The Data Space

Input data shared by every by-policy projection.

The four input CSVs are read here, once per model, and referenced from Projection as data. Projection is parameterized by point_id, so each Projection[N] is a separate ItemSpace with its own cells cache; if the readers lived there, every model point would re-read every file. Holding them in an unparameterized Space reads each file once no matter how many policies are projected.

Inputs are external files: plain CSVs in the model folder’s parent directory, products/endowment/, rather than data stored inside the model. The model folder therefore holds nothing but formulas — no _data/, no IOSpec, no embedded values — so a diff of the model shows logic changes only. This follows annuallife.TradLife_A; contrast basiclife.BasicTerm_S, which keeps its inputs inside the model through modelx’s IOSpec machinery.

The consequence worth knowing: the model is not portable on its own. Copying the Endowment_JP_A folder without its parent’s CSVs produces a model that reads and then fails on first evaluation.

input_dir() resolves the directory from _model.path.parent at run time, so the model works wherever the repository is checked out. Each table has a filename Reference and a reader Cells:

Reference	Cells	File
model_point_file	model_point_table()	model_point_table.csv
mort_table_file	mort_table()	mort_table.csv
lapse_table_file	lapse_table()	lapse_table.csv
benefit_schedule_file	benefit_schedule_table()	benefit_schedule_table.csv

The mortality table is a construction, not a copy

mort_table.csv is a [std] construction. 生保標準生命表2018（死亡保険用） (seiho hyōjun seimeihyō 2018, the standard mortality table for death cover) is published by 日本アクチュアリー会 (the Institute of Actuaries of Japan) at a stable public URL, free and in full, so anyone can retrieve it and check a rate — but the publisher’s site terms prohibit reproduction, alteration and transmission to third parties without written consent. This library therefore cites the table by URL, quotes the individual rates its worked example needs, and ships a table whose provenance column points at the IAJ entry row by row: an ANCHOR row is a rate read from the IAJ table and quoted under attribution, an INTERPOLATED row is the log-linear fill in ln q between the two neighbouring anchors, rounded to five decimals, which is the published table’s own granularity. Nothing here is a copy of the IAJ file and nothing here should be read as one.

The file is the library-wide canonical construction, identical row for row in every jplib product that ships it, so one cell carries one value and one provenance string wherever it appears. Both sexes are built the same way from their own sourced anchors: there is no ratio, no sex multiplier and no derivation of one sex from the other. It is restricted to attained ages 0 to 60, which is every age these nine model points reach — the oldest, the 養老保険 anchor cell, matures at attained age 60.

Two further distinctions survive that one. The shipped rates trace a valuation table carrying an explicit safety margin sized to roughly a 2-sigma level, not best-estimate experience, so a best-estimate basis is a further [std] adjustment of it — which is what Projection.mort_be_factor is for, and why it is 1.00 in the base run. And the table is read at 満年齢 (mannenrei, attained age) while the published table is built on a nearest-birthday basis, an understatement of up to half a year of age that the technical notes name rather than hide.

To swap in a company basis, replace mort_table.csv with a same-schema file, or point mort_table_file at a different name, then clear the cache. No formula changes: the lookup already carries the sex and attained age the tables need, and it is used for both lives — the 被保険者 (hihokensha, the insured) and, on the education cell, the 契約者 whose death triggers the waiver.

Cells Descriptions

input_dir()

The directory holding the input CSVs: the model folder’s parent.

Inputs are external files, not data stored inside the model, so the model folder is pure formulas. The path is resolved at run time from where the model was read, following annuallife.TradLife_A.

model_point_table()

The model point table, read from model_point_table.csv.

Indexed by point_id. point_id = 1 is the 養老保険 anchor cell of the technical notes’ worked example and point_id = 2 its 学資保険 cell.

mort_table()

The mortality rates by sex and attained age, from mort_table.csv.

A [std] construction anchored to 生保標準生命表2018（死亡保険用）and never a copy of it; see the Space docstring for what that means and why. Read at 満年齢 attained age for both lives — the insured and, on the education cell, the policyholder whose death triggers the waiver.

lapse_table()

Surrender and premium-default rates by policy year, from lapse_table.csv.

Two columns. lapse_rate is the voluntary surrender rate, 4 / 3 / 2 percent with the last row applying to every later year [std]; default_rate is the premium-default rate that feeds the automatic premium loan module, which is off in the base run because every shipped base model point carries apl_default_mult = 0.

benefit_schedule_table()

The staged 学資金 schedules, read from benefit_schedule_table.csv.

Indexed by schedule_id, one row per payment, each row giving the policy year and the payment as a fraction of 基準保険金額. The schedule is data, not formula: observed designs run from a single payment of 100% to four payments of 100% each, so an implementation that hard-codes a shape is modelling one carrier. The maturity benefit is not a row here — it is always present on both cells and is held separately, so that a schedule with no rows at all still matures.