DISTRIBUTION OF INCOME, CONSUMPTION, SAVING

AEG MEETING

WASHINGTON DC, 8-10 SEPTEMBER 2014

Presented by Jennifer Ribarsky (OECD)

• How to arrive at economic growth without people dropping out-> need for information on how income, consumption and wealth are

distributed across households

• Main issues:– Existing distributional information from micro

sources:• Often focus on one dimension

• In most cases no consistent time series

• Not following international standards, especially related to wealth

– National accounts data on households hardly provide any distributional information

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Background

• Early 2011: OECD-Eurostat Expert Group (EG DNA)

• Mandate: study feasibility to arrive at an internationally comparable methodology for generating distributional information consistent with national accounts

• Members: 25 countries, ECB, Luxembourg Income Studies

• Organisation of the work:– Phase 1 (2011): comparison between micro and macro data

sources on households’ income, consumption and wealth => to better understand similarities and divergences between both data sources

– Phase 2 (2012): allocation of national account totals to groups of households using a range of micro sources; derivation of disparity measures on income, consumption and saving, for a given year

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Background

• Sharing knowledge across countries and between micro and macro experts

• Better understanding of NA concepts and compilation procedures, household micro data collection, and differences between both of them

• Compilation of experimental disparity measures across households groups consistent with NA estimates: – for a range of OECD countries – based on common templates and methodology

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Main results of first EG DNA

*Difference between adjusted disposable income and actual final consumption plus the change in net equity of households in pension funds.

Savings* as a percentage of adjusted disposable income

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Transactions and transfers between households of different quintiles

difference of saving rates before and after transfers between households

Q1 Q2 Q3 Q4 Q5

Australia -0.1% 0.1% 0.5% 0.2% -0.2%

France 2.6% 0.7% 0.4% -0.4% -1.1%

Korea 0.5% 0.7% -0.6% -0.7% 0.4%

Netherlands -1.6% 0.8% 0.5% 0.2% -0.3%

Unites States -2.2% 0.0% 0.2% 0.1% 0.0%

Impact of transfers between households on saving ratespositive values refer to higher saving rates after transfers were taken into account

• Milton Friedman’s Permanent Income Hypothesis (PIH)– emphasizes the attempts of the individual to smooth its

consumption over time, adjusting consumption and saving levels according to an expected long-term permanent income, and therefore evaluating income shocks by their persistence: smoothing out temporary fluctuations in income, and adjusting consumption levels to income shocks that are perceived to be long lasting.

• Modigliani and Brumberg’s Life Cycle Hypothesis (LCH)– states that individuals plan their consumption behaviour over

their lifetime: in their early (student) years they may consume more than their income (for example on their education), then in their most productive (highest income earning years) they pay back the accumulated debt and save for their retirement, and finally they dis-save as pensioners (use up the accumulated assets). 7

Economic theories of consumption

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Average age of head of household by equivalised disposable income quintile

• Income related to the non-observed economy underestimated for the lower income quintiles?

• Inconsistent responses (case of France)

• Imperfect quintile allocation of households for consumption components

• Imputations related to owner occupied dwellings

(primarily due to delineation of what is included in intermediate consumption (such as FISIM on mortgages and maintenance and repairs))

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Statistical issues

• To produce information on income and consumption for a more recent year, via a streamlined questionnaire– To assess the robustness of the assumptions made– To assess the techniques developed to link micro

and macro data

• To develop and evaluate methods and sources for extrapolating distributional dynamics from benchmark years using more timely available aggregate statistics

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Goals of EG DNA (extended mandate)

• Expert group met in April 2014 – To discuss its mandate and organise the work – Results from previous exercise discussed (with

focus on negative saving rates and STiK)• September 2014 OECD secretariat will

issue a redesigned questionnaire template for the collection of data and metadata

• Next expert group meeting June 2015• Final report December 2015

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Milestones of EG DNA (extended mandate)

• To make readily available income, consumption and savings of households by income quintiles ;– Consistently with the corresponding national

accounts totals

– Ideally as part of the normal SNA/statistics production process

• This information is crucial to be able to add a distributional dimension to macroeconomic analysis

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Long term vision

Thank you for your attention!

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