16428 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 16428 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 1,023, 100% | 1,418,302 | 39,201,928 |
$199 or Less | 27, 2.64%, see rank | 1.98% | 1.50% |
$200 to $299 | 0, 0.00%, see rank | 4.36% | 3.18% |
$300 to $499 | 216, 21.11%, see rank | 9.44% | 7.37% |
$500 to $699 | 390, 38.12%, see rank | 19.30% | 16.01% |
$700 to $999 | 263, 25.71%, see rank | 32.15% | 29.17% |
$1,000 to $1,499 | 120, 11.73%, see rank | 23.68% | 26.88% |
$1,500 to $1,999 | 7, 0.68%, see rank | 5.77% | 9.79% |
$2,000 or More | 0, 0.00%, see rank | 3.33% | 6.10% |
Median | $617, see rank | $832 | $920 |
ACS 2008-2012 data
Monthly Rental | 16428 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 982, 100% | 1,389,264 | 37,562,111 |
$199 or Less | 45, 4.58%, see rank | 2.38% | 1.76% |
$200 to $299 | 41, 4.18%, see rank | 4.39% | 3.29% |
$300 to $499 | 261, 26.58%, see rank | 10.69% | 8.20% |
$500 to $699 | 341, 34.73%, see rank | 21.57% | 17.39% |
$700 to $999 | 178, 18.13%, see rank | 32.16% | 29.40% |
$1,000 to $1,499 | 94, 9.57%, see rank | 21.06% | 25.73% |
$1,500 to $1,999 | 10, 1.02%, see rank | 5.02% | 8.92% |
$2,000 or More | 12, 1.22%, see rank | 2.74% | 5.30% |
Median | $575, see rank | $794 | $889 |
US Census 2000 data
Monthly Rental | 16428 Zip Code | Pennsylvania | U.S. |
Occupied Units Paying Rent | 1,017, 100% | 1,270,837 | 33,386,326 |
$199 or Less | 81, 7.96%, see rank | 6.72% | 5.52% |
$200 to $299 | 102, 10.03%, see rank | 7.04% | 5.45% |
$300 to $499 | 526, 51.72%, see rank | 30.62% | 23.18% |
$500 to $699 | 212, 20.85%, see rank | 30.50% | 29.57% |
$700 to $999 | 90, 8.85%, see rank | 18.43% | 24.06% |
$1,000 to $1,499 | 6, 0.59%, see rank | 5.13% | 9.15% |
$1,500 to $1,999 | 0, 0.00%, see rank | 1.01% | 2.05% |
$2,000 or More | 0, 0.00%, see rank | 0.55% | 1.02% |
Median | $438, see rank | $531 | $602 |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.