A linked panel dataset of daily tourism arrivals, sectoral spending, local-unit consumption, and extreme-weather indicators for Jeju Island, South Korea (2019–2025)
Description
This dataset integrates four thematically related but institutionally dispersed data sources for Jeju Island, South Korea, covering January 2019 to September 2025. The dataset was compiled to support a multiscalar analysis of how extreme weather affects tourism arrivals, sectoral spending composition, and local spatial consumption patterns. File 1 - Daily tourism arrivals (2,465 observations): Daily visitor counts disaggregated by domestic and international visitors, compiled from the Jeju Tourism Association. Seven dates record zero arrivals corresponding to weather-induced complete gateway suspension. File 2 - Sectoral tourism spending (486 sector-month observations): Monthly tourism spending across six sectors (retail, transport, food services, accommodation, arts/sports/leisure, and other services) sourced from the Korea Tourism Organization Datalab (datalab.visitkorea.or.kr), based on Shinhan Card transaction records. File 3 - Local-unit tourism spending (43 administrative units x 81 months): Monthly tourism spending for 43 sub-municipal administrative units across Jeju-si and Seogwipo-si, sourced from the Jeju Tourism Organization data platform (data.ijto.or.kr). Subsequent platform restructuring has restricted equivalent access to this historical series. File 4 - Extreme-weather indicators: Daily binary indicators and monthly event-day counts for three extreme-weather types (heatwave 33°C or above, heavy rain 80mm or above, strong wind 14m/s or above) from four Korea Meteorological Administration ASOS stations (Jeju 184, Gosan 185, Seongsan 188, Seogwipo 189). The dataset spans a pre-pandemic baseline (2019), COVID-19 disruption period (2020-2022), and post-recovery extreme-weather intensification (2023-2025).
Files
Steps to reproduce
Raw data were collected from four separate institutional sources between 2024 and 2025. File 1: Daily arrival statistics were obtained from the Jeju Tourism Association portal as monthly files (one annual file for 2019; one file per month for 2020-2025, totalling approximately 70 source files) and manually restructured into a long-format daily panel. File 2: Monthly sectoral spending data were downloaded from the Korea Tourism Organization Datalab (datalab.visitkorea.or.kr) as individual monthly files across 81 months and compiled into a single panel. File 3: Local-unit spending data were collected from the Jeju Tourism Organization data platform (data.ijto.or.kr) as individual monthly CSV files through manual download across 81 months. Note: subsequent platform restructuring has restricted equivalent access to this historical series. File 4: Daily meteorological records were downloaded from the Korea Meteorological Administration ASOS open data portal (data.kma.go.kr) as annual station files and merged across 2019-2025. Binary threshold indicators were applied: Heatwave (daily maximum temperature >= 33C), Heavyrain (daily precipitation >= 80mm), Strongwind (maximum wind speed >= 14m/s). All data compilation and initial processing were performed in Microsoft Excel. Statistical analyses used IBM SPSS Statistics (version 24) and R (version 4.5.3). Figures were produced using R with ggplot2 and patchwork packages.
Institutions
- Jeju National UniversityJeju-do, Jeju City