DATA_DICTIONARY.md

# Data Dictionary — AFOS Germany 2025 Electoral Divergence

Every file and column, with type, unit and provenance. **Party-level**: polls measure party vote share; the market prices the probability of winning the most seats. Values are never imputed or smoothed — missing values are left **blank**.

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## `polls/germany-polls.csv`

Party vote-share polling, **long format** — one row per party × poll.

| Column | Type | Notes |
|--------|------|-------|
| `poll_date` | date | Fieldwork-end date (`YYYY-MM-DD`). |
| `fieldwork` | string | Fieldwork window as published. |
| `pollster` | string | Polling firm (Forsa, INSA, Infratest dimap, …). |
| `sample` | integer | Sample size; blank when not declared (thousands separators normalized). |
| `party` | string | Party (canonical): CDU/CSU, SPD, AfD, Grüne, Die Linke, FDP, BSW, Freie Wähler. |
| `party_full` | string | Full party name. |
| `percent` | number | Party vote-share intention, %. |

## `polls/germany-polls.json`

Full structured polls (pollster, fieldwork, sample, per-party results). Deduplicated by (pollster, date), keeping the most complete row.

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## `data/germany-market-odds-timeseries.csv`

Polymarket **"wins the most seats"** probability per party, daily, from the "Germany Parliamentary Election Winner" market.

| Column | Type | Notes |
|--------|------|-------|
| `date` | date | `YYYY-MM-DD`. |
| `party` | string | Canonical party name. |
| `polymarket_pct` | number | Implied probability of winning the most seats, %. |
| `volume_usd` | number | Cumulative traded volume for that party's market, USD. |

## `data/germany-divergence-timeseries.csv`

**Market × poll divergence** per party — each poll's party vote share joined to that party's market odds on the poll's date (nearest **on or before**).

| Column | Type | Notes |
|--------|------|-------|
| `poll_date` | date | Poll date. |
| `pollster` | string | Polling firm. |
| `party` | string | Canonical party name. |
| `poll_pct` | number | Party vote share, %. |
| `polymarket_pct` | number | Market "wins most seats" probability on `polymarket_date`, %. |
| `polymarket_date` | date | Market date used (nearest on-or-before `poll_date`). |
| `divergence_pp` | number | `polymarket_pct − poll_pct`, percentage points. |

> **Interpretation caveat:** a poll reports *vote share*; the market prices *probability of winning the most seats*. The two are different quantities — `divergence_pp` is the spread AFOS tracks, **not** an error metric. A party (e.g. AfD) can hold a large vote share while its probability of winning the plurality is near zero; the gap is the signal.

## `data/germany-poly-raw.json`

Raw Polymarket payload (event + per-party price histories), via a US-resolving function, kept for provenance.

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**Sources:** [Wikipedia — Opinion polling for the 2025 German federal election](https://en.wikipedia.org/wiki/Opinion_polling_for_the_2025_German_federal_election) · Polymarket "Germany Parliamentary Election Winner". Maintained by [AFOS Analytics](https://afos-analytics.com). CC BY 4.0.

## `data/germany-structural-context.csv`

Structural country context from the **World Bank**, complementary to the divergence data: it frames the country, it does **not** predict the electoral outcome. Long/tidy format, one row per indicator, latest available year per indicator.

| Column | Type | Notes |
|--------|------|-------|
| `category` | string | `governance`, `economy`, or `education`. |
| `indicator` | string | Machine code (e.g. `political_stability`, `gdp_usd`, `expected_years_schooling`). |
| `label` | string | Human-readable indicator name (English). |
| `value` | number | Governance on a 0–100 scale; economy in US$ / %; education in % of GDP or years. |
| `unit` | string | `index_0_100`, `USD`, `percent`, or `years`. |
| `year` | integer | Reference year of the value (latest available). |
| `source` | string | World Bank WGI (governance, via Data360) or WDI (economy & education). |
| `iso3` | string | ISO 3166 alpha-3 country code. |

Both sources are open-licensed (CC BY 4.0) and keyless. Governance = Worldwide Governance Indicators; economy & education = World Development Indicators.