QuantEcon · mmcky · Sep 6, 2026 · Sep 6, 2026 · Sep 6, 2026
diff --git a/AGENTS.md b/AGENTS.md
@@ -23,6 +23,10 @@ Classify as exactly one of:
 | **constructed** | built from upstream sources by our processing | all of the above **plus the builder script, committed here** |
 | **dynamic snapshot** | constructed, tracking a moving source (FRED, World Bank) | all of the above **plus a refresh cadence** |
 
+**Naming a published file** (policy settled 2026-09-07, [#113](https://github.com/QuantEcon/data-lectures/issues/113)): the tree is flat, so the filename is the URL and the future `qeld` key. Name the *variable*, add the *frequency* when the same variable exists at another frequency, name a composite for its *topic* rather than its lecture, no source prefix, never a vintage or coverage in a dynamic snapshot's name (a verbatim release keeps upstream's name). Rename freely while `consumers: []`; after that only as a new filename with the old one kept serving. The six rules with examples are in `manifest-schema.yml` beside `filename`.
+
+**The `schema` block is executable** (decisions of 2026-09-07 on [#120](https://github.com/QuantEcon/data-lectures/issues/120), [#121](https://github.com/QuantEcon/data-lectures/issues/121), [#122](https://github.com/QuantEcon/data-lectures/issues/122); validator in [#119](https://github.com/QuantEcon/data-lectures/issues/119)): column `pattern`s are ordered, contiguous, exhaustive and carry the date in a capture group; `known_nulls` integers are exact and a dynamic snapshot declares null *placement* under `nulls:`; dtypes use the pandas-3 names (`str`, not `string`/`object`) and are compared by family. `manifest-schema.yml` carries the rules.
+
 A constructed dataset without its committed builder is a bug. Manifest fields: `source`, `license` (with the `verified` date it was established), `retrieved`, `integrity` (`sha256` plus the `upstream` verification status, see Phase 7), `schema` (including `known_nulls`), `consumers` (repo + lecture file, machine-readable), `maintainer`, `builder` / `builder_status`, `cadence` (dynamic only). `manifest-schema.yml` is the authoritative, commented field reference — keep it and this list in step.
 
 **Verifying `integrity.upstream`, by class** (once here, not repeated per manifest): re-fetch-and-compare for **verbatim**; re-run the builder and compare the overlap window for **constructed / dynamic**; spot-check against the cited publication for author-assembled. When verification is impossible, say so plainly — `status: unverifiable` with a one-line `note` is a known status the catalog can show; silence is not. **Migration safety** (does the file byte-match what the consuming lecture used before a repoint?) is deliberately *not* a manifest field: it is a one-time gate recorded in the repoint PR, and the manifest's `sha256` keeps it reproducible afterwards.
@@ -112,7 +116,7 @@ The limits: **50 MiB** warns on push, **100 MiB** (104,857,600 B) is a hard bloc
 
 **One builder per published dataset, in `builders/`, named for the dataset it produces:** `builders/<stem>.<ext>` builds `lectures/<stem>.<ext2>`. The stem is the dataset's, not the lecture's — `builders/japan_earthquakes.py` writes `lectures/japan_earthquakes.csv`. That makes the manifest's `builder:` field predictable and lets CI assert it.
 
-Where one builder produces a **set** of files, name it for the set and let each file's manifest point at the same path — the SCF and Forbes builders each write two. The stem rule is the default, not an invariant; what CI asserts is that every `builder:` path exists, and that a dataset claiming a builder names one. A builder's **provenance byproducts** — upstream metadata dumps that are not datasets — go to `provenance/`, never `lectures/`: `business_cycle.py` writes one dataset there and two dumps here.
+Where one builder produces a **set** of files, name it for the set and let each file's manifest point at the same path — the SCF and Forbes builders each write two. The stem rule is the default, not an invariant; what CI asserts is that every `builder:` path exists, and that a dataset claiming a builder names one. A builder's **provenance byproducts** — upstream metadata dumps that are not datasets — go to `provenance/`, never `lectures/`: `business_cycle.py` writes three datasets there and two dumps here.
 
 `scripts/` is repo tooling — the audit dashboard and the catalog generator — and produces no dataset. Keep the two apart.
 

diff --git a/CATALOG.md b/CATALOG.md
@@ -18,7 +18,6 @@ The dataset registry, **auto-generated** from the sidecar manifests (`lectures/*
 | [**assignat.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/assignat.xlsx)<br><sub>French Revolution — assignat issues, budgets and seigniorage (Sargent-Velde)</sub> | verbatim | [Sargent and Velde, "Macroeconomic Features of the French Revolution" — supporting spreadsheets](https://www.journals.uchicago.edu/doi/10.1086/261992) |  | ✅ permitted | ⚠️ unverifiable | n/a (verbatim) | 204.6 KB | [lecture-python-intro · french_rev.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/french_rev.md)<br>[lecture-wasm · french_rev.md](https://github.com/QuantEcon/lecture-wasm/blob/main/lectures/french_rev.md)<br>[lecture-intro.zh-cn · french_rev.md](https://github.com/QuantEcon/lecture-intro.zh-cn/blob/main/lectures/french_rev.md)<br>[test-actions-lecture-intro · french_rev.md](https://github.com/QuantEcon/test-actions-lecture-intro/blob/main/lectures/french_rev.md)<br>[tom-econ370-2025 · french_rev.md](https://github.com/QuantEcon/tom-econ370-2025/blob/main/lectures/french_rev.md)<br><sub>⚠️ BROKEN reader (measured 2026-08-19): fetches this dataset through a stale `base_url` still pointing at lecture-python-intro's deleted `datasets/` copy (french_rev.md:70-75), which serves 404</sub> |
 | [**bbh_macro_quarterly.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/bbh_macro_quarterly.csv)<br><sub>Bhandari-Borovička-Ho replication — quarterly US macro series for the belief-wedge VAR, 1955Q1-2019Q4</sub> | constructed | [Replication package for "Survey data and subjective beliefs in business cycle models" (Bhandari, Borovička and Ho), file `data input/FRED/data_FRED.xlsx`](https://doi.org/10.5281/zenodo.10194324) | CC-BY-4.0 | ✅ permitted | ✅ verified | ✅ committed | 31.5 KB | [lecture-python-advanced.myst · subjective_beliefs_business_cycles.md](https://github.com/QuantEcon/lecture-python-advanced.myst/blob/main/lectures/subjective_beliefs_business_cycles.md) |
 | [**bbh_michigan_monthly.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/bbh_michigan_monthly.csv)<br><sub>Michigan Surveys of Consumers monthly aggregates and the US unemployment rate, 1978-01 to 2020-03 (BBH replication extract)</sub> | constructed | [Bhandari, Borovička and Ho replication package (Zenodo), carrying University of Michigan Surveys of Consumers published aggregates and a US Bureau of Labor Statistics series retrieved via FRED](https://doi.org/10.5281/zenodo.10194324) | CC-BY-4.0 | ⚠️ restricted | ✅ verified | ✅ committed | 11.9 KB | [lecture-python-advanced.myst · subjective_beliefs_business_cycles.md](https://github.com/QuantEcon/lecture-python-advanced.myst/blob/main/lectures/subjective_beliefs_business_cycles.md) |
-| [**business_cycle_data.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/business_cycle_data.csv)<br><sub>World Bank GDP growth (annual %) — nine economies, 1960 onward</sub> | dynamic-snapshot | [World Bank, World Development Indicators (national accounts data, and OECD National Accounts data files)](https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG) | CC BY-4.0 | ✅ permitted | ✅ verified | ✅ committed | 10.4 KB | — |
 | [**caron.npy**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/caron.npy)<br><sub>French Revolution — monthly specie value of the assignat, 1791-1796</sub> | constructed | unrecorded |  | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 1.1 KB | [lecture-python-intro · french_rev.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/french_rev.md)<br>[lecture-wasm · french_rev.md](https://github.com/QuantEcon/lecture-wasm/blob/main/lectures/french_rev.md)<br>[lecture-intro.zh-cn · french_rev.md](https://github.com/QuantEcon/lecture-intro.zh-cn/blob/main/lectures/french_rev.md)<br>[test-actions-lecture-intro · french_rev.md](https://github.com/QuantEcon/test-actions-lecture-intro/blob/main/lectures/french_rev.md)<br><sub>⚠️ Reads a local `datasets/` copy, not this file</sub><br>[tom-econ370-2025 · french_rev.md](https://github.com/QuantEcon/tom-econ370-2025/blob/main/lectures/french_rev.md)<br><sub>⚠️ Course fork with a live Pages site; reads its own blob-identical `datasets/` copy (french_rev.md:715-716), not this file, and its `base_url` still points at lecture-python-intro</sub><br>[python-lecture-sandpit.myst · french_rev.md](https://github.com/QuantEcon/python-lecture-sandpit.myst/blob/main/lectures/french_rev.md)<br><sub>⚠️ Public sandpit holding `lectures/_static/` copies</sub> |
 | [**chapter_3.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/chapter_3.xlsx)<br><sub>The Ends of Four Big Inflations — appendix tables, transcribed</sub> | constructed | [Sargent, "Rational Expectations and Inflation", chapter 3 appendix tables](https://press.princeton.edu/books/paperback/9780691158709/rational-expectations-and-inflation) |  | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 71.6 KB | [lecture-python-intro · inflation_history.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/inflation_history.md)<br>[lecture-wasm · inflation_history.md](https://github.com/QuantEcon/lecture-wasm/blob/main/lectures/inflation_history.md)<br>[lecture-intro.zh-cn · inflation_history.md](https://github.com/QuantEcon/lecture-intro.zh-cn/blob/main/lectures/inflation_history.md)<br>[test-actions-lecture-intro · inflation_history.md](https://github.com/QuantEcon/test-actions-lecture-intro/blob/main/lectures/inflation_history.md) |
 | [**cities_brazil.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/cities_brazil.csv)<br><sub>World Population Review — Brazilian city populations, 2023</sub> | verbatim | [World Population Review — cities in Brazil](https://worldpopulationreview.com/countries/cities/brazil) |  | ⚠️ restricted | ⚠️ unverifiable | n/a (verbatim) | 17.5 KB | [lecture-python-intro · heavy_tails.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/heavy_tails.md)<br>[lecture-wasm · heavy_tails.md](https://github.com/QuantEcon/lecture-wasm/blob/main/lectures/heavy_tails.md)<br>[lecture-intro.zh-cn · heavy_tails.md](https://github.com/QuantEcon/lecture-intro.zh-cn/blob/main/lectures/heavy_tails.md)<br>[test-actions-lecture-intro · heavy_tails.md](https://github.com/QuantEcon/test-actions-lecture-intro/blob/main/lectures/heavy_tails.md) |
@@ -33,6 +32,7 @@ The dataset registry, **auto-generated** from the sidecar manifests (`lectures/*
 | [**forbes-global2000.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/forbes-global2000.csv)<br><sub>Forbes Global 2000 — firm size measures</sub> | constructed | [Forbes Global 2000](https://www.forbes.com/lists/global2000/) |  | ⚠️ restricted | ⚠️ unverifiable | committed-frozen | 115.6 KB | [lecture-python-intro · heavy_tails.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/heavy_tails.md)<br>[lecture-wasm · heavy_tails.md](https://github.com/QuantEcon/lecture-wasm/blob/main/lectures/heavy_tails.md)<br>[lecture-intro.zh-cn · heavy_tails.md](https://github.com/QuantEcon/lecture-intro.zh-cn/blob/main/lectures/heavy_tails.md)<br>[test-actions-lecture-intro · heavy_tails.md](https://github.com/QuantEcon/test-actions-lecture-intro/blob/main/lectures/heavy_tails.md) |
 | [**fp.dta**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/fp.dta)<br><sub>Treisman (2016) Russia's Billionaires — country-year panel of billionaire counts and covariates</sub> | verbatim | [Replication package for Treisman (2016), "Russia's Billionaires" (AER Papers & Proceedings)](https://www.aeaweb.org/articles?id=10.1257/aer.p20161068) |  | ✅ permitted | ✅ verified | n/a (verbatim) | 1000.1 KB | [lecture-python.myst · mle.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/mle.md)<br>[lecture-python.zh-cn · mle.md](https://github.com/QuantEcon/lecture-python.zh-cn/blob/main/lectures/mle.md)<br>[lecture-stats · mle.md](https://github.com/QuantEcon/lecture-stats/blob/main/lectures/mle.md) |
 | [**fred_data.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/fred_data.csv)<br><sub>US Treasury yields and NBER recessions — GS1/GS5/GS10, DFII5/DFII10 and USREC, monthly 1953-04 to 2024-12</sub> | constructed | [FRED (Federal Reserve Bank of St. Louis) — series GS1, GS5, GS10, DFII5, DFII10, USREC](https://fred.stlouisfed.org) |  | ✅ permitted | ✅ verified | ✅ committed | 27.3 KB | [lecture-python-advanced.myst · risk_aversion_or_mistaken_beliefs.md](https://github.com/QuantEcon/lecture-python-advanced.myst/blob/main/lectures/risk_aversion_or_mistaken_beliefs.md) |
+| [**gdp_growth_annual.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/gdp_growth_annual.csv)<br><sub>World Bank GDP growth (annual %) — nine economies, 1960 onward</sub> | dynamic-snapshot | [World Bank, World Development Indicators (national accounts data, and OECD National Accounts data files)](https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG) | CC BY-4.0 | ✅ permitted | ✅ verified | ✅ committed | 10.4 KB | — |
 | [**hansen_jagannathan_1991_data.json**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/hansen_jagannathan_1991_data.json)<br><sub>Hansen-Jagannathan (1991) replication — US asset returns 1891-1986, with annual consumption (three-table bundle)</sub> | constructed | [Robert J. Shiller's public data workbooks (chapt26.xlsx, ie_data.xls) and FRED](http://www.econ.yale.edu/~shiller/data.htm) |  | ✅ permitted | ✅ verified | ⚠️ unrecovered | 62.0 KB | [lecture-python-advanced.myst · hansen_jagannathan_1991.md](https://github.com/QuantEcon/lecture-python-advanced.myst/blob/main/lectures/hansen_jagannathan_1991.md) |
 | [**hansen_singleton_1982_data.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/hansen_singleton_1982_data.csv)<br><sub>Hansen-Singleton (1982) replication — monthly US gross real market return and consumption growth, 1959-1978</sub> | constructed | [FRED (BEA and BLS monthly series) and the Ken French data library (F-F_Research_Data_Factors)](https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) |  | ✅ permitted | ✅ verified | ✅ committed | 11.4 KB | [lecture-python.myst · hansen_singleton_1982.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/hansen_singleton_1982.md)<br>[lecture-python.zh-cn · hansen_singleton_1982.md](https://github.com/QuantEcon/lecture-python.zh-cn/blob/main/lectures/hansen_singleton_1982.md) |
 | [**hansen_singleton_1983_data.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/hansen_singleton_1983_data.csv)<br><sub>Hansen-Singleton (1983) replication — monthly US returns, consumption and inflation, 1959-1978</sub> | constructed | [FRED (BEA and BLS monthly series) and the Ken French data library (F-F_Research_Data_Factors)](https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) |  | ✅ permitted | ✅ verified | ✅ committed | 25.5 KB | [lecture-python.myst · hansen_singleton_1983.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/hansen_singleton_1983.md)<br>[lecture-python.zh-cn · hansen_singleton_1983.md](https://github.com/QuantEcon/lecture-python.zh-cn/blob/main/lectures/hansen_singleton_1983.md) |