level
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
2000 2001 2002 2003
mill
ion
eu
ros
Higher
Medium
Lower
Growth rate of total compensations by educational level
-2,5
0,0
2,5
5,0
7,5
10,0
2001 2002 2003
%
Lower
Medium
Higher
4.Main uses: Direct indicators Compensations by level of education
1.
3.
2.Average percentage of compensations by educational level (2000-2003)
57%17%
26%Lower Medium Higher
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«
«
Between 2000 and 2003:
1. Compensations of the highest educ. level represent on average 26% but
2. Only 12% of jobs, on average
3. The number of jobs of the higher and medium levels of education grow more than the lower level,
Average percentage of compensations by educational level (2000-2003)
57%17%
26%Lower Medium Higher
Average percentage of jobs by educational level (2000-2003)
73%
15%
12%
Lower Medium Higher
4.Main uses: Direct indicators Jobs by level of education
1.
3.
2.
Growth rate of jobs by educational level
-5,0
-2,5
0,0
2,5
5,0
7,5
10,0
2001 2002 2003
%
Lower
Medium
Higher
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«
«4. 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.
Average total compensations by gender and educational level (200-2003) - detail for lower level
17%
26%
37%
20%
57%
Medium Higher Low er H Low er M
Average total compensations by gender and educacional level (2000-2003) - detail for medium level
57%
10%
7%
17%
26%
Low er Higher Medium H Medium M
Average total compensations by gender and education level (2000-2003) - detail for higher level
58%
17%
13%
12%
26%
Low er Medium Higher H Higher M
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«
«4.Main uses: Direct indicators Yearly average compensations by gender and level of education
For the same education level, women’s yearly average compensations are lower than men’s.
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.
Yearly average compensations by gender and eductaion level
0
10.000
20.000
30.000
40.000
50.000
2000 2001 2002 2003
euro
s
Lower M
Lower W
Medium M
Medium W
Higher M
Higher W
Total
37
«
«
4. Main uses: Direct indicators
Average compensations by industry …
Average compensations by industry and gender (2000-2003)
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
A B C D E F G H I J K L M N O P
NACE_A17
mil
lio
n e
uro
s
Women
Men
… gender
… and level of education
Average compensations by industry and educational level (2000-2003)
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
A B C D E F G H I J K L M N O P
NACE_A17
mil
lio
n e
uro
s
Lower Medium Higher
38
«
«4.Main uses: Direct indicators Average compensations in Manufacturing (2000-2003)
Manufacturing is an example of industry with predominance of compensations generated by:
• lower education job’s
• men job’s
Manufacturing - detail for lower level
12%
11%50%
27%
77%
Medium Higher Low er H Low er M Manufacturing - detail for medium level
77%
8%
4%
12%
11%
Low er Higher Medium H Medium M
Manufacturing - detail for higher level
77%
12%
8%
3%
11%
Low er Medium Higher H Higher M
39
«
«4.Main uses: Direct indicators Average jobs in Manufacturing (2000-2003)
Manufacturing is an example of industry with predominance of:
• lower education jobs’
• men job’s
Manufacturing - detail for lower level
10%
4% 46%
40%
86%
Medium Higher Low er H Low er M
Manufacturing - detail for medium level
87%
5%
4%
10%
4%
Low er Higher Medium H Medium M
Manufacturing - detail for higher level
85%
3%
2%
4%
10%
Low er Medium Higher H Higher M
40
«
«4.Main uses: Direct indicators Average compensations in Education (2000-2003)
Education - detail for lower level
8%
72%
6%
14%20%
Medium Higher Low er H Low er M
Education - detail for medium level
20%
3%
5%
8%
72%
Low er Higher Medium H Medium M
Education - detail for higher level
20%
8%23%
49%71%
Low er Medium Higher H Higher M
Education is an example of industry with predominance of compensations generated by:
• higher education job’s
• women job’s
41
«
«4.Main uses: Direct indicators Average jobs in Education (2000-2003)
Education - detail for lower level
10%
57%7%
26%32%
Medium Higher Low er H Low er M
Education - detail for medium level
32%
3%
7%
10%
58%
Low er Higher Medium H Medium M
Education - detail for higher level
32%
14%
44%59%
10%
Low er Medium Higher H Higher M
Education is an example of industry with predominance of:
• higher education job’s
• women job’s
42
«
«4.Main uses
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