Replication code for Lester (2026), \"Rational Foreclosure: A Stochastic Reference Point Model of Aspirational Abandonment under Positional Drift\"

This dataset contains the complete replication code for Lester (2026), \"Rational Foreclosure: A Stochastic Reference Point Model of Aspirational Abandonment under Positional Drift.\" The paper formalizes the decision to abandon a long-term positional race as an optimal stopping problem under loss-averse preferences with a stochastic reference point, and derives a volatility-delay theorem showing that higher reference volatility raises the option value of waiting and delays exit from losing positional races. The companion paper (Version 8) establishes existence and uniqueness of the optimal stopping boundary as a formal theorem (Theorem 1) via viscosity solution methods; see Appendix A of the working paper. The bundle includes a Python boundary value problem solver for the free-boundary problem of Section 3, three calibrated parameter sets spanning low-volatility, moderate (Genicot-Ray style), and high-volatility regimes, a reproduction script that regenerates Figure 1 of the paper with all six panels in approximately 17 seconds, and a comparative statics script that verifies the signs of all six theorems in Section 5. Every numerical claim in the paper is reproducible from this bundle alone on a standard laptop with no additional data or configuration. Full documentation is provided in the README, with a quick-start section, file manifest, verification instructions, and extension examples. The code is released under the MIT License. Citation information is provided in the included CITATION.cff file. For questions or collaboration inquiries, contact the author by email. Other Research by This Author Ryan Lester is an economist and Navy veteran at the University of Houston. For other working papers and replication data, visit: https://dataverse.harvard.edu/dataverse/ryanlester