jared
93300ae0c1
R-CMD-check / check (push) Successful in 3m5s
Rewrites expenditure/revenue classification off item-code first-letter
prefixes and onto summary_categories membership (F-018: prefix Y spans
revenue, expenditure, and balance codes), and exposes
expenditure_concept = c("primary", "direct", "total") with primary as
the new default:
primary = operations + capital + assistance
direct = primary + interest + insurance_benefits (Census Direct)
total = direct + intergovernmental (M/L/Q via ig views)
- inst/sql: flow views (20-25) select by crosswalk membership;
summary_categories moves to 11- so it registers before them (DuckDB
binds view sources eagerly). The IG leg gains Q11/Q12/Q18 state
school-system payments (F-017).
- R: one subtype scope per verb call drives the verb SQL, the
harmonization exclusion count, and the complete = TRUE grid;
flow_prefixes survives only to scope recipe suggestions.
cog_geographic_rollup/cog_peer_compare accept primary|direct, still
refuse total, and now actually pass the concept through.
- Balance codes can never reach a spending or revenue result
(uscogdata#25), asserted at both view and verb level.
- Deletes the #11 skip; per the 2026-07-30 owner ruling the F-018 Y01
proof is asserted against the crosswalk, not the default
cog_revenue() call (which stays General Revenue pending #12).
Suite: 696 pass / 0 fail / 1 skip (#12, expected).
Closes #11
142 lines
6.8 KiB
R
142 lines
6.8 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/spending.R
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\name{cog_spending}
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\alias{cog_spending}
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\title{Summarized spending by category}
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\usage{
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cog_spending(
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govid,
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years,
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category = NULL,
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per_capita = FALSE,
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adjust_to_year = NULL,
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basis = c("harmonized", "raw"),
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recipe = NULL,
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expenditure_concept = c("primary", "direct", "total"),
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complete = FALSE
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)
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}
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\arguments{
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\item{govid}{Character vector of `canonical_govid` values.}
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\item{years}{Integer vector of years.}
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\item{category}{Character vector of category names (from
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`summary_categories.category`), or `NULL` for all categories.}
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\item{per_capita}{If `TRUE`, adds `amt_per_capita_nominal` (and
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`amt_per_capita_real` when `adjust_to_year` is set) using the per-year
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Census F-33 population from `gov_population_yearly`. Result also gains
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a `pop_source` column with values `"census_f33"` or `"unavailable"`
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(the latter for gov types 4/5 and any row whose population is missing
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in that year).}
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\item{adjust_to_year}{Integer base year for CPI-U real-dollar conversion,
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or `NULL` for nominal only.}
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\item{basis}{`"harmonized"` (default) sums item codes through the
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cross-vintage harmonization mapping (folding series-break-affected
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codes onto a comparable target and excluding aggregate / discontinued
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rows -- see the `harmonization` block in `cog_explain()`); `"raw"`
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reproduces the pre-Phase-R2 behavior (published item codes, no
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folding). On a corpus with `schema_version < 5` (no harmonization
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tables), `basis` silently resolves to `"raw"` when left at its default
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and the resolution is recorded in the provenance; explicitly passing
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`basis = "harmonized"` on such a corpus aborts. Ignored when `recipe`
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is set (see below).}
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\item{recipe}{Optional harmonization recipe id (see [cog_recipes()]) for
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multi-code cross-vintage series that a 1:1 harmonized_code mapping
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can't express (e.g. a wide-era aggregate that only splits into leaf
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codes in the modern era). Mutually exclusive with `category`. The
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result's subtype column reads `"recipe"` and `category` reads the
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recipe's label. Requires `schema_version >= 5`. A recipe query bypasses
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`basis` entirely (it joins `long` directly rather than going through
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the `*_annotated`/`*_annotated_harmonized` views), so the `basis`
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argument is ignored and the result's provenance reports
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`basis = "recipe"` with an inert `harmonization` block (`applied =
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FALSE`, pointing at the `recipe` block instead) rather than a
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possibly-misleading `"harmonized"`/`"raw"` value.}
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\item{expenditure_concept}{Which spending concept to return. Concepts are
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defined as sets of the crosswalk's `spend_subtype` values -- never as
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item-code first letters, which cannot classify correctly (prefix `Y`
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alone spans revenue, expenditure, and balance codes):
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* `"primary"` (default) -- the government's own service provision:
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`operations` + `capital` + `assistance` subtypes.
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* `"direct"` -- Census's published Direct Expenditure: `primary` plus
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`interest` (interest on debt) and `insurance_benefits` (insurance
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trust benefit payments, e.g. pensions -- Census manual section
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5.2.2.1 includes payments to retirees in Direct).
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* `"total"` -- `direct` plus the intergovernmental leg: payments to
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local governments (`M` codes), to the state government (`L` codes,
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excluding the `L--` family-total rollup), and state payments to
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school systems (`Q11`/`Q12`/`Q18`), so results gain rows with
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`spend_subtype == "intergovernmental"`. Requires the active corpus's
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`summary_categories` to carry M/L rows (added by cog_pipeline PR
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#59); aborts with class `uscogdata_ig_categories_unsupported` on an
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older corpus rather than silently under-reporting. Mutually
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exclusive with `recipe` (a recipe already defines its own component
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codes).
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**Do not sum `"total"` results across levels of government** (e.g.
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state + county + city): a state's `M12` payment to a school district is
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the same dollar the district reports as its own direct `E12`, so
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summing both double-counts it. This matters in particular with
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[cog_geographic_rollup()], which sums across exactly that kind of
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multi-layer government set.
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In the legacy wide era (<= FY2011), some functions are published ONLY
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as an aggregate-flagged family total (e.g. Corrections' `E04`/`E05`
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split), which the Direct leg excludes by construction but the IG leg
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deliberately keeps (see `inst/sql/24-ig_long.sql`). For a `"total"`
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query, any (year, category) where this leaves intergovernmental rows
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with NO Direct counterpart is flagged: the affected rows' `notes`
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name the harmonization recipe that recovers the missing Direct
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component (when one exists), and
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`provenance$expenditure_concept_direct_suppressed` is `TRUE` -- the
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figure in those rows is the intergovernmental leg alone, not Direct +
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IG.}
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\item{complete}{If `TRUE`, fill the requested grid so that a cell the
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corpus does not carry still appears, labelled with **why** it is
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missing, and add a `value_source` column to every row:
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* `"reported"` — the corpus carries this cell.
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* `"census_zero"` — dense-source year (`<= FY2011`), cell absent:
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Census published `$0`. `amt_nominal` is `0`.
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* `"not_reported"` — sparse-source year (`>= FY2012`), cell absent: the
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government did not report, and the value is unknown. `amt_nominal` is
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`NA`, **not** `0` — writing a zero there would invent data.
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The grid comes from the corpus's `code_set` table, scoped to each
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government's own type, so a county is never filled with cells only a
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state can report. Reported rows are passed through untouched.
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Defaults to `FALSE` (the historical behaviour: absent cells simply do
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not appear). Needs a corpus published from 2026-07-29 onward, which is
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when `representation`/`code_set` began shipping; aborts with class
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`uscogdata_representation_unavailable` otherwise. Not available with
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`recipe` or with `expenditure_concept = "total"` (class
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`uscogdata_complete_unsupported`) — neither draws its cells from
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`code_set`.}
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}
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\value{
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Tibble with columns `year`, `canonical_govid`, `gov_name`,
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`spend_subtype`, `category`, `amt_nominal`, optional `amt_real`,
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optional `amt_per_capita_nominal`, optional `amt_per_capita_real`,
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optional `pop_source`, `codes_included`, `aggregate_fallback`, `notes`,
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and `value_source` when `complete = TRUE`.
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Carries a `provenance` attribute matching `inst/schemas/provenance-v1.json`,
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whose `completion` block reports `applied`, `rows_filled`, and the
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per-year `absence_means` rule that was applied.
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}
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\description{
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One row per `(year, canonical_govid, spend_subtype, category)`. Amounts are
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returned in **full U.S. dollars** (the raw corpus stores them in $1,000s;
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this verb multiplies by 1000 so downstream code can freely rescale to
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millions/billions). The conversion is recorded in the provenance attribute
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under `transformations$units_conversion`.
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}
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