Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Traverse City, MI (CBSA) (MEDLISPRIPERSQUFEEYY45900) from Jul 2017 to May 2025 about Traverse City, square feet, MI, listing, median, price, and USA.

Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Bay City, MI (CBSA) (MEDLISPRIPERSQUFEEYY13020) from Jul 2017 to May 2025 about Bay City, square feet, MI, listing, median, price, and USA.

Disclaimer: These data are updated by the author and are not an official product of the Federal Reserve Bank of Cleveland.This project provides two sets of migration estimates for the major US metro areas. The first series measures net migration of people to and from the urban neighborhoods of the metro areas. The second series covers all neighborhoods but breaks down net migration to other regions by four region types: (1) high-cost metros, (2) affordable, large metros, (3) midsized metros, and (4) small metros and rural areas. These series were introduced in a Cleveland Fed District Data Brief entitled “Urban and Regional Migration Estimates: Will Your City Recover from the Pandemic?"The migration estimates in this project are created with data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP). The CCP is a 5 percent random sample of the credit histories maintained by Equifax. The CCP reports the census block of residence for over 10 million individuals each quarter. Each month, Equifax receives individuals’ addresses, along with reports of debt balances and payments, from creditors (mortgage lenders, credit card issuers, student loan servicers, etc.). An algorithm maintained by Equifax considers all of the addresses reported for an individual and identifies the individual’s most likely current address. Equifax anonymizes the data before they are added to the CCP, removing names, addresses, and Social Security numbers (SSNs). In lieu of mailing addresses, the census block of the address is added to the CCP. Equifax creates a unique, anonymous identifier to enable researchers to build individuals’ panels. The panel nature of the data allows us to observe when someone has migrated and is living in a census block different from the one they lived in at the end of the preceding quarter. For more details about the CCP and its use in measuring migration, see Lee and Van der Klaauw (2010) and DeWaard, Johnson and Whitaker (2019). DefinitionsMetropolitan areaThe metropolitan areas in these data are combined statistical areas. This is the most aggregate definition of metro areas, and it combines Washington DC with Baltimore, San Jose with San Francisco, Akron with Cleveland, etc. Metro areas are combinations of counties that are tightly linked by worker commutes and other economic activity. All counties outside of metropolitan areas are tracked as parts of a rural commuting zone (CZ). CZs are also groups of counties linked by commuting, but CZ definitions cover all counties, both metropolitan and non-metropolitan. High-cost metropolitan areasHigh-cost metro areas are those where the median list price for a house was more than $200 per square foot on average between April 2017 and April 2022. These areas include San Francisco-San Jose, New York, San Diego, Los Angeles, Seattle, Boston, Miami, Sacramento, Denver, Salt Lake City, Portland, and Washington-Baltimore. Other Types of RegionsMetro areas with populations above 2 million and house price averages below $200 per square foot are categorized as affordable, large metros. Metro areas with populations between 500,000 and 2 million are categorized as mid-sized metros, regardless of house prices. All remaining counties are in the small metro and rural category.To obtain a metro area's total net migration, sum the four net migration values for the the four types of regions.Urban neighborhoodCensus tracts are designated as urban if they have a population density above 7,000 people per square mile. High density neighborhoods can support walkable retail districts and high-frequency public transportation. They are more likely to have the “street life” that people associate with living in an urban rather than a suburban area. The threshold of 7,000 people per square mile was selected because it was the average density in the largest US cities in the 1930 census. Before World War II, workplaces, shopping, schools and parks had to be accessible on foot. Tracts are also designated as urban if more than half of their housing units were built before WWII and they have a population density above 2,000 people per square mile. The lower population density threshold for the pre-war neighborhoods recognizes that many urban tracts have lost population since the 1960s. While the street grids usually remain, the area also needs su

Housing Inventory: Median Listing Price per Square Feet in Bay City, MI (CBSA) was 126.00000 U.S. $ in May of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Listing Price per Square Feet in Bay City, MI (CBSA) reached a record high of 137.00000 in September of 2024 and a record low of 61.00000 in November of 2016. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Listing Price per Square Feet in Bay City, MI (CBSA) - last updated from the United States Federal Reserve on June of 2025.

Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Bay City, MI (CBSA) was -4.01% in May of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Bay City, MI (CBSA) reached a record high of 35.50 in May of 2021 and a record low of -6.66 in July of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Bay City, MI (CBSA) - last updated from the United States Federal Reserve on June of 2025.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show value of owner-occupied housing units by city in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes:SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameOwnOcc_e# Owner-occupied housing units, 2017OwnOcc_m# Owner-occupied housing units, 2017 (MOE)ValLt50k_e# Owner-occupied units valued less than $50,000, 2017ValLt50k_m# Owner-occupied units valued less than $50,000, 2017 (MOE)pValLt50k_e% Owner-occupied units valued less than $50,000, 2017pValLt50k_m% Owner-occupied units valued less than $50,000, 2017 (MOE)Val50_100k_e# Owner-occupied units valued $50,000 to $99,999, 2017Val50_100k_m# Owner-occupied units valued $50,000 to $99,999, 2017 (MOE)pVal50_100k_e% Owner-occupied units valued $50,000 to $99,999, 2017pVal50_100k_m% Owner-occupied units valued $50,000 to $99,999, 2017 (MOE)Val100_150k_e# Owner-occupied units valued $100,000 to $149,999, 2017Val100_150k_m# Owner-occupied units valued $100,000 to $149,999, 2017 (MOE)pVal100_150k_e% Owner-occupied units valued $100,000 to $149,999, 2017pVal100_150k_m% Owner-occupied units valued $100,000 to $149,999, 2017 (MOE)Val150_200k_e# Owner-occupied units valued $150,000 to $199,999, 2017Val150_200k_m# Owner-occupied units valued $150,000 to $199,999, 2017 (MOE)pVal150_200k_e% Owner-occupied units valued $150,000 to $199,999, 2017pVal150_200k_m% Owner-occupied units valued $150,000 to $199,999, 2017 (MOE)Val200_300k_e# Owner-occupied units valued $200,000 to $299,999, 2017Val200_300k_m# Owner-occupied units valued $200,000 to $299,999, 2017 (MOE)pVal200_300k_e% Owner-occupied units valued $200,000 to $299,999, 2017pVal200_300k_m% Owner-occupied units valued $200,000 to $299,999, 2017 (MOE)Val300_500k_e# Owner-occupied units valued $300,000 to $499,999, 2017Val300_500k_m# Owner-occupied units valued $300,000 to $499,999, 2017 (MOE)pVal300_500k_e% Owner-occupied units valued $300,000 to $499,999, 2017pVal300_500k_m% Owner-occupied units valued $300,000 to $499,999, 2017 (MOE)Val500k_1m_e# Owner-occupied units valued $500,000 to $999,999, 2017Val500k_1m_m# Owner-occupied units valued $500,000 to $999,999, 2017 (MOE)pVal500k_1m_e% Owner-occupied units valued $500,000 to $999,999, 2017pVal500k_1m_m% Owner-occupied units valued $500,000 to $999,999, 2017 (MOE)Val1mP_e# Owner-occupied units valued $1,000,000 or more, 2017Val1mP_m# Owner-occupied units valued $1,000,000 or more, 2017 (MOE)pVal1mP_e% Owner-occupied units valued $1,000,000 or more, 2017pVal1mP_m% Owner-occupied units valued $1,000,000 or more, 2017 (MOE)ValLt100k_e# Owner-occupied units valued less than $100,000, 2017ValLt100k_m# Owner-occupied units valued less than $100,000, 2017 (MOE)pValLt100k_e% Owner-occupied units valued less than $100,000, 2017pValLt100k_m% Owner-occupied units valued less than $100,000, 2017 (MOE)Val100_300k_e# Owner-occupied units valued $100,000 to $299,999, 2017Val100_300k_m# Owner-occupied units valued $100,000 to $299,999, 2017 (MOE)pVal100_300k_e% Owner-occupied units valued $100,000 to $299,999, 2017pVal100_300k_m% Owner-occupied units valued $100,000 to $299,999, 2017 (MOE)Val300kPlus_e# Owner-occupied units valued $300,000 or more, 2017Val300kPlus_m# Owner-occupied units valued $300,000 or more, 2017 (MOE)pVal300kPlus_e% Owner-occupied units valued $300,000 or more, 2017pVal300kPlus_m% Owner-occupied units valued $300,000 or more, 2017 (MOE)mMedHUValue_eMedian value of owner-occupied unit (dollars), 2017mMedHUValue_mMedian value of owner-occupied unit (dollars), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

Housing Inventory: Median Listing Price per Square Feet Month-Over-Month in Bay City, MI (CBSA) was -0.77% in April of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Listing Price per Square Feet Month-Over-Month in Bay City, MI (CBSA) reached a record high of 15.12 in April of 2021 and a record low of -7.51 in February of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Listing Price per Square Feet Month-Over-Month in Bay City, MI (CBSA) - last updated from the United States Federal Reserve on May of 2025.

Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet in Bay County, MI (MEDLISPRIPERSQUFEE26017) from Jul 2016 to May 2025 about Bay County, MI; Bay City; square feet; MI; listing; median; price; and USA.

Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet Year-Over-Year in Bay County, MI (MEDLISPRIPERSQUFEEYY26017) from Jul 2017 to May 2025 about Bay County, MI; Bay City; square feet; MI; listing; median; price; and USA.