48162 Zip Code Historical Gross Rent Price Data
ACS 2010-2014 data
Monthly Rental | 48162 Zip Code | Michigan | U.S. |
Occupied Units Paying Rent | 3,363, 100% | 1,028,835 | 39,201,928 |
$199 or Less | 10, 0.30%, see rank | 1.86% | 1.50% |
$200 to $299 | 161, 4.79%, see rank | 3.88% | 3.18% |
$300 to $499 | 369, 10.97%, see rank | 9.32% | 7.37% |
$500 to $699 | 631, 18.76%, see rank | 23.63% | 16.01% |
$700 to $999 | 1,450, 43.12%, see rank | 35.23% | 29.17% |
$1,000 to $1,499 | 726, 21.59%, see rank | 20.17% | 26.88% |
$1,500 to $1,999 | 16, 0.48%, see rank | 3.85% | 9.79% |
$2,000 or More | 0, 0.00%, see rank | 2.06% | 6.10% |
Median | $777, see rank | $780 | $920 |
ACS 2008-2012 data
Monthly Rental | 48162 Zip Code | Michigan | U.S. |
Occupied Units Paying Rent | 3,463, 100% | 981,443 | 37,562,111 |
$199 or Less | 33, 0.95%, see rank | 2.26% | 1.76% |
$200 to $299 | 126, 3.64%, see rank | 3.90% | 3.29% |
$300 to $499 | 272, 7.85%, see rank | 10.27% | 8.20% |
$500 to $699 | 983, 28.39%, see rank | 25.57% | 17.39% |
$700 to $999 | 1,258, 36.33%, see rank | 34.03% | 29.40% |
$1,000 to $1,499 | 768, 22.18%, see rank | 18.68% | 25.73% |
$1,500 to $1,999 | 23, 0.66%, see rank | 3.45% | 8.92% |
$2,000 or More | 0, 0.00%, see rank | 1.83% | 5.30% |
Median | $774, see rank | $755 | $889 |
US Census 2000 data
Monthly Rental | 48162 Zip Code | Michigan | U.S. |
Occupied Units Paying Rent | 3,227, 100% | 933,547 | 33,386,326 |
$199 or Less | 186, 5.76%, see rank | 5.77% | 5.52% |
$200 to $299 | 105, 3.25%, see rank | 5.57% | 5.45% |
$300 to $499 | 805, 24.95%, see rank | 29.55% | 23.18% |
$500 to $699 | 1,323, 41.00%, see rank | 34.68% | 29.57% |
$700 to $999 | 717, 22.22%, see rank | 18.46% | 24.06% |
$1,000 to $1,499 | 82, 2.54%, see rank | 4.59% | 9.15% |
$1,500 to $1,999 | 9, 0.28%, see rank | 0.92% | 2.05% |
$2,000 or More | 0, 0.00%, see rank | 0.46% | 1.02% |
Median | $573, see rank | $546 | $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.