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"@type": ... | sc:Dataset | A Global Benchmark Dataset of Digital-Nomad Policy Adoption, Tourism Flows, and Labor-Market Indicators | A harmonized country-year panel dataset linking tourism metrics from UN Tourism and macroeconomic indices from the World Bank Open Data to a hand-coded, human-verified policy panel documenting 32 national digital-nomad visa configurations and an 11-jurisdiction comparison matrix of non-adopting major economies. | http://mlcommons.org/croissant/1.1 | https://huggingface.co/datasets/Intlrnz/DigitalNomadPolicy | https://spdx.org/licenses/CC-BY-4.0.html | 1.0.0 | Empirical analysis of cross-country mobility, post-pandemic economic recovery dynamics, tracking shifting compositions of visitor profiles, and testing multi-period staggered difference-in-differences designs or synthetic control emulation models. | [
"Evaluating the reliability of LLM-assisted policy extraction against a human-verified benchmark of digital-nomad visa policy.",
"Estimating the effect of digital-nomad visa adoption on tourism arrivals, tourism GDP share, and related macroeconomic indicators using TWFE and doubly robust DML estimators.",
"Comp... | Exhibits significant reporting missingness (up to 55%) natively present within the UN Tourism database streams (e.g., tourism direct employment and sector GDP shares), particularly concentrated among small island states, microstates, and heavily sanctioned economies. The verified policy benchmark covers 32 adopter juri... | The panel focuses deliberately on early pandemic-era legal policy trajectories and represents a curated, purposively chosen comparison sample for major economies rather than a globally randomized control sample. Countries with limited statistical capacity or restricted data-sharing agreements are systematically underre... | None. Contains exclusively aggregated institutional macro indices, historical figures, and qualitative cross-border immigration framework descriptions. No individual telemetry or private tracking is collected. | The dataset is intended to support transparent, reproducible policy research on digital-nomad mobility and to help evaluate whether AI-assisted policy extraction introduces errors that materially change downstream empirical conclusions. Potential risks include over-generalizing findings from a 32-jurisdiction convenien... | false | [
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] | Tourism and macroeconomic indicators were sourced from UN Tourism and the World Bank Open Data and merged into an annual country panel. Digital-nomad visa policy records were first extracted via LLM-assisted review of official government sources, then independently verified by human reviewers against primary legal docu... | [
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DigitalNomadPolicy
A Global Benchmark Dataset of Digital-Nomad Policy Adoption, Tourism Flows, and Labor-Market Indicators for Cross-Country Mobility Research
License: CC BY 4.0
Format: Excel (.xlsx) + Croissant Metadata
Overview
DigitalNomadPolicy is a benchmark dataset for trustworthy AI-assisted policy research. It combines a global macroeconomic panel with a human-verified dataset of digital nomad visa programmes, enabling researchers to evaluate both policy outcomes and the reliability of AI-generated policy extraction.
The dataset links approximately 190 countries of annual macroeconomic and tourism indicators with a human-verified benchmark of 32 digital nomad visa programmes. Every policy record has been independently verified against official government websites, legislation, or primary administrative sources.
Unlike existing policy datasets that rely exclusively on automated extraction or manual summaries, DigitalNomadPolicy includes an accompanying policy validation dataset documenting the verification process, coding decisions, and agreement between LLM-generated policy attributes and human validation.
The benchmark supports research in:
- Trustworthy AI
- Human-in-the-loop verification
- Computational social science
- Policy analytics
- Digital nomad visa research
- Reproducible empirical economics
What's Included
The repository contains two complementary resources.
1. Global Macroeconomic Panel
A harmonized annual panel covering approximately 190 countries.
Variables include:
- GDP per capita
- Inflation
- Exchange rate
- Unemployment
- Internet usage
- Price level index
- International tourist arrivals
- Tourism expenditures
- Tourism contribution to GDP
- Tourism employment
The macroeconomic indicators are primarily compiled from:
- World Bank Open Data
- UN Tourism (UNWTO)
2. Human-Verified Policy Benchmark
A cross-sectional benchmark covering 32 verified digital nomad visa programmes.
Each policy record includes standardized variables describing:
- Visa adoption year
- Minimum monthly income requirement
- Visa duration
- Government application fee
- Tax treatment
- Official policy references
All policy records have been independently verified using primary legal or government sources.
3. Policy Validation Dataset
The accompanying validation dataset documents the complete human verification workflow.
For every jurisdiction, the validation files include:
- Original LLM-extracted values
- Human-verified values
- Verification status
- Supporting official sources
- Notes on discrepancies
- Coding decisions
This enables researchers to evaluate the reliability of AI-assisted policy extraction and reproduce the validation process.
Dataset Structure
DigitalNomadDataset.xlsx
βββ tourism_and_macroeconomic_data
β
βββ policy_data
β
βββ policy_validation
β
βββ documentation
All tables use ISO 3166-1 alpha-3 (iso3) country identifiers.
Data Coverage
| Component | Coverage |
|---|---|
| Countries (macroeconomic panel) | ~190 |
| Verified digital nomad programmes | 32 |
| Time coverage | 2008β2024 |
| Observation unit | Country-year (macroeconomic panel) |
| Policy unit | Country |
Data Sources
Macroeconomic indicators are compiled from:
- World Bank Open Data
- United Nations World Tourism Organization (UN Tourism)
Policy information is verified using:
- Government immigration portals
- Official legislation
- Ministry publications
- Official visa documentation
Suggested Research Applications
The benchmark is intended for research on:
- AI-assisted policy extraction
- Human verification of LLM-generated structured data
- Trustworthy AI evaluation
- Digital government
- Cross-country policy comparison
- International mobility
- Tourism economics
- Panel data analysis
- Causal inference
Potential empirical applications include:
- Difference-in-Differences
- Fixed-effects panel models
- Machine learning for policy evaluation
- Benchmarking information extraction systems
- Policy diffusion studies
Data Quality
The benchmark prioritizes transparency over aggressive data cleaning.
Policy data
Every verified policy record has been independently checked against official sources.
The validation dataset preserves:
- original LLM outputs,
- corrected values,
- verification notes,
- and supporting references.
Macroeconomic data
Missing values are retained as reported by the original statistical agencies.
Most missing observations occur in tourism-related variables because reporting practices differ substantially across countries.
Users are encouraged to apply appropriate missing-data methods depending on their analytical objectives.
Responsible Use
DigitalNomadPolicy is intended for research, benchmarking, and reproducible scientific analysis.
Users should note that:
- policy variables represent standardized interpretations of official legal documents;
- legal frameworks may change after publication;
- governments occasionally update programme requirements without announcing major revisions;
- the benchmark reflects the verification status at the time of release.
Croissant Metadata
The repository includes machine-readable Croissant metadata describing:
- dataset structure,
- variable definitions,
- provenance,
- intended uses,
- known limitations,
- and Responsible AI documentation.
This enables compatibility with Google Dataset Search, Hugging Face, and MLCommons tooling.
License
This dataset is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
You are free to share, adapt, and redistribute the dataset provided appropriate attribution is given.
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