The World Top Incomes Database WTID: An Assessment Andrea Brandolini
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1 The World Top Incomes Database WTID: An Assessment Andrea Brandolini Bank of Italy, DG Economics, Statistics & Research Journal of Economic Inequality panel Appraising World Income Inequality Databases
2 Overview and background
3 Tax data and inequality Tax-based statistics on income inequality always seem to hit a nerve of the economics profession Worldwide debate on Pareto s Law (1895) Kuznets (1953): change in US income distribution... for its magnitude and persistence... unmatched in the record Burns: one of the great social revolutions of history Atkinson, Piketty, Saez ( ) The One Percent But not much used for inequality analysis: limited coverage & problems with income definition Surprising it has taken until 2011 to exploit known and accessible data such as tax records to construct an international inequality database
4 The World Top Incomes Database International database released in 2011 by Alvaredo, Atkinson, Piketty and Saez, in collaboration with large group of researchers Shares of personal income received by the richest groups of taxpayers 29 countries from all continents over a period of 143 years: 1870 (Denmark) to 2012 (many) All WTID figures are computed from tax records, except for China and more recent Finnish figures
5 The WTID project Dynamic: old series extended forwards and backwards and revised, new series for other countries, plan for new series on earnings and wealth Cooperative: everyone being aware of data that have not been exploited yet or having the possibility of getting unpublished data for so-far uncovered countries (even if only for a few recent years) is invited to collaborate Easy access: freely available database hosted by the Paris School of Economics :
6 WTID coverage (September 2014) Source: WTID.
7 WTID top 1% share
8 WTID: strengths & weaknesses Strengths length: more than 1/4 of 1718 values for top 1% share are pre-1946 density: relatively fewer missing values coverage of highest income earners Weaknesses income definitions reflect administrative rules reference unit is taxpaying unit discontinuities due to changes in tax legislations tax avoidance practices coverage of top fractions of population allows estimating only a class of inequality statistics, namely income shares of the richest taxpayers
9 Methods and problems with estimating inequality from tax data
10 WTID: raw material Example of income tax data: UK (from Atkinson-Piketty-Saez, Journal of Economic Literature 2010)
11 WTID: method Kuznets, Shares of Upper Income Groups in Income and Savings, NBER, New York (1953) The basic procedure is to compare the number and income of persons represented on federal income tax returns with the total population and its income receipts. Since except for a few recent years, tax returns cover only a small fraction of total population the fraction at the highest income levels our estimates of income shares are for only a small upper sector. Atkinson, Measuring Top Incomes: methodological issues, in Atkinson-Piketty (2007)
12 WTID: measurement issues Inequality measure: share of richest population fraction Control totals for population Individual taxation: no. adults 20+ (lower bound for income share) or 15+ (upper bound) Family taxation: subtract no. of married females Control totals for income Income tax data + estimated income of non-filers External control total (national accounts) Interpolation (for data in grouped tabulations) Fit a Pareto distribution, but there are alternatives (e.g. Cowell-Mehta, Review of Economic Studies 1982)
13 WTID: population controls Atkinson (2007) Control larger by (1+c) means going further down distribution to locate top x%, so that top income share up by (1+c) 1-1/α, assuming Pareto distribution Applies to choice of adult population: e.g. individuals 20+ vs. individuals 15+, etc. Applies to population revisions: e.g. reconstruction backwards after 2011 Census reduces Italians 20+ by 1.8% in 2009 (but small impact: 1% fall in shares) Variability across countries, and a few changes within countries
14 WTID population controls Number of adults Number of tax units Argentina Individuals aged 20+. Individuals aged 20+. Australia Individuals aged 15+. Individuals aged 15+. Canada Up to 1999, individuals aged 20+; from 2000, tax filers. Up to 1999, individuals aged 20+; from 2000, tax filers. China Individuals represented in the urban household surveys. Colombia Individuals aged 20+. Individuals aged 20+. Denmark Until 1969: individuals aged 15+. From 1970: tax returns. Until 1968: individuals aged 15+ minus married females. From 1970: tax returns (individuals aged 15+ plus those individuals below 15 years old who also file a tax return). Finland n.a. Individuals aged 15+ minus married females until 1969; individuals aged 15+ from France Individuals aged 20+. Families. Germany Single individuals aged 20+ plus one half of married individuals. India Individuals (40% of total population). Indonesia Households. Ireland Individuals aged 18+ minus married women. Italy Individuals aged 20+. Individuals aged 20+. Japan Individuals aged 20+. Individuals aged 20+. Malaysia Individuals aged 15+. Individuals aged 15+. Mauritius Individuals aged 15+. Individuals aged 15+ minus the number of married women and those not married but living together. Netherlands Number of individuals aged 15+ minus the min(number of married women, number of married men). New Zealand Until 1999: individuals aged 15+. From 2000: total individual taxpayers. Until 1952: individuals aged 15+ minus married women : individuals aged 15+ from 1953 to From 2000: total individual taxpayers. Norway Individuals aged 16+. Individuals aged 16+. Despite joint taxation, separate filing increasingly prevalent. From 1998 Statistics Norway ceased to treat married couples with joint taxation as one taxpayer. Portugal Individuals aged 20+ minus married women. Singapore Individuals aged 15+. Individuals aged 15+. South Africa Individuals aged 15+. Until 1989: individuals aged 15+ minus married women. From 1990: individuals aged 15+. Spain Individuals aged 20+. Individuals aged 20+. Sweden Until 1950: individuals aged 16+ minus married women : individuals aged 16+ minus married women with low or no income. From 1971: indviduals aged 16+. Switzerland Until 1995: individuals aged 20+. From 1996: individuals aged 18+. Until 1995: individuals aged 20+ minus one half of married men and women. From 1996: individuals aged 18+ minus one half of married men and women. Tanzania Individuals aged 15+. Every tax unit is assumed to be comprised by 1.6 adults (individuals aged 15+). United Kingdom Until 1989: individuals aged 15+ minus married females. From 1990: individuals aged 15+. United States Families. Uruguay Individuals aged 20+. Individuals aged 20+.
15 WTID: income controls Similar considerations apply to income controls, but impact likely to be larger Variability of covered components: non-taxable items vary across countries (transfers, capital gains) Revisions in external controls Compare to common external national accounts benchmark
16 WTID income controls: Australia Source: Burkhauser-Hahn-Wilkins, Journal of Economic Inequality forthcoming
17 Taxable vs. household pre-tax NA income 110 South Africa 100 Australia 90 Colombia 80 Norway 70 France 60 US 50 Finland 40 China Source: author s elaboration on WTID and OECD data.
18 About source comparisons
19 Tax-based vs. survey-based statistics Many good reasons to differ Income definition, reference unit, coverage, measurement errors,... Do they tell different stories? Leigh, Economic Journal 2007: strong and significant relationship between top income shares and broader inequality measures (Gini, Theil, etc.) Comparison with measures from WIID (but: household gross/net income) and LIS (but: household disposable income) Comforting, but work on reconciling definitions
20 36 Top 5% share in the US Percent PS pre-tax market, tax units CPS pre-tax, households CPS-BFJL pre-tax, tax units BEA pre-tax, households Source: Brandolini, Politics & Society 2010.
21 Top 1% share: WTID vs. LIS (PI) 25 LIS top 1% share (personal income, individuals 20+) WTID top 1% share Source: author s elaboration on WTID and LIS data.
22 The WTID database, and how it deals with problems
23 Using the WTID: website Take the perspective of a user seeking ready-to-use data not so mindful to go through the 1,200 pages of the two Atkinson-Piketty et al. volumes Do website & database give enough information? Website: friendly and well-designed Noticeboard informs on updates, new papers, etc. Nice feature: Preview option, which allows users to see immediately a chart with updated time series Graphics: user-friendly way to plot main variables Download: easy selection of countries/years/ variables; entire dataset quickly downloadable in excel file
24 Using the WTID: dataset Excel file with sources and two different layouts About 400 variables for 29 countries Basic structure (layout B) Variable code Top 5% income share Number of adults Number of tax units Income control Units % Thousand Thousand Nominal million Pesos Notes Estimates do not include Individuals aged 20+. Individuals aged 20+. capital gains. Statistics exclude taxpayers with wage income only
25 Using the WTID: dataset Excel file with sources and two different layouts About 400 variables for 29 countries Basic structure (layout B) Variable code Top 5% income share Number of adults Number of tax units Income control Units % Thousand Thousand Nominal million Pesos Notes Estimates do not include Individuals aged 20+. Individuals aged 20+. capital gains. Statistics exclude taxpayers with wage income only Codification rules not provided, but would be useful
26 Using the WTID: dataset Excel file with sources and two different layouts About 400 variables for 29 countries Basic structure (layout B) Variable code Top 5% income share Number of adults Number of tax units Income control Units % Thousand Thousand Nominal million Pesos Notes Estimates do not include Individuals aged 20+. Individuals aged 20+. capital gains. Statistics exclude taxpayers with wage income only One series for each top share (except tax unit/source change)
27 Using the WTID: dataset Excel file with sources and two different layouts About 400 variables for 29 countries Basic structure (layout B) Variable code Top 5% income share Number of adults Number of tax units Income control Units % Thousand Thousand Nominal million Pesos Notes Estimates do not include Individuals aged 20+. Individuals aged 20+. capital gains. Statistics exclude taxpayers with wage income only Important information on population/income controls
28 Using the WTID: dataset Excel file with sources and two different layouts About 400 variables for 29 countries Basic structure (layout B) Variable code Top 5% income share Number of adults Number of tax units Income control Units % Thousand Thousand Nominal million Pesos Notes Estimates do not include Individuals aged 20+. Individuals aged 20+. capital gains. Statistics exclude taxpayers with wage income only Notes: important to asses comparability, but meagre
29 Conclusions
30 Developing WTID Streamline and release variable codification rules Provide more details on taxable income items, to give an idea of how much income is captured Measurement choices affect results, but only one series available in WTID: provide lower and upper limits? Include original raw data to stimulate application of alternative assumptions Cross-validation with other sources Cross-country comparability deserves further research
31 Few last general words Exciting time: a lot of new data on inequality Alvaredo-Atkinson-Piketty-Saez have rediscovered a rich gold vein that had been largely neglected since the gold rush of Pareto s time Tax data have problems, but other data do as well Look at sources as complementary, rather than rival Substantive not only statistical reasons explain differences Integrate micro information with national accounts
32 Kuznets, 1953 It is as if one tried to paint a fine picture with thick brushes and large blobs of somewhat mixed colors But still better than a white page! Thank you for your attention.
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