SAMS AND MICRO-DATA: NEW AREAS OF RESEARCH

Paul Schreyer OECD

IIOATowards New Horizons ofInnovation, Environment andTrade

Kitakyushu July 2013

1. Measuring well-being and living standards - policy demand

2. Distributional information and the national accounts – bridging the gap

3. SAM as a tool to structure and analyse data

4. From SAMs to living standards 

Overview

1. Measuring well-being and living standards - policy demand

• While GDP is a key measure to monitor macro- economic activity, productivity, demand for paid-jobs

• GDP is not a metric for people’s well-being and is often at variance with people’s personal experiences

• Measuring well-being implies confronting values: from “treasuring what you measure” to “measuring what you treasure”

Increasing recognition that…

• UNDP Human Development Reports• OECD Fora since 2003 • Stiglitz-Sen-Fitoussi Commission

(2009)• EU: GDP and Beyond• And significant interest at national

and local level• OECD How’s Life?

Many activities

Dimensions – OECD Framework

Measuring Well-being requires looking at:

– Households and people

– Outcomes, not inputs or outputs

– Assessing inequalities alongside averages

Apply criteria to measuring material well-being and living standards:

– Households and people institutional sectors

– Outcomes HH income and its components

– Inequalities HH distributional information

This is exactly what SAMs have been conceived for

So where do SAM and micro-data come in?

• Richard Stone 1960s; Pyatt, Thorbecke 1970s

• Keunig (1994)• Eurostat Handbook 2003• Use for development planning (Pyatt and

Round 1977),• Concept: consistent integration of:

– SUTs or IOT– institutional sector accounts– socio-economic break-down of households

or labour – national accounts matrix with expanded

information on households or labour

A little reminder on SAMS

National Accounts Matrix

RoW

Accounts Product 1 … Product N Industry 1 … Industry MCompen-sation of

employees…

Other taxes on

productionNFC … HH NFC … HH NFC … HH

Product 1… (1.2)

Product NIndustry 1

… (2.1) (2.2) (2.6) (2.8) (2.9)Industry MCompen-sation of

employees… (3.2)

Other taxes on

productionNFC…

HHNFC…HH

NFC…HH

RoW

Goods and Services Production Generation of incomePrimary allocation and secondary distribution

of income

Use of disposable income

Capital accounts

Goods and Services

Production

Generation of income

Primary allocation

and secondary distribution of income

Use of disposable

income

Capital accounts

SAM

RoW

Accounts Product 1 … Product N Industry 1 … Industry MCompen-sation of

employees…

Other taxes on

productionNFC … HH NFC … HH NFC … HH

Product 1… (1.2)

Product NIndustry 1

… (2.1) (2.2) (2.6) (2.8) (2.9)Industry MCompen-sation of

employees… (3.2)

Other taxes on

productionNFC… (4.3) (4.4)

HHNFC… (6.1)HH

NFC…HH

RoW

Goods and Services

Production

Generation of income

Primary allocation

and secondary distribution of income

Use of disposable

income

Capital accounts

Goods and Services Production Generation of incomePrimary allocation and secondary distribution

of income

Use of disposable income

Capital accounts

For purpose at hand, SAMs are useful to:

• Systematise link between:– Primary income types:

• Wages and salaries• Mixed income• Gross operating surplus• Other net taxes on production

– Disposable income inequality = HHs grouped by quintiles, deciles, etc.

• Where does disposable income for a particular HH originate?

But there is a major statistical issue:

NA aggregates and HH survey data on (income) distribution are inconsistent

2. Distributional information and the national accounts – bridging

the gap

15

• Distributional information: bottom-up <- household surveys

• Average and macro information: top-down <- national accounts

• Conceptual differences:– Scope– Units (individuals vs households)– Definition of income

• Imputations: OOH, FISIM

• Empirical differences:– Property income (e.g., interest received)– Mixed income (self-employed)

Survey information and national accounts

• OECD-Eurostat Expert Group– To examine differences NA – Surveys– To develop NA-compatible distributional

data– Income, consumption and savings for

16 countries

• Results forthcoming (Fesseau et al 2013)

Do NA-Survey differences matter? Yes.

Adjustment coefficient for income components (NA/Survey ratio)

Average Median Minimum Maximum

Wages and salaries 11 1.1 1.1 0.9 1.5Mixed income * 9 2.4 1.7 0.9 7.5Property income received** 5 6.6 4.0 0.4 16.5Property income paid** 5 9.7 2.3 1.1 38.6Social benefits received 8 1.4 1.2 1.1 2.3Current taxes on income and wealth paid 9 1.4 1.2 1.0 2.9Actual social contributions 6 1.4 1.3 1.0 2.1

Number of countries

Value of the coefficient

Data needed by groups of HHs

19

Savings* as a percentage of adjusted disposable income, by income quintile

Example of disparity indicator: savings

3. Back to the SAMS:A tool to structure and analyse

data

New multipliers

• SAM flows for HH by type of HH• But also: multipliers

– Given a certain value-added generated in industries, what are the direct and indirect effects on HHs disposable income?

• Compare with traditional I/O multipliers:– Given a certain final demand, what are the

direct and indirect effects on industries production and value-added?

Example: Portugese SAM (Reich 2012)

Who receives?Primary

educationSecondary education

Tertiary education

Primary education

Secondary education

Tertiary education

5a Nonfinancial corporations -0,9% -0,8% -0,9% -0,8% -0,8% -0,8%5b Financial corporations 1,5% 1,5% 1,6% 1,5% 1,5% 1,5%5c General government 16,8% 16,5% 17,1% 16,1% 16,0% 16,6%5d-1 HHs, wages and salaries 63,9% 62,5% 65,5% 60,2% 59,6% 62,6%5d-2 HHs, mixed and capital inc. 3,0% 3,9% 2,5% 5,7% 5,8% 5,3%5d-3 HHs, retirement income 10,6% 10,8% 9,4% 12,0% 12,0% 9,7%5d-4 HHs, other transfers 1,6% 2,2% 1,2% 2,1% 2,8% 1,8%5e NPISH 1,9% 1,9% 1,9% 1,8% 1,8% 1,9%10 Rest of the world 0,5% 0,5% 0,5% 0,4% 0,4% 0,5%

Type of value added generatedCompensation of employees

Male Female

For OECD work on well-being,

classification by income group

would be preferable

No redistributional effect?

Missing: STIK

• Typical SAM does not cater for Social Transfers in Kind (STIK)

• Introduce adjusted disposable income and actual individual consumption

• Otherwise, measure of living standards incomplete

To be developed…

Relative position of the 20% richest households to the 20% poorest

households

From SAMs to measurement of living standards

• Large body of literature• Recent empirical studies

– Jorgenson and Slesnick (2013)– Fleurbaey and Gaulier (2009)– Jones and Klenow (2011)– Fleurbaey and Blanchard (2012)

(But not typically based on SAMs or on adjusted disposable income)

Aggregate measures of material well-being (welfare economics)

Basic Idea

)]y,...y,y(I1[y)y,...y,y(W N21N21

Averages Distribution

dardstansliving/'welfaresocial':)y,...y,y(W N21

measureinequalityAtkinsonKolm:)y,...y,y(I

incomedisposableaverage:y

N21

Jorgenson and Slesnick (2013) Measuring Social Welfare in the

US National Accounts

-1,00

-0,50

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

1973-1995 1995-2000 2000-2005 2005-2010

(Material) Standard of Living

Average consumption per HH equivalent member

Equity

GDP/capita

• Requires consistent information on HHs

• Micro – NA consistency would improve results in the literature that do not address this issue

• Best: structured in SAM

Construction of index of living standards/material well-being

• Increasing interest in measurement and analysis of well-being and living standards

• Requires:– consistent data on HH accounts, from

primary to disposable income– Break down by socio-economic

characteristics

• SAM is excellent accounting framework• Few SAMs exist but clear policy demand

may change this

Summing up

• Needed: bridge NA and micro survey data

• Also needed: consistency between micro data on consumption, income, wealth

Summing up (2)

32

• OECD guidance on the measurement of:

Commercial break for recent OECD methodological publications

Micro Statistics on Household Wealth

www.oecd.org/statistics/guidelines-for-micro-statistics-on-household-wealth.htm

the Distribution of Household Income, Consumption and Wealth

www.oecd.org/statistics/ICW-Framework.htm

• Looking ahead:– Microdata for STIKs– Microdata for bringing in non-market

production and consumption– From (adjusted) disposable to full income

• For analysis, use SAM multipliers and plug into literature on welfare measurement

• There’s much work to be done!

Summing up (2)

Thank you!

Paul.Schreyer@oecd.org