Code and Computational Results for “Outreach or Formation? Volunteer-Labor Allocation and Bottlenecks in Congregational Growth”

Published: 4 August 2026| Version 1 | DOI: 10.17632/zg3vg64nfm.1
Contributor:
Benoit Kudinga

Description

This dataset contains the Python code, parameter inputs, run instructions, numerical outputs, stage-pressure diagnostics, robustness results, and publication figures supporting the manuscript “Outreach or Formation? Volunteer-Labor Allocation and Bottlenecks in Congregational Growth.” It reproduces the optimized fixed allocation, the state-feedback policy, the perfect-foresight phase-adaptive benchmark, accounting and nonnegativity checks, and the 200-scenario robustness comparison. No external empirical data are used.

Files

Steps to reproduce

1. Download and extract the dataset ZIP file. 2. Place ESM_1_Reproducibility_Code.py in a writable folder. 3. Install Python 3.13.5 or a compatible version with numpy, pandas, matplotlib, and scipy. 4. Run: python ESM_1_Reproducibility_Code.py 5. The script creates a reproducibility_outputs folder containing regenerated CSV, JSON, and PNG files. All parameter inputs, initial conditions, the 60-period horizon, discount factor, canonical shock path, policy definitions, random seeds, and optimization settings are contained in the script. No external data files are required.

Categories

Cultural Economics, Computational Economics, Applied Economics

Licence