2e:null 2f:["$","title",null,{"children":"GRADE Corporate tax flows and the SDGs explorer | GRADE | Observable"}] 34:T5d3,globe = htl.html`

Global tax flows

${bertin.draw({ params: { projection: d3.geoAzimuthalEqualArea().rotate([globeInputValues.longitude, 1]).clipAngle(150), //width: 800, }, layers: [ { geojson: links, stroke: "#cf429d", strokeOpacity: 0.5, tooltip: { fields:[(d)=> { if (d.properties.tax_paid_2015_dollars >= 0){ return (mncName == "All MNCs" ? "" : (mncName + ": ")) + d.properties.upe_name + "\u2192" + d.properties.jur_name } else { return (mncName == "All MNCs" ? "" : (mncName + ": ")) + d.properties.jur_name + "\u2192" + d.properties.upe_name }}, (d)=> "$" + (Math.abs(d.properties.tax_paid_2015_dollars) / 1E6).toFixed(2) + "M"], fill:"white", fillOpacity:"70%", fontSize: [18, 14], fontStyle: ["normal", "normal"], }, strokeWidth: { type: "linear", values: "tax_paid_2015_dollars", //fixmax: d3.max(taxFlowLUT.map((d) => Math.max(d.tax_paid_2015_dollars,0))), fixmin: 1E8, k: globeInputValues.k * 10, //leg_x: 20, leg_y: 20, leg_w: 110, leg_title: "Tax flow in $", }, }, { geojson: world, fill: "orange", fillOpacity: 0.5, stroke: "none" }, { geojson: countriesSelected, fill: "red", fillOpacity:0.5, stroke: "none"}, { type: "graticule" }, { type: "outline" }, ] })}`35:T638,about = html`

About the model and data sources

This tool uses data on MNC tax contributions from Aliprandi, G., Borders, K., Gabriel, F., von Zedlitz, G. (2022): "Public Country-by-Country Reports: a new database." EU Tax Observatory. This raw data is first converted to US dollars, and then deflated to give values in 2015 USD. For further details of this conversion, see the accompanying data preparation and averaging notebooks.

To calculate the effect on the SDGs, the resulting absolute additional revenues (in constant 2015 $US) are used as inputs to the GRADE Determinants of Health (DOH) model, and the effects obtained as the instantaneous long-range effect for a given country and indicator of health, i.e., we estimate the improvement that would be achieved over the long term with such an uplift in revenue. For further details on the GRADE-DOH model, see the repository on Github, or this simple calculator tool.

For details of all Government Revenue and Development Estimations (GRADE) research, see the GRADE homepage.

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Positive MNC tax flows

Too much data to plot. Try selecting a country or MNC`\n } else if (mnc2Jur.length > 0) {\n return htl.html`

Positive MNC tax flows

\n ${\n SankeyChart({links:mnc2Jur},{nodeGroup: d => d.id.split(/\\W/)[0], // take first word for color\n linkColor: \"source-target\",\n format: (f => d => `$${f(d/1E6)}M`)(d3.format(\",.2~f\")),\n width,\n height: mnc2Jur.length > 1 ? 600 : 100,})\n }`}\n else {\n return htl.html`

Positive MNC tax flows

SDG progress

Select a country of registration and/or MNC to display people with increased access`\n }\n return htl.html`

SDG progress

`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":677,"value":"viewof mapInputValues = inputsGroup(\n [\n [\n Inputs.select(measureNames, {label:\"measure\"}),\n ],\n [\n Inputs.range([1, 100], { label: \"radius\", step: 1, value: 35 }),\n Inputs.range([1,10], {label: \"zoom\", step:.1, value:1}),\n ],\n [\n Inputs.range([-180,180], {step:1, value:0, label: \"pan X\"}),\n Inputs.range([-90,90], {step:1, value:0, label: \"pan Y\"})\n ]\n ],\n [\n [\"measure\",],\n [\"kRadius\", \"zoom\"],\n [\"panX\", \"panY\"]\n ]\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":597,"value":"effectsMap = map(mapData, mapInputValues.measure, mapInputValues.kRadius, countries, mapInputValues.zoom, mapInputValues.panX, mapInputValues.panY, 500, effects.length > 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":704,"value":"effectsData = effectsSafe","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"effectsData","database":"$undefined"},{"id":414,"value":"negativeFlows = {\n if (jur2Mnc.length > 50) {\n return htl.html`

Negative MNC tax flows

Too much data to plot. Try selecting a country or MNC`\n } else if (jur2Mnc.length > 0) {\n return htl.html`

Negative MNC tax flows

\n ${\n SankeyChart({links:jur2Mnc},{nodeGroup: d => d.id.split(/\\W/)[0], // take first word for color\n linkColor: \"source-target\",\n format: (f => d => `$${f(d/1E6)}M`)(d3.format(\",.2~f\")),\n width,\n height: jur2Mnc.length > 1 ? Math.max(600 * totalNegative / totalPositive, 200) : 100})\n }`}\n else {\n return htl.html`

Negative MNC tax flows

No data`\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":735,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":711,"value":"{return effects.length > 0 ? downloadButton(effects) : md``}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":135,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":3,"value":"bertin = require(\"bertin@latest\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"world = d3.json(\n \"https://raw.githubusercontent.com/neocarto/bertin/main/data/world.geojson\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"import {taxFlowLUT} from '@grade/tax-observatory-country-by-country-averages'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":707,"value":"import {downloadButton} from \"@jeremiak/buttons-that-download-json-as-csv\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"taxFlowLUTYear = taxFlowLUT.filter((x)=>x.year == inputValues.year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":118,"value":"taxFlowLUTYearCountries = taxFlowLUTYear.filter(d=>{\n return (inputValues.upe_name == \"All countries\" ? true : d.upe_name == inputValues.upe_name) && (inputValues.jur_name == \"All countries\" ? true : d.jur_name == inputValues.jur_name) && (!isNaN(d.tax_paid_2015_dollars)) && (d.tax_paid_2015_dollars != 0)})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"links = bertin.links({\n geojson: world,\n geojson_id: \"ISO3\",\n data: mncName == \"All MNCs\" ? taxFlowLUTYearCountries : reducedConvertedDatabaseFiltered,\n data_i: \"upe_code\",\n data_j: \"jur_code\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"upe_names = [\"All countries\"].concat([...new Set(taxFlowLUT.map(d=>d.upe_name))].sort())","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":79,"value":"jur_names = [\"All countries\"].concat([...new Set(taxFlowLUT.map(d=>d.jur_name))].sort())","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":240,"value":"import {reducedConvertedDatabase} from \"@grade/eu-tax-observatory-cbcr-conversion\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":967,"value":"reducedConvertedDatabase","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":256,"value":"reducedConvertedDatabaseFiltered = reducedConvertedDatabase.filter(d=>d.year == inputValues.year && (inputValues.upe_name == \"All countries\" ? true : d.upe_name == inputValues.upe_name) && (inputValues.jur_name == \"All countries\" ? true : d.jur_name == inputValues.jur_name)&& (mncName == \"All MNCs\" ? true : d.mnc == mncName) &&\n(!isNaN(d.tax_paid_2015_dollars)) && (d.tax_paid_2015_dollars != 0))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":298,"value":"mnc2Jur = reducedConvertedDatabaseFiltered.filter((d)=>d.tax_paid_2015_dollars > 0).map((d)=>{return {source:d.mnc + ` (${d.upe_name})`, target:d.jur_name, value:d.tax_paid_2015_dollars}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":746,"value":"totalPositive = d3.sum(mnc2Jur,(d)=>d.value)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":409,"value":"jur2Mnc = reducedConvertedDatabaseFiltered.filter((d)=>d.tax_paid_2015_dollars < 0).map((d)=>{return {target:d.mnc + ` (${d.upe_name})`, source:d.jur_name, value:-d.tax_paid_2015_dollars}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":749,"value":"totalNegative = d3.sum(jur2Mnc,(d)=>d.value)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":309,"value":"mncNames = [\"All MNCs\"].concat([...new Set(reducedConvertedDatabase.filter(d=>d.sector == sector || sector == \"All sectors\").filter(d=>d.upe_name == inputValues.upe_name || inputValues.upe_name == \"All countries\").map(d=>d.mnc))])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":764,"value":"sectors = [\"All sectors\"].concat([...new Set(reducedConvertedDatabase.map(d=>d.sector))])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"import {SankeyChart} from \"@d3/sankey-component\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":343,"value":"import {inputsGroup} from \"@stuwilmur/input-grid\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":469,"value":"countriesSelected = ({\n type: \"FeatureCollection\",\n features: world.features.filter((d) => (d.properties.NAMEen == inputValues.upe_name) || (d.properties.NAMEen == inputValues.jur_name))\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":576,"value":"import {measureNames, map, calculateEffectsFromRevenues, countries} from \"@grade/grade-map-component\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":582,"value":"import {data as gradeData} from \"@grade/import\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":970,"value":"gradeDataClean = gradeData.filter(x=>x['Government revenue per capita (constant 2015 USD)'] !== null && ! isNaN(x['Government revenue per capita (constant 2015 USD)']))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":610,"value":"revenues = {\n if (mncName == \"All MNCs\") {\n if (inputValues.upe_name == \"All countries\")\n {\n return d3.flatRollup(taxFlowLUTYearCountries.filter((d) => d.jur_code != \"OTHER\"), v => d3.sum(v, d => d.tax_paid_2015_dollars), d => d.jur_code, d => d.year).map(x=> {return {\n iso: x[0],\n year : x[1],\n revenue: x[2]\n }});\n }\n else{\n return taxFlowLUTYearCountries.filter((d) => d.jur_code != \"OTHER\")\n .map((d) => {\n return {\n year: d.year,\n iso: d.jur_code,\n revenue: d.tax_paid_2015_dollars\n };\n });\n }\n } else {\n return reducedConvertedDatabaseFiltered\n .filter((d) => d.tax_paid_2015_dollars > 0 && d.jur_code != \"OTHER\")\n .map((d) => {\n return {\n year: d.year,\n iso: d.jur_code,\n revenue: d.tax_paid_2015_dollars\n };\n });\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":587,"value":"effects = calculateEffectsFromRevenues(gradeDataClean, revenues).filter((d)=>d!=undefined)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":719,"value":"effectsSafe = effects.length > 0 ? effects : Object.assign([], {columns: [\"no data\"]})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":591,"value":"mapData = effects.length > 0 ? bertin.merge(countries, \"ISO3_CODE\", effects, \"countrycode\") : countries","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":728,"value":"import {spinner} from \"@stuwilmur/css-spinner\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":491,"value":"style = html`\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1","titling":"auto"}} 33:"$32:body"