DOI: 10.5281/zenodo.17672718
title: Shared Island, Divergent Institutions: The Dominican Republic as Counterfactual Evidence for Legal Infrastructure Investment in Postcolonial Civil Law Systems

description: Dominican Republic-Haiti Property Rights Institutional Divergence Analysis

Overview

This repository contains a complete replication package for the statistical analysis comparing property rights institutions between the Dominican Republic and Haiti from 2007-2025, using International Property Rights Index (IPRI) data.

Key Finding: The analysis documents a 106.6% expansion in the institutional gap between the two countries, with Physical Property Rights (PPR) accounting for the largest divergence (3.60-point gap in 2025).

Files Included



dr_haiti_ipri_analysis.ipynb - Jupyter notebook containing all analysis code

ipri_data.xlsx or ipri_data.csv - IPRI dataset (2437 observations, 27 variables, 2007-2025)

Output files generated by analysis:



dominican_haiti_comparison.png - 4-panel time series visualization

regional_comparison.png - Regional benchmarking bar chart

dr_haiti_comparison_data.csv - Extracted time series data

summary_statistics.csv - Key statistical metrics




Running the Analysis in Google Colab

Step 1: Upload Files to Google Colab



Go to Google Colab

Click File → Upload notebook and select dr_haiti_ipri_analysis.ipynb

Once the notebook opens, upload the data file:



Click the folder icon in the left sidebar

Click the upload button (document with up arrow)

Upload ipri_data.xlsx or ipri_data.csv




Step 2: Install Required Libraries (if needed)

The notebook uses standard Python data science libraries. If any are missing, run:

!pip install pandas numpy matplotlib seaborn scipy


Step 3: Run the Analysis



Run all cells: Click Runtime → Run all in the menu

Or run sequentially: Use Shift + Enter to execute each cell in order


The notebook will:



Load and validate the IPRI dataset

Extract Dominican Republic and Haiti records

Calculate institutional divergence metrics

Generate statistical analyses (correlations, regressions)

Create visualizations

Export formatted results


Step 4: Download Results

After execution completes:



Click the folder icon in the left sidebar

Right-click generated files to download:



PNG visualizations

CSV data exports

Summary statistics




Data Structure

Dataset: 2,437 observations across 27 variables

Key Variables:



IPRI - Overall International Property Rights Index

LP - Legal and Political Environment

PPR - Physical Property Rights

IPR - Intellectual Property Rights

Año - Year (2007-2025)


Country Coverage:



Dominican Republic: 19 years (2007-2025)

Haiti: 13 years (2013-2025)


Outputs Explained

Visualizations





dominican_haiti_comparison.png - Four-panel figure showing:



Overall IPRI trends

Legal Environment (LP) comparison

Physical Property Rights (PPR) comparison

Intellectual Property (IPR) comparison





regional_comparison.png - Bar chart comparing both countries against regional benchmarks (Costa Rica, Jamaica, Panama, Colombia)



Data Exports



dr_haiti_comparison_data.csv - Time series data for both countries

summary_statistics.csv - Statistical metrics including:



Correlation coefficients

Regression slopes

Component gaps

Volatility measures




Key Statistical Results



DR IPRI change (2007-2025): +0.66 points (+16.6%)

Haiti IPRI change (2013-2025): -1.27 points (-37.3%)

Gap expansion: From 1.20 points (2013) to 2.48 points (2025)

Haiti PPR collapse: -78.8% decline (3.40 → 0.72)

Annual divergence rate: 0.0881 points/year


Citation

If you use this analysis, please cite:

[Your Name] (2025). Dominican Republic-Haiti Property Rights Institutional 
Divergence Analysis: Replication Package. Zenodo. 
https://doi.org/[DOI will be assigned]


Requirements



Python 3.7+

pandas 2.0+

numpy 1.20+

matplotlib 3.3+

seaborn 0.11+

scipy 1.7+


Support

For questions or issues with replication, please [open an issue/contact information].

License

[Specify license - e.g., CC BY 4.0, MIT, etc.]



Last updated: November 2025