a financial social accounting matrix for the spanish economy sam spain... · “a sam is defined...

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A Financial Social Accounting Matrix for the Spanish Economy

Henry Aray Luis Pedauga

Agustín Velázquez

University of Granada

January 2016

Abstract

This article goes beyond the traditional methodology of Social Accounting Matrix

(SAM) at building a Financial Social Accounting Matrix for Spain (FSAM). It has had

to overcome the difficulties that arise at consolidating the data from the National

Statistics Institute (INE) and the Bank of Spain (BE). A RAS methodology is proposed

to estimate the property income distribution when no official data are available. This is

the first FSAM for the Spanish economy which could provides new tools to deepen the

analysis of the financial sector and the determinants of financial stability associated with

the interaction with other sectors of the economy.

Keywords: Financial Social Accounting Matrix, Spain; RAS.

JEL Classification: C67, D57.

2

1. Introduction.

In every economy there are five fully identified agents that are known as institutional

sectors: non-financial corporations, financial institutions, government, households and

non-profit institutions serving households (NPISHs). A sixth agent could be considered

the rest of the world (RW), which is also composed of the same five institutional sectors

as above. The reason for this grouping is related with the functions and activities

undertaken in a society by these five institutional sectors. Production and transactions of

these sectors are collected in the System of National Accounts (SNA).

The main activity of non-financial corporations, represented by companies, is the

production of different goods and services required by an economy. This sector

accounts for the productive economy and generates the main contribution to the Gross

Domestic Product (GDP) which in turn gives rise to the circular flow of income. This

sector is usually the largest in terms of number of players involved and it concentrates

the largest number of surplus and deficit agents of an economy.

The government sector includes central, regional and local governments, as well as,

any government agency that serves society. The services provided by the government

are carried out, in principle, without generating economic benefit for this sector.

The household sector consists mainly of individuals who have very special

characteristics. On the one hand, it provides labor to the rest of institutional sectors for

the development of their activities. On the other hand, it is the final goal of the

generation of goods and services provided by the other sectors. In addition, this sector

can also participate in the production of goods and services not necessarily established

as a legal entity.

The main role of the NPISHs sector is to provide services to the household sector, in

similar terms to those of the government, but from the private sector.

3

The financial sector serves as a link to interconnect all other sectors. It identifies

surplus and deficit agents and its main function is to be a channel for the transfer of

funds from the former to the latter. Therefore, achieving an adequate financial support

to deficit sectors becomes a paramount task for the financial sector.

The results of the decisions of institutional sectors are shown in the SNA, which

provides a complete system of integrated accounts for all economic activities. However,

this system is not enough to understand the complex interconnections between sectors.

The first attempt to deepen the analysis of these interconnections was through the input-

output model of Leontief (1936) which aimed at collecting the intra-industrial links to

show that the final product of a sector can be used as an intermediate good for other

sector. However, this approach is limited to the production and demand of goods and

services. Stone (1962) proposed a Social Accounting Matrix (SAM) to overcome the

limitations of both the SNA and the input-output model at considering all economic

transactions taking place within an economy and adding information about the

institutional sectors and income distribution. The SAM is basically a matrix

representation of the SNA with some extensions. The adoption of this framework by the

World Bank and the publication of the articles by Pyatt and Round (1977, 1979) made

the SAM a popular and powerful tool for national and international institutions to assess

the impact of economic programs and exogenous shocks on the economy.

The short-term perspective of the SAM allows reliable estimate of the effects of

economic policy proposals and reforms in the economy. Thereby, it is not surprising

that many countries have developed this tool in order to evaluate political economy

decisions. In the specific case of Spain, the first SAM was developed by Kehoe et al.

(1988) for the year 1980. After that, several authors have updated, expanded and

improved the precedent ones like Alvarez-Martinez and Polo (2014), who developed a

4

SAM for 2000 and collect the main references. To the best of our knowledge, the more

recent SAM for the Spanish economy is by Cansino et al. (2013) for 2007.

It should be stressed that most of the SAMs have been built to answer particular

questions of computable general equilibrium models with limited scopes for more

general applications.

The success of SAM has expanded to a regional perspective. The initial national

dimension of the SAM has led some countries to boost interest in building this tool at

the regional level. Among them, Spain has been very active in developing regional

SAMs as can be seen in Camara-Sanchez et al (2014).

Although the SAM is very useful for economic analysis and evaluation, it is an

incomplete tool because it is limited to the real economy at not including financial ties

across the sectors, that is, details on the financial institutions and transactions of the

agents through its financial assets and liabilities..

The recent financial crisis has reminded us the important role of the financial sector

in the economy. The discussion of the effect of financial development and stability in

economic growth has emerged recently with much more strength.1 Therefore, it is

necessary and required the development of new tools and methodologies that include

the financial market and its relationship with the rest of the economic system in order to

deal with similar situations in the future. Perhaps for that reason, FSAMs are beginning

to be built. The FSAM is an extension of the traditional SAM including details of the

financial sector, financial transactions and financial instruments of all institutional units.

Considering the best of our knowledge, FSAMs have been brought out for few

countries: Cameroon (Emini and Fofack, 2004), Portugal (Santos, 2007), Turkey

(Aslan, 2007), Colombia (Hernandez, 2008), China (Li, 2008 and Liu et al., 2015 ),

1 See Guerrera y Pastor (???) libro donde Luis tiene un capítulo.

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Pakistan (Waheed, 2008), Luxembourg (Hubic, 2012), Philippines (Viet et al., 2013),

Germany (Helbig, 2013) and Tunisia (Ayadi and Hadj Salem, 2014).2

The importance of the financial sector lies precisely in its role of financial

intermediation at serving as a connector for the entire productive sector of the economy.

The interconnection between the financial sector and the non-financial sector is the

mechanism through which is transmitted the strengths and vulnerabilities of the

economic activity. Thus, a major role of the financial sector is the identification of

surplus sectors in order to promote adequate financial support to deficit sectors. Despite

the intricate and complex interaction between this sector and other sectors, the financial

intermediation could lead to strength other sectors of the economy through the provision

of adequate financial leverage. However, precisely through the intermediation channels,

the financial sector may be vulnerable when borrowers (companies, governments,

households) have difficulties meeting their financial obligations. Moreover, such

vulnerability could result from the misallocation of portfolios when financial

institutions allocate funds in very risky assets that could adversely affect the

profitability of investors endangering the entire financial system. That is why the

financial sector is strongly legislated and several supervision institutions have been

established or strengthened aimed at achieving a well-functioning of the financial sector

in order to provide financial stability so that market participants can develop their

activities in a sound economic framework which would contribute to the good

performance of the economy.

Although the financial sector interacts with all other sectors of the economy, its main

task should be to provide the necessary financial resources for the productive sector,

which is concentrated in the non-financial sector. The participation and efficiency of

2 FSAM could be an instrument for economic policy making in some other countries. However, confidentially policy makes this instrument unavailable.

6

these two sectors have important consequences on the aggregate performance of the

whole economy as reflected in the traditional indicators such as GDP growth.

The contribution of this article is therefore the construction of the first FSAM for the

Spanish economy. To achieve this objective we have to combine the statistics of the

National Statistics Institute of Spain (INE) and Bank of Spain (BE) which becomes a

thorough and painstaking task. The FSAM allow extending the use of the multiplier

models associated with this literature for impact analysis of public policy. Moreover, it

could improve and enrich the scope of the computable general equilibrium (CGE)

models.

The article is organized as follows. Next section presents the methodological

framework and the data sources. Section 3 shows the technical aspects of the

construction of the FSAM, while section 4 shows the FSAM for 2009. Conclusions are

drawn in section5.

2. Methodological Framework and Data Sources.

It is considered the definition of Social Accounting Matrix presented in the System

of National Accounts (SNA93) of United Nation 1993,3 which states in Chapter XX that

“A SAM is defined here as the presentation of SNA accounts in a matrix which

elaborates the linkages between a supply and use table and institutional sector

accounts”. This definition remains in the European System of Integrated Accounts 1995

(ESA95) and in the Eurostat Manual of Supply, Use and Input-Output Tables 2008. The

methodology presented here uses as input the statistics of the SNA presented by the

INE, maintaining and respecting the statistical data provided by it, while contemplating

the procedures set out in the UN Manual of SNA93 for the construction of the SAM.

3 The SNA93 devotes an entire chapter with the methodological details for constructing a SAM. This is implicitly held in the SNA2008 which hardly provides new methodological tips.

7

The developments presented here contribute to incorporating new achievements

made by Uriel (1997), Rodriguez and Llanes (2005), Cardenete and Sancho (2007) and

more recently Cansino et al. (2013), the last ones develop the SAM of Spain for 2007 at

basic prices. Our proposal extends the previous SAMs since that one of the main

contributions of this article respect to references above is that the submatrix of property

income and other current transfers’ distributions are provided and detailed by

instruments and institutional sectors.. Moreover, we go beyond at incorporating the

submatrix of the financial sector which contains the asset and liabilities flows across

institutional sector, and thus constructing an FSAM.

In doing so, the SAM framework is extended beyond the information provided by the

INE at interconnecting and incorporating the financial statistical information provided

by the released data of the BE, which also follows the concepts and methodological

procedures in the SNA manual, thus obtaining the first FSAM for the Spanish economy.

Considering that both, the SNA of the INE and the Financial statistics of the BE

shape the entire SNA Manual, the FSAM shows in a matrix representation the entire

system as defined by SNA itself.

Both INE and BE data are for the year 2009 and follows the methodological

guidelines established in ESA95. The reason of choosing that year is because we are

constrained to use the more recent input-output official data of the INE when we started

to construct the FSAM.

2.1. Macro aggregate structure of the FSAM

The FSAM is formed by the same number of rows and columns determined by the

number of accounts, products, activities, institutional sectors and financial instruments.

Table 1 shows the representation of the FSAM at the highest level of aggregation

8

(Macro FSAM). It contains a total of 11 rows and columns, the first 8 represent the

large accounts of the SNA for the domestic economy, 9 and 10 correspond to the

Balance of Payments or the rest of the world and 11 represents the FSAM Total.

The number and order of rows and columns is equal, so that the intersection of rows

and columns represent the variables of the SNA. The order of the accounts is presented

in the same order as the accounts of the SNA. First, it is represented the accounts

concerning the information of rows and columns of the national economy and at the end

the rows and columns that contain the information regarding the rest of the world. In the

specific case of Spain, the development of matrices 1 to 7 and 9 are constructed with

data of the INE, while the matrices 8 and 10 with data of the BE. That is why for the

construction of the FSAM in Spain, it is required to combine data of both institutions.

Each of these accounts can be disaggregated according to the purpose of analysis or

research that is pursued with the construction of the FSAM. The maximum possible

opening of each account is established by the levels of disaggregation of the statistics

offered by these two institutions. In this sense, the FSAM built has information for 109

products (goods and services), 74 economic activities, 5 institutional sectors and 7

financial instruments, forming a 320x320 matrix.

9

Table 1. Design of the Financial Social Accounting Matrix for Spain

Goo

ds a

nd

serv

ices

Out

put

Inco

me

Gen

erat

ion

Prim

ary

Inco

me

Allo

catio

n

Seco

ndar

y di

strib

utio

n of

Inco

me

Use

of

Dis

posa

ble

Inco

me

Cap

ital A

ccou

ntFi

nanc

ial A

ccou

ntC

urre

nt A

ccou

ntC

apita

l Acc

ount

Com

mod

ities

Act

iviti

esV

alue

Add

ed

Cat

egor

ies

Inst

itutio

nal

Sec

tors

Inst

itutio

nal S

ecto

rsIn

stitu

tiona

l S

ecto

rsIn

stitu

tiona

l Sec

tors

Inst

itutio

nal S

ecto

rsC

omm

oditi

esA

ccum

ulat

ion

Acc

ount

s w

ith R

oW

12

34

56

78

910

11

Goo

ds a

nd

serv

ices

Com

mod

ities

1 In

term

edia

te

Con

sum

ptio

n F

inal

C

onsu

mpt

ion

Gro

ss F

ixed

C

apita

l Fo

rmat

ion

Exp

orts

T

otal

Dem

and

Out

put

Activ

ities

2 O

utpu

t T

otal

Out

put

From

Inco

me

Inco

me

Gen

erat

ion

Valu

e Ad

ded

Cat

egor

ies

3 G

ross

Val

ue

Add

ed

Wag

e In

com

e fro

m R

oW

Tot

al P

rimar

y In

com

e

Prim

ary

Inco

me

Allo

catio

n

Inst

itutio

nal

Sec

tors

4 T

axes

on

Pro

duct

s G

ross

Va

lue

Adde

d P

rope

rty

Inco

me

Pro

perty

In

com

e fro

m

RoW

Tot

al In

com

e +

Rece

ived

Pr

oper

ty

Inco

me

Seco

ndar

y di

strib

utio

n of

Inco

me

Inst

itutio

nal

Sec

tors

5 N

atio

nal

Inco

me

Cur

rent

tran

sfer

s,

Cur

rent

taxe

s on

inco

me,

we

alth

, etc

., Ne

t soc

ial

cont

ribut

ions

and

Oth

er

curr

ent t

rans

fers

.

Cur

rent

tran

sfer

s,

Cur

rent

taxe

s on

in

com

e, w

ealth

, et

c., N

et s

ocia

l co

ntrib

utio

ns a

nd

Oth

er c

urre

nt

trans

fers

, pai

d fro

m R

oW

Tot

al In

com

e +

Prop

erty

Inco

me

+ C

urre

nt tr

ansf

ers,

C

urre

nt ta

xes

on

inco

me,

wea

lth,

etc.

, an

d O

ther

.

Use

of

Dis

posa

ble

Inco

me

Inst

itutio

nal

Sec

tors

6 F

inal

con

sum

ptio

n ex

pend

iture

Tot

al u

se o

f di

spos

able

in

com

e

Cap

ital

Acc

ount

Inst

itutio

nal

Sec

tors

7 S

avin

g C

apita

l Tr

ansf

er

Net

bor

row

ing

(Net

acq

uisi

tion

of

finan

cial

liab

ilitie

s)

Cap

ital

Tran

sfer

from

R

oW

Tot

al U

ses

/ Re

sour

ces

of

the

Econ

omy

Fina

ncia

l A

ccou

ntIn

stitu

tiona

l S

ecto

rs8

Net

lend

ing

(Net

ac

quis

ition

of

finan

cial

ass

ets)

Net

lend

ing

(Net

ac

quis

ition

of

finan

cial

ass

ets

of

RoW

)

Tot

al h

oldi

ngs

of tr

ade

cred

its

Cur

rent

A

ccou

ntC

omm

oditi

es9

Impo

rts W

age

Inco

me

to

RoW

Pro

perty

In

com

e to

R

oW

Cur

rent

tran

sfer

s,

Cur

rent

taxe

s on

inco

me,

we

alth

, etc

., Ne

t soc

ial

cont

ribut

ions

and

Oth

er

curr

ent t

rans

fers

pai

d to

Ro

W

Tot

al In

com

e of

Ro

W fr

om

Cur

rent

Ac

coun

t

Cap

ital

Acc

ount

Accu

mul

atio

n Ac

coun

ts w

ith

RoW

10 C

apita

l Tra

nsfe

r to

RoW

Net

bor

rowi

ng (N

et

acqu

isiti

on o

f fin

anci

al li

abilit

ies

of

RoW

)

Cur

rent

ext

erna

l ba

lanc

e T

otal

Cap

ital

Acco

unt R

oW

11 T

otal

Su

pply

Tot

al

Out

put F

rom

Ex

pend

iture

Tot

al o

f Pa

ymen

ts

Tot

al

Paym

ents

+

Paid

Pr

oper

ty

Inco

me

Tot

al P

aym

ents

+

Prop

erty

Inco

me

+ C

urre

nt tr

ansf

ers,

C

urre

nt ta

xes

on

inco

me,

wea

lth,

etc.

, an

d O

ther

.

Tot

al F

inal

C

onsu

mpt

ion

Tot

al U

ses

/ Re

sour

ces

of

the

Econ

omy

Tot

al m

eans

of

paym

ent

Tot

al P

aym

ent

of R

oW fr

om

Cur

rent

Ac

coun

t

Tot

al C

apita

l Ac

coun

t RoW

Source: N

ational Institute of Statistics o

f Spain, Bank of Spain, own calcu

latio

ns1 / Inclu

des a

cquisitions less disp

osals o

f valuables

2 / Inclu

des a

cquisitions less disp

osals o

f non

-‐produ

ced assets

3 / Inclu

des statistical discrepancy

I O

S A M

F S A M

TOTA

L

NATIONAL ECONOMY REST OF THE WORLD

TOTA

L

Mac

ro -

SAM

ES

PAÑ

A

NATI

ONA

L EC

ONO

MY

RES

T O

F TH

E W

OR

LD

1) ARE

A OF RE

AL SEC

TOR EC

ONOMY

2) ARE

A OF

INCO

ME AN

D DISTRIBU

TION OF

INCO

ME

3) ARE

A OF FINAN

CIAL

SEC

TOR

ECONOMY

10

It can be noticed in Table 1 three main areas contained in the FSAM, the first one

refers to the information of the real sector of the economy (Area 1), that contains

elements of the supply and demand of goods and services. The second area refers to the

income distribution (Area 2), which contains the different variables of income and

expenditure that are quantified at the macroeconomic level. The last one refers to the

financial sector of the economy (Area 3), in which it is shown the value of the

transaction through the financial instruments available in the economy by the different

institutional sectors or economic agents.

As pointed out above, the intersection of rows and columns contains different

macroeconomic variables that come from the SNA with two meanings depending on the

reading by the side of the rows or by the side of the columns. The FSAM is read by the

side of the rows as inflows (credit entries, resources, or changes in liabilities or net

value) for the respective economic agents; while on the column side it is read as

outflows (debit entries, uses or changes in assets). Thus, the generic value of an

intersection of the FSAM (i, j) represents an income or entry by agent i coming from the

payment of agent j. Furthermore, as the system represents an accounting system, total

rows must be equal to the total of the columns so that the system is fully balanced,

representing all sizes within the matrix transactional flows occurring during the year

represented in the matrix.

It is interesting to identify the areas of the FSAM in the circular economy flows as

shown in Figure 1 which also gives insights to extend the use of multiplier models and

CGE models.

11

Figure 1. Circular Economic Flow from the Financial Social Accounting Framework

2.2. Data Sources As pointed out above, we have to consolidate the statistics published by the INE and

the BE. Table 2 represents the data provider for the three areas that make up the FSAM

Cir

cula

r Fl

ows

from

the

Fina

ncia

l Soc

ial A

ccou

ntin

g Fr

amew

ork

Leye

nd:

End

ogen

ous

Acc

ount

s fo

r the

Mul

tiplie

r Inp

ut -

Out

put M

odel

Mon

etar

y Fl

ows

End

ogen

ous

Acc

ount

s fo

r the

Acc

ount

ing

Mul

tiplie

r of S

AM

Mod

elP

rope

rty In

com

e In

flow

s fro

m th

e Fi

nanc

ial A

sset

s

End

ogen

ous

Acc

ount

s fo

r the

Acc

ount

ing

Mul

tiplie

r of F

SA

M M

odel

Pro

perty

Inco

me

Out

flow

s fro

m th

e Fi

nanc

ial L

iabi

litie

s

Sou

rce:

Ow

n de

sign

.

Productio

n

Interm

ediate

Consum

ption

Value Ad

ded

by Activity

Value Ad

ded

by Sector

Prop

erty

income & Other

Varia

bles Fi

nal

Consum

ption

Expe

nditu

re

Saving

Final

Consum

ption

by products

Investment b

y products

Capital

Transfer

Investment

by Sectors

Financial

Assets

Financial

Liabilitie

s

1) ARE

A OF RE

AL

SECT

OR EC

ONOMY

2) ARE

A OF

INCO

ME AN

D DISTRIBU

TION

OF INCO

ME

3) ARE

A OF

FINAN

CIAL

SECT

OR

ECONOMY

1 2

34

5

6

7

8

9 10

11

12

13

9

9

14

12

as indicated in Table 1. Thus, it can be noticed that the INE provides data for the

construction of the Area 1 and Area 2 and the BE for Area 3..

It is important to mention that even though the year selected for the development of

the methodology of construction of the FSAMS was 2009, the procedure proposes here

is designed to generate any other year of the series whenever the respective data are

available from the responsible institutions. Therefore, we considered as future research

the development of the fully time series of the FSAM for the years where data are

available.

Figure 2Sources of Información by areas of the FSAM

Areas of FSAM -‐ Sources of Information -‐ Institutions

Sub-‐Matrices Tables SourceMarco Input-‐outputMarco Input-‐Output -‐ Tablas de origen y destino 2009

Tabla de origen a precios básicos, incluida una transformación a precios de adquisición.Tabla de destino a precios de adquisición.Tabla de destino a precios básicos.Tabla de destino de la producción interior a precios básicos.Tabla de destino de las importaciones (cif).

Contabilidad nacional de España. Base 2008Cuentas económicas integradasCuenta de bienes y serviciosCuentas del total de la economía y de los sectores institucionalesCuentas del sector Instituciones financieras y sus subsectoresCuentas del sector Administraciones públicas y sus subsectoresCuentas del sector Resto del mundo y sus subsectoresAgregados por ramas de actividadValor añadido bruto por tipo de productorClasificación del gasto en consumo final de los hogares por finalidad (coicop)Gasto en consumo final de las Administraciones públicas por componentes y subsectoresFormación bruta de capital fijo por tipo de activoMatrices de formación bruta de capital fijo a precios de adquisiciónOperaciones de bienes y servicios con el Resto del Mundo

Cuentas Financieras de la Economía EspañolaCuadros generalesDetalles por instrumentos de las cuentas no consolidadasCuadros resumen de instrumentos por sectoresResumen por instrumentos y sectores de contrapartida de las cuentas no consolidadasEnlace entre el balance financiero al principio y al final del período

The names of the Tables stay en spanish as the originals in the wabe page of the sources.Source: Own elaboration.

1) AREA OF REAL SECTOR OF THE ECONOMY

Nationa

l Statistics Institute (IN

E)

2) AREA OF INCOME AND INCOME DISTRIBUTION

3) AREA FINANCIAL SECTOR OF THE ECONOMY

Bank

of

Spain (BE)

13

The statistical information from the INE is represented in structure of data separated

by years. In the case of the databases from the BE, the same information is expressed in

quarterly time series, so that it is used the entire structure of these databases and the

sections of the periods that are required are extracted in a dynamic form. Since the data

are in quarterly series, it was required difference treatments among figures expressed in

flows from those expressed in balances, adding the first to form flows of the year and

considering the figures of the last quarter as the closing balances of the respective year.

It should be stressed the detailed work that has to be done to integrate the information of

both institutions and especially the technical difficulties in extracting the required

statistics from the database of the BE to be placed in the FSAM even though they are

public, but in many case, very disaggregated for our purpose. For that reason, the

construction of the FSAM for the Spanish economy becomes a thorough and

painstaking task. An important aspect to be taken into account is that the SNA uses

various information classifiers contained in the statistics of the INE and BE. These

information classifiers will be respected and used to build the FSAM and they are listed

below in Table 3.

Table 3. Classifiers of information used

Código

1. Accounts and Variables Classification. SEC/95 2. Products by activities National Classification. CPA 1-109 3. Economics Activities National Classification. CNAE 1-74 4. Institutional Sectors Classification.

a. Non-Financial Sector S.11 b. Financial institutions S.12 c. Public administrations S.13 d. Households S.14 e. Nonprofit Institutions Serving Households (NPISHs) S.15

5. Financial Instruments Classification. a. Gold and SDR F.1 b. Cash and deposits F.2 c. Representative values of debt F.3 d. Loans F.4 e. Equity participations and investment funds F.5 f. Insurance systems, pension and standardized guarantee F.6 g. Other assets / liabilities F.7/8

14

3. Construction of the FSAM

As shown in Table 1, the FSAM is formed by three areas of the economy: the real

sector, the income and income distribution and the financial sector. Below is explained

how these three areas are obtained.

3.1. Construction of sub-matrices of the Real Sector (Area 1)

The first step is to get the main macroeconomic aggregates of the input-output (IO)

tables and cross them with the major macroeconomic aggregates presented in the tables

of the integrated economic accounts (IEA). It is important to point out that this data

crossing creates mismatch because the IEA are harmonized with the supply and use

tables (SUT) presented by the SNA. In the SUT the different components of supply are

estimated at basic prices as well as the components that allow calculating the supply at

purchaser prices (taxes and subsidies on products and trade and transport margins).

However, the information at basic prices of the components of demand of the economy

is not available in the SUT of the SNA.

In the case of Spain, the reason for using the input-output tables at basic prices are

due to they contain all the supply and demand variables at basic prices as well as the

breakdowns of the demand variables in national and imported origin. Thus, the IO

tables provides more useful and detail information than the SUT.

3.2. Construction of sub-matrices of income, income distribution and use of income (Area 2)

The accounts linked to the income, income distribution and use of income come from

the respective IEA. This set of accounts collects the specific variables of such accounts

as well as the aggregated variables of the system. Among the first, there are several

15

variables such as Property Income, Current Taxes on Income, Wealth, etc., Social

Contributions, Social Benefits different from Social Transfers in kind, Other Current

Transfers, Social Transfers in kind and Adjustment for the change of net participation of

households in the reserves of pension funds. While aggregated variables are represented

by the Value Added, National Income, Disposable Income, Final Consumption and

Savings among others. The variables from the rest of the world accounts in the IEA are

consistent with those from the Balance of Payments Tables of the ¿¿BE or INE ??and

are explicit in the FSAM.

Additionally, the submatrices are required to be opened by institutional sectors

indicating the received and paid for each one and for each variable. For most of the

variables the information is available in explicit form, especially in those variables that

have a single receiver or single payer. However, there are other variables in the IEA

such as Property Income and Current Transfers among others with no published data

available regarding the received and paid flows by the institutional sectors. In order to

overcome this, a methodology was developed as describe below.

3.2.1 Internal distribution of the Property Income Sub-matrix

For the construction of the sub-matrix “Property Income of the Account Allocation

of Primary Income” (rows and columns 5, Figure 1) the information published by the

INE is limited. Therefore, it is not possible to construct this sub- matrix with only the

subtotals presented in the IEA since that the income distribution received and paid by

each institutional sector required for the FSAM is not available. In order to overcome

that, we propose an estimation procedure using the RAS method and following the

recommendations of the Eurostat Manual of Supply, Use and Input-Output Tables 2008.

To estimate the sub-matrix Property income, we started by its definition provided by

the SNA2008 manual that states:

16

“7.107 Property income accrues when the owners of financial assets and natural

resources put them at the disposal of other institutional units. The income payable for

the use of financial assets is called investment income while that payable for the use of a

natural resource is called rent. Property income is the sum of investment income and

rent.”

“7.108 Investment income is the income receivable by the owner of a financial asset

in return for providing funds to another institutional unit…..”

Therefore, we can use the account balances of the financial account relating to

financial assets and liabilities across the institutional sectors as estimators of the shares

of income received and paid by each of them. Intuition suggests that the property

income received and/or paid for each institution sector should be directly proportional to

its levels of assets and/or liabilities. Therefore, satellite sub-matrices of balances of the

assets and liabilities by institutional sector are obtained from the financial account

statistics of the BE. Thus, Table 4 shows the breakdown of the total balance of assets

and liabilities for the whole economy and by institutional sectors . It is measured in

billions of Euros. Rows denote financial liabilities and columns financial assets. The

respective totals for each sector are in last row and column.

Table 4.Stocks: Total financial liabilities (rows) / Total Financial Assets (columns)

Balance at December 2009 EUR thousand millions

Non-financial corporations

Financial corporations

General Government

Households & NPISHs

Rest of the World

Total

Liabilities S.11 S.12 S.13 S.14/5 S.2

Non-financial corporations S.11 1.080 397 71 10 438 1.996

Financial corporations S.12 1.204 1.765 303 920 805 4.997

General Government S.13 113 157 81 15 24 391

Households & NPISHs S.14/15 339 1.295 22 - 61 1.717

Rest of the World S.2 740 1.286 273 2 (7) 2.295

Total Assets 3.476 4.901 749 948 1.321 11.395

Source: Bank of Spain and own calculations.

17

This sub-matrix provides the base for applying the RAS methodological process to

estimate the distribution of the property income, received and paid by each institutional

sector.4

The process is shown in Table 5 where the sub-matrix of balances of the total assets

and liabilities (Step 1) forms the matrix of input coefficients and provides the horizontal

structures or multipliers matrix row (Step 2) and the vertical structures or multiplier

matrix column (Step 3) to be applied in an iterative process to the total property income

received and paid of the Integrated Economic Account until having an internal

distribution of all property income sub-matrix (Step 4).

4 See Appendix for technical details.

18

Table 5. RAS procedure to estimate: D.4. Property Income.

Step 1 Matrix of input coefficients: Financial Liabilities (rows) / Financial Assets (columns)

Stocks at December 2009 EUR billions

Non-financial

corporations


General Government

Households & NPISHs

Rest of the World

Total

Liabilities

S.11 S.12 S.13 S.14/5 S.2 Non-financial corporations S.11 1.080 397 71 10 438 1.996 Financial corporations S.12 1.204 1.765 303 920 805 4.997 General Government S.13 113 157 81 15 24 391 Households & NPISHs S.14/15 339 1.295 22 - 61 1.717 Rest of the World S.2 740 1.286 273 2 (7) 2.295 Total Assets 3.476 4.901 749 948 1.321 11.395

Step 2 Matrix of multipliers for rows

(%)

Non-financial

corporations


General Government

Households & NPISHs

Rest of the

World Total

S.11 S.12 S.13 S.14/5 S.2 Non-financial corporations S.11 54,1 19,9 3,5 0,5 21,9 100

Financial corporations S.12 24,1 35,3 6,1 18,4 16,1 100 General Government S.13 28,9 40,2 20,7 4,0 6,2 100 Households & NPISHs S.14/15 19,7 75,4 1,3 - 3,5 100 Rest of the World S.2 32,3 56,0 11,9 0,1 (0,3) 100

Step 3 Matrix of multipliers for columns

(%)

Non-financial

corporations


General Government

Households & NPISHs

Rest of the World

S.11 S.12 S.13 S.14/5 S.2

Non-financial corporations S.11 31,08 8,10 9,45 1,05 33,14 Financial corporations S.12 34,62 36,02 40,45 97,06 60,93 General Government S.13 3,25 3,21 10,78 1,63 1,84 Households & NPISHs S.14/15 9,75 26,43 2,91 - 4,61 Rest of the World S.2 21,30 26,25 36,40 0,26 (0,53) Total 100 100 100 100 100

Step 4 D.4. Property Income (final iteration)

Flows Jan. to Dec. 2009 EUR thousand millions



General Government

Households & NPISHs

Rest of the World Total

S.11 S.12 S.13 S.14/5 S.2

Non-financial corporations S.11 17.782 5.634 1.161 140 11.270 35.988 Financial corporations S.12 28.291 35.780 7.100 18.537 29.587 119.295 General Government S.13 3.646 4.374 2.598 428 1.225 12.272 Households & NPISHs S.14/15 11.844 39.051 760 - 3.330 54.985 Rest of the World S.2 23.834 35.707 8.750 67 (349) 68.008 Total 85.398 120.546 20.369 19.172 45.063 290.548

Source: NSI, Bank of Spain and own calculations based on Eurostat (2008).

19

3.2.2 Internal distribution of the Sub-matrix of other Current Transfers

Regarding the sub-matrix Other Current Transfers (Row and Column 6, Table 1),

which has the same limitation of property income; we also proceeded according to the

definition of this variable in the SNA2008 Manual where it is defined as follows:

“8.19 Other current transfers consist of all current transfers between resident

institutional units, or between resident and non-resident units, other than current taxes

on income, wealth, etc., social contributions and benefits, and social benefits in kind…”.

The most important categories are: Net premiums non-life insurance, Compensation

of non-life insurance, Current transfers within general government, Current

international cooperation, Current Transfers to NPISHs, Current transfers between

households, Fines and penalties, Lotteries and gambling and Compensation payments.

In this case there was not any available matrix that could serve as a bridge for the

estimation. However, with the total paid and received for this item, we proceeded to

distribute it between the sectors based on those where this kind of transaction is more

common. In doing so, it was considered that the transfers paid by NPISHs and the rest

of the world were received by households as well as those received by these two sectors

were paid by households. The difference of the total paid by households less the amount

paid to NPISHs and the rest of the world was considered received by public

administrations. On the other hand, the received by non- financial corporations and

financial institutions was considered as paid by the public administrations. Internal

transfers between public administrations are available, so that the difference respect the

total paid by them was considered paid to households. The remaining difference of what

was received by households was distributed following the same shares provided by the

IEA for the financial institutions and non-financial sectors. Finally, the difference

20

between the total paid by non-financial and financial sectors respect to that paid to

households, was considered paid to public institutions (Table 6).

Table 6. Other current transfers EUR thousand millions

Step 1 Financial Liabilities (rows) / Financial Assets (columns)

Stocks at December 2009 EUR billions



General Government

Households & NPISHs

Rest of the

World Total

S.11 S.12 S.13 S.14/5 S.2

Non-financial corporations S.11 - - 5.108 - - 5.108 Financial corporations S.12 - - 22.427 - - 22.427 General Government S.13 10.511 16.354 81.920 17.765 - 126.550 Households & NPISHs S.14/15 4.913 7.685 27.364 13.517 10.325 63.804 Rest of the World S.2 - - - 21.895 - 21.895

Total 15.424 24.039 136.819 53.177 10.325 239.784 Source: NSI and own calculations.

Finally, it is important to point out that within this methodological process of

estimation, not only the sub-matrix of property income but also the sub-matrix of Other

Current Transfers can be improved or replaced whenever official data from the INE are

available.

3.3. Construction of submatrices of the Financial Sector of the Economy (Area 3)

The financial account of the FSAM uses data published by the BE which have to be

transformed to extract the required information.

The asset and liability variables across sector come from the primary database tables

for institutional sector and total economy, providing not only the respective annual

balance of the year of study but also the four quarterly flows that these variables have

during the respective year. The maximum disaggregated information provided by the

BE is considered.

The importance of having available both the stocks and the flows implies that the

latter ones are those that would be used properly within the FSAM, while the first ones,

21

the stocks, can be collected in a satellite submatrix that allows estimate the distribution

of the property income as explained above.

The total value of each variable of financial assets and liabilities and their respective

counterpart are available for each institutional. This represents the flow of funds of the

Spanish economy. These tables also complement the information of the FSAM through

satellite matrices that provides detailed information of the flow of funds of the Spanish

Economy.

3.3.1 Sub - matrix of financial assets flows

Table 7 shows the sub-matrix of flows of financial assets. It can be seen from column

3 to 7 the variation of the monetary flows for each financial asset describes in the first

column across the institutional sector of the economy. The totals for each financial asset

and for each institutional sector are shown in last column and row, respectively.

Negative flows (in brackets) imply decreases in asset holdings of the respective

financial instruments, while positive flows imply increases.

As an example, in Table 7, a box marked by the letter “a” shows the flows of assets

for the financial instrument “currency and deposits” (F.2) that each institutional sector

had at the end of 2009. The not financial sector, the financial sector and the rest of the

world, decreased 517, 41,931 and 5,645 billions of Euros, respectively. While the

government and households/ ISFLSH increase the holdings of this asset in 17,814 and

26,901 billions of Euros, respectively, At aggregated level, the currency and deposits

decrease 3,378 billions of Euros.

22

Table 7. Flows: Financial Assets Billions of Euros

January to December 2009



General Government

Households & NPISHs

Rest of the World Total

Assets S.11 S.12 S.13 S.14/5 S.2

Monetary gold and SDRs F.1 - 310 - - - 310

Currency and deposits F.2 (517) (41.931) 17.814 26.901 (5.645) (3.378)

Debt securities F.3 (11.592) 152.957 6.210 7.423 32.158 187.156

Loans F.4 (14.811) 3.648 8.742 - 1.765 (656) Equity and investment fund shares F.5 3.906 20.476 344 1.727 10.686 37.138

Insurance, pension and standardized guarantee schemes

F.6 (411) (411) - 7.866 262 7.307

Other accounts receivable/payable F.7/8 (69.135) (1.007) 2.755 (7.185) 312 (74.260)

Total Assets F (92.560) 134.042 35.866 36.731 39.538 153.618


3.3.2 Sub-matrix of Financial Liabilities Flows

Table 8 shows the flows of financial liabilities. The transpose way respect to Table 7

has to do with how such data appears in the FSAM.

It can be seen the variation of the monetary flow of each financial liability variable

(column 3 to 7) for each institutional sectors (column 1). Last column and row show the

total by institutional sector and by instrument for the aggregate economy.

As an example, in Table 8, a box marked by the letter “b” shows the liability flows

for the financial instrument “currency and deposits” (F.2). that each institutional sector

had at the end of 2009. It can be seen that the issuance of these instruments is

concentrated in two sectors, Financial Institutions which increased in 28,995 billions of

Euros and the Rest of the World with a decrease in 32,321 billions of Euros. A small

amount of 40 billions of Euros increase is reflected by the government. Notice that

aggregate values in Table 8 equal the aggregate values in Table 7. Therefore, these two

Tables are complementary so that they show, on the one hand, which institutional

sectors emit the financial instruments and which institutional sectors have the

possession of them.

(a)

23

In the construction of the FSAM, a difference arise between the net lending or

borrowing calculated provided by the capital account by the NSI respect to that obtained

from the difference between assets and liabilities by BS. In order to reconcile these two

sub- matrices of the area of the financial sector of the FSAM with the rest of the whole

Matrix, one column and one row were incorporated to collect the statistical discrepancy.

Table 8. Flows: Financial Liabilities Thousand millions of Euros

January to December 2009

Mon

etar

y go

ld

and

SDR

s

Cur

renc

y an

d de

posi

ts

Deb

t sec

uriti

es

Loan

s

Equi

ty a

nd

inve

stm

ent

fund

shar

es

Insu

ranc

e,

pens

ion

and

stan

dard

ized

gu

aran

tee

sche

mes

Oth

er a

ccou

nts

rece

ivab

le /

paya

ble

Total Liabilities

F.1 F.2 F.3 F.4 F.5 F.6 F.7/8

Non-financial corporations S.11 - - 10 (25.903) 16.696 (1) (91.495) (100.693)

Financial corporations S.12 - 28.895 63.299 13.700 883 8.233 (437) 114.574

General Government S.13 - 48 132.957 12.635 2.250 - 6.212 154.103

Households & NPISHs

S.14/15 - - - (2.776) - - (7.560) (10.336)

Rest of the World S.2 310 (32.321) (9.111) 1.688 17.309 (925) 19.020 (4.030)

Total Liabilities 310 (3.378) 187.156 (656) 37.138 7.307 74.260) 153.618

(b)


3.3.3 Satellites Sub-matrices of Flow of Funds

As previously explained above, Tables 7 and 8 provide the total of flow of asset or

liability that each institutional sector has for each financial instrument. However, it

cannot be seen in those sub-matrices the distribution of each financial instrument that

each institutional sector has respect to the rest of the sector. In order to overcome this,

satellite sub-matrices of flow of funds for each financial instrument are constructed with

the available data provided by the BS. Such sub-matrices are not contained within the

internal structure of the FSAM. Thereby, they are considered satellites. They are shaped

both by rows and by columns for the five institutional sectors. Table 5 shows the results

24

for F.2.5 Rows denote financial liabilities and columns financial assets. The respective

totals for each sector are in last row and column which coincides with boxes (a) and (b)

in Tables 3 and 4, respectively. As can be seen, it shows the breakdown of the liability

flows (on the side of the rows) and the flows of assets (by the side of the columns ) with

each of the institutional sectors.

Table 5. Flows: Financial Liabilities (rows) / Financial Assets (columns) EUR thousand millions

F.2. Currency and deposits January to December 2009

Non-financial

corporations


General Government

Households & NPISHs

Rest of the

World

Total

Liabilities

S.11 S.12 S.13 S.14/5 S.2 Non-financial corporations S.11 - - - - - -

Financial corporations S.12 1.181 (22.984) 17.814 38.530 (5.645) 28.895

General Government S.13 - 48 - - - 48

Households & NPISHs S.14/15 - - - - - -

Rest of the World S.2 (1.697) (18.995) - (11.629) - (32.321)

Total Assets (517) (41.931) 17.814 26.901 (5.645) (3.378)

(b)


4. Financial Social Accounting Matrix for 2009

The FSAM structure follows the methodological recommendations contained in the

SNA Manual that were mentioned in the first part of this paper. To the FSAM of Figure

1 has been incorporated some adjustments based on the information available from the

input-output tables at basic prices as well as the breakdown of the components of

demand in domestic and imported. In this regard, Table 9 shows the structure of the

FSAM of Spain with the appropriate information for each of the macroeconomic

variables in 2009. It is shown for each cell in the FSAM the name of the macro variable,

the respective amount and the color that refers to the source of information from which

it is obtained.

5 Results for the rest of instruments are available upon request.

(a)

25

It can be seen in row 1 and column 2 (R1,C2) of Table 9 that the information of the

real sector of the economy comes from the input-output tables, including information of

Net taxes on products (row 4) and imports distributed according to components of

demand (row 11). On the other hand, the variables located on the main diagonal come

from the Integrated Economic Accounts by Institutional Sectors: Property income

(R5,C5), Current taxes on income, wealth , etc. and current transfers (R6,C6),

Adjustment for the change in net equity of households in pension funds (R7,C7), and

capital transfers (R8,C8), as much as residents and the Rest of the World (row and

Column 12 and 13),.

Variables representing large aggregates that come from calculation within the FSAM

are also differentiated within the matrix. They are: Net value added (F3,C2), Net income

generated (F5,C3), Net taxes on products (F5,C4), Net national income (F6,C5),

Disposable income (F7,C6), Net savings (F8,C7), Net fixed capital formation (F9,C8),

Imports of goods and services (F12,C11), and current external balance (F13,C12).

Finally, the variables referring to the financial area of the matrix coming from the BS

are: Loans (Acquisition of financial assets) (F10 ,C9) and Debt (Incurrence of

liabilities) (F9 ,C10) for the domestic economy. And, for the rest of the world: Loans

(Acquisition of financial assets of the Rest of the World) (F10,C13) and Debt

(Incurrence of liabilities of the Rest of the World) (F13,C10) . In Table 9 the total

aggregates of the variables are presented. However, they were obtained according to

the distribution shown in Table 1 and 2 with information by institutional sector and

financial instrument. One of the most important aspects of the FSAM at a macro level as

shown in Table 9 is that it allows the validation of the main macroeconomic aggregates

as well as it works as an useful harmonization mechanism to disaggregate different

accounts at rows and columns levels.

26

Table 9. Macro Financial Social Accounting Matrix for Spain 2009

27

It has been also highlighted the sub-matrices that have been the object of the greatest

contribution of this work within the FSAM. The blue boxes represent the work of

disaggregation of the Internal Property Income and with the Rest of the World (Table 5,

Step 4). On the other hand the cream boxes represent the breakdowns of the Financial

Account by financial instrument and institutional sector, which are shown in Tables 7

and 8.

5. Conclusions

This article presents the first financial social accounting matrix (FSAM) for the

Spanish economy. The maximum disaggregation with the data available was obtained.

Thus a 320x320 FSAM was built. The constructions of this tool had to overcome the

difficulties that arise at consolidating data of the Spanish Statistical Institute (INE) and

Bank of Spain (BE). Moreover, we propose an estimation methodology when data are

unavailable. This FSAM goes beyond the traditional SAMs that are especially designed

for answers particular questions of computable general equilibrium (CGE) models and

whose scopes are limited. Therefore, the FSAM presented here could be very useful in

improving and extending the multiplier models for impact analysis of public policies

and Financial CGE models.

28

Appendix: RAS-Algorithm for obtaining the distribution of property income

A common problem in compiling and updating Social Accounting Matrices (SAM) or

Input–Output (IO) tables is that of incomplete information. In the case of Spain, the

Income and Expenditure Accounts provide only Total Property Income paid and

received by each institutional sector. Thus, the National Bureau of Statistics (INE) does

not breakdown the totals by institutional destination and source.

Missing matrix elements may be due to a variety of reasons, such as costly and therefore

incomplete industry surveys, or the suppression of confidential information. However,

external data points can be used to formulate a system of equations that constrain the

unknown matrix elements.

As Leung and Secrieru (2012) we approximated this breakdown by using data on the

assets and liabilities of each institution compiled in the National Balance Sheet accounts

already estimated by BE applying a RAS-algorithm (Miller and Blair, 2009)

The estimation problem is that, for an nxn matrix, we seek to identify n2 unknown

parameters (the cells of X), but have only 2n – 1 independent row and column adding-

up restrictions.

The RAS-algorithm (Junius and Oosterhaven, 2003), Lenzen, Wood and Gallego ,

2007) iteratively adjusts a baseline known matrix Z, with row sums u(0) and column

sums v(0), to a ‘new’ matrix X that satisfies a ‘new’ set of given row sums u(1) and

column sums v(1). With minimum loss of information the RAS-algorithm produces the

new (target) matrix X with the required row and column sums such that:

X = ř A ŝ

Where ř(1) and ŝ(1) are diagonal matrices with entries on the main diagonal, such that

the vector x(1) = ř i correspond to the total Flow Property Income (target).

Step 1: Based in the matrix Z (Balance Stock), the baseline bi-proportional matrix of

coefficients is obtained:

Z = ř(0) A(0) ŝ(0)

29

Step 2: Beginning with the conjecture that the baseline have not changed, we first

examine the row sums of A(0) x(1), in light of u(1):

Z1 = A(0) x(1) and

u1 = Z1 i

Step 3: Given that u1 is nowhere near to u(1) an adjustment is needed. Then forming the

diagonal adjustment matrix:

ř1 = û(1) [û1]-1 and

A1 = ř1A(0)

The elements in ř1 ensure that the row sums of A1x(1) will equal u(1)

Step 4: Checking the column sums of A1x(1) will not equal v(1). Then, the following

row adjustment is necessary:

ŝ1 = v(1) [v1]-1 and

A2 = A1 ŝ1

While A2 now contains elements that, in conjunction with x(1), satisfy the v(1) margins,

it will generally be the case that in modifying A1 to A2 we will have disturbed the row

sum property of A1, given in the step 3.

Step n: Notice that each subsequent row modification will generally upset the previous

column modification, and vice versa – a column modification will upset the previous

row modification

A2n = [ řn … ř1 ] A(0) [ ŝ1 … ŝn ]

30

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