stats: jobs & cost of living theme (unemployment by age, vacancies, JOLTS, graduates, job quality, wages, price levels, housing), grad view cards, Beveridge curve; jobs collector (OECD SDMX, Big Mac index, derived series) + Eurostat/World Bank/FRED jobs series, stats-jobs.timer

deploy/stats-collector/README.md

@@ -3,33 +3,34 @@
 Host-side collector for the public [/stats](https://stanrunge.dev/stats) section. It pulls open
 statistics into the `stats` schema with `scripts/stats-fetch.ts`:
 
-| source           | timer                        | schedule (Europe/Amsterdam) | what                                                                                                                                                                                                                                                                              |
-| ---------------- | ---------------------------- | --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `cbs`            | `stats-cbs.timer`            | nightly 05:40               | CBS StatLine OData v4: checks every table's `Modified`, re-pulls changed ones, flags discontinued tables (base-year swaps)                                                                                                                                                        |
-| `eurostat`       | `stats-eurostat.timer`       | Mondays 06:20               | Eurostat JSON-stat datasets (energy prices, yields, HICP index 2015 = 100 + annual rates by ECOICOP 2 category (`prc_hicp_minr`), government finance…)                                                                                                                            |
-| `fred`           | `stats-fred.timer`           | daily 07:20                 | FRED graph CSV (Brent, TTF, Fed, Treasuries, US energy prices, indices, US CPI by category)                                                                                                                                                                                       |
-| `bis`            | `stats-bis.timer`            | daily 07:50                 | BIS central bank policy rates (monthly + daily) and long CPI series `WS_LONG_CPI` (index 2010 = 100) for the core-7 and comparison countries                                                                                                                                      |
-| `worldbank`      | `stats-worldbank.timer`      | Mondays 04:15               | World Bank WDI indicators for the compared countries                                                                                                                                                                                                                              |
-| `oecd`           | `stats-oecd.timer`           | Thursdays 06:35             | OECD Data Explorer SDMX CSV (no key): CPI index by category for Korea, Japan (ends 2021-06) and China (total + food), 10-year government bond yields                                                                                                                              |
-| `statcan`        | `stats-statcan.timer`        | daily 16:10                 | Statistics Canada WDS table 18-10-0004-01: CPI all items, food, shelter, energy, core (2002 = 100)                                                                                                                                                                                |
-| `imf`            | `stats-imf.timer`            | 1st of the month 04:05      | IMF WEO (DataMapper), stored per WEO vintage with forecast flags                                                                                                                                                                                                                  |
-| `owid`           | `stats-owid.timer`           | 2nd of the month 04:35      | Our World in Data: Maddison GDP per capita, energy dataset                                                                                                                                                                                                                        |
-| `energycharts`   | `stats-energycharts.timer`   | hourly at :19               | Energy-Charts NL day-ahead prices + cross-border flows (last 3 days; `--backfill` from 2015)                                                                                                                                                                                      |
-| `rijksfinancien` | `stats-rijksfinancien.timer` | 3rd of the month 05:05      | Rijksfinanciën budget tables, last year to next year (`--backfill` from 2015)                                                                                                                                                                                                     |
-| `ustreasury`     | `stats-ustreasury.timer`     | daily 23:25                 | US Treasury MTS receipts/outlays + Debt to the Penny (last 400 days; `--backfill` all)                                                                                                                                                                                            |
-| `usaspending`    | `stats-usaspending.timer`    | Sundays 06:10               | USAspending budgetary resources per agency and fiscal year                                                                                                                                                                                                                        |
-| `eponline`       | `stats-eponline.timer`       | 3rd of the month 05:20      | EP-Online monthly total file (RVO energy labels): homes per label for NL, Gouda and Gouda PC4s; aggregates only. Needs `EP_ONLINE_API_KEY` in `~/.config/stats/ep-online.env` (mode 600), which the runner exports for this source only                                           |
-| `elections`      | `stats-elections.timer`      | 15th of the month 04:50     | A14: Kiesraad Tweede Kamer results 2010→ (data.overheid.nl CSV + EML zips read with HTTP ranges; national, municipality, Gouda polling stations), CBS 37278 (1918–2006), MIT US presidential by state. Finished elections are skipped unless `--force`                            |
-| `parties`        | `stats-parties.timer`        | quarterly, 16th 04:40       | A15: CHES trend file + V-Party (RData via `~/.local/share/stats-py`, pyreadr) linked with Party Facts into `wo_party`/`wo_party_position`                                                                                                                                         |
-| `wikipolls`      | `stats-wikipolls.timer`      | daily 08:10                 | A16: Wikipedia poll tables (NL seats, Trump approval, Lee Jae-myung approval, KR party polls); wikitext snapshot per revision                                                                                                                                                     |
-| `gtrends`        | `stats-gtrends.timer`        | daily 21:45                 | A16: Google Trends trending-now RSS for NL, US, KR                                                                                                                                                                                                                                |
-| `gdelt`          | `stats-gdelt.timer`          | nightly 02:30               | A16: GDELT DOC timelinevol, 10 countries × 12 themes, last 30 days, ≥5.5 s between requests                                                                                                                                                                                       |
-| `eurobarometer`  | `stats-eurobarometer.timer`  | 20th of the month 05:35     | A16: Standard Eurobarometer volume A xlsx (QA3/QA4/QA5 most important issues, trust in institutions); new waves only                                                                                                                                                              |
-| `whr`            | `stats-whr.timer`            | 21st of the month 05:10     | A16: World Happiness Report Figure 2.1 (life evaluation and components, 2011→)                                                                                                                                                                                                    |
-| `cbscw`          | `stats-cbscw.timer`          | Tuesdays 05:50              | CBS Curaçao: scrapes the topic pages (cbs.cw), matches each table's file by regex, re-imports only when its sha256 changes (`stats.cw_cbs_file`); CPI from PDF (pdfjs), GDP, government finance, population since 1900, LFS, tourism from xlsx                                    |
-| `cwintl`         | `stats-cwintl.timer`         | Wednesdays 05:50            | Curaçao from international APIs: ILOSTAT SDMX (labour, with retries), OWID grapher CSVs (population, life expectancy, median age, CO₂), UN SDG area 531, UN Comtrade public preview reporter 531. EU trade with Curaçao (Eurostat `ext_lt_maineu`) runs with the `eurostat` timer |
-| –                | –                            | manual                      | CBCS (centralbank.cw) blocks scripts with a Cloudflare challenge: download the BoP xlsx by hand and load it into `stats.cw_cbcs_bop` (period, item, mln_ang)                                                                                                                      |
-| –                | –                            | manual                      | China CPI by category beyond food (NBS, data.stats.gov.cn) has no stable no-key API: not collected. Japan e-Stat needs an app id: skipped                                                                                                                                         |
+| source           | timer                        | schedule (Europe/Amsterdam) | what                                                                                                                                                                                                                                                                                                                                                                                                                                          |
+| ---------------- | ---------------------------- | --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `cbs`            | `stats-cbs.timer`            | nightly 05:40               | CBS StatLine OData v4: checks every table's `Modified`, re-pulls changed ones, flags discontinued tables (base-year swaps)                                                                                                                                                                                                                                                                                                                    |
+| `eurostat`       | `stats-eurostat.timer`       | Mondays 06:20               | Eurostat JSON-stat datasets (energy prices, yields, HICP index 2015 = 100 + annual rates by ECOICOP 2 category (`prc_hicp_minr`), government finance…)                                                                                                                                                                                                                                                                                        |
+| `fred`           | `stats-fred.timer`           | daily 07:20                 | FRED graph CSV (Brent, TTF, Fed, Treasuries, US energy prices, indices, US CPI by category)                                                                                                                                                                                                                                                                                                                                                   |
+| `bis`            | `stats-bis.timer`            | daily 07:50                 | BIS central bank policy rates (monthly + daily) and long CPI series `WS_LONG_CPI` (index 2010 = 100) for the core-7 and comparison countries                                                                                                                                                                                                                                                                                                  |
+| `worldbank`      | `stats-worldbank.timer`      | Mondays 04:15               | World Bank WDI indicators for the compared countries                                                                                                                                                                                                                                                                                                                                                                                          |
+| `oecd`           | `stats-oecd.timer`           | Thursdays 06:35             | OECD Data Explorer SDMX CSV (no key): CPI index by category for Korea, Japan (ends 2021-06) and China (total + food), 10-year government bond yields                                                                                                                                                                                                                                                                                          |
+| `statcan`        | `stats-statcan.timer`        | daily 16:10                 | Statistics Canada WDS table 18-10-0004-01: CPI all items, food, shelter, energy, core (2002 = 100)                                                                                                                                                                                                                                                                                                                                            |
+| `imf`            | `stats-imf.timer`            | 1st of the month 04:05      | IMF WEO (DataMapper), stored per WEO vintage with forecast flags                                                                                                                                                                                                                                                                                                                                                                              |
+| `owid`           | `stats-owid.timer`           | 2nd of the month 04:35      | Our World in Data: Maddison GDP per capita, energy dataset                                                                                                                                                                                                                                                                                                                                                                                    |
+| `energycharts`   | `stats-energycharts.timer`   | hourly at :19               | Energy-Charts NL day-ahead prices + cross-border flows (last 3 days; `--backfill` from 2015)                                                                                                                                                                                                                                                                                                                                                  |
+| `rijksfinancien` | `stats-rijksfinancien.timer` | 3rd of the month 05:05      | Rijksfinanciën budget tables, last year to next year (`--backfill` from 2015)                                                                                                                                                                                                                                                                                                                                                                 |
+| `ustreasury`     | `stats-ustreasury.timer`     | daily 23:25                 | US Treasury MTS receipts/outlays + Debt to the Penny (last 400 days; `--backfill` all)                                                                                                                                                                                                                                                                                                                                                        |
+| `usaspending`    | `stats-usaspending.timer`    | Sundays 06:10               | USAspending budgetary resources per agency and fiscal year                                                                                                                                                                                                                                                                                                                                                                                    |
+| `eponline`       | `stats-eponline.timer`       | 3rd of the month 05:20      | EP-Online monthly total file (RVO energy labels): homes per label for NL, Gouda and Gouda PC4s; aggregates only. Needs `EP_ONLINE_API_KEY` in `~/.config/stats/ep-online.env` (mode 600), which the runner exports for this source only                                                                                                                                                                                                       |
+| `elections`      | `stats-elections.timer`      | 15th of the month 04:50     | A14: Kiesraad Tweede Kamer results 2010→ (data.overheid.nl CSV + EML zips read with HTTP ranges; national, municipality, Gouda polling stations), CBS 37278 (1918–2006), MIT US presidential by state. Finished elections are skipped unless `--force`                                                                                                                                                                                        |
+| `parties`        | `stats-parties.timer`        | quarterly, 16th 04:40       | A15: CHES trend file + V-Party (RData via `~/.local/share/stats-py`, pyreadr) linked with Party Facts into `wo_party`/`wo_party_position`                                                                                                                                                                                                                                                                                                     |
+| `wikipolls`      | `stats-wikipolls.timer`      | daily 08:10                 | A16: Wikipedia poll tables (NL seats, Trump approval, Lee Jae-myung approval, KR party polls); wikitext snapshot per revision                                                                                                                                                                                                                                                                                                                 |
+| `gtrends`        | `stats-gtrends.timer`        | daily 21:45                 | A16: Google Trends trending-now RSS for NL, US, KR                                                                                                                                                                                                                                                                                                                                                                                            |
+| `gdelt`          | `stats-gdelt.timer`          | nightly 02:30               | A16: GDELT DOC timelinevol, 10 countries × 12 themes, last 30 days, ≥5.5 s between requests                                                                                                                                                                                                                                                                                                                                                   |
+| `eurobarometer`  | `stats-eurobarometer.timer`  | 20th of the month 05:35     | A16: Standard Eurobarometer volume A xlsx (QA3/QA4/QA5 most important issues, trust in institutions); new waves only                                                                                                                                                                                                                                                                                                                          |
+| `whr`            | `stats-whr.timer`            | 21st of the month 05:10     | A16: World Happiness Report Figure 2.1 (life evaluation and components, 2011→)                                                                                                                                                                                                                                                                                                                                                                |
+| `cbscw`          | `stats-cbscw.timer`          | Tuesdays 05:50              | CBS Curaçao: scrapes the topic pages (cbs.cw), matches each table's file by regex, re-imports only when its sha256 changes (`stats.cw_cbs_file`); CPI from PDF (pdfjs), GDP, government finance, population since 1900, LFS, tourism from xlsx                                                                                                                                                                                                |
+| `cwintl`         | `stats-cwintl.timer`         | Wednesdays 05:50            | Curaçao from international APIs: ILOSTAT SDMX (labour, with retries), OWID grapher CSVs (population, life expectancy, median age, CO₂), UN SDG area 531, UN Comtrade public preview reporter 531. EU trade with Curaçao (Eurostat `ext_lt_maineu`) runs with the `eurostat` timer                                                                                                                                                             |
+| `jobs`           | `stats-jobs.timer`           | Thursdays 06:55             | Jobs & cost of living: OECD SDMX (average/minimum wages USD PPP, hours, 50+ h weeks, temporary/part-time shares, long-term unemployment, monthly youth unemployment, EAG graduate employment + earnings premium, house price-to-income/-rent, comparative price levels USA = 100), Economist Big Mac index (CC BY 4.0), derived US openings per unemployed (run after `fred`). Eurostat/World Bank/FRED jobs series run with their own timers |
+| –                | –                            | manual                      | CBCS (centralbank.cw) blocks scripts with a Cloudflare challenge: download the BoP xlsx by hand and load it into `stats.cw_cbcs_bop` (period, item, mln_ang)                                                                                                                                                                                                                                                                                  |
+| –                | –                            | manual                      | China CPI by category beyond food (NBS, data.stats.gov.cn) has no stable no-key API: not collected. Japan e-Stat needs an app id: skipped                                                                                                                                                                                                                                                                                                     |
 
 Each timer starts `stats-collector@<source>.service`, which runs
 `~/.local/bin/stats-collector-run.sh <source>`: it updates a detached checkout of `origin/main`

deploy/stats-collector/stats-jobs.timer

@@ -0,0 +1,11 @@
+[Unit]
+Description=/stats collector: jobs & cost of living (OECD wages/hours/LFS/EAG/house prices/price levels, Big Mac index, JOLTS ratio), Thursdays
+
+[Timer]
+OnCalendar=Thu *-*-* 06:55:00 Europe/Amsterdam
+RandomizedDelaySec=10min
+Persistent=true
+Unit=stats-collector@jobs.service
+
+[Install]
+WantedBy=timers.target

scripts/stats-fetch.ts

@@ -17,6 +17,7 @@
 //   bun scripts/stats-fetch.ts elections [--force] [--only=kiesraad,cbs,mit]   A14
 //   bun scripts/stats-fetch.ts parties            CHES + V-Party + Party Facts (A15)
 //   bun scripts/stats-fetch.ts wikipolls|eurobarometer [--force]|whr|gtrends|gdelt   A16
+//   bun scripts/stats-fetch.ts jobs [--only=wages,quality,finding,grads,housing,prices,bigmac,jolts,pricelevel]
 //   bun scripts/stats-fetch.ts normalise-cbs     rebuild CBS chart series from the raw rows
 import { ensureMeta, sql } from './stats/common';
 import { cbs, normaliseCbs } from './stats/cbs';
@@ -43,6 +44,7 @@ import { whr } from './stats/whr';
 import { gtrends } from './stats/gtrends';
 import { gdelt } from './stats/gdelt';
 import { history } from './stats/history';
+import { jobs } from './stats/jobs';
 
 const [source, ...args] = process.argv.slice(2);
 const flag = (name: string) => args.includes(`--${name}`);
@@ -124,12 +126,15 @@ try {
 		case 'history':
 			await history({ only: value('only'), job });
 			break;
+		case 'jobs':
+			await jobs({ only: value('only'), job });
+			break;
 		case 'gdelt':
 			await gdelt({ job, timespan: value('timespan') });
 			break;
 		default:
 			throw new Error(
-				`Unknown source "${source}" (cbs, eurostat, fred, bis, oecd, statcan, worldbank, imf, owid, energycharts, rijksfinancien, ustreasury, usaspending, eponline, cbscw, cwintl, elections, parties, wikipolls, eurobarometer, whr, gtrends, gdelt, history, normalise-cbs)`
+				`Unknown source "${source}" (cbs, eurostat, fred, bis, oecd, statcan, worldbank, imf, owid, energycharts, rijksfinancien, ustreasury, usaspending, eponline, cbscw, cwintl, elections, parties, wikipolls, eurobarometer, whr, gtrends, gdelt, history, jobs, normalise-cbs)`
 			);
 	}
 } finally {

scripts/stats/common.ts

@@ -382,6 +382,14 @@ export const SOURCES = [
 		key_required: false,
 		attribution: 'Source: Pew Research Center (2025), via Our World in Data'
 	},
+	{
+		source_id: 'economist',
+		name: 'The Economist Big Mac index',
+		base_url: 'https://github.com/TheEconomist/big-mac-data',
+		licence: 'CC BY 4.0',
+		key_required: false,
+		attribution: 'Source: The Economist, Big Mac index (CC BY 4.0)'
+	},
 	{
 		source_id: 'history',
 		name: 'Curated history and culture notes',
@@ -397,6 +405,7 @@ export const REGIONS: { region_code: string; name: string; kind: string; parent:
 		{ region_code: 'WLD', name: 'World', kind: 'aggregate', parent: null },
 		{ region_code: 'EU27', name: 'European Union (27)', kind: 'aggregate', parent: 'WLD' },
 		{ region_code: 'EA', name: 'Euro area', kind: 'aggregate', parent: 'EU27' },
+		{ region_code: 'OECD', name: 'OECD members', kind: 'aggregate', parent: 'WLD' },
 		{ region_code: 'NLD', name: 'Netherlands', kind: 'country', parent: 'EU27' },
 		{ region_code: 'USA', name: 'United States', kind: 'country', parent: 'WLD' },
 		{ region_code: 'KOR', name: 'South Korea', kind: 'country', parent: 'WLD' },

scripts/stats/eurostat.ts

@@ -129,7 +129,103 @@ export const EUROSTAT_DATASETS: Dataset[] = [
 		theme: 'economy',
 		params: { unit: ['CP_MEUR', 'CLV_PCH_PRE'], na_item: 'B1GQ' }
 	},
-	{ code: 'demo_pjan', theme: 'countries', params: { sex: 'T', age: 'TOTAL', unit: 'NR' } }
+	{ code: 'demo_pjan', theme: 'countries', params: { sex: 'T', age: 'TOTAL', unit: 'NR' } },
+	// ── Jobs & cost of living (/stats/<place>/jobs) ──
+	{
+		code: 'une_rt_m',
+		theme: 'jobs',
+		params: { s_adj: 'SA', age: ['TOTAL', 'Y_LT25', 'Y25-74'], unit: 'PC_ACT', sex: 'T' },
+		geos: [...EU_GEOS, 'US', 'JP']
+	},
+	{
+		code: 'lfsa_urgan',
+		theme: 'jobs',
+		params: { unit: 'PC', sex: 'T', age: ['Y15-24', 'Y25-29', 'Y15-74'], citizen: 'TOTAL' }
+	},
+	{
+		code: 'jvs_q_nace2',
+		theme: 'jobs',
+		params: { s_adj: 'NSA', nace_r2: 'B-S', sizeclas: 'TOTAL', indic_em: 'JVR' }
+	},
+	{
+		// Employment rate of recent graduates (left education 1–3 years ago), 20–34.
+		code: 'edat_lfse_24',
+		theme: 'jobs',
+		params: { duration: 'Y1-3', isced11: ['ED3-8', 'ED5-8'], age: 'Y20-34', sex: 'T', unit: 'PC' }
+	},
+	{
+		// NEET rate: not employed, not in education or training.
+		code: 'edat_lfse_20',
+		theme: 'jobs',
+		params: {
+			sex: 'T',
+			age: ['Y15-29', 'Y15-24'],
+			training: 'NO_FE_NO_NFE',
+			wstatus: 'NEMP',
+			unit: 'PC'
+		}
+	},
+	{
+		code: 'lfsa_etpgan',
+		theme: 'jobs',
+		params: { unit: 'PC', sex: 'T', age: ['Y15-64', 'Y15-24', 'Y25-34'], citizen: 'TOTAL' }
+	},
+	{
+		code: 'lfsa_eppga',
+		theme: 'jobs',
+		params: { unit: 'PC', sex: 'T', age: ['Y15-64', 'Y15-24'] }
+	},
+	{
+		code: 'lfsa_ewhan2',
+		theme: 'jobs',
+		params: {
+			nace_r2: 'TOTAL',
+			wstatus: 'EMP',
+			worktime: ['TOTAL', 'FT'],
+			age: 'Y15-64',
+			sex: 'T',
+			unit: 'HR'
+		}
+	},
+	{
+		code: 'earn_mw_cur',
+		theme: 'jobs',
+		params: { currency: ['EUR', 'PPS'] },
+		geos: [...EU_GEOS, 'US']
+	},
+	{
+		// Price level indices (EU27 = 100): everything, food, alcohol & tobacco, housing, transport, restaurants.
+		code: 'prc_ppp_ind',
+		theme: 'jobs',
+		params: {
+			na_item: 'PLI_EU27_2020',
+			ppp_cat: ['GDP', 'A01', 'A0101', 'A0104', 'A0107', 'A0111']
+		},
+		geos: [...EU_GEOS, 'US', 'JP']
+	},
+	{
+		// Housing cost overburden: households spending > 40 % of disposable income on housing.
+		code: 'ilc_lvho07a',
+		theme: 'jobs',
+		params: { unit: 'PC', rskpovth: 'TOTAL', age: ['TOTAL', 'Y18-24', 'Y25-29'], sex: 'T' }
+	},
+	{
+		code: 'une_ltu_a',
+		theme: 'jobs',
+		params: { indic_em: 'LTU', age: 'Y15-74', sex: 'T', unit: 'PC_UNE' }
+	},
+	{
+		// Share of young adults still living with their parents.
+		code: 'ilc_lvps08',
+		theme: 'jobs',
+		params: { age: ['Y25-29', 'Y25-34'], sex: 'T', unit: 'PC' }
+	},
+	{
+		// Structure of earnings survey (every 4 years): mean and median earnings, firms with 10+ staff.
+		code: 'earn_ses_pub2s',
+		theme: 'jobs',
+		params: { sizeclas: 'GE10', sex: 'T', unit: ['EUR', 'PPS'] }
+	}
 ];
 
 type JsonStat = {

scripts/stats/fred.ts

@@ -185,6 +185,103 @@ export const FRED_SERIES: Fred[] = [
 		freq: 'Q',
 		region: 'USA',
 		theme: 'economy'
+	},
+	// Jobs & cost of living
+	{
+		id: 'LNS14024887',
+		title: 'US unemployment rate, 16–24',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'LNS14000036',
+		title: 'US unemployment rate, 20–24',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'JTSJOL',
+		title: 'US job openings (JOLTS)',
+		unit: 'Thousands',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'JTSJOR',
+		title: 'US job openings rate (JOLTS)',
+		unit: '% of jobs + openings',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'JTSHIR',
+		title: 'US hires rate (JOLTS)',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'JTSQUR',
+		title: 'US quits rate (JOLTS)',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'UNEMPLOY',
+		title: 'US unemployed persons',
+		unit: 'Thousands',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'LNS13025703',
+		title: 'US long-term unemployed (27+ weeks), share of unemployed',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'CGBD2534',
+		title: 'US unemployment rate, bachelor’s degree, 25–34',
+		unit: '%',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'LES1252881600Q',
+		title: 'US median usual weekly real earnings',
+		unit: '1982–84 CPI-adjusted USD',
+		freq: 'Q',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'LES1252881500Q',
+		title: 'US median usual weekly earnings, full-time',
+		unit: 'USD',
+		freq: 'Q',
+		region: 'USA',
+		theme: 'jobs'
+	},
+	{
+		id: 'FEDMINNFRWG',
+		title: 'US federal minimum wage',
+		unit: 'USD per hour',
+		freq: 'M',
+		region: 'USA',
+		theme: 'jobs'
 	}
 ];
 

scripts/stats/jobs.ts

@@ -0,0 +1,498 @@
+// Jobs & cost of living (/stats/<place>/jobs), the parts that are not a plain Eurostat / World
+// Bank / FRED series list:
+//   - OECD Data Explorer SDMX (no key): average and minimum wages in USD PPP, hours, long hours,
+//     temporary-job shares, long-term unemployment, graduate employment and the tertiary
+//     earnings premium (Education at a Glance), house price-to-income / price-to-rent, monthly
+//     youth unemployment and comparative price levels (USA = 100). Series `oecd:jobs:<name>:<ISO3>`.
+//   - Derived from those: real wage growth (yearly change of the constant-price average wage) and
+//     an approximate median full-time wage (real minimum wage ÷ minimum-to-median ratio),
+//     `jobs:realwagegrowth:<ISO3>` and `jobs:medianwage:<ISO3>`.
+//   - The Economist Big Mac index (GitHub CSV, CC BY 4.0): `economist:bigmac:<ISO3>:<measure>`.
+//   - Derived from FRED: US job openings per unemployed person (JTSJOL / UNEMPLOY).
+//   - Derived from World Bank: price level of private consumption, USA = 100
+//     (PA.NUS.PRVT.PP ÷ PA.NUS.FCRF; WDI dropped PA.NUS.PPPC.RF), `jobs:pricelevel:<ISO3>`.
+// Numbeo is not used: it has no free API and its terms forbid scraping.
+import {
+	getText,
+	http,
+	log,
+	parsePeriod,
+	REGIONS,
+	run,
+	sql,
+	writeSeries,
+	type ObsRow,
+	type SeriesRow
+} from './common';
+
+const OECD = 'https://sdmx.oecd.org/public/rest/data';
+const CSV = { accept: 'application/vnd.sdmx.data+csv; charset=utf-8' };
+/** Countries and aggregates asked from OECD; non-members simply come back empty. */
+const AREAS = [
+	'NLD',
+	'USA',
+	'KOR',
+	'JPN',
+	'CAN',
+	'CHN',
+	'DEU',
+	'FRA',
+	'BEL',
+	'GBR',
+	'IND',
+	'BRA',
+	'EU27_2020',
+	'EA20',
+	'OECD'
+];
+const AREA_REGION: Record<string, string> = { EU27_2020: 'EU27', EA20: 'EA', OECD: 'OECD' };
+const areaRegion = (a: string) => AREA_REGION[a] ?? a;
+
+type OecdSpec = {
+	job: string;
+	/** Dataflow `agency,id,version`. */
+	flow: string;
+	/** Key after the area, e.g. `.WG.USD_PPP.A.Q.MEAN._Z` (the area list is prefixed). */
+	key: string;
+	start?: string;
+	/** Row → our series name (or null to skip). */
+	pick: (r: Record<string, string>) => string | null;
+	meta: Record<string, { title: string; unit: string }>;
+};
+
+const SPECS: OecdSpec[] = [
+	{
+		job: 'wages',
+		flow: 'OECD.ELS.SAE,DSD_EARNINGS@AV_AN_WAGE,1.0',
+		key: '.WG.USD_PPP.A.Q.MEAN._Z',
+		pick: () => 'avwage',
+		meta: {
+			avwage: {
+				title: 'Average annual wage, full-time equivalent (constant prices, USD PPP)',
+				unit: 'USD PPP'
+			}
+		}
+	},
+	{
+		job: 'wages',
+		flow: 'OECD.ELS.SAE,DSD_EARNINGS@RMW,1.0',
+		key: '.SM_WG.USD_PPP.A+H.Q._Z._Z',
+		pick: (r) => (r.PAY_PERIOD === 'A' ? 'minwage' : r.PAY_PERIOD === 'H' ? 'minwage_h' : null),
+		meta: {
+			minwage: { title: 'Real statutory minimum wage, yearly (USD PPP)', unit: 'USD PPP' },
+			minwage_h: { title: 'Real statutory minimum wage, hourly (USD PPP)', unit: 'USD PPP / h' }
+		}
+	},
+	{
+		job: 'wages',
+		flow: 'OECD.ELS.SAE,DSD_EARNINGS@MIN2AVE,1.0',
+		key: '.MR_WG_FT.PT_WG_A_SAL_FT._Z._Z.MEDIAN._Z',
+		pick: () => 'min2median',
+		meta: {
+			min2median: {
+				title: 'Minimum wage relative to the median full-time wage',
+				unit: '% of median'
+			}
+		}
+	},
+	{
+		job: 'quality',
+		flow: 'OECD.ELS.SAE,DSD_HW@DF_AVG_ANN_HRS_WKD,1.0',
+		key: '.HW.H_Y_PS._Z._Z.EMP.A.ACTUAL._T._Z.MEAN._Z._T',
+		pick: () => 'hours',
+		meta: { hours: { title: 'Average annual hours actually worked per worker', unit: 'hours' } }
+	},
+	{
+		job: 'quality',
+		flow: 'OECD.ELS.SAE,DSD_HW@DF_EMP_LNG_USL_WK_HRS,1.0',
+		key: '.SH_EMP_H.PT_WR_SEX_AGE_EMP_ST._T.Y15T64.EMP.W.USUAL._T._Z.OBS.H_GE50.MAIN',
+		pick: () => 'longhours',
+		meta: {
+			longhours: {
+				title: 'Employees and self-employed usually working 50+ hours a week',
+				unit: '% of employed'
+			}
+		}
+	},
+	{
+		job: 'quality',
+		flow: 'OECD.ELS.SAE,DSD_TEMP@DF_TEMP_I,1.0',
+		key: '.EMP_TEMP.PT_POP_SUB._T._T+Y15T24.ICSE93_1.A',
+		pick: (r) => (r.AGE === '_T' ? 'temp' : 'temp_youth'),
+		meta: {
+			temp: { title: 'Temporary employment, share of employees', unit: '% of employees' },
+			temp_youth: {
+				title: 'Temporary employment, share of employees aged 15–24',
+				unit: '% of employees'
+			}
+		}
+	},
+	{
+		job: 'finding',
+		flow: 'OECD.ELS.SAE,DSD_DUR@DF_DUR_I,1.0',
+		key: '.UNEMP.PT_POP_SUB._T._T.Y_GE1.A',
+		pick: () => 'ltu',
+		meta: {
+			ltu: { title: 'Long-term unemployment (1 year or more)', unit: '% of unemployed' }
+		}
+	},
+	{
+		job: 'finding',
+		flow: 'OECD.SDD.TPS,DSD_LFS@DF_IALFS_UNE_M,1.0',
+		key: '.UNE_LF_M.PT_LF_SUB._Z.Y._T.Y15T24+Y_GE25+Y_GE15._Z.M',
+		start: '1990-01',
+		pick: (r) =>
+			r.AGE === 'Y15T24'
+				? 'unemp_youth'
+				: r.AGE === 'Y_GE25'
+					? 'unemp_25plus'
+					: r.AGE === 'Y_GE15'
+						? 'unemp'
+						: null,
+		meta: {
+			unemp: { title: 'Unemployment rate, monthly (OECD harmonised)', unit: '%' },
+			unemp_youth: { title: 'Youth unemployment rate 15–24, monthly', unit: '%' },
+			unemp_25plus: { title: 'Unemployment rate 25+, monthly', unit: '%' }
+		}
+	},
+	{
+		job: 'grads',
+		flow: 'OECD.EDU.IMEP,DSD_EAG_LSO_EA@DF_LSO_NEAC_EMP,1.0',
+		key: '._T.Y25T34.ISCED11A_5T8._T.EMPLOYMENT._Z._T._Z.ED_NED.EMP._Z.PT_POP_SUB.OBS._Z.NEAC.A',
+		pick: () => 'grademp',
+		meta: {
+			grademp: {
+				title: 'Employment rate of tertiary-educated 25–34 year-olds',
+				unit: '% of age group'
+			}
+		}
+	},
+	{
+		job: 'grads',
+		flow: 'OECD.EDU.IMEP,DSD_EAG_LSO_EA@DF_LSO_EARN_REL_UPPER,1.0',
+		key: '._T.Y25T34.ISCED11A_5T8._T.EARN_RELATIVE._Z._T._Z.ED_NED.EMP._Z.PT_EARN_WR_ISCED11A_3.OBS.FT.EARNINGS.A',
+		pick: () => 'premium',
+		meta: {
+			premium: {
+				title:
+					'Earnings of tertiary-educated 25–34 year-olds (full-time), relative to upper secondary',
+				unit: 'upper secondary = 100'
+			}
+		}
+	},
+	{
+		job: 'housing',
+		flow: 'OECD.ECO.MPD,DSD_AN_HOUSE_PRICES@DF_HOUSE_PRICES,1.0',
+		key: '.Q.HPI_YDH_AVG+HPI_RPI_AVG+RPI.',
+		start: '1970-Q1',
+		pick: (r) =>
+			r.MEASURE === 'HPI_YDH_AVG'
+				? 'ptoi'
+				: r.MEASURE === 'HPI_RPI_AVG'
+					? 'ptor'
+					: r.MEASURE === 'RPI'
+						? 'rent'
+						: null,
+		meta: {
+			ptoi: {
+				title: 'House price-to-income ratio, vs its long-term average',
+				unit: 'long-term avg = 100'
+			},
+			ptor: {
+				title: 'House price-to-rent ratio, vs its long-term average',
+				unit: 'long-term avg = 100'
+			},
+			rent: { title: 'Rent price index', unit: 'Index 2015=100' }
+		}
+	},
+	{
+		job: 'prices',
+		flow: 'OECD.SDD.TPS,DSD_PPP_M@DF_PP_CPL_M,1.0',
+		key: '.M.CPL.IX..USA',
+		start: '2015-01',
+		pick: (r) => (r.COUNTERPART_AREA === 'USA' ? 'cpl' : null),
+		meta: {
+			cpl: {
+				title: 'Comparative price level of final consumption (USA = 100)',
+				unit: 'USA = 100'
+			}
+		}
+	}
+];
+
+function parseCsv(text: string): Record<string, string>[] {
+	const lines = text.trim().split(/\r?\n/);
+	const head = lines[0].split(',');
+	return lines.slice(1).map((l) => Object.fromEntries(l.split(',').map((v, i) => [head[i], v])));
+}
+
+const sleep = (ms: number) => new Promise((r) => setTimeout(r, ms));
+
+async function pullOecd(spec: OecdSpec): Promise<number> {
+	const url = `${OECD}/${spec.flow}/${AREAS.join('+')}${spec.key}?startPeriod=${spec.start ?? '1990'}`;
+	const res = await http(url, { headers: CSV });
+	const rows = parseCsv(await res.text());
+	const series = new Map<string, SeriesRow>();
+	const obs: ObsRow[] = [];
+	for (const r of rows) {
+		const name = spec.pick(r);
+		if (!name || r.OBS_VALUE === '' || r.OBS_VALUE == null) continue;
+		const value = Number(r.OBS_VALUE);
+		const p = parsePeriod(r.TIME_PERIOD ?? '');
+		if (!p || !Number.isFinite(value)) continue;
+		const region = areaRegion(r.REF_AREA);
+		const id = `oecd:jobs:${name}:${region}`;
+		if (!series.has(id)) {
+			const m = spec.meta[name];
+			series.set(id, {
+				series_id: id,
+				source_id: 'oecd',
+				source_code: `${spec.flow}/${r.REF_AREA}${spec.key}`,
+				title: m.title,
+				unit: m.unit,
+				freq: p.freq,
+				region_code: region,
+				theme: 'jobs',
+				meta: { url: 'https://data-explorer.oecd.org/', flow: spec.flow }
+			});
+		}
+		obs.push({ series_id: id, period: p.date, value, status: r.OBS_STATUS || null });
+	}
+	if (!obs.length) throw new Error(`no rows for ${spec.flow}`);
+	// One row per (series, period): SDMX can repeat a period with a different status.
+	const seen = new Set<string>();
+	const unique = obs.filter((o) => {
+		const k = `${o.series_id}|${o.period}`;
+		if (seen.has(k)) return false;
+		seen.add(k);
+		return true;
+	});
+	await writeSeries([...series.values()], unique);
+	log(`jobs oecd ${spec.flow.split(',')[1]}: ${unique.length} obs, ${series.size} series`);
+	return unique.length;
+}
+
+// ── Big Mac index ─────────────────────────────────────────────────────────────────────────
+const BIGMAC =
+	'https://raw.githubusercontent.com/TheEconomist/big-mac-data/master/output-data/big-mac-full-index.csv';
+const BIGMAC_REGION: Record<string, string> = { EUZ: 'EA' };
+
+async function bigmac(): Promise<number> {
+	const rows = parseCsv(await getText(BIGMAC));
+	const known = new Set(REGIONS.map((r) => r.region_code));
+	const measures: Record<string, { title: string; unit: string }> = {
+		dollar_price: { title: 'Big Mac price in US dollars', unit: 'US$' },
+		USD_raw: {
+			title: 'Big Mac index: local currency vs the US dollar (raw)',
+			unit: '% over/under-valued'
+		}
+	};
+	const series = new Map<string, SeriesRow>();
+	const obs: ObsRow[] = [];
+	for (const r of rows) {
+		const region = BIGMAC_REGION[r.iso_a3] ?? r.iso_a3;
+		if (!known.has(region) || !/^\d{4}-\d{2}-\d{2}$/.test(r.date)) continue;
+		for (const [m, meta] of Object.entries(measures)) {
+			const raw = Number(r[m]);
+			if (r[m] === '' || !Number.isFinite(raw)) continue;
+			const id = `economist:bigmac:${region}:${m}`;
+			if (!series.has(id))
+				series.set(id, {
+					series_id: id,
+					source_id: 'economist',
+					source_code: `big-mac-full-index/${r.iso_a3}/${m}`,
+					title: meta.title,
+					unit: meta.unit,
+					freq: 'S',
+					region_code: region,
+					theme: 'jobs',
+					meta: { url: 'https://github.com/TheEconomist/big-mac-data' }
+				});
+			obs.push({
+				series_id: id,
+				period: r.date,
+				value: m === 'USD_raw' ? Math.round(raw * 1000) / 10 : raw,
+				status: null
+			});
+		}
+	}
+	if (!obs.length) throw new Error('Big Mac CSV: no rows');
+	await writeSeries([...series.values()], obs);
+	log(`jobs bigmac: ${obs.length} obs, ${series.size} series`);
+	return obs.length;
+}
+
+// ── Derived: US openings per unemployed person ─────────────────────────────────────────────
+async function joltsRatio(): Promise<number> {
+	const rows = await sql<{ period: string; value: number }[]>`
+		select o.period::text as period, round((o.value / u.value)::numeric, 3)::float8 as value
+		from stats.obs o join stats.obs u on u.period = o.period and u.series_id = 'fred:UNEMPLOY'
+		where o.series_id = 'fred:JTSJOL' and u.value > 0 and o.value is not null
+		order by o.period`;
+	if (!rows.length) throw new Error('JOLTS ratio: run the fred collector first (JTSJOL, UNEMPLOY)');
+	const id = 'jobs:openings_per_unemployed:USA';
+	await writeSeries(
+		[
+			{
+				series_id: id,
+				source_id: 'fred',
+				source_code: 'JTSJOL/UNEMPLOY',
+				title: 'US job openings per unemployed person (JOLTS openings ÷ unemployed)',
+				unit: 'openings per unemployed',
+				freq: 'M',
+				region_code: 'USA',
+				theme: 'jobs',
+				meta: { url: 'https://fred.stlouisfed.org/series/JTSJOL', derived: 'JTSJOL / UNEMPLOY' }
+			}
+		],
+		rows.map((r) => ({ series_id: id, period: r.period, value: r.value, status: null }))
+	);
+	return rows.length;
+}
+
+// ── Derived: real wage growth and an approximate median wage ────────────────────────────────
+async function wageDerived(): Promise<number> {
+	const growth = await sql<{ region: string; period: string; value: number }[]>`
+		select s.region_code as region, o.period::text as period,
+			round((100 * (o.value / p.value - 1))::numeric, 2)::float8 as value
+		from stats.series s
+		join stats.obs o on o.series_id = s.series_id
+		join stats.obs p on p.series_id = s.series_id and p.period = o.period - interval '1 year'
+		where s.series_id like 'oecd:jobs:avwage:%' and p.value > 0 and o.value is not null
+		order by 1, 2`;
+	const median = await sql<{ region: string; period: string; value: number }[]>`
+		select s.region_code as region, o.period::text as period,
+			round((o.value / (r.value / 100))::numeric, 0)::float8 as value
+		from stats.series s
+		join stats.obs o on o.series_id = s.series_id
+		join stats.obs r on r.series_id = 'oecd:jobs:min2median:' || s.region_code and r.period = o.period
+		where s.series_id like 'oecd:jobs:minwage:%' and r.value > 0 and o.value is not null
+		order by 1, 2`;
+	const write = async (
+		rows: { region: string; period: string; value: number }[],
+		name: string,
+		title: string,
+		unit: string,
+		derived: string
+	) => {
+		const regions = [...new Set(rows.map((r) => r.region))];
+		await writeSeries(
+			regions.map((region) => ({
+				series_id: `jobs:${name}:${region}`,
+				source_id: 'oecd',
+				source_code: derived,
+				title,
+				unit,
+				freq: 'A',
+				region_code: region,
+				theme: 'jobs',
+				meta: { url: 'https://data-explorer.oecd.org/', derived }
+			})),
+			rows.map((r) => ({
+				series_id: `jobs:${name}:${r.region}`,
+				period: r.period,
+				value: r.value,
+				status: null
+			}))
+		);
+		return rows.length;
+	};
+	if (!growth.length) throw new Error('wage derived: run the wages job first');
+	return (
+		(await write(
+			growth,
+			'realwagegrowth',
+			'Real average wage growth (constant prices)',
+			'%',
+			'yoy(AV_AN_WAGE, constant prices)'
+		)) +
+		(await write(
+			median,
+			'medianwage',
+			'Median full-time wage, approx. (real minimum wage ÷ minimum-to-median ratio)',
+			'USD PPP',
+			'RMW / MIN2AVE(median)'
+		))
+	);
+}
+
+// ── Derived: price level (USA = 100) from the World Bank PPP and exchange rate ─────────────
+async function priceLevel(): Promise<number> {
+	const rows = await sql<{ region: string; period: string; value: number }[]>`
+		select p.region_code as region, o.period::text as period,
+			round((100 * o.value / x.value)::numeric, 1)::float8 as value
+		from stats.series p
+		join stats.obs o on o.series_id = p.series_id
+		join stats.obs x on x.period = o.period and x.series_id = 'wb:PA.NUS.FCRF:' || p.region_code
+		where p.series_id like 'wb:PA.NUS.PRVT.PP:%' and p.region_code is not null
+			and x.value > 0 and o.value is not null
+		order by 1, 2`;
+	if (!rows.length)
+		throw new Error('price level: run worldbank first (PA.NUS.PRVT.PP, PA.NUS.FCRF)');
+	const regions = [...new Set(rows.map((r) => r.region))];
+	await writeSeries(
+		regions.map((region) => ({
+			series_id: `jobs:pricelevel:${region}`,
+			source_id: 'worldbank',
+			source_code: 'PA.NUS.PRVT.PP/PA.NUS.FCRF',
+			title: 'Price level of household consumption (PPP ÷ exchange rate, USA = 100)',
+			unit: 'USA = 100',
+			freq: 'A',
+			region_code: region,
+			theme: 'jobs',
+			meta: {
+				url: 'https://data.worldbank.org/indicator/PA.NUS.PRVT.PP',
+				derived: '100 × PA.NUS.PRVT.PP / PA.NUS.FCRF'
+			}
+		})),
+		rows.map((r) => ({
+			series_id: `jobs:pricelevel:${r.region}`,
+			period: r.period,
+			value: r.value,
+			status: null
+		}))
+	);
+	return rows.length;
+}
+
+export async function jobs(opts: { only?: string; job: string }) {
+	await run('oecd', `jobs:${opts.job}`, async (note) => {
+		const want = (j: string) => !opts.only || opts.only.split(',').includes(j);
+		let total = 0;
+		for (const spec of SPECS) {
+			if (!want(spec.job)) continue;
+			try {
+				total += await pullOecd(spec);
+			} catch (error) {
+				note(`${spec.flow}: ${error instanceof Error ? error.message : String(error)}`);
+			}
+			await sleep(3200); // OECD: ≤ 20 requests a minute
+		}
+		if (want('bigmac'))
+			try {
+				total += await bigmac();
+			} catch (error) {
+				note(`bigmac: ${error instanceof Error ? error.message : String(error)}`);
+			}
+		if (want('jolts'))
+			try {
+				total += await joltsRatio();
+			} catch (error) {
+				note(`jolts: ${error instanceof Error ? error.message : String(error)}`);
+			}
+		if (want('wages') || want('derived'))
+			try {
+				total += await wageDerived();
+			} catch (error) {
+				note(`wage derived: ${error instanceof Error ? error.message : String(error)}`);
+			}
+		if (want('pricelevel'))
+			try {
+				total += await priceLevel();
+			} catch (error) {
+				note(`pricelevel: ${error instanceof Error ? error.message : String(error)}`);
+			}
+		if (!total) throw new Error('nothing loaded');
+		return total;
+	});
+}

scripts/stats/worldbank.ts

@@ -102,6 +102,43 @@ export const WB_INDICATORS: { id: string; title: string; unit: string; theme: st
 		title: 'Renewable electricity output',
 		unit: '% of electricity',
 		theme: 'energy'
+	},
+	// Jobs & cost of living (modelled ILO estimates; cover China and most others).
+	{
+		id: 'SL.UEM.1524.ZS',
+		title: 'Youth unemployment, 15–24 (ILO modelled)',
+		unit: '%',
+		theme: 'jobs'
+	},
+	{
+		id: 'SL.UEM.NEET.ZS',
+		title: 'Youth not in education, employment or training (NEET)',
+		unit: '% of youth',
+		theme: 'jobs'
+	},
+	{
+		id: 'SL.UEM.ADVN.ZS',
+		title: 'Unemployment with advanced education',
+		unit: '% of labour force with advanced education',
+		theme: 'jobs'
+	},
+	{
+		id: 'SL.TLF.PART.ZS',
+		title: 'Part-time employment',
+		unit: '% of total employment',
+		theme: 'jobs'
+	},
+	{
+		id: 'PA.NUS.FCRF',
+		title: 'Official exchange rate',
+		unit: 'LCU per US$, period average',
+		theme: 'jobs'
+	},
+	{
+		id: 'PA.NUS.PRVT.PP',
+		title: 'PPP conversion factor, private consumption',
+		unit: 'LCU per international $',
+		theme: 'jobs'
 	}
 ];
 

src/lib/stats/JobsExtras.svelte

@@ -0,0 +1,165 @@
+<script lang="ts">
+	// Extras on /stats/<place>/jobs: a "grad view" card per place (the five numbers a recent
+	// graduate cares about first) and a Beveridge curve (unemployment against vacancies), both
+	// built from the theme's metric results, so they show exactly the series the charts use.
+	import StatChart from './StatChart.svelte';
+	import { beveridgeOption, quarterPairs } from './chart.js';
+	import { compact, num, period } from './format.js';
+	import { PLACE_BY_CODE, placeName } from './matrix.js';
+	import type { MetricResult } from '#lib/server/stats-matrix.js';
+
+	let {
+		metrics,
+		codes,
+		attributions
+	}: { metrics: MetricResult[]; codes: string[]; attributions: Record<string, string> } = $props();
+
+	const byKey = $derived(new Map(metrics.map((m) => [m.metric.key, m])));
+	/** Card rows: the first metric key with data wins (per place). */
+	const ROWS: { label: string; keys: string[] }[] = [
+		{ label: 'Youth unemployment', keys: ['youth', 'young'] },
+		{ label: 'Recent-grad employment', keys: ['gradrate', 'grademp'] },
+		{ label: 'Average wage (PPP)', keys: ['avwage', 'medwage', 'mwmonth'] },
+		{ label: 'Price level', keys: ['pricelevel', 'cpl', 'pli'] },
+		{ label: 'Housing squeeze', keys: ['overburden', 'ptoi', 'parents'] }
+	];
+	const cell = (code: string, keys: string[]) => {
+		for (const k of keys) {
+			const m = byKey.get(k);
+			const l = m?.lines.find((x) => x.code === code);
+			const p = l?.points.at(-1);
+			if (m && l && p) {
+				const v = Math.abs(p[1]) >= 1e5 ? compact(p[1]) : num(p[1], m.metric.decimals ?? 1);
+				return { value: v, unit: m.metric.unit, title: m.metric.title, when: period(p[0], l.freq) };
+			}
+		}
+		return null;
+	};
+	const cards = $derived(
+		codes.map((code) => ({
+			code,
+			place: PLACE_BY_CODE.get(code),
+			rows: ROWS.map((r) => ({ label: r.label, c: cell(code, r.keys) }))
+		}))
+	);
+	const anyCard = $derived(cards.some((c) => c.rows.some((r) => r.c)));
+
+	const curves = $derived.by(() => {
+		const u = byKey.get('unemp');
+		const v = byKey.get('vacancy');
+		if (!u || !v) return [];
+		return v.lines
+			.map((vl) => {
+				const ul = u.lines.find((x) => x.code === vl.code);
+				return {
+					code: vl.code,
+					name: placeName(vl.code),
+					color: PLACE_BY_CODE.get(vl.code)?.color,
+					pairs: ul ? quarterPairs(ul.points, vl.points, '2010-01-01') : [],
+					sources: [ul?.sourceId, vl.sourceId].filter((s): s is string => !!s)
+				};
+			})
+			.filter((c) => c.pairs.length > 3);
+	});
+	const noCurve = $derived(codes.filter((c) => !curves.some((x) => x.code === c)));
+</script>
+
+{#if anyCard}
+	<h2 class="stats-section-title">Grad view</h2>
+	<div class="grad-cards">
+		{#each cards as card (card.code)}
+			<article class="grad-card" style:--accent={card.place?.color ?? '#64748b'}>
+				<header>
+					<span class="flag" aria-hidden="true">{card.place?.flag}</span>
+					<strong>{card.place?.name ?? card.code}</strong>
+				</header>
+				<dl>
+					{#each card.rows as r (r.label)}
+						<div title={r.c?.title}>
+							<dt>{r.label}</dt>
+							<dd>
+								{#if r.c}
+									<span class="v">{r.c.value}</span>
+									<span class="u">{r.c.unit} · {r.c.when}</span>
+								{:else}<span class="na">no data</span>{/if}
+							</dd>
+						</div>
+					{/each}
+				</dl>
+			</article>
+		{/each}
+	</div>
+{/if}
+
+{#if curves.length}
+	<div class="stats-grid">
+		<StatChart
+			title="Beveridge curve: how hard is it to find a job?"
+			subtitle="quarterly unemployment rate (x) vs job vacancy rate (y), since 2010 · up and left = tighter market, easier to get hired"
+			sources={curves.flatMap((c) => c.sources)}
+			{attributions}
+			height="340px"
+			wide
+			note={noCurve.length ? `No vacancy series for ${noCurve.map(placeName).join(', ')}.` : ''}
+			option={(t) => beveridgeOption(t, curves, { xUnit: 'unemployment %', yUnit: 'vacancies %' })}
+		/>
+	</div>
+{/if}
+
+<style>
+	.grad-cards {
+		display: grid;
+		grid-template-columns: repeat(auto-fill, minmax(15rem, 1fr));
+		gap: 0.75rem;
+		margin-bottom: 1.5rem;
+	}
+	.grad-card {
+		border: 1px solid var(--site-border);
+		border-top: 3px solid var(--accent);
+		border-radius: 0.75rem;
+		padding: 0.75rem 0.9rem;
+		background: var(--site-surface, transparent);
+	}
+	.grad-card header {
+		display: flex;
+		align-items: center;
+		gap: 0.45rem;
+		margin-bottom: 0.5rem;
+		font-size: 0.95rem;
+	}
+	.flag {
+		font-size: 1.15rem;
+	}
+	dl {
+		display: grid;
+		gap: 0.35rem;
+		margin: 0;
+	}
+	dl > div {
+		display: flex;
+		justify-content: space-between;
+		align-items: baseline;
+		gap: 0.5rem;
+	}
+	dt {
+		color: var(--site-muted);
+		font-size: 0.78rem;
+	}
+	dd {
+		margin: 0;
+		text-align: right;
+	}
+	.v {
+		font-weight: 650;
+		font-variant-numeric: tabular-nums;
+	}
+	.u {
+		display: block;
+		color: var(--site-muted);
+		font-size: 0.65rem;
+	}
+	.na {
+		color: var(--site-muted);
+		font-size: 0.75rem;
+	}
+</style>

src/lib/stats/beveridge.test.ts

@@ -0,0 +1,33 @@
+import { describe, expect, it } from 'vitest';
+import { quarterPairs } from './chart.js';
+
+describe('quarterPairs', () => {
+	it('averages monthly x per quarter and pairs it with quarterly y', () => {
+		const x: [string, number][] = [
+			['2024-01-01', 4],
+			['2024-02-01', 5],
+			['2024-03-01', 6],
+			['2024-04-01', 3]
+		];
+		const y: [string, number][] = [
+			['2024-01-01', 2.5],
+			['2024-04-01', 3],
+			['2024-07-01', 9]
+		];
+		expect(quarterPairs(x, y)).toEqual([
+			[5, 2.5, '2024-Q1'],
+			[3, 3, '2024-Q2']
+		]);
+	});
+	it('drops quarters before `from`', () => {
+		const x: [string, number][] = [
+			['2009-10-01', 8],
+			['2010-01-01', 7]
+		];
+		const y: [string, number][] = [
+			['2009-10-01', 1],
+			['2010-01-01', 1.2]
+		];
+		expect(quarterPairs(x, y, '2010-01-01')).toEqual([[7, 1.2, '2010-Q1']]);
+	});
+});

src/lib/stats/chart.ts

@@ -228,3 +228,108 @@ export function yoy(points: StatPoint[] = [], lag = 12): StatPoint[] {
 	}
 	return out;
 }
+
+/** Quarter key (`2024-Q3`) and its start date for a YYYY-MM-DD period. */
+function quarterOf(date: string): { key: string; start: string } {
+	const y = date.slice(0, 4);
+	const q = Math.floor((Number(date.slice(5, 7)) - 1) / 3) + 1;
+	return { key: `${y}-Q${q}`, start: `${y}-${String((q - 1) * 3 + 1).padStart(2, '0')}-01` };
+}
+
+function quarterMeans(points: StatPoint[]): Map<string, { start: string; value: number }> {
+	const acc = new Map<string, { start: string; sum: number; n: number }>();
+	for (const [d, v] of points) {
+		if (v == null || !Number.isFinite(v)) continue;
+		const q = quarterOf(d);
+		const a = acc.get(q.key) ?? { start: q.start, sum: 0, n: 0 };
+		a.sum += v;
+		a.n += 1;
+		acc.set(q.key, a);
+	}
+	return new Map([...acc].map(([k, a]) => [k, { start: a.start, value: a.sum / a.n }]));
+}
+
+/**
+ * Beveridge-curve pairs: quarterly mean of x (unemployment) against quarterly mean of y
+ * (vacancies), for the quarters both have, oldest first: [x, y, quarter label].
+ */
+export function quarterPairs(
+	x: StatPoint[],
+	y: StatPoint[],
+	from = '0000-01-01'
+): [number, number, string][] {
+	const qx = quarterMeans(x);
+	const qy = quarterMeans(y);
+	const out: [number, number, string][] = [];
+	for (const [key, a] of [...qx].sort((m, n) => m[1].start.localeCompare(n[1].start))) {
+		const b = qy.get(key);
+		if (!b || a.start < from) continue;
+		out.push([Math.round(a.value * 100) / 100, Math.round(b.value * 100) / 100, key]);
+	}
+	return out;
+}
+
+/** Beveridge curve: one connected scatter per place, unemployment (x) against vacancies (y). */
+export function beveridgeOption(
+	theme: ChartTheme,
+	curves: { name: string; color?: string; pairs: [number, number, string][] }[],
+	o: { xUnit: string; yUnit: string }
+): EChartsCoreOption {
+	const axisLabel = { color: theme.muted, fontSize: 11 };
+	const splitLine = { lineStyle: { color: theme.border, opacity: 0.6 } };
+	const axis = (name: string) => ({
+		type: 'value',
+		scale: true,
+		axisLabel,
+		splitLine,
+		name,
+		nameTextStyle: { color: theme.muted, fontSize: 11 }
+	});
+	return {
+		animation: false,
+		grid: { left: 8, right: 24, top: curves.length > 1 ? 56 : 32, bottom: 28, containLabel: true },
+		legend:
+			curves.length < 2
+				? undefined
+				: {
+						top: 0,
+						left: 0,
+						type: 'scroll',
+						textStyle: { color: theme.muted, fontSize: 11 },
+						icon: 'roundRect',
+						itemWidth: 10,
+						itemHeight: 10
+					},
+		tooltip: {
+			trigger: 'item',
+			backgroundColor: theme.surface,
+			borderColor: theme.border,
+			textStyle: { color: theme.text, fontSize: 12 },
+			formatter: (p: { seriesName: string; data: [number, number, string] }) =>
+				`${p.seriesName} · ${p.data[2]}<br>unemployment ${p.data[0]} % · vacancies ${p.data[1]} %`
+		},
+		xAxis: { ...axis(o.xUnit), nameLocation: 'middle', nameGap: 24 },
+		yAxis: axis(o.yUnit),
+		series: curves.map((c, i) => {
+			const color = c.color ?? PALETTE[i % PALETTE.length];
+			const last = c.pairs.length - 1;
+			return {
+				name: c.name,
+				type: 'line',
+				data: c.pairs,
+				itemStyle: { color },
+				lineStyle: { width: 1.5, color, opacity: 0.55 },
+				symbolSize: (_: unknown, p: { dataIndex: number }) => (p.dataIndex === last ? 10 : 4),
+				label: {
+					show: true,
+					position: 'top',
+					fontSize: 10,
+					color: theme.muted,
+					formatter: (p: { dataIndex: number; data: [number, number, string] }) =>
+						p.dataIndex === last || p.dataIndex === 0 ? p.data[2] : ''
+				},
+				emphasis: { focus: 'series' }
+			};
+		})
+	};
+}

src/lib/stats/matrix.ts

@@ -420,7 +420,408 @@ export const THEMES: Theme[] = [
 		icon: 'stats-jobs',
 		blurb:
 			'For recent grads: how easy it is to find work, how good the jobs are, what they pay and what life costs.',
-		metrics: [{ ...UNEMP, group: 'Unemployment', byCode: { USA: ['fred:UNRATE'] } }]
+		metrics: [
+			// ── Unemployment ──
+			{
+				...UNEMP,
+				group: 'Unemployment',
+				subtitle: 'monthly where available',
+				ids: [
+					'oecd:jobs:unemp:{c}',
+					'eurostat:une_rt_m:SA.TOTAL.PC_ACT.T.{e}',
+					'imf:LUR:{c}',
+					'wb:SL.UEM.TOTL.ZS:{c}'
+				],
+				byCode: { USA: ['fred:UNRATE'], CUW: ['cw:lfs:unemployment_rate_pct:total'] },
+				from: '2000-01-01'
+			},
+			{
+				key: 'youth',
+				group: 'Unemployment',
+				title: 'Youth unemployment, 15–24',
+				subtitle: 'US 16–24',
+				unit: '%',
+				ids: [
+					'oecd:jobs:unemp_youth:{c}',
+					'eurostat:une_rt_m:SA.Y_LT25.PC_ACT.T.{e}',
+					'wb:SL.UEM.1524.ZS:{c}'
+				],
+				byCode: {
+					USA: ['fred:LNS14024887'],
+					CUW: ['cw:lfs:unemployment_rate_pct:15-24', 'ilostat:une_deap_sex_age_rt:total:15-24']
+				},
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'young',
+				group: 'Unemployment',
+				title: 'Unemployment, 25–29',
+				subtitle: 'CW 25–34 · US 20–24',
+				unit: '%',
+				ids: ['eurostat:lfsa_urgan:PC.T.Y25-29.TOTAL.{e}'],
+				byCode: {
+					CUW: ['cw:lfs:unemployment_rate_pct:25-34'],
+					USA: ['fred:LNS14000036']
+				},
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'gradunemp',
+				group: 'Unemployment',
+				title: 'Unemployment with a degree',
+				subtitle: 'advanced education · US bachelor’s, 25–34',
+				unit: '%',
+				ids: ['wb:SL.UEM.ADVN.ZS:{c}'],
+				byCode: { USA: ['fred:CGBD2534'] },
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			// ── Finding a job ──
+			{
+				key: 'vacancy',
+				group: 'Finding a job',
+				title: 'Job vacancy rate',
+				subtitle: 'vacancies ÷ (jobs + vacancies) · US JOLTS openings rate',
+				unit: '%',
+				ids: ['eurostat:jvs_q_nace2:NSA.B-S.TOTAL.JVR.{e}'],
+				byCode: { USA: ['fred:JTSJOR'] },
+				from: '2005-01-01',
+				lowerIsBetter: false
+			},
+			{
+				key: 'openings',
+				group: 'Finding a job',
+				title: 'Job openings per unemployed person',
+				subtitle: 'above 1 = more openings than jobseekers',
+				unit: 'ratio',
+				decimals: 2,
+				ids: ['jobs:openings_per_unemployed:{c}'],
+				lowerIsBetter: false
+			},
+			{
+				key: 'ltu',
+				group: 'Finding a job',
+				title: 'Long-term unemployed (1 year +)',
+				subtitle: 'share of the unemployed',
+				unit: '% of unemployed',
+				ids: ['oecd:jobs:ltu:{c}', 'eurostat:une_ltu_a:LTU.Y15-74.T.PC_UNE.{e}'],
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'quits',
+				group: 'Finding a job',
+				title: 'Quits rate',
+				subtitle: 'people leaving their job voluntarily, a sign of confidence (JOLTS)',
+				unit: '%',
+				ids: [],
+				byCode: { USA: ['fred:JTSQUR'] },
+				from: '2001-01-01'
+			},
+			// ── Graduates ──
+			{
+				key: 'gradrate',
+				group: 'Graduates',
+				title: 'Employment rate of recent graduates',
+				subtitle: 'tertiary, left education 1–3 years ago, aged 20–34',
+				unit: '%',
+				ids: ['eurostat:edat_lfse_24:Y1-3.ED5-8.Y20-34.T.PC.{e}'],
+				from: '2000-01-01',
+				lowerIsBetter: false
+			},
+			{
+				key: 'grademp',
+				group: 'Graduates',
+				title: 'Employment rate, tertiary-educated 25–34',
+				unit: '%',
+				ids: ['oecd:jobs:grademp:{c}'],
+				lowerIsBetter: false
+			},
+			{
+				key: 'neet',
+				group: 'Graduates',
+				title: 'Not in employment, education or training (NEET)',
+				subtitle: 'EU 15–29 · elsewhere 15–24',
+				unit: '%',
+				ids: ['eurostat:edat_lfse_20:T.Y15-29.NO_FE_NO_NFE.NEMP.PC.{e}', 'wb:SL.UEM.NEET.ZS:{c}'],
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'premium',
+				group: 'Graduates',
+				title: 'Graduate earnings premium',
+				subtitle: 'full-time earnings of tertiary-educated 25–34s, upper secondary = 100',
+				unit: 'index',
+				decimals: 0,
+				ids: ['oecd:jobs:premium:{c}']
+			},
+			// ── Job quality ──
+			{
+				key: 'temp',
+				group: 'Job quality',
+				title: 'Temporary contracts',
+				subtitle: 'share of employees',
+				unit: '%',
+				ids: ['eurostat:lfsa_etpgan:PC.T.Y15-64.TOTAL.{e}', 'oecd:jobs:temp:{c}'],
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'tempyouth',
+				group: 'Job quality',
+				title: 'Temporary contracts, 15–24',
+				unit: '%',
+				ids: ['eurostat:lfsa_etpgan:PC.T.Y15-24.TOTAL.{e}', 'oecd:jobs:temp_youth:{c}'],
+				from: '2000-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'parttime',
+				group: 'Job quality',
+				title: 'Part-time work',
+				subtitle: 'share of employment',
+				unit: '%',
+				ids: ['eurostat:lfsa_eppga:PC.T.Y15-64.{e}', 'wb:SL.TLF.PART.ZS:{c}'],
+				from: '2000-01-01'
+			},
+			{
+				key: 'hours',
+				group: 'Job quality',
+				title: 'Hours worked per worker, per year',
+				unit: 'hours',
+				decimals: 0,
+				ids: ['oecd:jobs:hours:{c}'],
+				from: '1990-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'longhours',
+				group: 'Job quality',
+				title: 'Very long hours (50 h + a week)',
+				subtitle: 'work–life balance: share of workers',
+				unit: '%',
+				ids: ['oecd:jobs:longhours:{c}'],
+				lowerIsBetter: true
+			},
+			{
+				key: 'weekhours',
+				group: 'Job quality',
+				title: 'Usual weekly hours, full-time job',
+				unit: 'hours',
+				ids: ['eurostat:lfsa_ewhan2:TOTAL.EMP.FT.Y15-64.T.HR.{e}'],
+				lowerIsBetter: true
+			},
+			// ── Wages ──
+			{
+				key: 'avwage',
+				group: 'Wages',
+				title: 'Average annual wage',
+				subtitle: 'full-time equivalent, constant prices, PPP',
+				unit: 'US$ PPP',
+				decimals: 0,
+				ids: ['oecd:jobs:avwage:{c}'],
+				from: '1990-01-01',
+				lowerIsBetter: false
+			},
+			{
+				key: 'medwage',
+				group: 'Wages',
+				title: 'Median full-time wage (approx.)',
+				subtitle: 'real minimum wage ÷ minimum-to-median ratio, PPP',
+				unit: 'US$ PPP',
+				decimals: 0,
+				ids: ['jobs:medianwage:{c}'],
+				lowerIsBetter: false
+			},
+			{
+				key: 'wagegrowth',
+				group: 'Wages',
+				title: 'Real wage growth',
+				subtitle: 'yearly change of the average wage after inflation',
+				unit: '%',
+				ids: ['jobs:realwagegrowth:{c}'],
+				from: '1995-01-01',
+				lowerIsBetter: false
+			},
+			{
+				key: 'minwage',
+				group: 'Wages',
+				title: 'Minimum wage, hourly',
+				subtitle: 'constant prices, PPP',
+				unit: 'US$ PPP',
+				decimals: 2,
+				ids: ['oecd:jobs:minwage_h:{c}'],
+				from: '2000-01-01',
+				lowerIsBetter: false
+			},
+			{
+				key: 'min2med',
+				group: 'Wages',
+				title: 'Minimum wage vs median wage',
+				unit: '% of median',
+				ids: ['oecd:jobs:min2median:{c}'],
+				from: '2000-01-01'
+			},
+			{
+				key: 'mwmonth',
+				group: 'Wages',
+				title: 'Minimum wage, monthly (EU)',
+				subtitle: 'purchasing power standards',
+				unit: 'PPS',
+				decimals: 0,
+				ids: ['eurostat:earn_mw_cur:PPS.{e}'],
+				byCode: { USA: ['eurostat:earn_mw_cur:PPS.US'] },
+				from: '2000-01-01',
+				lowerIsBetter: false
+			},
+			// ── Cost of living ──
+			{
+				key: 'pricelevel',
+				group: 'Cost of living',
+				title: 'Price level of household consumption',
+				subtitle: 'how expensive life is at market exchange rates, USA = 100',
+				unit: 'USA = 100',
+				decimals: 0,
+				ids: ['jobs:pricelevel:{c}'],
+				from: '1990-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'cpl',
+				group: 'Cost of living',
+				title: 'Price level now (OECD, monthly)',
+				subtitle: 'comparative price level, USA = 100',
+				unit: 'USA = 100',
+				decimals: 0,
+				ids: ['oecd:jobs:cpl:{c}'],
+				bars: true,
+				lowerIsBetter: true
+			},
+			{
+				key: 'pli',
+				group: 'Cost of living',
+				title: 'Price level of household consumption (EU27 = 100)',
+				unit: 'EU27 = 100',
+				decimals: 0,
+				ids: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A01.{e}'],
+				byCode: {
+					USA: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A01.US'],
+					JPN: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A01.JP']
+				},
+				from: '1995-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'plifood',
+				group: 'Cost of living',
+				title: 'Price level: food (EU27 = 100)',
+				unit: 'EU27 = 100',
+				decimals: 0,
+				ids: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A0101.{e}'],
+				bars: true,
+				lowerIsBetter: true
+			},
+			{
+				key: 'plihousing',
+				group: 'Cost of living',
+				title: 'Price level: housing, water, energy (EU27 = 100)',
+				unit: 'EU27 = 100',
+				decimals: 0,
+				ids: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A0104.{e}'],
+				bars: true,
+				lowerIsBetter: true
+			},
+			{
+				key: 'plitransport',
+				group: 'Cost of living',
+				title: 'Price level: transport (EU27 = 100)',
+				unit: 'EU27 = 100',
+				decimals: 0,
+				ids: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A0107.{e}'],
+				bars: true,
+				lowerIsBetter: true
+			},
+			{
+				key: 'plirest',
+				group: 'Cost of living',
+				title: 'Price level: restaurants and hotels (EU27 = 100)',
+				unit: 'EU27 = 100',
+				decimals: 0,
+				ids: ['eurostat:prc_ppp_ind:PLI_EU27_2020.A0111.{e}'],
+				bars: true,
+				lowerIsBetter: true
+			},
+			{
+				key: 'bigmac',
+				group: 'Cost of living',
+				title: 'Big Mac price',
+				subtitle: 'NL and EU: euro-area average',
+				unit: 'US$',
+				decimals: 2,
+				ids: ['economist:bigmac:{c}:dollar_price'],
+				byCode: {
+					NLD: ['economist:bigmac:EA:dollar_price'],
+					EU27: ['economist:bigmac:EA:dollar_price'],
+					DEU: ['economist:bigmac:EA:dollar_price'],
+					FRA: ['economist:bigmac:EA:dollar_price'],
+					BEL: ['economist:bigmac:EA:dollar_price']
+				},
+				lowerIsBetter: true
+			},
+			// ── Housing ──
+			{
+				key: 'ptoi',
+				group: 'Housing',
+				title: 'House price-to-income',
+				subtitle: 'vs its own long-term average (= 100)',
+				unit: 'index',
+				decimals: 0,
+				ids: ['oecd:jobs:ptoi:{c}'],
+				from: '1980-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'ptor',
+				group: 'Housing',
+				title: 'House price-to-rent',
+				subtitle: 'vs its own long-term average (= 100)',
+				unit: 'index',
+				decimals: 0,
+				ids: ['oecd:jobs:ptor:{c}'],
+				from: '1980-01-01'
+			},
+			{
+				key: 'rent',
+				group: 'Housing',
+				title: 'Rents',
+				unit: 'Index 2015=100',
+				decimals: 0,
+				ids: ['oecd:jobs:rent:{c}'],
+				from: '2000-01-01'
+			},
+			{
+				key: 'overburden',
+				group: 'Housing',
+				title: 'Housing cost overburden, aged 25–29',
+				subtitle: 'living in a household spending over 40 % of income on housing',
+				unit: '%',
+				ids: ['eurostat:ilc_lvho07a:PC.TOTAL.Y25-29.T.{e}'],
+				from: '2005-01-01',
+				lowerIsBetter: true
+			},
+			{
+				key: 'parents',
+				group: 'Housing',
+				title: 'Still living with their parents, 25–29',
+				unit: '%',
+				ids: ['eurostat:ilc_lvps08:Y25-29.T.PC.{e}'],
+				from: '2005-01-01',
+				lowerIsBetter: true
+			}
+		]
 	},
 	{
 		slug: 'energy',

src/routes/stats/[place]/[theme]/+page.svelte

@@ -3,6 +3,7 @@
 	// render where one fits the combination; otherwise the generic metric charts do.
 	import TrackerIcon from '#lib/components/TrackerIcon.svelte';
 	import MatrixMetrics from '#lib/stats/MatrixMetrics.svelte';
+	import JobsExtras from '#lib/stats/JobsExtras.svelte';
 	import EconomyView from '#lib/stats/views/EconomyView.svelte';
 	import EnergyView from '#lib/stats/views/EnergyView.svelte';
 	import GoudaView from '#lib/stats/views/GoudaView.svelte';
@@ -31,6 +32,9 @@
 		</h1>
 		<p>{theme.blurb}</p>
 	</section>
+	{#if data.theme === 'jobs'}
+		<JobsExtras metrics={data.metrics} codes={sel.codes} attributions={data.attributions} />
+	{/if}
 	<MatrixMetrics metrics={data.metrics} codes={sel.codes} attributions={data.attributions} />
 {:else}
 	{#each data.views as v, i (i)}