1{2 "experiment": 12,3 "name": "sensitivity_oat",4 "hypothesis": "Sensitivity and convergence: qualitative results (signs) are robust to +-25% parameter changes and to the G family; equilibrium objects converge in the number of seller types and in tolerances; Monte Carlo simulation of the listing process matches analytic hazards and prices.",5 "rows": 23,6 "columns": [7 "parameter",8 "mult",9 "value",10 "converged",11 "theta",12 "d_theta",13 "dlog_theta",14 "price_mean",15 "d_price_mean",16 "dlog_price_mean",17 "mean_tom_sold_months",18 "d_mean_tom_sold_months",19 "dlog_mean_tom_sold_months",20 "D_urgent",21 "d_D_urgent",22 "dlog_D_urgent",23 "D_mean",24 "d_D_mean",25 "dlog_D_mean",26 "price_between_share",27 "d_price_between_share",28 "dlog_price_between_share",29 "price_sd_total",30 "d_price_sd_total",31 "dlog_price_sd_total",32 "Q",33 "d_Q",34 "dlog_Q",35 "S",36 "d_S",37 "dlog_S",38 "welfare_total",39 "d_welfare_total",40 "dlog_welfare_total",41 "base_theta",42 "base_price_mean",43 "base_mean_tom_sold_months",44 "base_D_urgent",45 "base_D_mean",46 "base_price_between_share",47 "base_price_sd_total",48 "base_Q",49 "base_S",50 "base_welfare_total"51 ],52 "env": {53 "python": "3.14.4",54 "numpy": "2.4.4",55 "scipy": "1.17.1",56 "pandas": "3.0.2",57 "config_hash": "0a165f317815d76c",58 "seed": 20261020,59 "timestamp": "2026-10-20T08:04:46"60 }61}