Housing Data & Technology Innovation Challenge

Minnesota Housing
Policy Simulator

A transparent decision tool for testing how pro-housing reforms could change housing production — and inspecting the evidence behind every assumption.

2026 STATE PERMIT NOWCAST 23,267

Permit authorizations — not starts or completions.

116.3K

Central five-year baseline, 2027–2031

59 / 87

Counties with MnGeo open parcel coverage

5

Policy scenarios with low, central and high sensitivities

7

Live public GIS evidence layers monitored by the tool

MODEL A POLICY

What changes the production outlook?

Choose a reform and sensitivity. Open advanced assumptions to see the exact parameters — and change them yourself.

CENTRAL CASE
1,617
incremental housing units over five years
Total production117,951
Lift vs. baseline+1.39%
Baseline116,333

Baseline sensitivity95.9K — 136.7K
Central baseline is intentionally simple. Policy scenarios are standalone counterfactuals; do not add them without an overlap model.

Five-year incremental units

WHY THIS TOOL

Policy analysis should expose its assumptions — not hide them.

The simulator separates the statewide production baseline from reform-specific response assumptions. Users can see what is measured, what is calibrated, what is uncertain, and what is only a sensitivity.

LIVE EVIDENCE MAP

Move from statewide scenarios to local evidence.

Map colors show evidence coverage, not predicted policy impact. Turn on live public layers to inspect parcels, permits, zoning and transit context.

County evidence Grade B — parcel or metro evidence Grade C — aggregate fallback Selected

Twin Cities residential permit units by year

Loading live Met Council data…

This chart is queried directly from the Metropolitan Council Residential Permits service at page load. It is separate from the statewide BPS baseline used by the policy model.

MODEL + VALIDATION

History, baseline and backtest.

The central baseline keeps the model deliberately legible. Historical permits, low/high sensitivity and alternative mean-reversion specifications remain visible.

Observed + baseline outlook

2003–2025 are annual permit authorizations. 2026 is a nowcast; 2027–2031 show the flat central baseline and low/high sensitivity.

Mean-reversion sensitivity

Correction: λ=0.10 has the lowest tested one-year MAE (3,144.3), slightly below λ=0 (3,168.5). The public central baseline retains λ=0 for transparency and parsimony; mean reversion remains a sensitivity.

01

Baseline

Hold the 2026 permit nowcast flat through 2027–2031. Low/high bounds use the historical 2016–2025 coefficient of variation.

02

Policy response

Each reform has its own transparent exposure and realization assumptions. The tool does not force a single elasticity across all reforms.

03

Local evidence

Live GIS layers provide parcel, permit, zoning and transit context. They validate exposure and feasibility assumptions; they are not parcel-level causal forecasts.

View policy formulas
ADUpolicy gap × detached stock × annual take-up × 5 years
Missing Middlepolicy gap × detached stock × annual activation × net units × 5 years
TODbaseline × metro multifamily share × high-frequency transit share × 2+ share × zoning-binding × capacity uplift × realization
Parkingbaseline × 2+ share × affected share × (cost relief / post-policy fee benchmark) × pass rate
Feesbaseline × threshold-crossing share
TRANSPARENCY

Live source health + provenance.

“Endpoint online” and “data current” are different questions. The table reports browser-visible service status and metadata separately.

—sources responding
—last checked
67.8%county parcel coverage
SourcePublisherTypeEndpointMetadata / vintage
USE WITH CARE

What this simulator does not claim.

It does not estimate parcel-level causal impacts.

It does not treat permits as completed homes.

It does not add policy scenarios together without an overlap model.

It does not treat missing parcel data as zero housing opportunity.

METHODOLOGY

Transparent by design.

The central production baseline is a flat extension of the 2026 permit nowcast. Low/high baseline cases apply the observed 2016–2025 coefficient of variation. Each policy module then applies an explicit exposure/realization framework calibrated from public Minnesota evidence and treated as a sensitivity rather than a causal estimate.

Interpretation rules

Backtest selection

Among tested mean-reversion speeds, λ=0.10 has the lowest one-year MAE. The difference from λ=0 is small, so the central public specification retains λ=0 for interpretability and keeps mean reversion as a sensitivity.