IvoSteimanis/payments_democracy

Replication package for "The Appearance of Democracy: How Conditional Payments Reshape Behavior Among Local Leaders" (Ecological Economics). Lab-in-the-field experiment with 64 local leaders and 384 villagers across 32 villages in northern Namibia. De-identified data, Stata/R/Python code, and every published figure and table. # Replication Package ## The Appearance of Democracy: How Conditional Payments Reshape Behavior Among Local Leaders **Authors**: Ivo Steimanis 1,+ , Esther Blanco 2,3 , Björn Vollan 1 1 Department of Economics, Philipps University Marburg, Germany 2 Department of Public Finance, University of Innsbruck, Austria 3 The Ostrom Workshop, Indiana University, USA + Corresponding author: ivo.steimanis@staff.uni-marburg.de **Published in**: Ecological Economics **Keywords**: conditional payments, democratic governance, lab-in-the-field experiment, local leaders, environmental governance, Namibia, crowding out **Note**: This study was not pre-registered. Data collection (2014) predates widespread adoption of pre-registration for lab-in-the-field experiments. --- ## Overview This repository contains the data, code, and materials to replicate all tables and figures reported in the paper and its supplementary online material (SOM). The study uses a lab-in-the-field experiment with 64 local leaders and 384 villagers across 32 villages in the Ohangwena region of northern Namibia to examine whether conditional payments for democratic governance crowd in or crowd out democratic behavior among local leaders who manage communal natural resources. --- ## Quick start 1. Download or clone this repository. 2. Open Stata and run `do run.do`. The script resolves the package root from its own path, so your working directory does not matter. 3. Run the two R scripts and the Python script (see Running the full pipeline). All output is written to `results/figures/` and `results/tables/`. --- ## Repository structure ``` . ├── README.md # This file ├── LICENSE.txt # CC-BY 4.0 ├── requirements.txt # Python dependencies ├── run.do # Master script (start here) │ ├── data/ # Raw, de-identified experimental data │ ├── leader_raw.dta # Leaders (N = 64) │ ├── villagers_raw.dt …