Illinois housing market · statistical outlook
Three independent calculations use only the recorded monthly history of the Illinois RDN Market, Buy and Sell Scores. Compare central estimates with historical-error ranges and inspect how the methods performed in backtests. You can also Estimate your home's value range.
Latest stored score update: October 3, 2026.
Homeowner planning tool
Enter your own estimate and an Illinois ZIP code to apply historical area-wide home-value changes to that starting value.
Values are on a 0–100 scale. “Central estimate” is a statistical midpoint, not a predicted outcome.
Latest recorded month · Oct 2026
49.7Current recorded score / 100
Persistence — keeping the current level was historically the most accurate central estimate.
Latest recorded month · Oct 2026
40.8Current recorded score / 100
Persistence — keeping the current level was historically the most accurate central estimate.
Latest recorded month · Oct 2026
42.4Current recorded score / 100
Mean reversion toward the long-run average of 58.3.
Explore the recorded series
Solid: recorded score · Dashed: central estimate · Shading: 50% and 80% statistical ranges
The latest recorded month is the dividing line. Ranges describe variation seen in the model’s historical errors, not limits on what could happen.
RDN Market Score · Probabilities are estimates based on historical model errors, not guarantees.
| Months ahead | Month | Central estimate | 50% range | 80% range | Chance ≥ 40 | Chance ≥ 55 | Chance ≥ 70 | Typical historical error |
|---|---|---|---|---|---|---|---|---|
| 6 | Apr 2027 | 49.7 | 43–57 | 35–63 | 81% | 32% | 0% | ±8.5 pts (100 tests) |
| 12 | Oct 2027 | 49.7 | 39–59 | 30–67 | 72% | 34% | 7% | ±11.1 pts (94 tests) |
| 18 | Apr 2028 | 49.7 | 38–57 | 30–65 | 73% | 35% | 6% | ±10.7 pts (88 tests) |
| 24 | Oct 2028 | 49.7 | 40–57 | 35–68 | 76% | 28% | 9% | ±10.4 pts (82 tests) |
| 30 | Apr 2029 | 49.7 | 37–57 | 29–70 | 71% | 32% | 11% | ±12.5 pts (76 tests) |
| 36 | Oct 2029 | 49.7 | 36–60 | 26–67 | 71% | 39% | 7% | ±13.8 pts (70 tests) |
| 42 | Apr 2030 | 49.7 | 35–63 | 25–68 | 69% | 49% | 8% | ±13.8 pts (59 tests) |
| 48 | Oct 2030 | 49.7 | 43–60 | 31–68 | 77% | 51% | 2% | ±11.2 pts (47 tests) |
“Typical historical error” is mean absolute error (MAE) from out-of-sample tests at that horizon. Where there are too few backtest errors, ranges and probabilities use an in-sample residual-based approximation instead.
Candidate methods were compared at shared rolling origins using observations unavailable when each estimate was made. Lower average mean absolute error (MAE) is better.
Selected: Persistence. The selection uses the lowest average out-of-sample error across eligible horizons; ties or absent comparisons favor mean reversion when it can be fitted.
In these comparisons, the data showed no reliable trend signal beyond the current level.
12-month horizon: 94 backtests; 11.1 pts MAE. 48-month horizon: 47 backtests; 11.2 pts MAE.
Selected: Persistence. The selection uses the lowest average out-of-sample error across eligible horizons; ties or absent comparisons favor mean reversion when it can be fitted.
In these comparisons, the data showed no reliable trend signal beyond the current level.
12-month horizon: 94 backtests; 9.4 pts MAE. 48-month horizon: 47 backtests; 14 pts MAE.
Selected: Mean reversion. The selection uses the lowest average out-of-sample error across eligible horizons; ties or absent comparisons favor mean reversion when it can be fitted.
12-month horizon: 94 backtests; 11.1 pts MAE. 48-month horizon: 47 backtests; 11.4 pts MAE.
Typical errors can grow with the horizon. Historical-error ranges are not hard bounds; long horizons may have fewer backtests. Where fewer than 12 eligible backtest errors exist, the projection helper substitutes an in-sample residual-based approximation.
Method version 1.1. The score’s own recorded history is its only projection input.
Monthly score history, available from 2012 onward, is a retrospective recalculation using currently published data, including later revisions. It is not a record of what readers knew in each past month. Only the latest uninterrupted run of monthly observations is used for fitting.
Each future horizon is fitted separately. Expanding-window, rolling-origin backtests fit using observations available at each historical origin and compare against a later actual score—without looking ahead.
The candidates are persistence (no change), mean reversion toward a historical average, and regression using distance from that average plus 12-month momentum. The lowest average comparable backtest MAE selects one method for the projected path.
With enough backtest errors, 50% and 80% ranges use their empirical distribution. Threshold probabilities are the share of those errors that would place a score at or above the stated threshold. When backtests are insufficient, the helper uses an in-sample, normal-approximation fallback; those results have less independent validation.
Scores are bounded from 0 to 100. A roughly decade-and-a-half-long history is a small sample for multi-year projections. Structural breaks, new policies, economic shocks and revisions may defeat historical relationships. Some underlying score components, such as Buy Score property-tax inputs, may be unavailable in a given month.
The outlook is recalculated from stored history as scores refresh; a new monthly observation can shift every horizon. These numbers do not project the underlying source measures.
The Score projections concern Illinois RDN's editorial Market, Buy and Sell Scores, not home prices. The separate home value tool gives statistical ranges based on past Zillow ZIP, county or statewide home-value history scaled to your own estimate. It is not an appraisal or a prediction for any specific property.
It uses Zillow Home Value Index (ZHVI) history for your ZIP code, or your county or Illinois when ZIP history is too short. The methods are tested with backtests, and your entered value isn't saved.
No. It is an automated statistical analysis of recorded score history, not advice or a recommendation to buy, sell, borrow or invest. Consult a licensed professional about your circumstances.
The ranges reflect variation in historical model errors, which can be substantial, particularly farther from the latest observation. They are not limits on future scores; shocks and revisions can produce results outside them.
If keeping the latest level produced the lowest comparable backtest error, the persistence method is selected. A flat central estimate does not mean conditions are expected to remain unchanged.
Projections are recalculated from stored score history when the outlook data refreshes. The page checks for updates after one hour; a new or revised monthly score may change the results.