{"id":20188,"date":"2026-07-13T10:14:41","date_gmt":"2026-07-13T10:14:41","guid":{"rendered":"https:\/\/prod.wid.world\/?page_id=20188"},"modified":"2026-10-12T13:48:00","modified_gmt":"2026-10-12T13:48:00","slug":"data-quality-5","status":"publish","type":"page","link":"https:\/\/wid.world\/hi\/data-quality-5\/","title":{"rendered":"Data Quality"},"content":{"rendered":"<div style=\"margin: 20px 0; padding: 20px; background: #f3f9fa; border-left: 4px solid #2a7f89; border-radius: 4px;\"><strong style=\"display: block; margin-bottom: 6px; color: #14545c;\">Introduction<br \/>\n<\/strong><\/p>\n<p style=\"margin: 0 0 14px 0;\">The accurate measurement of income and wealth inequality in WID.world relies on the release of detailed microdata, aggregated tabulations, and survey results by statistical agencies and governments. To make sense of the diverse information that becomes available, we assign data quality grades from 0 to 5 at the observational level for our main series.<\/p>\n<p style=\"margin: 0;\">The grades vary by year within a country-series combination. The data quality is available for all years in a series. This time dimension enables users to track how data quality evolves year by year, spot improvements, identify gaps in coverage, and compare trends across countries. The detailed criteria for each grade are summarized below.<\/p>\n<\/div>\n<hr \/>\n<h2>Table of Contents<\/h2>\n<ul>\n<li><a href=\"#download-data-quality\">1. Where Can I Download the Data Quality?<\/a><\/li>\n<li><a href=\"#quality-grade-descriptions\">2. Quality Grade Descriptions<\/a><\/li>\n<li><a href=\"#how-to-use-data-quality\">3. How to Use Data Quality?<\/a><\/li>\n<li><a href=\"#data-quality-over-time\">4. How Does Data Quality Change Over Time?<\/a><\/li>\n<li><a href=\"#aggregated-score\">5. How Do We Summarize Data Quality Over Time?<\/a><\/li>\n<li><a href=\"#what-we-know\">6. Making Explicit What We Know and Do Not Know<\/a><\/li>\n<\/ul>\n<hr \/>\n<h2 id=\"download-data-quality\" style=\"text-align: justify; scroll-margin-top: 100px;\"><strong>WHERE CAN I DOWNLOAD THE DATA QUALITY?<\/strong><\/h2>\n<p>The yearly data quality grades are downloaded by default as an additional column when downloading WID data, either via our user-friendly <a href=\"\/\/wid.world\/data\/\">direct download<\/a> on the website or via the statsitical software packages in <a href=\"\/\/github.com\/world-inequality-database\/wid-r-tool\">R<\/a> or <a href=\"\/\/github.com\/world-inequality-database\/wid-stata-tool\">STATA<\/a>. There is no need to request the metadata variables, it downloads by default in WID.data.<\/p>\n<div style=\"display: flex; flex-wrap: wrap; gap: 10px; margin: 20px 0;\">\n<p><a style=\"display: inline-block; padding: 11px 18px; background: white; border: 1px solid #16717c; color: #16717c; text-decoration: none; border-radius: 4px;\" href=\"\/\/wid.world\/data\/\" target=\"_blank\" rel=\"noopener\">Download WID data<br \/>\n<\/a><\/p>\n<p><a style=\"display: inline-block; padding: 11px 18px; background: white; border: 1px solid #16717c; color: #16717c; text-decoration: none; border-radius: 4px;\" href=\"\/\/github.com\/world-inequality-database\/wid-r-tool\" target=\"_blank\" rel=\"noopener\">Use the R package<br \/>\n<\/a><\/p>\n<p><a style=\"display: inline-block; padding: 11px 18px; background: white; border: 1px solid #16717c; color: #16717c; text-decoration: none; border-radius: 4px;\" href=\"\/\/github.com\/world-inequality-database\/wid-stata-tool\" target=\"_blank\" rel=\"noopener\">Use the Stata command<br \/>\n<\/a><\/p>\n<\/div>\n<details style=\"margin: 15px 0;\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">\u25b6\u00a0Can\u2019t see the new data quality column in your downloads?<\/summary>\n<div style=\"padding: 12px 0 0 18px;\">\n<p style=\"margin: 0;\">If you are downloading data through R or Stata and cannot see the data quality column, you may be using an older version of the WID package. Please <strong>uninstall<\/strong> and <strong>reinstall the package<\/strong> to access the latest version. The column is included automatically in new downloads and does not need to be requested separately.<\/p>\n<\/div>\n<\/details>\n<h2 id=\"quality-grade-descriptions\" style=\"text-align: justify; scroll-margin-top: 100px;\"><strong>QUALITY GRADE DESCRIPTIONS<\/strong><\/h2>\n<p style=\"text-align: justify; scroll-margin-top: 100px;\">What does each 0-5 grade signify? The definition depends on the type of variable.<\/p>\n<h3 style=\"scroll-margin-top: 100px; text-align: center;\"><span style=\"text-decoration: underline;\">Distributed concepts<\/span><\/h3>\n<table style=\"width: 100%; border-collapse: collapse; text-align: center; table-layout: fixed;\" border=\"1\">\n<colgroup>\n<col style=\"width: 10%;\" \/>\n<col style=\"width: 27%;\" \/>\n<col style=\"width: 27%;\" \/>\n<col style=\"width: 36%;\" \/> <\/colgroup>\n<tbody>\n<tr>\n<th style=\"padding: 8px; text-align: center;\">Grade<\/th>\n<th style=\"padding: 8px; text-align: center;\">Distributed income<\/th>\n<th style=\"padding: 8px; text-align: center;\">Distributed wealth<\/th>\n<th style=\"padding: 8px; text-align: center;\">Female labour income share<\/th>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">0<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed regional average<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No data is available (imputed regional average). This is the lowest-quality category and is used only as a last resort to ensure coverage.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Income inequality-based weighting<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Estimates are based on the observed correlation between income inequality and wealth inequality. Wealth distribution is predicted using an income inequality weighted average of other countries\u2019 wealth distributions, with adjustments for rich-list and national accounts.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed regional average<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No income and employment data is available (imputed regional average). This is the lowest-quality category and is used only as a last resort to ensure coverage.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">1<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Carry forward or backward<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">The value is imputed by carrying the nearest available observation forward or backward, filling short gaps in an otherwise continuous series.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Survey data<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Estimates based solely on survey data, statistically adjusted to approximate missing top-end values. They include rich list and national accounts corrections when available (typically from the 1990s onwards).<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Predicted values (OLS) fully imputed<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated using an OLS regression model with female shares of wage and self-employment as the main predictors; employment data are drawn from ILO modelled estimates. Unlike grade 2, no observed income data are available for the country, so the full series is model-generated.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">2<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Interpolation<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by linear interpolation between two known data points, typically for short, internal gaps.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Wealth\/estate tabulated tax data, probate microdata, simplified multiplier method<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Wealth distribution estimates are imputed either via a simplified mortality-based multiplier method, from micro inheritance\/probate data, or from wealth tax tabulations. These are supplemented by rich list and\/or national accounts adjustments when available (typically from the 1990s onwards).<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Predicted values (OLS) level-adjusted<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated using an OLS regression model with female shares of wage and self-employment as the main predictors; employment data are drawn from ILO modelled estimates. Where observed income data exist for the country, the predicted trend is level-adjusted to match those observations, anchoring the series to real data points.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">3<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\"><span data-sheets-root=\"1\">Only one type of source: survey data or tax data. <\/span><\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\"><span data-sheets-root=\"1\">Only one type of source is used: either income\/consumption surveys, or tax tabulations; the two sources are not jointly available. Tax tabulations are typically the sole source for the historical series (pre 1980) or fiscal income series.<\/span><\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Survey data scaled to national accounts wealth aggregates<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Aggregate wealth figures are derived from national-accounts balancing items, then distributed according to survey shares.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Interpolation<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by linear interpolation between two known data points, typically for short, internal gaps.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">4<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Tax and survey data<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Tax and survey data are both available, but at least one source is in tabulated (not micro) form.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Mixed model of income capitalization or tabulated wealth\/estate tax data and survey data<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Wealth distribution is modeled using a hybrid of either income-capitalization techniques or wealth\/estate tax tabulations and survey information, with rich list\/national accounts adjustments.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed microdata \u2013 supplementary source<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Female and male wage and self-employment incomes are derived from a supplementary survey source. These observations are used to extend the time series beyond the years covered by the benchmark source, and are therefore of slightly lower priority but remain grounded in observed microdata.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 8px;\">5<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Tax and survey microdata<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Fully integrated micro-level data from tax records and household surveys are available.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Wealth tax microdata or administrative wealth registers<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">High-quality wealth microdata from administrative registers or tax declarations, requiring only minor imputations for unobserved assets.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed microdata \u2013 benchmark source<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Female and male wage and self-employment incomes are directly observed from the benchmark survey source for each country. The benchmark source is selected based on breadth of coverage, methodological consistency, and systematic data collection procedures. These observations represent the highest data quality in the series.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3 style=\"margin-top: 30px; text-align: center;\"><span style=\"text-decoration: underline;\">Aggregate concepts<\/span><\/h3>\n<table style=\"width: 100%; border-collapse: collapse; text-align: center; table-layout: fixed;\" border=\"1\">\n<colgroup>\n<col style=\"width: 10%;\" \/>\n<col style=\"width: 22.5%;\" \/>\n<col style=\"width: 22.5%;\" \/>\n<col style=\"width: 22.5%;\" \/>\n<col style=\"width: 22.5%;\" \/> <\/colgroup>\n<tbody>\n<tr>\n<th style=\"padding: 10px; text-align: center; white-space: nowrap;\">Grade<\/th>\n<th style=\"padding: 10px; text-align: center;\">Aggregate income<\/th>\n<th style=\"padding: 10px; text-align: center;\">Aggregate wealth*<\/th>\n<th style=\"padding: 10px; text-align: center;\">Indices &amp; Exchange Rates<\/th>\n<th style=\"padding: 10px; text-align: center;\">Population<\/th>\n<\/tr>\n<p><!-- GRADE 0 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">0<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed regional average<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No data are available. Values are assigned using a regional average or another assumed value solely to ensure coverage. This is the lowest-quality category and is used only as a last resort.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed regional average<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No data are available. Values are assigned using a regional average to ensure coverage. This is the lowest-quality category and is used only as a last resort.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Assumed static value<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No data are available; a static value is assumed. This is the lowest-quality category and is used only as a last resort to ensure coverage.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">N\/A<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">No observation is classified with this score.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<p><!-- GRADE 1 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">1<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Carry forward\/backward or simple extrapolation<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by extrapolating nearby observations using simple assumptions, such as forward\/backward projection, moving averages, regional growth rates, or stable relationships with a related country or former common jurisdiction.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Predicted and extended with regional trend<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by extrapolating nearby OLS predictions with a regional average.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed from related countries<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">The value is imputed either directly or by projecting an observation using a secondary variable\u2014or the same variable\u2014as a reference for growth observed in one or more neighbouring countries or countries with historical affiliations. For example, exchange rates may be imputed based on comparisons of Yugoslav GDP values expressed in different currency terms, with the resulting estimates applied to the former Yugoslav countries.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Carry forward or backward<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">The value is imputed by projecting the nearest available observation forward or backward, assuming constant relative shares, estimated in a recent reference period, between the country and the aggregate of another country with which it was part of the same jurisdiction at some point in time\u2014for example, the Czech Republic and Slovakia following the dissolution of Czechoslovakia.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<p><!-- GRADE 2 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">2<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Predicted values (mainly OLS)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated using statistical or econometric methods, such as OLS regressions on relevant macroeconomic covariates or signal-extraction techniques (e.g., Hodrick\u2013Prescott filtering).<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\"><span data-sheets-root=\"1\">Observed and extended with regional trend<\/span><\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\"><span data-sheets-root=\"1\">Values are estimated by extending nearby directly observed data with regional average.<\/span><\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed from domestic indicators<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">The value is imputed by projecting an observation using a secondary variable observed within the same country as a reference\u2014for example, a KP PPP exchange rate calculated based on the comparison of GDP values expressed in different currency terms\u2014or by carrying the nearest available observation forward or backward.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle;\">Imputed using domestic growth rates<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">The value is imputed by projecting the nearest available observation forward or backward, using growth rates or age shares observed in the country\u2019s available totals.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<p><!-- GRADE 3 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">3<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Interpolation &#8211; Enforce<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by linear interpolation between observed data points or derived through the simultaneous adjustment of macroeconomic identities to ensure internal consistency.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\"><span data-sheets-root=\"1\">Predicted using macroeconomic covariates<\/span><\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\"><span data-sheets-root=\"1\">Values are estimated using OLS regressions on relevant macroeconomic country-specific covariates rather than past observations.<\/span><\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Interpolation<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by linear interpolation between two known data points, filling short internal gaps.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Interpolation<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated using linear interpolation between adjacent data points to fill short internal gaps.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<p><!-- GRADE 4 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">4<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed (historical SNA or academic sources)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly sourced from older national accounting frameworks, benchmark academic studies, or historical compilations. Comparability with current standards may be limited.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed and extended with OLS prediction<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are estimated by extending nearby directly observed data with OLS predictions.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed (historical SNA, academic sources, or forecasts)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are sourced from benchmark academic research, historical compilations, forecasts under the latest SNA (e.g., IMF WEO estimates of deflators for some countries in the past year), or from older SNA frameworks.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed historical compilations<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly sourced from historical compilations; comparability with current standards may be limited.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<p><!-- GRADE 5 --><\/p>\n<tr>\n<td style=\"padding: 8px; text-align: center;\">5<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed (latest SNA)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly observed from the most recent national accounts compiled under the latest SNA standards. This is the highest-quality category.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly observed in official balance sheets (from the most recent national accounts compiled under the latest SNA standards), global asset datasets, or validated academic studies. This is the highest-quality category.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed (latest SNA)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly observed from the most recent national accounts under the latest SNA, representing the highest-quality data.<\/p>\n<\/details>\n<\/td>\n<td style=\"padding: 8px; vertical-align: middle; background-color: #f3f9fa;\">Observed (UN WPP or latest SNA)<\/p>\n<details style=\"margin: 0;\">\n<summary style=\"margin: 0; padding: 0; line-height: 1.1; cursor: pointer; color: #94b6b5; font-size: 11px;\">Read more<\/summary>\n<p style=\"margin: 6px 0 0; text-align: left; font-size: 14px; line-height: 1.5;\">Values are directly observed from the UN World Population Prospects or from the most recent national accounts compiled under the latest SNA, representing the highest-quality data.<\/p>\n<\/details>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p><b>Note:<\/b><span style=\"font-weight: 400;\"> The values calculated in-house are derived using accounting identities or assumptions based on already calculated variables. Their grade reflects the quality of the underlying components. See t<\/span><span style=\"font-weight: 400;\">echnical note for more details<\/span><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><em>*Aggregate wealth grade definitions are currently being revised and may be subject to change.<\/em><\/p>\n<h2 style=\"text-align: left;\"><strong>HOW TO USE DATA QUALITY?<\/strong><\/h2>\n<p>The 0-5 yearly grades enable users to filter their dataset based on the quality of data they desire.<\/p>\n<details style=\"margin: 15px 0;\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">\u25b6\u00a0Why are some grades highlighted in blue?<\/summary>\n<div style=\"margin: 12px 0 0; padding: 20px; background: #f3f9fa; border-left: 4px solid #2a7f89; border-radius: 4px;\">\n<p style=\"margin: 0;\">If the 0\u20135 grades had to be divided into two binary categories, the grades highlighted in blue represent broadly \u201cobserved\u201d data points. In our graph visualisation, these grades display the year with a solid line segment, while years with the non-highlighted grades are visualised using a dashed line segment.<br \/>\n<span style=\"font-weight: 400;\"><br \/>\nOne useful application is that users handling distributed income data, for example, can restrict their analysis to years for which the underlying data are observed.<br \/>\n<\/span><\/p>\n<div style=\"display: flex; flex-wrap: wrap; gap: 10px; margin: 20px 0;\"><a style=\"display: inline-block; padding: 11px 18px; background: #16717c; color: white; text-decoration: none; border-radius: 4px;\" href=\"\/\/wid.world\/world\/#sptinc_p90p100_z\/US;FR;DE;CN;ZA;GB;WO-PPP\/last\/eu\/k\/p\/yearly\/s\/false\/24.708000000000002\/80\/curve\/false\/country\" target=\"_blank\" rel=\"noopener noreferrer\">Click to check out the visualisation on wid.world<br \/>\n<\/a><\/div>\n<div style=\"margin-top: 10px;\">The cut-off grade used for the solid\/dashed line visualisation varies by concept:<\/div>\n<ul>\n<li>Distributed income variables: Grade \u2265 3<\/li>\n<li>Distributed wealth variables: Grade \u2265 1<\/li>\n<li>Female labour income share: Grade \u2265 4<\/li>\n<li>Aggregate income variables (including Indices, Exchange Rates, Population): Grade \u2265 3<\/li>\n<li>Aggregate wealth variables: Grade \u2265 3<\/li>\n<\/ul>\n<p style=\"margin-bottom: 0;\">For more details, consult the <a href=\"#quality-grade-descriptions\">Grade Descriptions<\/a>.<\/p>\n<\/div>\n<\/details>\n<h2 style=\"text-align: left;\"><strong>HOW DOES DATA QUALITY CHANGE OVER TIME?<\/strong><iframe class=\"quality-iframe\" style=\"border: 0px; overflow: hidden; width: 100%;\" src=\"\/\/wid.world\/data-quality-over-time\/?r\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">\ufeff<\/span><\/iframe><\/h2>\n<h2 style=\"text-align: left;\"><strong>HOW DO WE SUMMARIZE DATA QUALITY OVER TIME?<\/strong><\/h2>\n<p>To provide an overall picture of data quality for each country and series, we combine the yearly grades into a single score as a weighted average.<\/p>\n<details style=\"margin: 15px 0;\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">\u25b6\u00a0How do we construct the average score?<\/summary>\n<div style=\"margin: 12px 0 0; padding: 20px; background: #f3f9fa; border-left: 4px solid #2a7f89; border-radius: 4px;\">\n<p style=\"margin: 0; line-height: 1.6;\">The average quality score is a weighted average of the data quality across years for a given country-series. More recent years receive greater weight, while the influence of older years gradually decreases. This ensures that the score reflects current data quality without disregarding valuable historical information. As such, it reflects both the richness of the underlying data sources and the consistency of coverage over time.<\/p>\n<p style=\"margin: 12px 0 0; line-height: 1.6;\">The average score can take non-integer values between 0 and 5, rounded to one decimal place.<\/p>\n<\/div>\n<\/details>\n<p style=\"margin: 12px 0 0; line-height: 1.6;\">For a technical explanation of the score construction and the exact weights attributed in the time-decay weighting, we invite you to consult the technical note (coming soon).<\/p>\n<p><a style=\"display: inline-block; margin-top: 16px; padding: 11px 18px; background: #16717c; color: white; text-decoration: none; border-radius: 4px;\" href=\"\/\/wid.world\/document\/world-inequality-lab-technical-note-2026-05\" target=\"_blank\" rel=\"noopener noreferrer\">Technical Note<br \/>\n<\/a><\/p>\n<h3 style=\"text-align: center;\"><span style=\"text-decoration: underline;\">World map of average quality score per country<\/span><iframe class=\"quality-iframe\" style=\"border: 0px; overflow: hidden; width: 100%;\" src=\"\/\/wid.world\/data-quality-score-world-map\/?r\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">\ufeff<\/span><\/iframe><span style=\"text-decoration: underline;\">The distribution of average quality scores <\/span><iframe class=\"quality-iframe\" style=\"border: 0px; overflow: hidden; width: 100%;\" src=\"\/\/wid.world\/average-data-quality-score-across-countries\/?r#sptinc_p90p100_z\/ALL\/last\/eu\/k\/p\/yearly\/s\/false\/0\/1\/curve\/false\/country\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">\ufeff<\/span><\/iframe><\/h3>\n<details style=\"margin: 15px 0;\">\n<summary style=\"cursor: pointer; color: #16717c; font-size: 15px; font-weight: 600; list-style: none;\">\u25b6 <span style=\"text-decoration: underline;\">Click to learn more about country examples in the distributed income graph<\/span><\/summary>\n<div style=\"margin: 12px 0 0; padding: 20px; background: #f3f9fa; border-left: 4px solid #2a7f89; border-radius: 4px;\">\n<details style=\"margin: 15px 0;\" open=\"\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">Why do France and the United States score so highly?<\/summary>\n<div style=\"padding: 12px 0px 0px 18px; text-align: left;\">France and the United States have among the highest-quality pre-tax income series, with scores of 4.7 and 5, respectively. This reflects the extensive use of micro-data from tax records and household surveys, which are available nearly every year and result in most observations receiving grades of 4 or 5. To construct both series, we also take advantage of exceptional historical data coverage, incorporating observed data dating back to 1900 for France and 1820 for the United States. Their underlying sources are therefore both rich in detail and extensive in their coverage over time.<\/div>\n<\/details>\n<details style=\"margin: 15px 0;\" open=\"\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">\u00a0Why are there no scores between 0 and 1 for the pre-tax income series?<\/summary>\n<div style=\"padding: 12px 0 0 18px;\">\n<p style=\"margin: 0;\">There are no countries with a score between 0 and 1 due to the nature of the distributed income <a href=\"#quality-grade-descriptions\">Grade Descriptions<\/a>. A yearly grade of 0 indicates a regional imputation, which is applied to the country\u2019s entire series. Therefore, if one year is graded 0, all years are graded 0, resulting in a weighted average score of 0. By contrast, a grade of 1 indicates that values have been imputed by carrying forward or backward from a nearby observed year, so the overall score cannot fall below 1.<\/p>\n<\/div>\n<\/details>\n<details style=\"margin: 15px 0;\" open=\"\">\n<summary style=\"cursor: pointer; color: #16717c; font-weight: 600; list-style: none;\">How does the average score balance historical coverage and recent data efforts? Case studies: India, Japan, and Zambia<\/summary>\n<div style=\"padding: 12px 0 0 18px;\">The score rewards both historical coverage and recent data production, giving relatively greater weight to recent years in order to reward ongoing data-production efforts. Information from past years remains partially relevant but gradually loses weight as the data become outdated, also avoiding penalizing countries with longer historical series where data quality fades out. For instance, India scores 3.7, partly thanks to the incorporation of extensive historical observed data dating as far back as 1900. Japan, despite significant historical data, scores 1.3 because the series has only three observed data points in the past two decades. By contrast, Zambia\u2019s regular incorporation of newly released survey data contributes to a score of 2.2.<\/div>\n<\/details>\n<\/div>\n<\/details>\n<h2 style=\"text-align: left;\"><strong>MAKING EXPLICIT WHAT WE KNOW AND DO NOT KNOW<\/strong><\/h2>\n<p>We are aware that there are limitations to our ability to measure the evolution of income and wealth inequality. The objective of WID.world is not to claim to have perfect data series, but rather to make explicit what we know and what we do not know. We aim to combine and reconcile in a systematic manner the different data sources at our disposal: national income and wealth accounts, household income and wealth surveys, fiscal data coming from taxes on income, inheritance and wealth (when they exist), and wealth rankings. None of these data sources and associated methodologies is sufficient in itself. In particular, we stress that our ability to measure the distribution of wealth is limited, and that the different data sources at our disposal are not always fully consistent with one another. But we believe that by combining these data sources in the most explicit manner, we can contribute to a better-informed public debate. The research papers upon which our series are based are available online and present our methods and assumptions in the most transparent manner. All raw data sources and computer codes are released so that our work can be extended and improved by others.<\/p>\n<div style=\"margin: 20px 0; padding: 20px; background: #f3f9fa; border-left: 4px solid #2a7f89; border-radius: 4px;\">\n<p style=\"margin: 0;\">To make the most of the World Inequality Database, we encourage our users to consult a selection of key resources: the <a href=\"\/\/wid.world\/document\/distributional-national-accounts-dina-guidelines-2025-methods-and-concepts-used-in-the-world-inequality-database\/\">Distributional National Accounts (DINA) Guidelines<\/a>, which provide our methodological framework; the <a href=\"\/\/wid.world\/codes-dictionary\/\">Codes Dictionary<\/a>; the <a href=\"\/\/wid.world\/data\/\">user-friendly data page <\/a>for direct data downloads; our <a href=\"https:\/\/github.com\/world-inequality-database\">GitHub <\/a>repositories, which contain replication packages and commands for <a href=\"https:\/\/github.com\/world-inequality-database\/wid-stata-tool\">Stata <\/a>and <a href=\"https:\/\/github.com\/world-inequality-database\/wid-r-tool\">R<\/a>; our user-friendly <a href=\"https:\/\/github.com\/world-inequality-database\/wid-bulk-downloader\/\">bulk data downloader<\/a>; and the <a href=\"\/\/wid.world\/methodology\/\">Methodology page <\/a>for further resources.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Introduction The accurate measurement of income and wealth inequality in WID.world relies on the release of detailed microdata, aggregated tabulations, and survey results by statistical agencies and governments. To make sense of the diverse information that becomes available, we assign data quality grades from 0 to 5 at the observational<\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-wid-default-pages.php","meta":{"footnotes":""},"class_list":["post-20188","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Quality - WID - World Inequality Database<\/title>\n<meta name=\"description\" content=\"Data Quality The source for global inequality data. 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