Model Lab · evidence for your home search

Understand the market behind your shortlist.

Compare buying conditions, test your budget, and explore model predictions alongside their actual outcomes.

Market tools and forecast evaluations cover the eight research cities. Compare prices and historical changes across all 25 cities →

Market conditions · observed history

How competitive is the market?

Compare homes for sale and time to reach a contract. Look at the same season a year earlier to put today’s conditions in context.

Latest captured market, rent and mortgage update

Checking the source archive… The reviewed history below keeps its published dates.

Market yearPeriod ending

Jun 2026–Aug 2026Three-month rolling window

Explore the history

Mar 2012Aug 2026

Single-family homes · Jun 2026–Aug 2026. Revised data retrieved 2026-09-16; this does not recreate what was published at the time.

Redwood City

Inventory and contract speed give a mixed picture

Homes for sale at period end: 33
Median days to a contract: 13
Closed sales over three months: 119
Median sale price: $2,361,116

See the year-earlier comparison

Aug 2026 versus Aug 2025; each sales measure spans three months.
Measure	Selected period	Year earlier
Inventory	33	25
Days to contract	13	15
Closed sales	119	111
New listings	115	84
Pending sales	104	98

San Mateo

Inventory and contract speed give a mixed picture

Homes for sale at period end: 25
Median days to a contract: 11
Closed sales over three months: 140
Median sale price: $2,148,741

See the year-earlier comparison

Aug 2026 versus Aug 2025; each sales measure spans three months.
Measure	Selected period	Year earlier
Inventory	25	40
Days to contract	11	11
Closed sales	140	136
New listings	122	147
Pending sales	123	140

Homes available over time

Homes counted in each named geography. 2012-03 to 2026-08.

Redwood City 33San Mateo 25

View exact values (174 periods)

Homes available over time: homes; missing values are unavailable
Month	Redwood City	San Mateo
2026-08	33	25
2026-07	34	21
2026-06	35	31
2026-05	38	35
2026-04	36	32
2026-03	34	38
2026-02	28	29
2026-01	22	29
2025-12	12	17
2025-11	18	30
2025-10	37	46
2025-09	38	47
2025-08	25	40
2025-07	25	45
2025-06	40	37
2025-05	51	50
2025-04	55	49
2025-03	35	46
2025-02	31	41
2025-01	24	32
2024-12	23	23
2024-11	34	33
2024-10	42	53
2024-09	52	69
2024-08	35	50
2024-07	35	36
2024-06	37	42
2024-05	32	41
2024-04	27	48
2024-03	28	31
2024-02	35	28
2024-01	35	33
2023-12	18	18
2023-11	35	38
2023-10	42	57
2023-09	45	42
2023-08	33	41
2023-07	31	38
2023-06	30	34
2023-05	27	39
2023-04	22	36
2023-03	26	35
2023-02	24	37
2023-01	31	43
2022-12	24	34
2022-11	38	54
2022-10	54	65
2022-09	53	50
2022-08	37	57
2022-07	42	77
2022-06	39	57
2022-05	41	55
2022-04	42	41
2022-03	34	29
2022-02	28	27
2022-01	19	19
2021-12	8	3
2021-11	14	26
2021-10	20	48
2021-09	36	40
2021-08	45	36
2021-07	47	54
2021-06	39	47
2021-05	37	28
2021-04	40	37
2021-03	36	34
2021-02	31	45
2021-01	34	41
2020-12	24	33
2020-11	55	51
2020-10	60	71
2020-09	71	68
2020-08	82	75
2020-07	85	77
2020-06	81	94
2020-05	71	79
2020-04	59	82
2020-03	44	60
2020-02	52	59
2020-01	36	41
2019-12	29	24
2019-11	49	42
2019-10	76	71
2019-09	73	95
2019-08	46	72
2019-07	61	72
2019-06	93	96
2019-05	109	95
2019-04	80	73
2019-03	55	51
2019-02	41	44
2019-01	41	39
2018-12	35	36
2018-11	62	62
2018-10	68	64
2018-09	63	78
2018-08	41	54
2018-07	27	48
2018-06	30	59
2018-05	30	53
2018-04	24	50
2018-03	23	27
2018-02	18	17
2018-01	24	27
2017-12	5	10
2017-11	27	19
2017-10	33	21
2017-09	36	40
2017-08	32	36
2017-07	21	26
2017-06	17	34
2017-05	19	29
2017-04	37	31
2017-03	26	30
2017-02	22	24
2017-01	19	22
2016-12	13	18
2016-11	22	33
2016-10	57	59
2016-09	54	62
2016-08	57	59
2016-07	59	71
2016-06	63	55
2016-05	57	55
2016-04	55	51
2016-03	42	33
2016-02	35	33
2016-01	22	27
2015-12	17	16
2015-11	36	27
2015-10	43	42
2015-09	42	66
2015-08	42	64
2015-07	39	51
2015-06	35	45
2015-05	31	28
2015-04	28	40
2015-03	30	26
2015-02	22	36
2015-01	16	23
2014-12	11	15
2014-11	19	25
2014-10	27	47
2014-09	48	47
2014-08	28	34
2014-07	30	35
2014-06	36	46
2014-05	41	42
2014-04	37	36
2014-03	31	38
2014-02	26	43
2014-01	20	28
2013-12	10	18
2013-11	24	18
2013-10	35	44
2013-09	39	60
2013-08	39	48
2013-07	38	41
2013-06	41	42
2013-05	48	42
2013-04	53	42
2013-03	34	40
2013-02	43	39
2013-01	30	32
2012-12	27	28
2012-11	46	42
2012-10	52	58
2012-09	52	60
2012-08	54	73
2012-07	56	73
2012-06	41	83
2012-05	58	71
2012-04	68	72
2012-03	63	76

Time to reach a contract

Median days from listing to contract for the named series. 2012-03 to 2026-08.

Redwood City 13San Mateo 11

View exact values (174 periods)

Time to reach a contract: days; missing values are unavailable
Month	Redwood City	San Mateo
2026-08	13	11
2026-07	12	12
2026-06	10	12
2026-05	9	12
2026-04	10	11
2026-03	11	11
2026-02	15	14
2026-01	17	14
2025-12	15	13
2025-11	14	12
2025-10	14	11
2025-09	19	12
2025-08	15	11
2025-07	15	12
2025-06	12	12
2025-05	12	12
2025-04	10	12
2025-03	11	12
2025-02	13	13
2025-01	15	15
2024-12	14	15
2024-11	14	15
2024-10	14	13
2024-09	14	12
2024-08	10	11
2024-07	10	11
2024-06	9	10
2024-05	9	10
2024-04	9	11
2024-03	11	12
2024-02	15	13
2024-01	21	15
2023-12	19	13
2023-11	13	11
2023-10	12	11
2023-09	11	12
2023-08	11	12
2023-07	11	10
2023-06	13	11
2023-05	14	11
2023-04	18	14
2023-03	16	13
2023-02	20	16
2023-01	27	25
2022-12	24	20
2022-11	18	22
2022-10	13	18
2022-09	13	16
2022-08	12	13
2022-07	10	12
2022-06	10	10
2022-05	9	8
2022-04	8	8
2022-03	8	8
2022-02	10	12
2022-01	9	12
2021-12	11	11
2021-11	11	10
2021-10	12	10
2021-09	11	10
2021-08	9	9
2021-07	8	9
2021-06	8	9
2021-05	9	10
2021-04	9	10
2021-03	11	10
2021-02	20	14
2021-01	25	15
2020-12	20	17
2020-11	18	16
2020-10	16	22
2020-09	18	28
2020-08	19	33
2020-07	24	34
2020-06	24	33
2020-05	21	23
2020-04	20	15
2020-03	27	16
2020-02	39	29
2020-01	32	33
2019-12	26	29
2019-11	22	27
2019-10	30	26
2019-09	33	27
2019-08	32	22
2019-07	28	20
2019-06	24	17
2019-05	18	14
2019-04	15	13
2019-03	23	27
2019-02	31	31
2019-01	30	28
2018-12	24	18
2018-11	18	16
2018-10	12	15
2018-09	11	14
2018-08	12	14
2018-07	11	12
2018-06	11	12
2018-05	10	11
2018-04	11	12
2018-03	12	12
2018-02	13	12
2018-01	13	13
2017-12	12	12
2017-11	11	13
2017-10	11	12
2017-09	11	11
2017-08	11	11
2017-07	11	11
2017-06	11	11
2017-05	11	10
2017-04	12	11
2017-03	17	13
2017-02	14	19
2017-01	16	21
2016-12	20	24
2016-11	26	22
2016-10	27	16
2016-09	23	14
2016-08	16	13
2016-07	15	13
2016-06	13	13
2016-05	13	12
2016-04	13	12
2016-03	12	14
2016-02	16	14
2016-01	13	14
2015-12	15	16
2015-11	13	16
2015-10	13	16
2015-09	13	13
2015-08	12	13
2015-07	11	12
2015-06	11	11
2015-05	11	10
2015-04	11	11
2015-03	10	11
2015-02	12	14
2015-01	14	18
2014-12	13	15
2014-11	12	14
2014-10	11	13
2014-09	12	13
2014-08	12	13
2014-07	12	13
2014-06	12	12
2014-05	11	11
2014-04	10	11
2014-03	12	12
2014-02	13	13
2014-01	13	14
2013-12	13	14
2013-11	12	13
2013-10	12	12
2013-09	13	11
2013-08	12	11
2013-07	12	12
2013-06	11	12
2013-05	11	12
2013-04	12	13
2013-03	13	13
2013-02	13	13
2013-01	12	14
2012-12	13	13
2012-11	14	13
2012-10	14	13
2012-09	13	14
2012-08	13	14
2012-07	14	13
2012-06	15	14
2012-05	15	15
2012-04	18	18
2012-03	28	21

Use this when you review a listing

More available homes and longer marketing times can give you more options to investigate. Ask how the actual property compares with other listings in its price range. These city observations do not predict your offer’s outcome.

What the data and research support

Redfin’s sales and prices cover completed sales; contract time covers homes going under contract. Those populations differ. Inventory is the count at period end. Rolling windows overlap, so adding them would double-count activity. A changing median price can reflect the mix of homes sold.

Year-earlier differences are calculated from retained levels. The two-direction summary appears only when both periods have at least ten closed sales and the two required measures. It describes the observations, with no fitted score or forecast.

Listing behavior motivated this view. The Federal Reserve listing study and buyer-search study use richer inputs and different geographies. This view is not a replication of those forecasts.

Redfin definitions Research and data coverage Download the evidence

Market outlook · experimental

Will homes take longer to reach a contract?

Apply four ways of thinking about the market. Compare what each predicts for the next quarter, then inspect its past misses.

One clear target: days from listing to contract

Longer contract times may give buyers more time to compare listings. This forecasts a city’s median for a calendar quarter, not a particular home’s selling time or price.

No added model earned selection. Same season remains the baseline. See the historical comparison below.

Forecast yearForecast quarter

Oct–Dec 2026Frozen on 2026-09-16

Current blend: Same season 100%.

Apply models and adjust their weights

Weights express your scenario. They are normalized to 100%; they are not probabilities. Changing them recomputes the historical comparison too. This experiment is separate from the annual price-forecast weights.

Current pace

Contract time stays at the latest observed pace.

The most recent eligible three-month window.Current pace weight0 (0% of blend)

Same season

Next quarter resembles the same quarter last year.

The same calendar quarter one year earlier. The retained baseline.Same season weight100 (100% of blend)

Contract-time trend

Recent changes in contract speed help explain what comes next.

Changes in contract days over three months and one year; fitted on other California cities.Contract-time trend weight0 (0% of blend)

Supply & demand

Homes available and the flow of new listings and contracts add information.

Contract-time trends, inventory relative to sales, inventory and sales growth, and pending contracts relative to new listings.Supply & demand weight0 (0% of blend)

Redwood City

Your scenario · Oct–Dec 202615 days

Latest input: 13 days · window ending 2026-08-31. Target: 2026-10-01–2026-12-31.

Check the live outcome record below for progress. The frozen study predictions remain unchanged when you adjust these weights.

See every model’s prediction

Redwood City, Oct–Dec 2026, median days to contract
Current pace	13 days
Same season	15 days
Contract-time trend	14.6 days
Supply & demand	18.7 days
Equal blend	15.3 days

Latest training outcome: 2026-06-30. 14,606 peer training rows, 49 quarter origins. Inputs stop at 2026-08-31.

San Mateo

Your scenario · Oct–Dec 202613 days

Latest input: 11 days · window ending 2026-08-31. Target: 2026-10-01–2026-12-31.

Check the live outcome record below for progress. The frozen study predictions remain unchanged when you adjust these weights.

See every model’s prediction

San Mateo, Oct–Dec 2026, median days to contract
Current pace	11 days
Same season	13 days
Contract-time trend	13.1 days
Supply & demand	9.9 days
Equal blend	11.7 days

Latest training outcome: 2026-06-30. 14,606 peer training rows, 49 quarter origins. Inputs stop at 2026-08-31.

How large were the misses?

The selection period chose the baseline. Later history checks that decision without changing it. Both are exploratory replays using today’s revised source history and an assumed one-month reporting allowance.

Evaluation period

Your cities and weights · average miss3.1 days

Same-season average miss · same rows3.1 days

Largest scenario miss13 days

34 comparable city/quarter rows across 17 quarter origins and 2 selected cities. Average miss is mean absolute error in days; it is not a confidence interval.

Redwood City: scenario versus observed contract time

Median days from listing to contract for the named series. 2022 Q2 to 2026 Q2.

Your scenario 12Observed 10

View exact values (17 periods)

Redwood City: scenario versus observed contract time: days; missing values are unavailable
Quarter	Your scenario	Observed
2026 Q2	12	10
2026 Q1	11	11
2025 Q4	14	15
2025 Q3	14	19
2025 Q2	9	12
2025 Q1	11	11
2024 Q4	19	14
2024 Q3	11	14
2024 Q2	13	9
2024 Q1	16	11
2023 Q4	24	19
2023 Q3	13	11
2023 Q2	10	13
2023 Q1	8	16
2022 Q4	11	24
2022 Q3	11	13
2022 Q2	8	10

The CSV includes the full available replay and forward scenario with your weights. It is a scenario export, not a new registered forecast.

Full study comparison and selection rule

All eight covered cities, single-family homes. Average absolute miss in days.
Model	Selection period	Later replay
Current pace	7 days	5.8 days
Same season	9.8 days	5.2 days
Contract-time trend	7.6 days	5.7 days
Supply & demand	6.6 days	5.3 days
Equal blend	6.7 days	4.7 days

No candidate passed the prespecified sample, improvement and consistency gate. Retain same-season baseline. A candidate must improve average error at least 10% against both simple baselines, beat same season in at least 7 of 12 origins, and meet the minimum local sample. The sample gate passed.

The selection period has 96 comparable rows and 12 origins; later replay has 136 rows and 17 origins. There are no random city-row splits, and training targets end before each input cutoff. Other California cities can still share regional shocks.

Coefficient fitting uses 299 other California cities; our eight cities are evaluated separately. Neighboring markets are correlated, so city counts overstate independent evidence.

The next live check

October–December 2026: keep the prediction, check the outcome

Thirteen city/home-type forecasts were frozen before October 1. Each week, the data worker captures source evidence. After December 31, it locks each first eligible outcome and reports errors. Thin or missing outcomes remain pending.

Checking the capture record…

Capture status and locked outcomes Latest captured observations and sources

Download the study and source references Frozen October–December predictions What remains untested

Source: Redfin Data Center, retrieved 2026-09-16. Contract-time medians and closed-sales counts describe different transaction populations. The ten-sale quality rule is not a calibrated uncertainty claim. Public 2025 outcomes were already inspected; this is not an untouched historical test.

Rent or buy · your cost scenario

What could owning cost you?

Start with a home price and rent for a comparable home. See the monthly budget, equity built through repayments, and how your assumptions change the longer-term comparison.

Use a dated local price or rent benchmark

Local benchmarks to help you start

Sale prices are for single-family homes. Rental benchmarks include all rental housing and multifamily. They describe different populations; use a comparable property’s rent for your decision.

Redwood City

$2,361,116Median sale price · Jun 2026–Aug 2026

$4,077 / monthCity-wide rental benchmark · Jul 2026

San Mateo

$2,148,741Median sale price · Jun 2026–Aug 2026

$3,821 / monthCity-wide rental benchmark · Jul 2026

Your assumptions

Enter your own figures, or use a benchmark above. Inputs stay in this page; they are not sent to the server.

Home price ($)Comparable monthly rent ($)Down payment (%)Mortgage interest rate (%)Years you expect to stayAssumed yearly home-price change (%)

Starting mortgage rate: Freddie Mac’s 6.76% national 30-year average, 2026-09-10. Replace it with your lender’s quote, especially for a jumbo loan or different loan term.

Home-price change is your assumption. The starting 0% holds the price flat. It is not a prediction from the research models.

Edit taxes, fees and other assumptions

Taxes, insurance, upkeep and transaction costs start as examples. Check the actual property and your loan terms. Recurring-cost growth is an assumption, not a projection of local tax rules.

Loan term (years)Annual property tax (% of purchase price)Home insurance per month ($)Annual maintenance (% of purchase price)HOA fees per month ($)Mortgage insurance per month ($)Buying costs (% of purchase price)Selling costs (% of sale price)Assumed yearly rent increase (%)Assumed yearly increase in recurring costs (%)Alternative annual return on your cash (%)

Current cost assumptions: 1.2% property tax per year, $250 insurance per month, 1% annual upkeep, $0 HOA per month, 2% buying costs and 5% selling costs. Loan term: 30 years.

Build your comparison

Enter a home price and comparable rent, or use the local benchmarks above.

Start with your budget

What price fits your monthly limit and cash?

Uses the down payment, financing, taxes, upkeep, insurance, HOA and buying fees above. Enter cash set aside for the purchase after keeping your emergency reserves. This estimates a spending limit, not lender approval.

Monthly ownership budget ($)Cash available for the purchase ($)

Enter both budgets and valid cost assumptions to calculate a price limit. Mortgage insurance must be specified when required above.

Explore mortgage rates and purchasing power over time

Freddie Mac PMMS, retrieved from FRED, Federal Reserve Bank of St. Louis. 2,894 weekly observations through 2026-09-10. This national conforming-loan benchmark is not a quote for a Bay Area jumbo borrower. The method changed on November 17, 2022.

Mortgage history year

6.76% on 2026-09-10, the last available observation in 2026. At that fixed rate a $100,000, 30-year loan has a $649 monthly principal-and-interest payment, before all other costs.

National 30-year mortgage rate history

Annual interest rate, percent. 1971-04 to 2026-09.

Monthly average of observed weekly rates 6.7%

View exact values (666 periods)

National 30-year mortgage rate history: percent; missing values are unavailable
Month	Monthly average of observed weekly rates
2026-09	6.73%
2026-08	6.67%
2026-07	6.54%
2026-06	6.49%
2026-05	6.44%
2026-04	6.33%
2026-03	6.18%
2026-02	6.05%
2026-01	6.10%
2025-12	6.19%
2025-11	6.24%
2025-10	6.25%
2025-09	6.35%
2025-08	6.59%
2025-07	6.72%
2025-06	6.82%
2025-05	6.82%
2025-04	6.72%
2025-03	6.65%
2025-02	6.84%
2025-01	6.96%
2024-12	6.71%
2024-11	6.80%
2024-10	6.43%
2024-09	6.18%
2024-08	6.50%
2024-07	6.85%
2024-06	6.92%
2024-05	7.06%
2024-04	6.99%
2024-03	6.82%
2024-02	6.78%
2024-01	6.64%
2023-12	6.81%
2023-11	7.44%
2023-10	7.62%
2023-09	7.20%
2023-08	7.07%
2023-07	6.84%
2023-06	6.71%
2023-05	6.42%
2023-04	6.34%
2023-03	6.54%
2023-02	6.26%
2023-01	6.27%
2022-12	6.36%
2022-11	6.80%
2022-10	6.90%
2022-09	6.11%
2022-08	5.22%
2022-07	5.41%
2022-06	5.52%
2022-05	5.23%
2022-04	4.98%
2022-03	4.17%
2022-02	3.76%
2022-01	3.45%
2021-12	3.10%
2021-11	3.07%
2021-10	3.07%
2021-09	2.90%
2021-08	2.84%
2021-07	2.87%
2021-06	2.98%
2021-05	2.96%
2021-04	3.06%
2021-03	3.08%
2021-02	2.81%
2021-01	2.73%
2020-12	2.68%
2020-11	2.77%
2020-10	2.83%
2020-09	2.89%
2020-08	2.94%
2020-07	3.02%
2020-06	3.16%
2020-05	3.23%
2020-04	3.31%
2020-03	3.45%
2020-02	3.46%
2020-01	3.62%
2019-12	3.72%
2019-11	3.69%
2019-10	3.69%
2019-09	3.61%
2019-08	3.62%
2019-07	3.77%
2019-06	3.80%
2019-05	4.07%
2019-04	4.14%
2019-03	4.26%
2019-02	4.37%
2019-01	4.46%
2018-12	4.64%
2018-11	4.87%
2018-10	4.83%
2018-09	4.63%
2018-08	4.55%
2018-07	4.53%
2018-06	4.57%
2018-05	4.59%
2018-04	4.47%
2018-03	4.44%
2018-02	4.33%
2018-01	4.03%
2017-12	3.95%
2017-11	3.92%
2017-10	3.90%
2017-09	3.81%
2017-08	3.88%
2017-07	3.97%
2017-06	3.90%
2017-05	4.01%
2017-04	4.04%
2017-03	4.20%
2017-02	4.17%
2017-01	4.15%
2016-12	4.20%
2016-11	3.77%
2016-10	3.47%
2016-09	3.46%
2016-08	3.44%
2016-07	3.44%
2016-06	3.57%
2016-05	3.60%
2016-04	3.60%
2016-03	3.69%
2016-02	3.66%
2016-01	3.87%
2015-12	3.96%
2015-11	3.94%
2015-10	3.80%
2015-09	3.89%
2015-08	3.90%
2015-07	4.05%
2015-06	3.98%
2015-05	3.84%
2015-04	3.67%
2015-03	3.77%
2015-02	3.71%
2015-01	3.67%
2014-12	3.86%
2014-11	4.00%
2014-10	4.04%
2014-09	4.16%
2014-08	4.12%
2014-07	4.13%
2014-06	4.16%
2014-05	4.19%
2014-04	4.34%
2014-03	4.34%
2014-02	4.30%
2014-01	4.43%
2013-12	4.46%
2013-11	4.25%
2013-10	4.19%
2013-09	4.49%
2013-08	4.46%
2013-07	4.37%
2013-06	4.07%
2013-05	3.54%
2013-04	3.45%
2013-03	3.57%
2013-02	3.53%
2013-01	3.41%
2012-12	3.35%
2012-11	3.35%
2012-10	3.38%
2012-09	3.50%
2012-08	3.60%
2012-07	3.55%
2012-06	3.67%
2012-05	3.80%
2012-04	3.91%
2012-03	3.95%
2012-02	3.89%
2012-01	3.92%
2011-12	3.96%
2011-11	3.99%
2011-10	4.07%
2011-09	4.11%
2011-08	4.27%
2011-07	4.54%
2011-06	4.51%
2011-05	4.64%
2011-04	4.84%
2011-03	4.84%
2011-02	4.95%
2011-01	4.75%
2010-12	4.71%
2010-11	4.30%
2010-10	4.23%
2010-09	4.35%
2010-08	4.43%
2010-07	4.56%
2010-06	4.74%
2010-05	4.89%
2010-04	5.10%
2010-03	4.97%
2010-02	4.99%
2010-01	5.03%
2009-12	4.93%
2009-11	4.88%
2009-10	4.95%
2009-09	5.06%
2009-08	5.19%
2009-07	5.22%
2009-06	5.42%
2009-05	4.86%
2009-04	4.81%
2009-03	5.00%
2009-02	5.13%
2009-01	5.05%
2008-12	5.29%
2008-11	6.09%
2008-10	6.20%
2008-09	6.04%
2008-08	6.48%
2008-07	6.43%
2008-06	6.32%
2008-05	6.04%
2008-04	5.92%
2008-03	5.97%
2008-02	5.92%
2008-01	5.76%
2007-12	6.10%
2007-11	6.21%
2007-10	6.38%
2007-09	6.38%
2007-08	6.57%
2007-07	6.70%
2007-06	6.66%
2007-05	6.26%
2007-04	6.18%
2007-03	6.16%
2007-02	6.29%
2007-01	6.22%
2006-12	6.13%
2006-11	6.24%
2006-10	6.36%
2006-09	6.40%
2006-08	6.52%
2006-07	6.76%
2006-06	6.68%
2006-05	6.60%
2006-04	6.51%
2006-03	6.32%
2006-02	6.25%
2006-01	6.15%
2005-12	6.27%
2005-11	6.33%
2005-10	6.06%
2005-09	5.77%
2005-08	5.82%
2005-07	5.70%
2005-06	5.58%
2005-05	5.72%
2005-04	5.86%
2005-03	5.93%
2005-02	5.63%
2005-01	5.71%
2004-12	5.75%
2004-11	5.73%
2004-10	5.72%
2004-09	5.75%
2004-08	5.87%
2004-07	6.06%
2004-06	6.29%
2004-05	6.27%
2004-04	5.83%
2004-03	5.45%
2004-02	5.63%
2004-01	5.71%
2003-12	5.88%
2003-11	5.93%
2003-10	5.95%
2003-09	6.15%
2003-08	6.26%
2003-07	5.63%
2003-06	5.23%
2003-05	5.48%
2003-04	5.81%
2003-03	5.75%
2003-02	5.84%
2003-01	5.92%
2002-12	6.05%
2002-11	6.07%
2002-10	6.11%
2002-09	6.09%
2002-08	6.29%
2002-07	6.49%
2002-06	6.65%
2002-05	6.81%
2002-04	6.99%
2002-03	7.01%
2002-02	6.89%
2002-01	7.00%
2001-12	7.07%
2001-11	6.66%
2001-10	6.62%
2001-09	6.82%
2001-08	6.95%
2001-07	7.13%
2001-06	7.16%
2001-05	7.14%
2001-04	7.08%
2001-03	6.95%
2001-02	7.05%
2001-01	7.03%
2000-12	7.38%
2000-11	7.75%
2000-10	7.79%
2000-09	7.91%
2000-08	8.03%
2000-07	8.15%
2000-06	8.29%
2000-05	8.51%
2000-04	8.15%
2000-03	8.24%
2000-02	8.33%
2000-01	8.21%
1999-12	7.91%
1999-11	7.74%
1999-10	7.85%
1999-09	7.82%
1999-08	7.94%
1999-07	7.63%
1999-06	7.55%
1999-05	7.15%
1999-04	6.92%
1999-03	7.04%
1999-02	6.81%
1999-01	6.79%
1998-12	6.74%
1998-11	6.87%
1998-10	6.71%
1998-09	6.72%
1998-08	6.92%
1998-07	6.95%
1998-06	7.00%
1998-05	7.14%
1998-04	7.14%
1998-03	7.13%
1998-02	7.04%
1998-01	6.99%
1997-12	7.10%
1997-11	7.21%
1997-10	7.29%
1997-09	7.43%
1997-08	7.48%
1997-07	7.50%
1997-06	7.69%
1997-05	7.94%
1997-04	8.14%
1997-03	7.90%
1997-02	7.65%
1997-01	7.82%
1996-12	7.60%
1996-11	7.62%
1996-10	7.92%
1996-09	8.23%
1996-08	8.00%
1996-07	8.25%
1996-06	8.32%
1996-05	8.07%
1996-04	7.93%
1996-03	7.62%
1996-02	7.08%
1996-01	7.03%
1995-12	7.20%
1995-11	7.38%
1995-10	7.47%
1995-09	7.64%
1995-08	7.86%
1995-07	7.61%
1995-06	7.57%
1995-05	7.96%
1995-04	8.32%
1995-03	8.46%
1995-02	8.83%
1995-01	9.15%
1994-12	9.20%
1994-11	9.17%
1994-10	8.93%
1994-09	8.64%
1994-08	8.51%
1994-07	8.61%
1994-06	8.40%
1994-05	8.60%
1994-04	8.32%
1994-03	7.67%
1994-02	7.15%
1994-01	7.06%
1993-12	7.17%
1993-11	7.16%
1993-10	6.83%
1993-09	6.92%
1993-08	7.11%
1993-07	7.21%
1993-06	7.42%
1993-05	7.46%
1993-04	7.47%
1993-03	7.50%
1993-02	7.68%
1993-01	7.99%
1992-12	8.21%
1992-11	8.30%
1992-10	8.09%
1992-09	7.92%
1992-08	7.97%
1992-07	8.13%
1992-06	8.51%
1992-05	8.67%
1992-04	8.85%
1992-03	8.93%
1992-02	8.76%
1992-01	8.43%
1991-12	8.50%
1991-11	8.71%
1991-10	8.86%
1991-09	9.01%
1991-08	9.24%
1991-07	9.57%
1991-06	9.62%
1991-05	9.47%
1991-04	9.49%
1991-03	9.50%
1991-02	9.37%
1991-01	9.64%
1990-12	9.67%
1990-11	10.01%
1990-10	10.18%
1990-09	10.18%
1990-08	10.10%
1990-07	10.04%
1990-06	10.16%
1990-05	10.48%
1990-04	10.37%
1990-03	10.27%
1990-02	10.20%
1990-01	9.89%
1989-12	9.74%
1989-11	9.77%
1989-10	9.95%
1989-09	10.13%
1989-08	9.98%
1989-07	9.88%
1989-06	10.20%
1989-05	10.77%
1989-04	11.05%
1989-03	11.03%
1989-02	10.64%
1989-01	10.73%
1988-12	10.61%
1988-11	10.27%
1988-10	10.30%
1988-09	10.48%
1988-08	10.60%
1988-07	10.43%
1988-06	10.46%
1988-05	10.46%
1988-04	10.20%
1988-03	9.93%
1988-02	9.89%
1988-01	10.38%
1987-12	10.64%
1987-11	10.65%
1987-10	11.26%
1987-09	10.89%
1987-08	10.33%
1987-07	10.28%
1987-06	10.54%
1987-05	10.60%
1987-04	9.83%
1987-03	9.04%
1987-02	9.08%
1987-01	9.20%
1986-12	9.31%
1986-11	9.70%
1986-10	9.97%
1986-09	10.01%
1986-08	10.20%
1986-07	10.51%
1986-06	10.68%
1986-05	10.14%
1986-04	9.94%
1986-03	10.08%
1986-02	10.71%
1986-01	10.89%
1985-12	11.26%
1985-11	11.78%
1985-10	12.13%
1985-09	12.19%
1985-08	12.19%
1985-07	12.03%
1985-06	12.21%
1985-05	12.91%
1985-04	13.19%
1985-03	13.17%
1985-02	12.92%
1985-01	13.07%
1984-12	13.18%
1984-11	13.64%
1984-10	14.13%
1984-09	14.35%
1984-08	14.47%
1984-07	14.67%
1984-06	14.42%
1984-05	13.94%
1984-04	13.65%
1984-03	13.39%
1984-02	13.23%
1984-01	13.37%
1983-12	13.42%
1983-11	13.44%
1983-10	13.53%
1983-09	13.73%
1983-08	13.81%
1983-07	13.42%
1983-06	12.87%
1983-05	12.63%
1983-04	12.78%
1983-03	12.80%
1983-02	13.04%
1983-01	13.25%
1982-12	13.62%
1982-11	13.82%
1982-10	14.61%
1982-09	15.43%
1982-08	16.27%
1982-07	16.82%
1982-06	16.70%
1982-05	16.68%
1982-04	16.89%
1982-03	17.16%
1982-02	17.60%
1982-01	17.48%
1981-12	16.95%
1981-11	17.83%
1981-10	18.45%
1981-09	18.16%
1981-08	17.29%
1981-07	16.83%
1981-06	16.70%
1981-05	16.40%
1981-04	15.58%
1981-03	15.40%
1981-02	15.13%
1981-01	14.90%
1980-12	14.79%
1980-11	14.21%
1980-10	13.79%
1980-09	13.20%
1980-08	12.56%
1980-07	12.19%
1980-06	12.71%
1980-05	14.26%
1980-04	16.33%
1980-03	15.28%
1980-02	13.04%
1980-01	12.88%
1979-12	12.90%
1979-11	12.83%
1979-10	11.64%
1979-09	11.30%
1979-08	11.09%
1979-07	11.09%
1979-06	11.04%
1979-05	10.69%
1979-04	10.50%
1979-03	10.43%
1979-02	10.41%
1979-01	10.39%
1978-12	10.35%
1978-11	10.11%
1978-10	9.86%
1978-09	9.76%
1978-08	9.79%
1978-07	9.74%
1978-06	9.71%
1978-05	9.57%
1978-04	9.36%
1978-03	9.20%
1978-02	9.14%
1978-01	9.02%
1977-12	8.96%
1977-11	8.92%
1977-10	8.92%
1977-09	8.90%
1977-08	8.94%
1977-07	8.94%
1977-06	8.86%
1977-05	8.83%
1977-04	8.75%
1977-03	8.69%
1977-02	8.67%
1977-01	8.72%
1976-12	8.79%
1976-11	8.81%
1976-10	8.93%
1976-09	8.98%
1976-08	9.00%
1976-07	8.93%
1976-06	8.85%
1976-05	8.77%
1976-04	8.73%
1976-03	8.75%
1976-02	8.81%
1976-01	9.02%
1975-12	9.10%
1975-11	9.14%
1975-10	9.22%
1975-09	9.13%
1975-08	8.94%
1975-07	8.89%
1975-06	8.89%
1975-05	8.91%
1975-04	8.82%
1975-03	8.90%
1975-02	9.11%
1975-01	9.43%
1974-12	9.62%
1974-11	9.79%
1974-10	9.98%
1974-09	9.96%
1974-08	9.59%
1974-07	9.28%
1974-06	9.09%
1974-05	8.97%
1974-04	8.58%
1974-03	8.41%
1974-02	8.46%
1974-01	8.54%
1973-12	8.54%
1973-11	8.58%
1973-10	8.77%
1973-09	8.81%
1973-08	8.50%
1973-07	8.05%
1973-06	7.73%
1973-05	7.65%
1973-04	7.54%
1973-03	7.46%
1973-02	7.44%
1973-01	7.44%
1972-12	7.44%
1972-11	7.43%
1972-10	7.42%
1972-09	7.42%
1972-08	7.40%
1972-07	7.39%
1972-06	7.37%
1972-05	7.37%
1972-04	7.29%
1972-03	7.30%
1972-02	7.32%
1972-01	7.44%
1971-12	7.48%
1971-11	7.55%
1971-10	7.63%
1971-09	7.69%
1971-08	7.70%
1971-07	7.60%
1971-06	7.53%
1971-05	7.43%
1971-04	7.31%

Monthly chart values average the observations dated in each month; the latest month can be partial. These are current-vintage data. A historical rate applied to today’s price is a scenario, not a reconstruction of historical affordability.

Explore the city-wide rent history

Zillow Observed Rent Index, all rental homes and multifamily, smoothed and not seasonally adjusted. Missing months remain missing. A rent index divided by a sale-price median is not a matched-property rental yield.

Rent observation month

Rental benchmarks for Jul 2026
City	Monthly rental benchmark
Redwood City	$4,077
San Mateo	$3,821

City-wide rents over time

Nominal dollars. Each series covers the named geography. 2015-04 to 2026-07.

Redwood City $4.1KSan Mateo $3.8K

View exact values (136 periods)

City-wide rents over time: nominal USD; missing values are unavailable
Month	Redwood City	San Mateo
2026-07	$4,077	$3,821
2026-06	$4,007	$3,745
2026-05	$3,897	$3,690
2026-04	$3,845	$3,641
2026-03	$3,798	$3,591
2026-02	$3,764	$3,549
2026-01	$3,732	$3,522
2025-12	$3,722	$3,529
2025-11	$3,761	$3,540
2025-10	$3,766	$3,560
2025-09	$3,765	$3,565
2025-08	$3,754	$3,559
2025-07	$3,756	$3,551
2025-06	$3,744	$3,533
2025-05	$3,719	$3,513
2025-04	$3,665	$3,478
2025-03	$3,622	$3,463
2025-02	$3,577	$3,405
2025-01	$3,572	$3,365
2024-12	$3,545	$3,316
2024-11	$3,542	$3,327
2024-10	$3,568	$3,338
2024-09	$3,593	$3,351
2024-08	$3,611	$3,359
2024-07	$3,581	$3,363
2024-06	$3,565	$3,349
2024-05	$3,517	$3,319
2024-04	$3,479	$3,286
2024-03	$3,433	$3,260
2024-02	$3,406	$3,224
2024-01	$3,392	$3,192
2023-12	$3,400	$3,185
2023-11	$3,395	$3,200
2023-10	$3,407	$3,229
2023-09	$3,416	$3,245
2023-08	$3,459	$3,266
2023-07	$3,482	$3,264
2023-06	$3,480	$3,249
2023-05	$3,477	$3,228
2023-04	$3,436	$3,225
2023-03	$3,408	$3,206
2023-02	$3,361	$3,177
2023-01	$3,343	$3,137
2022-12	$3,339	$3,139
2022-11	$3,372	$3,173
2022-10	$3,429	$3,221
2022-09	$3,478	$3,258
2022-08	$3,526	$3,280
2022-07	$3,529	$3,288
2022-06	$3,498	$3,264
2022-05	$3,452	$3,237
2022-04	$3,396	$3,204
2022-03	$3,347	$3,169
2022-02	$3,280	$3,121
2022-01	$3,239	$3,060
2021-12	$3,238	$3,039
2021-11	$3,255	$3,027
2021-10	$3,294	$3,065
2021-09	$3,290	$3,075
2021-08	$3,280	$3,057
2021-07	$3,233	$2,989
2021-06	$3,174	$2,919
2021-05	$3,108	$2,877
2021-04	$3,053	$2,856
2021-03	$3,037	$2,851
2021-02	$3,033	$2,856
2021-01	$3,009	$2,868
2020-12	$3,020	$2,894
2020-11	$3,042	$2,938
2020-10	$3,103	$2,983
2020-09	$3,165	$3,031
2020-08	$3,226	$3,073
2020-07	$3,314	$3,110
2020-06	$3,367	$3,120
2020-05	$3,448	$3,140
2020-04	$3,459	$3,154
2020-03	$3,459	$3,165
2020-02	$3,402	$3,167
2020-01	$3,383	$3,150
2019-12	$3,386	$3,167
2019-11	$3,407	$3,157
2019-10	$3,408	$3,190
2019-09	$3,428	$3,222
2019-08	$3,421	$3,228
2019-07	$3,428	$3,187
2019-06	$3,411	$3,141
2019-05	$3,362	$3,112
2019-04	$3,325	$3,113
2019-03	$3,293	$3,066
2019-02	$3,293	$3,043
2019-01	$3,283	$3,053
2018-12	$3,241	$3,079
2018-11	$3,272	$3,102
2018-10	$3,295	$3,089
2018-09	$3,320	$3,095
2018-08	$3,320	$3,098
2018-07	$3,283	$3,108
2018-06	$3,247	$3,060
2018-05	$3,168	$3,007
2018-04	$3,166	$2,969
2018-03	$3,177	$2,975
2018-02	$3,196	$2,989
2018-01	$3,166	$2,971
2017-12	$3,151	$2,968
2017-11	$3,167	$2,972
2017-10	$3,196	$2,984
2017-09	$3,196	$2,978
2017-08	$3,178	$2,998
2017-07	$3,183	$2,987
2017-06	$3,172	$2,969
2017-05	$3,132	$2,942
2017-04	$3,068	$2,935
2017-03	$3,069	$2,929
2017-02	$3,080	$2,865
2017-01	$3,087	$2,871
2016-12	$3,080	$2,870
2016-11	$3,055	$2,895
2016-10	$3,070	$2,877
2016-09	$3,046	$2,886
2016-08	$3,117	$2,884
2016-07	$3,093	$2,871
2016-06	$3,075	$2,867
2016-05	$3,006	$2,855
2016-04	$2,994	$2,827
2016-03	$3,000	$2,791
2016-02	$3,078	$2,794
2016-01	$3,090	$2,804
2015-12	Unavailable	$2,813
2015-11	$2,982	$2,816
2015-10	$2,966	$2,820
2015-09	$3,015	$2,805
2015-08	$3,002	$2,798
2015-07	$2,978	$2,740
2015-06	$2,944	$2,710
2015-05	$2,866	$2,624
2015-04	$2,839	$2,631

Why rents and ownership costs belong in the lab

They make the price of a home easier to interpret. They also give us a separate longer-term hypothesis to test. Your cost assumptions do not become an appreciation forecast or a weight in the forecast mixer.

Research on prices and rents Research on ownership cost Data coverage and limits

Jobs & housing · structural evidence

Is housing keeping up with local growth?

See how employment and the number of homes changed. Housing-stock totals let us compare construction across cities of different sizes.

Supply comparison year

Housing: January 1. Jobs: Q2 snapshot. Completions: full calendar year.All housing types. Job history currently ends in 2023.

2023 snapshots and three-year growth through 2023. The jobs and stock reference months differ, as labeled.
Measure	Redwood City	San Mateo
Total homes · Jan 1, 2023	33,189	43,325
Housing-stock growth · Jan 2020–Jan 2023	+2.5%	+2.6%
Workplace jobs · Q2 2023	60,919	59,573
Job growth · Q2 2020–Q2 2023	-7.6%	+3.8%
Completed homes during 2023	340	122
Completions per 100 homes present at the start of the year	1.02	0.28

Completions include replacement construction. “2 completions per 100 homes” does not mean the stock grew 2%. Workplace jobs are not resident households.

Housing stock over time

All series start at 100 in 2011. 2011 to 2023.

Redwood City 112.9San Mateo 108.0

View exact values (13 periods)

Housing stock over time: homes; missing values are unavailable
January 1 snapshot	Redwood City	San Mateo
2023	33,189	43,325
2022	33,092	43,077
2021	32,391	42,809
2020	32,366	42,220
2019	31,847	42,041
2018	31,357	41,874
2017	31,242	41,499
2016	31,149	41,272
2015	30,487	40,777
2014	30,221	40,442
2013	29,766	40,294
2012	29,631	40,195
2011	29,385	40,116

Workplace jobs over time

All series start at 100 in 2012. 2012 to 2023.

Redwood City 116.4San Mateo 133.7

View exact values (12 periods)

Workplace jobs over time: jobs; missing values are unavailable
Q2 snapshot year	Redwood City	San Mateo
2023	60,919	59,573
2022	60,308	58,637
2021	63,739	56,164
2020	65,948	57,401
2019	70,190	60,959
2018	69,469	56,173
2017	62,596	55,940
2016	61,425	57,830
2015	61,258	58,718
2014	56,126	51,252
2013	53,847	46,610
2012	52,349	44,568

The idea we’re testing

Stronger demand may translate into higher prices when housing responds slowly. A useful test needs both sides of that relationship. Low construction on its own can also reflect weak demand.

Evidence, gaps and the next test

Federal Reserve research on jobs and construction constraints supports studying the interaction. It does not establish a forecast for these cities.

The new stock history closes a denominator gap. The proposed multi-year forecasting study still has too few mature observations under its source-lag assumptions. Two completion years remain withheld: San Bruno 2020 and South San Francisco 2024. We need documented historical availability and broader coverage before a new predictive test.

DOF estimates include vacant homes and revisions. We use January snapshots consistently and reconcile the overlapping April 2020 benchmarks. Geography definitions across DOF, Census and city completion reports also need care. All charts are reconstructed from the retained releases.

Housing-stock sources Jobs and completion sources Download the evidence

Price forecasts · experimental

Explore a thesis, then check its record

The current annual forecasts use three price and tax-base signals. None earned selection over matching the county. The new Market outlook predicts contract time in days. It has its own weights and track record; cost scenarios and jobs/housing evidence also answer different questions.

See each family’s research and validation status →

Understand the models, then choose weights

These three models test price and tax-base signals. Each learns a relationship from earlier data, then estimates the city's next-year home-value growth relative to San Mateo County. An input is not itself a prediction.

None passed the original selection test. “Match the county” remains the selected baseline. The models share data and a study design; agreement is not independent confirmation.

Momentum · experimental

Recent price performance

Does how a city performed recently help predict its next year?

What it measures: The city's home-value growth over the past 12 months, minus San Mateo County's growth over those same months.
Made-up example · input only: City values rise 12% and county values rise 8%. The input is +4 percentage points of recent outperformance.
How to interpret it: The fitted relationship can favor a reversal. This model does not simply predict that recent winners keep winning; “Repeat recent relative growth” is the separate rule that does that.

Exact input calculation and earlier test

City 12-month percentage change − county 12-month percentage change.

Average absolute prediction error in the earlier model-selection test: 1.601 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.

Momentum weight (%)

Relative value · experimental

Price gap versus history

Does a change in a city's usual price relationship to the county help predict its next year?

What it measures: Today's city-to-county home-value ratio, compared with its average over the preceding 60 months.
Made-up example · input only: The city's index is 80% of the county index today, versus an average of 88% previously. The model's gap input is +10%: 88 ÷ 80 − 1.
How to interpret it: This measures relative price level, not relative growth or affordability. A positive gap is not proof of a bargain and does not imply a 10% price rise.

Exact input calculation and earlier test

100 × (average of the preceding 60 monthly city/county ratios ÷ current ratio − 1). The current month is excluded from the average.

Average absolute prediction error in the earlier model-selection test: 1.398 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.

Relative value weight (%)

Assessment growth · experimental

Taxable property growth

Does growth in the taxable property base help predict home-value growth?

What it measures: Three-year growth in the city's net assessment roll, minus the county's growth. The roll is the taxable value of property, across property classes.
Made-up example · input only: The city's taxable property total grows 12% over three years and the county's grows 8%. The input is +4 percentage points.
How to interpret it: Tax rules and multiple property classes affect this total. It is not a home-price index, city revenue, or a direct measure of jobs or commercial growth.

Exact input calculation and earlier test

City three-year net assessment-roll percentage change − county change. Use January of the year before the July feature cutoff, with a three-year lookback. This assumed lag is not verified historical publication timing.

Average absolute prediction error in the earlier model-selection test: 1.392 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.

Assessment growth weight (%)

Weights total 0%. Set whole percentages totaling 100% to see a blend.

A 50% weight means half of that model's prediction contributes to the mix. It does not mean a 50% chance the model is right. Zero removes a model; changing weights does not retrain it. The exact equal-weight average stays visible as a comparison.

Choose a single model or set weights totaling 100%.

Methods, versions and source files

Component forecasts were issued 2026-09-15T02:02:10Z. model-lab-v1 uses the original housing-screen-v1 rules and data. Every model shares the same target, benchmark, home type, cutoff and horizon. A missing selected prediction withholds the blend; no weight is silently reassigned.

Earlier validation selected the county baseline. The original decision and paper record stay unchanged. Scores here are recomputed from blended predictions, not averaged component errors.

Download all component predictions, historical outcomes and source hashes · Read the original track record

Source manifest SHA-256: 46f922fcefd73314d74781232e4679632900b1fe429ec6af31c61ab00df388d7

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The idea we’re testing

Explore a thesis, then check its record

Understand the models, then choose weights

Recent price performance

Price gap versus history

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