bringing distribution indicators in the households ... · bringing distribution indicators in the...

Bringing distribution indicators in the

Households National Accounts

NTTS 2013, Brussels 5-7 March 2013

Francesca Tartamella, ISTAT : [email protected]

Alessandra Coli, University of Pisa: [email protected]

Background (1): the issue


National Accounts (NAs) describe the economic behaviour of a representative household without investigating heterogeneity.

Micro data sources provide information on the distribution of income and consumption among people but fail in detecting all economic entries and outlays (lack of exhaustiveness)

It is incorrect to simply accompany NAs measures with individual based data indicators in that macro and micro data sources often refer to (capture) different economic phenomena.

Ideally, NAs measures should incorporate distribution information


Background (2): bringing distribution indicators in NAs

1

ESA 1995 directives: i) Households sub-secoting; ii) Social Accounting Matrices

Eurostat Leadership Group (LEG) on “Social Accounting Matrices and Labour Accounts” (Eurostat 2003) Europ. Commission “GDP and Beyond” communication, (2009)

Stiglitz-Sen-Fitoussi Commission on the measurement of economic performance and social progress (Stiglitz Commission, 2009): “more prominence of the distribution of income, consumption and wealth within the NAs framework”


Background (2): bringing distribution indicators in NAs

1

Sponsorship Group on Measuring Progress “Final Report” 2011

2011-2013 OECD-Eurostat Expert Group on “Disparities in a National Accounts framework”

ESA 2010 (to be published): satellite accounts on “the analysis of the income and expenditure of households on the basis of micro-oriented concepts of income and expenditure”


Objectives

1

Reconcile micro and macro data on disposable income and consumption expenditure.

Breakdown of disposable income (and sub-components) and consumption expenditure by households groups:

first application: households grouped according to the family’s income quintile.

second application: households grouped according to the composition (single, adults with or without children etc.) and age of its members.


Data (year 2008)

1

Macro

Italian Households Accounts

Micro

IT-Silc: Istat Italian survey on income and living conditions

Hbs: Istat Survey on Households Budgets


The Method: Top-down approach

1

We break down NAs values (top) using information from individual-based data.

Assumption: NAs values are the standard.

First step: reconcile micro-macro data on income (sub-components) and consumption expenditure.

Second step: calculate indicators on the basis of survey data in order to break down the NAs values


Micro-macro gaps

1

Micro and macro estimates may differ for different reasons

different populations

different time periods

the NAs item does not find a suitable counterpart in the survey

households surveys may suffer of under-reporting, whereas NAs are supposed to be exhaustive

it is unlikely that small population is surveyed


The steps

1

Surveys and NAs data are harmonized with respect to population and time period

Survey’s variables best representing NAs item are identified at the highest disaggregation level.The distribution of such variables by households groups provides the structure for breaking down the NAs items

When possible, micro values have been re-computed according to NA methodologies


Analysis of results (1)

1

The micro-macro reconciliation has a heavy impact on income distribution

Before reconciliation

After micro-macro

reconciliation

Q1 Q5 Q5/Q1 Q1 Q5 Q5/Q1

Wages and salaries 4 43 10 6 37 6

Self employment income 6 55 9 2 66 27

operating surplus from own

account production 16 28 2 15 30 2

Property income (received less

paid) 2 57 23 - 5 77 -17

Actual social contributions paid

by households 5 47 11 6 43 7

Current taxes on income and

wealth 2 55 29 2 53 21

Social benefits including social

transfers in kind (received less

paid) + other current transfers 15 23 1 14 25 2

Total 11 35 3,3 9 39 4,2



1

It is possible to point how the households groups differently determine their income

Q1 Q2 Q3 Q4 Q5

Total

covered

Wages and salaries 27 31 43 49 38 39

Self employment income 6 9 12 20 40 23

Operating surplus from own

account production

17 13 12 10 9 11

Property income (received

less paid)

-4 2 4 6 15 8

Actual social contributions

paid by households

4 4 6 7 6 6

Current taxes on income and

wealth

4 9 13 16 21 15

Social benefits including

social transfers in kind

(received less paid) + other

current transfers

61 58 49 38 26 40

Total 100 100 100 100 100 100



1

It is possible to point how the households groups differently determine their income and allocate consumption

Single

less 65

Single 65

and older

Single with

children living

at home

Two adults less

65 no child

living at home

Total

covered

Total disposable income per CU 28.942 25.087 23.864 32.424 29.583

Actual final consumption per CU 32.605 23.826 29.416 30.917 26.945

Consumption propensities (%) 110 94 121 93 89

Two adults at

least one 65

and older no

child living at

home

Two adults

with less than

3 children

living at home

Two adults

with at least 3

children living

at home

Others Total

covered

Total disp. income per CU 30.691 29.700 26.062 30.795 29.583

Actual final cons. per CU 24.959 27.919 25.180 23.635 26.945

Consumption propensities (%) 80 92 95 76 89


Final considerations

1

Combining micro and macro data can improve the analysis

on income distribution, thus:

- showing how average income variations are differently distributed among household categories (who is bearing the costs of economic crises or taking benefits in case of economic expansion?).

- Support government: economic policies can be better shaped and (scarce) public resources better allocated


Agenda for future research

1

• It is advisable to match the data drawn from the micro data sources before calculating breaking-down indicators: this would allow to disaggregate consumption expenditure also according to income-based classification criteria

• It is advisable to better investigate the reasons of the micro-macro discrepancy. Data coming from households budget survey data and/or administrative archives should represent an input for the whole NAs process leading to the GDP estimate

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