# WP19 baseline parameterisation — ILLUSTRATIVE, not calibrated to data. # Time unit = year. Values and prices in units of the mean buyer valuation of the quality segment (q = 1). name: baseline seed: 20261020 preferences: r: 0.04 # discount rate (per year) sellers: s: 1.0 # listing inflow (normalisation; per year) delta: 0.5 # exogenous withdrawal hazard (per year): ~10-20 % of listings withdrawn at baseline hazards w0: 0.8 # seller's own-use (withdrawal) value, units of q: gains from trade ~20 % + match component c_min: 0.02 # carrying cost of the most patient seller (2 % of value per year: maintenance, taxes) c_max: 0.30 # carrying cost of the most urgent seller (30 %/yr: double housing, bridge loan, relocation, distress) n_types: 9 # discrete approximation of F (Gauss-Jacobi-like midpoints of a Beta distribution) beta_a: 2.0 # Beta(a,b) shape of F on [c_min, c_max] beta_b: 4.0 # -> right-skewed: most sellers patient, a minority urgent buyers: k: 0.02 # sunk entry cost (2 % of value: inspections, search set-up, agent engagement) kappa_b: 0.05 # flow search cost while active (5 %/yr: temporary housing, time, uncertainty) phi: 0.85 # qualification probability per meeting (baseline screen) matching: A: 4.5 # matching efficiency: meetings per year per side at theta = 1 alpha: 0.5 # elasticity of meetings w.r.t. buyers bargaining: beta: 0.5 # seller's Nash share match_values: dist: truncnorm # log-concave density => IFR (Proposition 2 conditions hold) mu: 1.0 sigma: 0.10 lo: 0.70 hi: 1.30 financing_extension: # Experiment 4 only pi: 0.30 # share of cash buyers at entry nu: 12.0 # financing resolution rate (per year): ~1 month phi: 0.85 # approval probability numerics: theta_bounds: [0.02, 60.0] root_xtol: 1.0e-12 grid_check_points: 60 dynamics: # Experiment 9 T: 8.0 # horizon (years) dt: 0.02 # time step (years), ~1 week damping: 0.3 tol: 1.0e-7 max_iter: 400