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Welcome to the September 2017 Fullerton Rent Report. In this report, we'll evaluate trends in the Fullerton rental market, including comparisons to cities throughout the metro, state, and nation.
Fullerton rents have increased 0.7% over the past month, and are up significantly by 4.0% in comparison to the same time last year. Currently, median rents in Fullerton stand at $1,520 for a one-bedroom apartment and $1,950 for a two-bedroom. Fullerton's year-over-year rent growth lags the state average of 4.5%, but exceeds the national average of 3.0%.
Throughout the past year, rent increases have been occurring not just in the city of Fullerton, but across the entire metro. Of the largest 10 cities that we have data for in the Los Angeles 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 in Fullerton, large cities nationwide have seen rents grow more modestly, or in some cases, even decline. Compared to most large cities across the country, Fullerton is less affordable for renters.
| City | Median 1BR price | Median 2BR price | M/M price change | Y/Y price change |
|---|---|---|---|---|
| Los Angeles | $1,350 | $1,740 | 0.5% | 5.0% |
| Long Beach | $1,350 | $1,730 | 0.3% | 3.8% |
| Anaheim | $1,600 | $2,050 | 0.1% | 4.6% |
| Santa Ana | $1,430 | $1,830 | 0.3% | 6.3% |
| Irvine | $2,080 | $2,670 | 1.5% | 5.0% |
| Glendale | $1,370 | $1,760 | -0.1% | 0.8% |
| Huntington Beach | $1,840 | $2,360 | 0.5% | 2.6% |
| Santa Clarita | $1,940 | $2,490 | 0.6% | 6.6% |
| Pomona | $1,150 | $1,470 | 0.4% | 10.5% |
| Pasadena | $1,590 | $2,040 | 0.3% | -0.5% |
| Fullerton | $1,520 | $1,950 | 0.7% | 4.0% |
| Costa Mesa | $1,790 | $2,300 | -0.3% | 1.1% |
| West Covina | $1,710 | $2,200 | 1.6% | 9.8% |
| Burbank | $1,560 | $2,010 | 1.6% | 6.7% |
| Mission Viejo | $2,050 | $2,630 | -0.3% | 4.4% |
| Santa Monica | $1,670 | $2,150 | -0.7% | 3.7% |
| Newport Beach | $2,760 | $3,540 | 0.3% | 4.7% |
| Lake Forest | $1,840 | $2,360 | 0.6% | 4.5% |
| Tustin | $1,920 | $2,470 | 0.7% | 6.4% |
| San Clemente | $2,250 | $2,910 | -0.9% | 5.7% |
| Laguna Niguel | $1,820 | $2,340 | 1.4% | 2.7% |
| Dana Point | $2,040 | $2,630 | 1.1% | 5.4% |
| Laguna Beach | $2,120 | $2,720 | 0.9% | 2.2% |
| Marina del Rey | $3,490 | $4,490 | -0.0% | 2.4% |
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.
