30:T12a5,chart = width > 900 ? vl.hconcat( vl.vconcat( bars .width(makeWidth(self.innerWidth) * 1.1) .height(280) ) .resolve({ legend: { "fill": "independent", "size": "independent", "strokeDash": "independent"} }), vl.vconcat(vl.hconcat( makeChartLinesPoints( data_anteile .filter(d => d.frequency === "j") .filter(d => d.treatment === select_treatment), "att", null, // [-10,20], "Effect in percentage points", "Years", "top", 1 ) .width(makeWidth(self.innerWidth) / 2) .height(280), makeChartLinesPoints( data_anteile .filter(d => d.frequency === "j") .filter(d => d.treatment === select_treatment), "patt", null, // [-25,60] "As a percentage of effect", "Years", "top", 1 ) .width(makeWidth(self.innerWidth) / 2) .height(280) )) .resolve({ "legend": { "fill": "independent", "size": "independent", "strokeDash": "independent"} }) ) .resolve({ legend: { "fill": "independent", "size": "independent", "StrokeDash": "independent" }, scale: { "fill": "independent", "size": "independent", "StrokeDash": "independent" } }) .padding({"left": 5, "top": 5, "right": 5, "bottom": 5}) .config({ view: {stroke: "transparent"}, background: "transparent", font: "FFDaxPro", axis: { labelFontSize: 14, titleFontSize: 14, titleFontWeight: "normal", }, legend: { labelFontSize: 14, titleFontSize: 14, titleFontWeight: "normal", }, mark: { fontSize: 14 }, title: { fontSize: 16, subtitleFontSize: 14, }, locale: {number: { decimal: ".", thousands: ",", grouping: [3], format: ',.4' }} }) .title({ text: " ", subtitle: subtitle, // "Q: IMF, Statistik Austria, WIFO", orient: "bottom", anchor: "start" }) .render({renderer: 'svg'}) : vl.vconcat( vl.vconcat( bars .width(makeWidth(self.innerWidth) * 1.65) .height(200) ) .resolve({ legend: { "fill": "independent", "size": "independent", "strokeDash": "independent"} }), vl.vconcat(vl.hconcat( makeChartLinesPoints( data_anteile .filter(d => d.frequency === "j") .filter(d => d.treatment === select_treatment), "att", [-10,20], "Effect in percentage points", "Years", "top", 1 ) .width(makeWidth(self.innerWidth) / 1.6) .height(200), makeChartLinesPoints( data_anteile .filter(d => d.frequency === "j") .filter(d => d.treatment === select_treatment), "patt", [-25,60], "As a percentage of effect", "Years", "top", 1 ) .width(makeWidth(self.innerWidth) / 1.6) .height(200) )) .resolve({ "legend": { "fill": "independent", "size": "independent", "strokeDash": "independent"} }) ) .resolve({ legend: { "fill": "independent", "size": "independent", "StrokeDash": "independent" }, scale: { "fill": "independent", "size": "independent", "StrokeDash": "independent" } }) .padding({"left": 5, "top": 5, "right": 5, "bottom": 5}) .config({ view: {stroke: "transparent"}, background: "transparent", font: "FFDaxPro", axis: { labelFontSize: 14, titleFontSize: 14, titleFontWeight: "normal", }, legend: { labelFontSize: 14, titleFontSize: 14, titleFontWeight: "normal", }, mark: { fontSize: 14 }, title: { fontSize: 16, }, locale: {number: { decimal: ".", thousands: ",", grouping: [3], format: ',.4' }} }) .title({ text: " ", subtitle: subtitle, orient: "bottom", anchor: "start" }) .render({renderer: 'svg'})31:Taa9,makeChartBarMini = function(data, domain, yTitle, toolTitle, formatLabels) { const chartBar = vl.markBar({ stroke: "none", size: makeWidth(self.innerWidth) / 10 }) .data(data) .encode( vl.x() .fieldQ("outlength2") .axis({ title: "Years after (hypothetical) programme start", tickCount: 6, grid: false, tickMinStep: 1, tickColor: "black", tickWidth: 0.66, domainColor: "black", domainWidth: 0.66 }), vl.y() .fieldQ("value") .scale({ // domain: domain, padding: 20, }) .axis({ title: yTitle, domain: false, ticks: false, labelPadding: 10, labelFLush: true, minExtent: 34, }), vl.fill() .fieldN("measure") .scale({ range: ["#72bb6f","#559bd5"] }) .legend({ orient: "top", direction: "vertical", title: null, labelLimit: width > 900 ? 1000 : 160, values: ["Treatment group","Control group"] }),//{ symbolType: "square" } vl.tooltip([{'field': 'measure', 'title': "Gruppe"},{'field': 'value', 'title': yTitle, "format": formatLabels}]), ) const chartTextDiffPatt = vl.markText({ fontSize: width > 1000 ? 14 : 12 }) .data(data .filter(d => d.diff !== null) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ("max_diff_patt"), vl.text() .fieldN("diff_patt") ) const chartTextDiff = vl.markText({ fontSize: width > 1000 ? 14 : 12 }) .data(data .filter(d => d.diff !== null) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ("max_diff"), vl.text() .fieldN("diff") ) const chartTextBar = vl.markText({ fontSize: width > 1000 ? 12 : 10 }) .data(data) .encode( vl.x() .fieldQ("outlength2"), vl.y() .fieldQ("valueText1"), vl.text({"field": "value", "type": "quantitative", "format": formatLabels}) ) const image = vl.markImage({ width: 30, height: 30, clip: false, zindex: 1, baseline: "bottom" }) .data([{info: info}]) .encode( vl.url() .value("https://upload.wikimedia.org/wikipedia/commons/e/e4/Infobox_info_icon.svg"), vl.x() .value(250), vl.y() .value(-20), vl.tooltip("info"), ) const barChart = vl.layer( chartBar, chartTextBar, chartTextDiff, chartTextDiffPatt, // image ) return barChart }32:T59c,subtitle = select_treatment != "Wage subsidy" ? (width > 900 ? [ "Source: WIFO INDI-DV based on Public Employment Service, Federation of Social Insurances and WIFO.", "*** . . . significant at a 1 percent level, ** . . . significant at a 5 percent level, * . . . significant at a 10 percent level." ] : [ "Source: WIFO INDI-DV based on Public Employment Service,", "Federation of Social Insurances and WIFO.", "*** . . . significant at a 1 percent level,", "** . . . significant at a 5 percent level,", "* . . . significant at a 10 percent level." ] ) : (width > 900 ? [ "Source: WIFO INDI-DV based on Public Employment Service, Federation of Social Insurances and WIFO.", "°°° . . . significant at a 1 percent level, °° . . . significant at a 5 percent level, ° . . . significant at a 10 percent level.", "Average effect computed from two control groups (with and without job take-up at start of subsidy)." ] : [ "Source: WIFO INDI-DV based on Public Employment Service,", "Federation of Social Insurances and WIFO.", "°°° . . . significant at a 1 percent level,", "°° . . . significant at a 5 percent level,", "° . . . significant at a 10 percent level.", "Average effect computed from two control groups", "(with and without job take-up at start of subsidy)." ] )33:T641,info = "An example of the group's applied research in the field of labur market is the evaluation of labour market policy interventions carried out by the Public Employment Service (AMS). The graph below shows the effects that qualification subsidies have on the employment integration of subsidised unemployed individuals in subsequent years. In order to create an adequate comparison situation between a subsidised and a non-subsidised person, Propensity Score Matching is used. This method assigns several control persons to each subsidised person, who were as similar as possible in a multitude of observable characteristics - from demographic and regional characteristics to employment history - in the past. Subsequently, certain employment characteristics of the treatment and control group are measured and compared in the following years. Taking vocational orientation as an example, it is shown that six years after the start of funding, the proportion of subsidised persons in non-subsidised, dependent employment is 3.6 percentage points or 9.6% higher than among comparable non-subsidised persons. Broadly speaking, it is shown that qualifications during unemployment have a long-term positive influence on employment, in favour of lower employment inactivity. It is also very noticeable that the effects usually unfold over a long period of time and especially in the first year have slightly negative effects on employment. These results are of high relevance in order to use the financial resources allocated for the unemployed where they help those affected by unemployment the most."34:Ta3a,makeChartBar = function(data, domain, yTitle, toolTitle, formatLabels) { const chartBar = vl.markBar({ stroke: "none", size: width > 900 ? makeWidth(self.innerWidth) / 16 : makeWidth(self.innerWidth) / 13 }) .data(data) .encode( vl.x() .fieldQ("outlength2") .axis({ title: "Years after (hypothetical) programme start", tickCount: 6, grid: false, tickMinStep: 1, tickColor: "black", tickWidth: 0.66, domainColor: "black", domainWidth: 0.66 }), vl.y() .fieldQ("value") .scale({ domain: domain }) .axis({ title: yTitle, domain: false, ticks: false, labelPadding: 10, }), vl.fill() .fieldN("measure") .scale({ range: ["#72bb6f","#559bd5"] }) .legend({ orient: "top", direction: "vertical", title: null, values: ["Treatment group","Control group"] }),//{ symbolType: "square" } vl.tooltip([{'field': 'measure', 'title': "Group"},{'field': 'value', 'title': yTitle, "format": formatLabels}]), ) const chartTextDiffPatt = vl.markText({ fontSize: width > 1000 ? 14 : 12 }) .data(data .filter(d => d.diff !== null) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ("max_diff_patt"), vl.text() .fieldN("diff_patt") ) const chartTextDiff = vl.markText({ fontSize: width > 1000 ? 14 : 12 }) .data(data .filter(d => d.diff !== null) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ("max_diff"), vl.text() .fieldN("diff") ) const chartTextBar = vl.markText({ fontSize: width > 1000 ? 12 : 0 }) .data(data) .encode( vl.x() .fieldQ("outlength2"), vl.y() .fieldQ("valueText1"), vl.text({"field": "value", "type": "quantitative", "format": formatLabels}) ) const image = vl.markImage({ width: 30, height: 30, clip: false, zindex: 1, baseline: "bottom" }) .data([{info: info}]) .encode( vl.url() .value("https://upload.wikimedia.org/wikipedia/commons/e/e4/Infobox_info_icon.svg"), vl.x() .value(250), vl.y() .value(-20), vl.tooltip("info"), ) const barChart = vl.layer( chartBar, chartTextBar, chartTextDiff, chartTextDiffPatt, image ) return barChart }35:Tcfa,makeChartLinesPoints = function(data, effect, domain, yTitle, xTitle, lPos, lCol) { const chartLines = vl.markLine({ opacity: 0.25 }) // , clip: true .data(data) .encode( vl.x() .fieldQ("outlength") .axis({ title: xTitle, tickOunt: 6, grid: false, tickMinStep: 1, tickColor: "black", tickWidth: 0.66, domainColor: "black", domainWidth: 0.66 }), vl.y() .fieldQ(effect) .axis({ minExtent: 34, labelFlush: true, title: yTitle, domain: false, ticks: false, labelPadding: 10, tickCount: 6, tickMinStep: 5, tickRound: false, gridColor: { "condition": {"test": {"field": "value", "equal": 0}, "value": "black"}, "value": "lightgray"} }) .scale({ // domain: domain, padding: 20 }), vl.color() .fieldN("outcome") .scale({range: colorsFill}) .legend(null), ) const chartPoints = vl.markPoint({ opacity: 0.20 }) .data(data) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ(effect), vl.fill() .fieldN("outcome") .scale({range: colorsFill}) // KOntrollgruppe und tratmentgruppe at 4,5 .legend({ title: "Outcome", symbolOpacity: 1, orient: lPos, values: legendFill, columnPadding: 15, labelLimit: width > 900 ? 1000 : 160, columns: lCol, }), vl.color() .fieldN("outcome") .scale({range: colorsFill}) .legend(null), vl.size() .fieldN("sig2") .scale({range: [5,30]}) .legend({ title: "Significance (5%)", symbolOpacity: 1, // values: ["signifikant","insignifikant"], orient: lPos, columns: 1, }), ) const chartLinesHighlight = vl.markLine({ opacity: 1, zindex: 1 }) .data(data .filter(d => d.outcome === select_outcome) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ(effect), vl.color() .fieldN("outcome"), ) const chartPointsHighlight = vl.markPoint({ opacity: 1 }) .data(data .filter(d => d.outcome === select_outcome) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ(effect), vl.fill() .fieldN("outcome"), vl.color() .fieldN("outcome"), vl.size() .fieldN("sig2") .scale({range: [5,30]}), ) const chartPointsTooltip = vl.markPoint({ opacity: 0, size: 280 }) .data(data .filter(d => d.outcome === select_outcome) ) .encode( vl.x() .fieldQ("outlength"), vl.y() .fieldQ(effect), vl.tooltip([{'field': 'diff', 'title': 'Absolute effect'},{'field': 'diff_patt', 'title': 'Effect in %'}]), ) const chartLinesPoints = vl.layer(chartLines, chartPoints, chartLinesHighlight, chartPointsHighlight, chartPointsTooltip) return chartLinesPoints }36:T4dd,makeChartBarAll = function(data, domain, yTitle, toolTitle) { const brush = vl.selectPoint() .fields("outcome") .on("mouseover") .clear(false).nearest(true) .value(""); const chartBar = vl.markBar({stroke: "none", size: 23}) .data(data) .params(brush) .encode( vl.x() .fieldN("measure") .axis({ title: null, tickCount: 6, grid: false, tickMinStep: 1 }), vl.column({ spacing: 5 }) .fieldN("outlength3"), vl.y() .fieldQ("value") .scale({ domain: [0,100], padding: 20, }) .axis({ title: yTitle, labelFlush: true, minExtent: 34, }), vl.fill() .fieldN("outcome") .scale({ range: colorsFill }) .legend({ orient: "right", direction: "vertical", title: null, }), vl.tooltip([ {'field': 'measure', 'title': "Gruppe"}, {'field': 'value', 'title': yTitle, 'format': '.3r'} ]), vl.opacity() .value(1) .if(brush, vl.opacity().value(0)) ) const barChart = chartBar return barChart }37:[{"id":"43bc018d09e0235884e1ff9f9ad75a8feccd06b36cea2f96a9a8de53a8484a7a9aecbad38f7bc33a33f33799057c4b2f2f90b4aaa82263798180c192ec9bfff8","href":"https://static.observableusercontent.com/files/43bc018d09e0235884e1ff9f9ad75a8feccd06b36cea2f96a9a8de53a8484a7a9aecbad38f7bc33a33f33799057c4b2f2f90b4aaa82263798180c192ec9bfff8","name":"export_anteile.csv","type":"text/csv","lastModified":1684437307694.116,"size":210992}] 2e:{"title":"Effectiveness of active labour market policies","cells":[{"id":0,"value":"\n\n # Effectiveness of active labour market policies\n ## FG2 web chart\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":2218,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":2168,"value":"title = htl.html`\n

Effectiveness of active labour market policies

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"viewof select_treatment = Inputs.select(new Set(names_treatment), {label: \"Subsidy\", width: width > 800 ? 580 : 200 })","pinned":false,"hidden":false,"mode":"ojs"},{"id":128,"value":"viewof select_outcome = Inputs.select(\n new Set(legendFill), \n {label: \"Outcome\", width: width > 800 ? 580 : 200 }\n) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":2298,"value":"chartMini = \n vl.hconcat(\n vl.vconcat(\n barsMini\n .width(makeWidth(self.innerWidth) * 2)\n .height(280)\n ))\n .title({\n text: \" \",\n subtitle: subtitle, // \"Q: IMF, Statistik Austria, WIFO\",\n orient: \"bottom\",\n anchor: \"start\"\n })\n .padding({\"left\": 5, \"top\": 5, \"right\": 5, \"bottom\": 5})\n .config({\n view: {stroke: \"transparent\"}, \n background: \"transparent\",\n font: \"FFDaxPro\",\n axis: {\n labelFontSize: 14, \n titleFontSize: 14,\n titleFontWeight: \"normal\",\n },\n legend: {\n labelFontSize: 14, \n titleFontSize: 14,\n titleFontWeight: \"normal\",\n },\n mark: {\n fontSize: 14\n },\n title: {\n fontSize: 16,\n subtitleFontSize: 14,\n },\n locale: {number: {\n decimal: \".\", \n thousands: \",\", \n grouping: [3], \n format: ',.4'\n }}\n })\n .render({renderer: 'svg'})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1983,"value":"---\n\n\n# Appendix\n","pinned":false,"hidden":false,"mode":"md"},{"id":2300,"value":"$31","pinned":true,"hidden":false,"mode":"ojs"},{"id":2302,"value":"barsMini = makeChartBarMini(\n data_anteile\n .filter(d => d.frequency === \"j\")\n .filter(d => d.outcome === select_outcome)\n .filter(d => d.treatment === select_treatment), \n [0,100], \n \"Percentage share\",\n null,\n \".3s\"\n )","pinned":true,"hidden":false,"mode":"ojs"},{"id":2283,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":2163,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1389,"value":"lockin = makeChartLinesPoints(\n data_anteile\n .filter(d => d.frequency === \"m\")\n .filter(d => d.treatment === select_treatment), \n \"att\",\n null, \n \"Effect in percentage points\", \n \"Monate\",\n \"top\",\n 2)\n // .title({text: \"Effekte auf die Erwerbsintegration in der kurzen Frist\", \n // fontWeight: \"normal\", \n // fontSize: 9,\n // align: \"left\",\n // anchor: \"left\",\n // subtitle: \"Hallo\"})\n .width(makeWidth(self.innerWidth) / 2.4)\n .height(280)","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"bars = makeChartBar(\n data_anteile\n .filter(d => d.frequency === \"j\")\n .filter(d => d.outcome === select_outcome)\n .filter(d => d.treatment === select_treatment), \n [0,100], \n \"Percentage share\",\n null,\n \".3s\"\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":1060,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":1077,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":771,"value":"legendFill = [\"Non-subsidised, dependent active employment\", \"Employment\", \"Registered unemployment\", \"Economic inactivity\", ]","pinned":false,"hidden":false,"mode":"ojs"},{"id":764,"value":"colorsFill = [\"#12a7e7\", \"#72bb6f\", \"#559e8f\",\"#559bd5\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":2042,"value":"data_anteile = csv\n .map(d => ({...d, sig_en: d.sig_en == \"significant\" ? \"Significant\" : d.sig_en }))\n .map(d => ({...d, sig_en: d.sig_en == \"insignificant\" ? \"Insignificant\" : d.sig_en }))\n .map(d => ({...d, diff_patt: d.diff_patt && typeof d.diff_patt === 'string' ? d.diff_patt.replace(/-/g, '−') : d.diff_patt }))\n .map(d => ({...d, diff: d.diff && typeof d.diff === 'string' ? d.diff.replace(/-/g, '−') : d.diff }))\n .map(d => ({\n ...d, \n outcome: d.outcome_en === \"Non-subsidised, dependent, active employment\" ? \"Non-subsidised, dependent active employment\": d.outcome_en,\n treatment: d.treatment_en,\n measure: d.measure_en + \" group\",\n sig2: d.sig2_en,\n diff_patt: d.diff_patt == null ? null : d.diff_patt.replace(\",\", \".\"),\n diff: d.diff == null ? null : d.diff.replace(\",\", \".\"),\n })) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"csv = FileAttachment(\"export_anteile.csv\")\n .csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"names_treatment = data_anteile.map(d => d.treatment)","pinned":false,"hidden":false,"mode":"ojs"},{"id":133,"value":"names_outcome = data_anteile.map(d => d.outcome)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1686,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":2102,"value":"makeWidth = function(inputWidth) {\n if (inputWidth<600) {\n return Math.sqrt(inputWidth)*8\n }\n if (inputWidth<900) {\n return Math.sqrt(inputWidth+200)*8\n }\n if (inputWidth<1200) {\n return Math.sqrt(inputWidth+200)*9\n }\n if (inputWidth<1400) {\n return Math.sqrt(inputWidth+140)*10\n }\n if (inputWidth<1600) {\n return Math.sqrt(inputWidth)*10\n }\n else {\n return Math.sqrt(inputWidth)*13/1.75\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"import { vl } from \"@vega/vega-lite-api-v5\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"","pinned":false,"hidden":false,"mode":"html"}],"files":"$W37","stdlib":"1","titling":"auto"}