MIRACLE integrates multiple archival source types into a single framework built around time-consistent geographic identifiers. Each township carries a miracle_id that tracks it through South Korea's two major boundary reorganisations (1963, 1973) and dozens of smaller changes, allowing researchers to follow the same unit across three decades without manually reconciling administrative maps. The municipal statistical yearbooks form the natural backbone — published annually by every county government, they provide the richest and most consistent subnational coverage for this period. Additional archival layers, from forest type maps to foreign loan records and colonial-era household registries, extend the panel into domains the yearbooks do not reach.
MIRACLE starts with South Korea's municipal statistical yearbooks, but the ambition extends in two directions. First, within Korea, we plan to incorporate additional administrative sources — expressway construction logs, agricultural extension records, Korea Forest Service archives, colonial-era household registries, and local personnel files — to deepen the panel and enable research designs that link infrastructure, agricultural modernisation, and environmental policy to local institutional conditions.
Second, across countries, the infrastructure we build is designed to accommodate other growth miracle economies with comparable subnational statistical traditions. If similar municipal records exist for Taiwan, or district-level yearbooks for post-war Japan, they belong in the same framework. The goal is a comparative subnational data platform for studying rapid development wherever it has occurred.
- Municipal Statistical Yearbooks 통계연보 Core — digitising now
Township-level demographics, agriculture, industry, infrastructure, public finance, and education. Published annually by county governments. - Forest Type Maps 산림유형도 Collected
Korea Forest Service spatial archives. Shapefiles available from 조선임야분포도 (1910) and forest type maps from 1974 onward. Enables studying one of history's largest reforestation programmes. - Loan Relation Files 차관관계철 Planned
Foreign loan records linking firms to locations and financing sources. Geocoding firms and mapping industrial networks. - Household Registries 호적부 Planned
Colonial-era and early-Republic household records. Pre-treatment institutional measures including clan concentration and land ownership. - Agricultural Extension Records Planned
Farm-level adoption of high-yield rice varieties and extension programme participation. - Expressway Construction Logs Planned
Construction timelines and route data for the Gyeongbu Expressway and subsequent motorway network. - Personnel Files Planned
Local government personnel records. Bureaucratic capacity and institutional quality measures.
MIRACLE draws on multiple administrative source types. Municipal statistical yearbooks form the backbone; additional archival layers extend the platform to forestry, industrial, and institutional data.
Published annually by county governments. Township-level data on demographics, agriculture, industry, infrastructure, public finance, and education. Dispersed across provincial archives — never systematically compiled.
Korea Forest Service spatial archives. Shapefiles available from 조선임야분포도 (1910) and forest type maps from 1974. Enables studying one of history's largest reforestation programmes.
Foreign loan records linking firms to locations and financing sources. Geocoding firms and mapping industrial networks.
Colonial-era and early-Republic household records. Pre-treatment institutional measures including clan concentration and land ownership.
From archive to analysis-ready panel in six steps:
Archive discovery & source identification Done
Systematic survey of provincial archives, university libraries, and government collections to locate surviving yearbook volumes. Mapping what exists, what is missing, and where physical copies are held.
Outreach & scanning Done
Building partnerships with municipalities, counties, and provincial archives. Physical scanning of bound volumes into high-resolution page images — the raw input for digitisation.
AI-OCR for mixed scripts Current focus
Custom pipeline fine-tuned for mixed Hangul/Hanja archival tables. 87% pilot accuracy, targeting 92–95%. This is what makes the project feasible — these documents were previously unusable at scale.
| 읍면 | 합계 | 논 (답) | 밭 (전) | ✓ | ||
|---|---|---|---|---|---|---|
| 소계 | 1모작 | 2모작 | ||||
| 남해 | 8,054 | 5,849 | 1,230 | 4,619 | 2,205 | ✓ balanced |
| 이동 | 10,993 | 7,544 | 1,175 | 6,369 | 3,449 | ✓ balanced |
| 삼동 | 12,785 | 7,349 | 1,239 | 6,110 | 5,436 | ✓ balanced |
| 남면 | 11,470 | 6,012 | 857 | 5,155 | 5,458 | ✓ balanced |
| 고현 | 8,310 | 5,680 | 743 | 4,937 | 2,630 | ✓ balanced |
| 창선 | 13,173 | 7,901 | 2,311 | 5,590 | 5,272 | ✓ balanced |
See structured output table above.
Variable harmonisation Current focus
Definitions, units, and table structures changed across editions and municipalities. We build crosswalks reconciling these into consistent time series.
Boundary concordances Pilot complete
Two major reorganisations (1963, 1973) plus dozens of smaller changes. We construct time-consistent miracle_id identifiers.
Geocoding & GIS Pilot complete
Every township linked to satellite, elevation, slope, soil, and transport network data. 196 Namhae-gun villages fully geocoded.
The dataset is organised into modules by domain, each a flat township-year panel. Merge across modules using Core Keys. CSV & Stata formats, with full codebook and variable documentation.
| miracle_id | year | prov | muni | twp | pop | hh | paddy_ha | schools | road_km |
|---|---|---|---|---|---|---|---|---|---|
| KR-48-840-010 | 1970 | 경남 | 남해군 | 남해읍 | 28,412 | 5,680 | 1,245 | 7 | 23.4 |
| KR-48-840-010 | 1975 | 경남 | 남해군 | 남해읍 | 25,891 | 5,320 | 1,198 | 8 | 31.7 |
| KR-48-840-010 | 1980 | 경남 | 남해군 | 남해읍 | 22,105 | 5,010 | 1,152 | 8 | 38.2 |
| KR-47-720-030 | 1970 | 경북 | 영주시 | 풍기읍 | 31,550 | 6,140 | 1,870 | 9 | 18.6 |
| Module | Description | ETA |
|---|---|---|
| Core Keys miracle_id · province · municipality · township · concordances | Geographic identifiers and boundary concordances across the 1963/1973 reorganisations. | 2026 |
| Demographics population · households · age structure | Population counts, household numbers, demographic composition. | 2026 |
| Agriculture paddy area · crop output · livestock | Cultivated area, output (harmonised to metric units), livestock. | 2026 |
| Industry establishments · employment · output | Industrial establishments, manufacturing employment, sectoral output. | 2027 |
| Infrastructure roads · electricity · water · telecom | Road length, electrification, public utilities. | 2027 |
| Public Finance revenues · expenditures · transfers | Municipal revenue/expenditure, central transfers, fiscal capacity. | 2027 |
| Education schools · enrolment · teachers | School counts, enrolment, teachers, educational infrastructure. | 2027 |
| Geospatial shapefiles · centroids · boundaries | GIS boundary files with consistent township geometries. | 2027 |
| Institutions clan concentration · bureaucratic capacity | Pre-treatment institutional measures from 1930 registries and personnel files. | 2028 |
Work in progress and working papers using MIRACLE data:
- Seol, BooKang (2026). "The Saemaul Undong and Rural Development in South Korea." R&R at Journal of Political Economy.
- Growth Miracles knowledge bank — comparative subnational data platform
- Hyunjoo Yang (양현주, Sogang University) — DGM project, related digitisation work on Korean municipal records
If you are using or interested in using MIRACLE data, we would like to hear from you. Get in touch.
Digitisation proceeds province by province, constrained by the uneven survival of physical yearbooks across Korea's provincial archives. Hover over each province for details on coverage, year range, and scanning status.
Last updated March 2026
▶ Interactive coverage mapChangkeun Lee
Hyunjoo Yang
Hiring research assistants for 2026–27. Get in touch.
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@techreport{seol2026miracle,
author = {Seol, BooKang and Lee, Changkeun and Yang, Hyunjoo},
title = {{MIRACLE}: Subnational Economic Data for
South Korea's Developmental Period, 1960--1989},
institution = {London School of Economics},
year = {2026}
}