OECD Expert Group on Disparities in National Accounts Work Summary

The OECD Expert Group on Disparities in National Accounts focuses on developing methodology to produce distributional results for household income, consumption, and saving. Their work involves adjusting national accounts totals, identifying relevant variables from micro data sources, imputing missing elements, clustering households into groups, and deriving relevant indicators. The group has conducted exercises to calculate distributional results for various household groupings, contributing to a better understanding of people's well-being and economic disparities.

• OECD
• Expert Group
• National Accounts
• Distributional Results
• Methodology

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1. WORK OF THE OECD EXPERT GROUP ON DISPARITIES IN NATIONAL ACCOUNTS Advisory Expert Group on National Accounts Paris, France, April 13 15, 2016 Jorrit Zwijnenburg National Accounts Division OECD

2. Contents Background Aim of the project Methodology Results from a recent exercise Work on nowcasting Way forward 2

3. Background Stiglitz, households to better measure people s well-being, amongst others by putting more focus on distributional aspects 2011: Launch of OECD/Eurostat Disparities in National Account (EG DNA) to develop methodology to produce distributional results consistent with national accounts concepts using micro data sources 2013: Publication of results from a first exercise 2014: Continuation of the work by an OECD EG DNA to further improve methodology and timeliness 2015: Second exercise on basis of improved methodology Sen, Fitoussi report (2009): More focus on Expert Group on 3

4. Aim of the project Aim: Develop methodology to produce distributional results for household income, consumption and saving consistent with national accounts concepts using micro data sources Household groups Q2 Q1 MACRO DATA Macro concepts -> Totals, growth Q3 Q5 Q4 MICRO DATA Micro concepts -> Distribution

5. Methodology: Step-by-step procedure Step 1 Adjust national accounts totals (exclude NPISHs, expenditures of non-resident hh s and people living in non- private dwellings) Step 2 Identify relevant variables from micro data sources that could be matched to NA variables (different data sources may be used for the various income an consumption items) Step 3 Impute missing elements and scale the micro data to the adjusted national accounts totals (e.g. imputation for STiK, FISIM, income attributable to policy holders) Step 4 Cluster households into groups (on the basis of equivalized disposable income) Step 5 Derive relevant indicators for household groups (e.g. ratio to the average, highest to lowest) 5

6. Results from the recent exercise Distributional results for three household groupings: Disposable income quintile (5 groups) Main source of income (4 groups) (optional) Household type (8 groups) (optional) Calculations performed by members of the EG DNA: AUS, AUT, CHE, FRA, GBR, ISR, JPN, MEX, NLD, PRT, SVN, SWE, USA Most recent year: 2012 6

7. Results from the recent exercise: Ratio to average Relative position of each household group compared to the average, for adjusted disposable income 7

8. Results from the recent exercise: Ratio of highest to lowest income Relative position of the 20% highest to the 20% lowest income households on the basis of adjusted disposable income 14.0 12.0 10.0 2010 8.0 6.0 2006 2010 4.0 2008 2009 2003 2.0 0.0 8

9. Results from the recent exercise: Savings ratios Saving as a percentage of disposable income by equivalized disposable income quintile France Israel Mexico 9

10. Main conclusions from exercise Results look encouraging! Results from both exercises look consistent and plausible Results provide interesting insights Some countries are already planning to publish results However Longer time series are needed to check robustness Further research is needed into micro-macro gaps 10

11. Challenge of micro-macro gaps Adjustment coefficient (macro / micro aggregate) for the main income components Average Minimum Maximum Code Instrument most recent year second most recent year most recent year second most recent year most recent year second most recent year B2 Operating surplus 1.79 1.27 0.94 1.12 2.43 1.42 B3 Mixed income 2.20 1.79 1.30 1.67 3.50 1.91 D1R Compensation of employees 1.19 1.16 1.20 D41R Interest (not adjusted for FISIM), received 2.08 1.90 0.66 0.72 6.40 4.77 D42R Distributed income of corporations 5.06 10.67 0.70 3.00 17.76 23.50 D41P Interest (not adjusted for FISIM), paid 3.58 2.47 1.02 1.01 11.31 4.65 D5P Current taxes on income and wealth 1.18 1.19 0.78 0.74 1.54 1.78 D61P Net social contributions 1.23 2.01 1.19 1.28 1.27 2.73 D62R Social benefits other than STiK 1.22 1.30 0.97 0.98 1.55 1.65 D63R1 Education 0.94 0.88 0.72 0.78 1.13 0.98 D63R2 Health 1.36 1.37 1.16 0.99 1.73 1.75 11

12. Nowcasting exercise There is a strong demand for recent data However, the timeliness of micro data sources is often poor Looking for nowcasting techniques to compile timely data: Top-down Bottom-up Meso For the time being, focus on top-down approach due to data availability Various methods tested (t-1, average, regression against trend and totals) 12

13. Main findings regarding nowcasting Preliminary results show relatively good results when it comes to the shares of the various groupings Larger gaps observable looking at changes and growth rates Further research is needed to understand results and to improve methodology Limited availability of data limits the current analyses Larger availability of countries and time series would be very helpful! Also data would be welcome to test the micro and meso approaches Paper with nowcasting results is sent to the EG DNA with an accompanying request to provide additional data, whenever available 13

14. Way forward for EG DNA Working paper on results of the second exercise will be published in summer 2016 Further improve methodology Providing guidance on how to deal with micro-macro gaps Explore how countries currently link data from various surveys Finding a way to combine and publish all knowledge and experience Set up a regular data collection from countries, possibly extending coverage with own estimates Further explore nowcast methodologies Extending the exercise to distribution of wealth Next meeting of the EG DNA in the fall of 2016 14

15. Thank you for your attention For more information please contact: Jorrit.Zwijnenburg@oecd.org 15