Sensitivity Checks for Tourism-Environment Governance IV Estimates

Figshare dataset provides sensitivity checks for instrumental variable estimates from a study on tourism and environmental governance. The analysis uses enterprise-level data and geocoded locations of China's national 5A tourist attractions from 2014. It examines relationships between firm proximity to attractions and corporate environmental governance.

Use Cases

• Validate the robustness of IV-based estimates for the proximity-environmental governance relationship.
• Assess sensitivity of findings across alternative model specifications mentioned in the study.
• Replicate checks for the relationship's variation by attraction type (natural-landscape) and city characteristics (innovation, marketization).

Strengths

• Data underpins a peer-reviewed study with results robust across alternative specifications.
• Focuses on a specific, policy-relevant research question linking tourism, geography, and industrial environmental governance.
• Released under a permissive CC BY 4.0 license for reuse.

Limitations

• Very small scale at 9.5 KB, containing only analysis checks, not the primary enterprise-level or geospatial datasets.
• Temporal scope is limited to a single year (2014), preventing longitudinal analysis.
• Geographic coverage is restricted to China, limiting generalizability.

Provenance

Source

Figshare, authored by Xiancheng Xiong.

Collection Method

Derived from enterprise-level data and geocoded locations of China's 5A tourist attractions for a specific academic study.

Time Range

2014.

Freshness

Last updated March 2026.

Geography

China.