Frame Availability

Parent: Layer 1: Data Source, Target y, Predictor x
Current group: Official transform / frame availability

missing_availability decides how Layer 1 closes availability gaps after the source frame exists. It is a source-frame policy, not a forecast-time information policy and not raw-source repair.

Runtime order:

Load FRED data, custom data, or FRED-plus-custom data.
Apply raw-source missing/outlier policies when non-default values are set.
Apply official FRED transform codes when available and enabled.
Apply missing_availability to the resulting Layer 1 source frame.
Hand the source frame to Layer 2 representation and research preprocessing.

Axis	Choices	Default / rule
`missing_availability`	`zero_fill_leading_predictor_gaps`, `require_complete_rows`, `keep_available_rows`, `impute_predictors_only`	Default `zero_fill_leading_predictor_gaps`; `impute_predictors_only` requires `leaf_config.x_imputation`.

Value catalog

Value	Meaning
`zero_fill_leading_predictor_gaps`	Default. Fill predictor leading gaps after source-frame construction; target gaps remain guarded by target availability checks.
`require_complete_rows`	Require complete rows for the source frame. Use when the study intentionally avoids any frame-level missingness.
`keep_available_rows`	Keep rows that are usable under the current target/predictor availability contract.
`impute_predictors_only`	Impute predictor x gaps only. Requires `leaf_config.x_imputation` in {`mean`, `median`, `ffill`, `bfill`}; target y is not imputed here.

Boundary rule:

Raw missing values already present in loaded source files belong to 4.1.5 Raw Source Cleaning.
Publication timing belongs to 4.1.2 Forecast-Time Information.
Researcher-chosen missing-data strategies after representation construction belong to Layer 2.
Target y imputation is not done by this axis. Missing target values remain a supervised-learning contract issue.

YAML:

path:
  1_data_task:
    fixed_axes:
      missing_availability: zero_fill_leading_predictor_gaps

Predictor-only imputation example:

path:
  1_data_task:
    fixed_axes:
      missing_availability: impute_predictors_only
    leaf_config:
      x_imputation: ffill