"Top Incomes in the Long Run of History" with Tony Atkinson and

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28Journal of Economic Literature, Vol. XLIX (March 2011)Table 4Key Features of Estimates for Each Country (continued)Spain Portugal ItalyReferences Alvaredo and Saez (2009) Alvaredo (2009) Alvaredo and Pisano (2010)Years covered 1933–2005(gap 1962–1980 except 1971)(49 years)1936–2005(1983–1988 missing)(64 years)1974–2004(29 years)InitialcoverageTop .01% initiallyTop 10% since 1981Top 0.1% initially Top 10%Unit of analysis Individual Family IndividualPopulationdefinitionPopulationaged 20 and over fromNational CensusPopulation aged 20 and overminus married women fromcensus statisticsPopulationaged 20 and over fromNational CensusMethod ofcalculatingcontrol totalsfor incomeTotal income constructedfrom national accountsinitially as 66% of GDP andlater refinedTotal income constructedfrom national accountsinitially as 66% of GDP andlater refinedTotal income constructedprimarily from nationalaccounts: wages, pensions,50% of business income, andcapital income from tax returnsIncomedefinitionGross income Gross income Gross income but excludinginterest incomeTreatment ofcapital gainsExcluded(series with capital gains alsoestimated after 1981)ExcludedExcludedBreaksin series?Significant change in incometax scope after 1978Change from family toindividual taxation in 1988(corrected for)Method ofinterpolationPareto Pareto ParetoSpecialfeaturesOtherreferencesTop wage income series alsoconstructed after 1981Top wage income series alsoconstructed after 1964Guilera Rafecas (2008)Source: Atkinson and P. Ketty (2007, 2010).
Atkinson, Piketty, and Saez: Top Incomes in the Long Run of History29shortcomings of the income tax data. It is truethat income tax data cover only the taxpayingpopulation, which, in the early years of incometax, was typically only a small fraction of thetotal population. As a result, tax data cannotbe used to describe the whole distribution butwe can estimate the upper part of the Lorenzcurve, i.e., top income shares.But why not use household surveys thatcover the whole (noninstitutional) population?Why use income tax data? There are twomain answers. The first is that household surveysthemselves are not without shortcom ings.These include sampling error, which may besizable with the typical sample sizes for sur -veys, whereas tax data drawn from administrativerecords are based on very much largersamples. Indeed, in some cases the tax statisticsrelate to the whole universe of taxpayers.Household surveys suffer from differentialnonresponse and incomplete response (thesetwo being the survey counterpart of tax evasion),as well as measurement error, Suchproblems particularly affect the top incomeranges, as is recognized in studies that combinehousehold survey data with informationon upper income ranges from tax sources (see,for example, in the United Kingdom, MichaelBrewer et al. 2008). Indeed, most surveysimpose top coding to limit the effects of measurementerror on aggregates, which severelylimit the analysis of top incomes using surveydata. The second answer is that household surveysare a fairly recent innovation. Householdsurveys only became regular in most countriesin the 1970s or later and, in a number ofcases, they are held at intervals rather thanannually. The beauty of income tax evidenceis that it is available for long runs of years,typically on an annual basis, and that it isavailable for a wide variety of countries.3.2.1 Comparison with Household SurveyData: U.S. Case StudyThe important recent study by Richard V.Burkhauser et al. (2009) tries to reconcilethe Piketty and Saez (2003) top income shareseries, estimated with tax statistics, with topincome shares measured using CPS data butfollowing the same methodology as in Pikettyand Saez (2003) in terms of income definitionand family unit. 18 Burkhauser et al. (2009)find that their CPS based top income shareseries match the Piketty and Saez (2003)series very closely for the second vingtileand the next 4 percent (i.e., the top decileexcluding the top percentile). As depicted onfigure 5, the top 1 percent share measuredby the CPS also appears to follow the samequalitative trend as the top 1 percent sharefrom tax data. However there are importantquantitative differences that remain, especiallycomparing the CPS series with the taxseries including realized capital gains (whichare not measured in the CPS questionnaire).Four points are worth noting.First, the top 1 percent share measuredby the CPS is consistently lower than the top1 percent income share measured with taxdata. This is due to the fact that (a) the CPSdoes not record important income sources atthe top (such as realized capital gains or stockoption gains), (b) CPS incomes are by designrecorded with top code, 19 (c) there might beunderreporting of incomes at the top in theCPS (i.e., some top income individuals mightdecide to under report their true income,even in the absence of uncertainty about theincome concept).18 Edward N. Wolff and Ajit Zacharias (2009) and ArthurB. Kennickell (2009) also compute top income shares usingthe Survey of Consumer Finances, which is not top codedand oversamples the rich. Wolff and Zacharias (2009) inparticular use wealth data to estimate more comprehensivemeasures of capital income that cannot be observed in taxdata. The trend of their estimated series is in line with thetax based estimates of Piketty and Saez (2003).19 Burkhauser et al. (2009) use the internal CPS. Theinternal CPS is further top coded for confidentiality reasonsbefore being publicly disclosed. However, even theinternal CPS remains top coded by design. Such top codesare necessary in survey data to avoid having a handful ofreporting errors having significant effects on aggregatestatistics.
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