Welcome to the January 2019 Ontario Rent Report. Ontario rents remained steady over the past month. In this report, we'll evaluate trends in the Ontario rental market, including comparisons to cities throughout the metro, state, and nation.
View full Ontario Rent Report
Welcome to the January 2019 Ontario Rent Report. Ontario rents remained steady over the past month. In this report, we'll evaluate trends in the Ontario rental market, including comparisons to cities throughout the metro, state, and nation.
Ontario rents have remained flat over the past month, however, they have increased moderately by 2.3% year-over-year. Currently, median rents in Ontario stand at $1,190 for a one-bedroom apartment and $1,490 for a two-bedroom. Ontario's year-over-year rent growth leads the state average of 0.3%, as well as the national average of 0.9%.
Throughout the past year, rent increases have been occurring not just in the city of Ontario, but across the entire metro. Of the largest 10 cities that we have data for in the Riverside metro, 9 of them have seen prices rise. Here's a look at how rents compare across some of the largest cities in the metro.
As rents have increased moderately in Ontario, a few large cities nationwide have seen rents grow more modestly, or in some cases, even decline. Compared to most large cities across the country, Ontario is less affordable for renters.
| City | Median 1BR price | Median 2BR price | M/M price change | Y/Y price change |
|---|---|---|---|---|
| Riverside | $1,060 | $1,330 | -0.1% | 1.5% |
| San Bernardino | $850 | $1,060 | 0.4% | 1.1% |
| Fontana | $1,060 | $1,330 | 0.5% | 0.2% |
| Moreno Valley | $1,370 | $1,710 | 0.1% | 0.9% |
| Rancho Cucamonga | $1,420 | $1,780 | 0.8% | 3.6% |
| Ontario | $1,190 | $1,490 | -0.0% | 2.3% |
| Corona | $1,760 | $2,200 | 0.2% | 2.7% |
| Murrieta | $1,400 | $1,750 | -0.0% | 1.1% |
| Temecula | $1,460 | $1,840 | -0.3% | 1.1% |
| Indio | $970 | $1,220 | 0.4% | -0.9% |
| Chino Hills | $1,560 | $1,980 | -0.1% | 3.9% |
| Upland | $1,480 | $1,880 | 0.9% | 3.4% |
| Redlands | $920 | $1,150 | 0.7% | 1.5% |
| Lake Elsinore | $1,500 | $1,900 | -0.5% | 1.5% |
| Palm Desert | $970 | $1,210 | 0.2% | 0.8% |
| Palm Springs | $920 | $1,160 | 0.1% | 0.9% |
| La Quinta | $1,120 | $1,400 | 0.0% | 0.4% |
| Twentynine Palms | $670 | $830 | 0.2% | 1.8% |
Data from private listing sites, including our own, tends to skew toward luxury apartments, which introduces sample bias when estimates are calculated directly from these listings. To address these limitations, we’ve recently made major updates to our methodology, which we believe have greatly improved the accuracy and reliability of our estimates.
Read more about our new methodology below, or see a more detailed post here.
Apartment List is committed to making our rent estimates the best and most accurate available. To do this, we start with reliable median rent statistics from the Census Bureau, then extrapolate them forward to the current month using a growth rate calculated from our listing data. In doing so, we use a same-unit analysis similar to Case-Shiller’s approach, comparing only units that are available across both time periods to provide an accurate picture of rent growth in cities across the country.
Our approach corrects for the sample bias inherent in other private sources, producing results that are much closer to statistics published by the Census Bureau and HUD. Our methodology also allows us to construct a picture of rent growth over an extended period of time, with estimates that are updated each month.
Read more about our methodology here.
Apartment List publishes monthly reports on rental trends for hundreds of cities across the U.S. We intend these reports to be a source of reliable information that help renters and policymakers make sound decisions, and we invest significant time and effort in gathering and analyzing rent data. Our work is covered regularly by journalists across the country.
We are continuously working to improve our methodology and data, with the goal of providing renters with the information that they need to make the best decisions.
