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:where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n2dgw7l5.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-scene nx-es-scene\" data-scene=\"text\" data-ground=\"none\" data-es-org=\"gcri\" aria-labelledby=\"nx-scene-title\"><div class=\"nx-scene-intro nx-es-intro\"><p class=\"nx-eyebrow\"><abbr title=\"The Global Centre for Risk and Innovation\">GCRI<\/abbr> \u00b7 Society and Human Development<\/p><span class=\"nx-scene-rule\" aria-hidden=\"true\"><\/span><h1 id=\"nx-scene-title\" class=\"nx-scene-title\">Econometrics for social outcomes<\/h1><p class=\"nx-scene-lede\">Econometrics estimates relationships in social and economic data. In this field it measures how income, prices, shocks and policies relate to poverty, wellbeing and inequality, using panels and time series with uncertainty stated.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/human-development\/write-to-us\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/human-development\/stem\/\">Back to STEM foundation of Society and Human Development<\/a><\/div><\/div><\/section><section id=\"nx-s-1-sec\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" aria-labelledby=\"nx-s-1\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Register<\/span><\/div><h2 id=\"nx-s-1\" class=\"nx-section-title\">Econometrics for social outcomes on the record.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-es-fig\" data-es-layout=\"workbench\"><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Method record<\/strong><\/span><span class=\"nx-eyebrow\">STEM method<\/span><\/div><ol class=\"nx-register-rows\"><li><div><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Econometrics<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Steward<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/economic-development\/\">Economic Development<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Applied in<\/span><span class=\"nx-register-v\">Society and Human Development<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Data<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-data\">3 inputs<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Checks<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-checks\">3 validation steps<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Canonical page<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/econometrics\/\">STEM Commons<\/a><\/span><\/div><\/li><\/ol><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-application\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Application<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">What econometrics does here.<\/h2><p class=\"nx-lede\">Econometrics applies statistical methods to economic data to estimate relationships, test theories and forecast. It provides empirical evidence on how shocks and policies affect economic outcomes. In society and human development and information and public trust, econometric evidence estimates how disasters, pandemics and financial shocks affect output, employment and prices. It informs the economic case for <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 risk-reduction\" data-tk=\"Nexus risk vocabulary\" data-td=\"Preventing new risk, reducing existing risk and managing residual risk, all contributing to resilience.\" data-ts=\"NRS-C1\" data-tr=\"draft\">risk reduction<\/a>. The canonical description is on <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/econometrics\/\">the STEM Commons<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cols\"><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 3v18h18\"\/><path d=\"m19 9-5 5-4-4-3 3\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Poverty dynamics with panel data<\/h3><p class=\"nx-p nx-mt-1\">Panel surveys track the same households over time to estimate who moves into and out of poverty and what predicts those moves.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"8\" cy=\"8\" r=\"6\"\/><path d=\"M18.09 10.37A6 6 0 1 1 10.34 18\"\/><path d=\"M7 6h1v4\"\/><path d=\"m16.71 13.88.7.71-2.82 2.82\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Price shock incidence<\/h3><p class=\"nx-p nx-mt-1\">Household spending patterns and price data estimate how food and energy price changes affect real incomes across the distribution.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M22 12h-2.48a2 2 0 0 0-1.93 1.46l-2.35 8.36a.25.25 0 0 1-.48 0L9.24 2.18a.25.25 0 0 0-.48 0l-2.35 8.36A2 2 0 0 1 4.49 12H2\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Inequality decomposition<\/h3><p class=\"nx-p nx-mt-1\">Inequality is decomposed into differences within and between groups, such as regions or genders, to see where gaps come from.<\/p><\/article><\/div><\/div><\/div><\/section><section id=\"nx-s-3-sec\" class=\"nx-section\" data-hue=\"social\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Monitor<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Econometric model.<\/h2><p class=\"nx-lede\">The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-fk nx-cx\" data-fk=\"cx-society-method-regress\" data-cx=\"society.method-regress\" data-variant=\"section\" aria-label=\"Econometric model: illustrative console with example names and values\"><div class=\"nx-fk-head\"><div class=\"nx-fk-heading\"><h3 class=\"nx-fk-title\">Econometric model<\/h3><p class=\"nx-fk-sub\">Society and human development \u00b7 Econometrics for social outcomes \u00b7 Run R-6763<\/p><\/div><div class=\"nx-fk-actions\"><button type=\"button\" class=\"nx-fk-btn\" data-fk-act=\"menu\" aria-haspopup=\"true\" aria-expanded=\"false\" hidden><svg viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M12 4v11\"\/><path d=\"m7 10 5 5 5-5\"\/><path d=\"M5 20h14\"\/><\/svg>Export<\/button><ul class=\"nx-fk-menu\" data-fk-menu=\"true\" hidden><li><button type=\"button\" data-fk-act=\"export-png\">Image<small>PNG of the map or chart<\/small><\/button><\/li><li><button type=\"button\" data-fk-act=\"export-csv\">Data<small>CSV of the figure&#8217;s values<\/small><\/button><\/li><\/ul><\/div><\/div><div class=\"nx-cx-status\"><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>Estimates stable<\/span><span class=\"nx-cx-prod\">GCRI \u00b7 Society and Human Development<\/span><\/div><div class=\"nx-cx-grid\"><div class=\"nx-fk-panel nx-cx-p\" data-w=\"4\" data-t=\"table\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Estimates<\/h4><p class=\"nx-fk-panel-sub\">robust standard errors<\/p><\/div><\/div><div class=\"nx-fk-tablewrap\" data-fk-view=\"table:cx-society-method-regress-t0\"><table class=\"nx-fk-table\" data-fk-table=\"cx-society-method-regress-t0\" aria-label=\"Estimates\"><thead><tr><th scope=\"col\" data-col=\"c0\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c0\">Term<\/button><\/th><th scope=\"col\" data-col=\"c1\" data-num=\"true\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c1\">Estimate<\/button><\/th><th scope=\"col\" data-col=\"c2\" data-num=\"true\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c2\">Std error<\/button><\/th><th scope=\"col\" data-col=\"c3\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c3\">95 pct interval<\/button><\/th><th scope=\"col\" data-col=\"c4\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c4\">Sig.<\/button><\/th><\/tr><\/thead><tbody><tr data-fk-key=\"cx-society-method-regress:r0-0\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>People in need<\/td><td data-num=\"true\" data-sv=\"0.58\">0.58<\/td><td data-num=\"true\" data-sv=\"0.07\">0.07<\/td><td>[\u22120.2, 1.0]<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Yes<\/span><\/td><\/tr><tr data-fk-key=\"cx-society-method-regress:r0-1\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Multidimensional poverty<\/td><td data-num=\"true\" data-sv=\"-0.22\">\u22120.22<\/td><td data-num=\"true\" data-sv=\"0.08\">0.08<\/td><td>[\u22120.5, 0.9]<\/td><td><span class=\"nx-fk-pill\" data-state=\"off\"><i aria-hidden=\"true\"><\/i>No<\/span><\/td><\/tr><tr data-fk-key=\"cx-society-method-regress:r0-2\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Internally displaced people<\/td><td data-num=\"true\" data-sv=\"0.24\">0.24<\/td><td data-num=\"true\" data-sv=\"0.09\">0.09<\/td><td>[\u22120.6, 0.7]<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Yes<\/span><\/td><\/tr><tr data-fk-key=\"cx-society-method-regress:r0-3\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>School attendance<\/td><td data-num=\"true\" data-sv=\"0.14\">0.14<\/td><td data-num=\"true\" data-sv=\"0.11\">0.11<\/td><td>[\u22120.3, 0.3]<\/td><td><span class=\"nx-fk-pill\" data-state=\"off\"><i aria-hidden=\"true\"><\/i>No<\/span><\/td><\/tr><\/tbody><\/table><\/div><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"2\" data-t=\"kv\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Method card<\/h4><\/div><\/div><dl class=\"nx-fk-dl\"><div><dt>Method<\/dt><dd>Econometrics<\/dd><\/div><div><dt>Sample<\/dt><dd>3302 obs<\/dd><\/div><div><dt>Design<\/dt><dd>panel, fixed effects<\/dd><\/div><div><dt>Label<\/dt><dd><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>MODELLED<\/span><\/dd><\/div><\/dl><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"6\" data-t=\"chart\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Residuals by group<\/h4><\/div><\/div><svg class=\"nx-fk-svg\" viewBox=\"0 0 520 210\" width=\"520\" height=\"210\" role=\"img\" focusable=\"false\" preserveAspectRatio=\"xMidYMid meet\" aria-label=\"Residuals by group\" data-fk-chart=\"cx-society-method-regress-c2\" data-nx-z=\"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\"><\/svg><\/div><\/div><div class=\"nx-fk-tip\" aria-hidden=\"true\" hidden><\/div><figcaption class=\"nx-fk-cap\"><span>Econometric model: the screen&#8217;s structure, terms and states for Society and human development.<\/span><span data-honesty=\"true\">Example names and illustrative values; a design, not a record or a live system.<\/span><\/figcaption><\/figure><\/div><\/div><\/section><section id=\"nx-sec-data\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Data<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">What the method consumes.<\/h2><p class=\"nx-lede\">Datasets and records used by econometrics on this platform, with the role each plays and the label its values carry. Sources are listed in <a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/research\/sources\/\">the source register<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Data<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Data\">Panel household surveys<\/td><td data-label=\"Role\">Dynamics<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Price indices<\/td><td data-label=\"Role\">Price changes<\/td><td data-label=\"Label\"><span class=\"nx-chip\">Published statistics<\/span><\/td><\/tr><tr><td data-label=\"Data\">Income and consumption surveys<\/td><td data-label=\"Role\">Distribution<\/td><td data-label=\"Label\"><span class=\"nx-chip\">ESTIMATED<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"data\" data-nxf-kind=\"data\" data-nxf-resource=\"nexus:\/\/gcri\/G-P16\/stem\/econometrics\/#data\" data-nxf-title=\"Method record\" data-nxf-height=\"520\" hidden><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G-P16\/stem\/econometrics\/#evidence\" data-nxf-title=\"Evidence\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-audience\" class=\"nx-section\" data-hue=\"social\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and evidence<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">How econometrics for social outcomes is modelled, measured and tested.<\/h2><p class=\"nx-lede\">The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-au\" data-au-voice=\"science\" data-au-n=\"1\"><figure class=\"nx-au-c\" data-au-fig=\"system-model\"><h3 class=\"nx-h4\">System model<\/h3><p class=\"nx-p nx-au-what\">The couplings between the systems in econometrics for social outcomes: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.<\/p><div class=\"nx-au-fig\"><svg class=\"nx-au-svg\" viewBox=\"0 0 560 250\" role=\"img\" aria-label=\"Causal loop diagram of Society, Information, Communities, Economy\" focusable=\"false\"><line class=\"nx-au-ac\" x1=\"280\" y1=\"32\" x2=\"404.7\" y2=\"118\"\/><text class=\"nx-au-t nx-au-sign\" x=\"342.35\" y=\"71\" text-anchor=\"middle\">+<\/text><line class=\"nx-au-ln\" x1=\"404.7\" y1=\"118\" x2=\"280\" y2=\"204\"\/><text class=\"nx-au-t nx-au-sign\" x=\"342.35\" y=\"157\" text-anchor=\"middle\">+<\/text><line class=\"nx-au-ln\" x1=\"280\" y1=\"204\" x2=\"155.3\" y2=\"118\"\/><text class=\"nx-au-t nx-au-sign\" x=\"217.65\" y=\"157\" text-anchor=\"middle\">\u2212<\/text><line class=\"nx-au-ln\" x1=\"155.3\" y1=\"118\" x2=\"280\" y2=\"32\"\/><text class=\"nx-au-t nx-au-sign\" x=\"217.65\" y=\"71\" text-anchor=\"middle\">+<\/text><circle class=\"nx-au-nd nx-au-nd-ac\" cx=\"280.0\" cy=\"32.0\" r=\"6\"\/><text class=\"nx-au-t nx-au-lb\" x=\"280\" y=\"20\" text-anchor=\"middle\">Society<\/text><circle class=\"nx-au-nd nx-au-nd-ac\" cx=\"404.7\" cy=\"118.0\" r=\"6\"\/><text class=\"nx-au-t nx-au-lb\" x=\"416.7\" y=\"122\" text-anchor=\"start\">Information<\/text><circle class=\"nx-au-nd\" cx=\"280.0\" cy=\"204.0\" r=\"6\"\/><text class=\"nx-au-t nx-au-lb\" x=\"280\" y=\"192\" text-anchor=\"middle\">Communities<\/text><circle class=\"nx-au-nd\" cx=\"155.3\" cy=\"118.0\" r=\"6\"\/><text class=\"nx-au-t nx-au-lb\" x=\"143.3\" y=\"136\" text-anchor=\"end\">Economy<\/text><text class=\"nx-au-t nx-au-lb\" x=\"280\" y=\"114\" text-anchor=\"middle\">R  reinforcing<\/text><text class=\"nx-au-t\" x=\"280\" y=\"132\" text-anchor=\"middle\">B  balancing<\/text><\/svg><\/div><figcaption class=\"nx-caption\"><span>Causal loop diagram from the page&#8217;s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-chips nx-au-fw\" aria-label=\"Frameworks cited\"><span class=\"nx-chip\">FAIR guiding principles \u00b7 GO FAIR and FORCE11<\/span><span class=\"nx-chip\">W3C PROV \u00b7 World Wide Web Consortium<\/span><span class=\"nx-chip\">Guidance on consistent treatment of uncertainties \u00b7 IPCC<\/span><span class=\"nx-chip\">CEOS Analysis Ready Data \u00b7 Committee on Earth Observation Satellites<\/span><\/div><\/div><\/div><\/section><section id=\"nx-sec-checks\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Validation<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">How results are checked.<\/h2><p class=\"nx-lede\">Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Check<\/th><th scope=\"col\">How it is done<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Check\">Measurement error<\/td><td data-label=\"How it is done\">Analyses account for measurement error in income and consumption<\/td><\/tr><tr><td data-label=\"Check\">Robustness to specification<\/td><td data-label=\"How it is done\">Results are tested across models<\/td><\/tr><tr><td data-label=\"Check\">Attrition analysis<\/td><td data-label=\"How it is done\">Panel attrition is assessed for bias<\/td><\/tr><\/tbody><\/table><\/div><p class=\"nx-note nx-mt-3\">Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.<\/p><\/div><\/div><\/section><section id=\"nx-s-7-sec\" class=\"nx-section\" data-hue=\"social\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Process<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">How the process runs.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-pe\" id=\"nx-pe-prisma\" data-nx-pe=\"nx-pe-prisma\" data-active=\"prisma\"><div class=\"nx-pe-shell\"><p class=\"nx-pe-eb\">Process<\/p><h2 class=\"nx-pe-title\">Econometrics for social outcomes: PRISMA 2020 review reporting<\/h2><p class=\"nx-pe-cap\">PRISMA 2020 is a reporting guideline for systematic reviews; the steps follow its checklist, not a mandated sequence, and no Nexus document adopts it.<\/p><ol class=\"nx-pe-steps\"><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">01 Plan<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">01<\/span><span class=\"nx-pe-st\">Registration and protocol<\/span><span class=\"nx-pe-k\">Record \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for registration details, access to the protocol and any amendments.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">02<\/span><span class=\"nx-pe-st\">Eligibility criteria<\/span><span class=\"nx-pe-k\">Record \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for the inclusion and exclusion criteria and how studies were grouped.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">02 Find and select<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">03<\/span><span class=\"nx-pe-st\">Search: sources and strategies<\/span><span class=\"nx-pe-k\">Step \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for the information sources and the full search strategies. It does not fix which sources are used.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">04<\/span><span class=\"nx-pe-st\">Selection of studies<\/span><span class=\"nx-pe-k\">Step \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks how studies were judged eligible, including how many reviewers screened. It does not fix the number of reviewers.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">05<\/span><span class=\"nx-pe-st\">Flow diagram<\/span><span class=\"nx-pe-k\">Record<\/span><span class=\"nx-pe-sm\">The flow diagram shows the number of records found, the number of studies included and the reasons for exclusion.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">03 Analyse<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">06<\/span><span class=\"nx-pe-st\">Data collection<\/span><span class=\"nx-pe-k\">Step \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks how data were collected from reports and which data items were sought.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">07<\/span><span class=\"nx-pe-st\">Risk of bias<\/span><span class=\"nx-pe-k\">Step \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for the methods and tools used to assess risk of bias.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">08<\/span><span class=\"nx-pe-st\">Synthesis<\/span><span class=\"nx-pe-k\">Model \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for the effect measures and the synthesis methods. It does not prescribe meta-analysis.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">09<\/span><span class=\"nx-pe-st\">Certainty of evidence<\/span><span class=\"nx-pe-k\">Step \u00b7 The review team<\/span><span class=\"nx-pe-sm\">The guideline asks for the methods used to assess certainty, and reports the result per outcome. It does not name a grading scale.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">04 Report<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">10<\/span><span class=\"nx-pe-st\">Review report<\/span><span class=\"nx-pe-k\">Record<\/span><span class=\"nx-pe-sm\">The guideline helps authors report why the review was done, what they did and what they found.<\/span><\/li><\/ol><\/li><\/ol><p class=\"nx-pe-foot\"><span><a class=\"nx-link\" href=\"https:\/\/docs.therisk.global\/organization\/programme\/reports\" rel=\"noopener\">Reports<\/a><\/span><span>Outline of an externally published reporting guideline, not a Nexus process and not a record of operation. PRISMA 2020 mainly covers reviews of intervention effects. No Nexus page names it. Every programme is at service level R0.<\/span><\/p><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-connections\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connections<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Topics that rely on this method.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/poverty-and-inequality\/\"><span>Poverty and inequality<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/demographic-transitions\/\"><span>Demographic transitions<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/human-security-and-wellbeing\/\"><span>Human security and wellbeing<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/education-and-capabilities\/\"><span>Education and capabilities<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/technology-and-social-cohesion\/\"><span>Technology and social cohesion<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/urban-social-vulnerability\/\"><span>Urban social vulnerability<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/human-development\/topics\/humanitarian-risk\/\"><span>Humanitarian risk<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-stewardship\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Stewardship<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who maintains the method.<\/h2><p class=\"nx-lede\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/economic-development\/\">Economic Development<\/a> stewards econometrics for the Consortium and reviews how it is applied across platforms.<\/p><\/div><div class=\"nx-section-body\"><p class=\"nx-p\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/econometrics\/\">Canonical page: Econometrics<\/a><\/p><\/div><\/div><\/section><section id=\"nx-s-10-sec\" class=\"nx-section\" data-hue=\"social\" data-tone=\"alt\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connected<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Where this page leads across the 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