Graph and download economic data for Mortgage Debt Service Payments as a Percent of Disposable Personal Income (MDSP) from Q1 1980 to Q1 2025 about disposable, payments, mortgage, debt, personal income, percent, personal, services, income, and USA.

Housing affordability in the UK has worsened notably since 2020, with the share of income spent on mortgage payments rising for first-time and repeat buyers. In 2024, homebuyers spent, on average, 20.5 percent of their income on mortgage payments, up from 16.2 percent in 2020. First-time buyers spent a notably higher percentage than repeat buyers. One of the main factors for the declining affordability is the rising housing costs. House prices have increased rapidly since the COVID-19 pandemic. Mortgage rates have also soared since, leading to notably higher monthly payments.

When comparing the mortgage or rental costs incurred by owners with mortgage, private renters and social renters in England, private renters pay a considerably larger share of their income than the other two groups. While owner occupiers with mortgages paid approximately **** percent of their income on mortgage in 2024, private renters paid ** percent, or more than *********. In terms of average monthly costs, renting a three-bedroom house is more expensive than buying.

As at February 2025, couples aged 25 to 34 years old in Sydney, Australia spent an average of around **** percent of their household income on mortgage repayments for an entry-priced house. In comparison, couples in the same age bracket in Darwin were spending around **** percent of their household income on mortgage repayments for a house.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner with Mortgage by Deciles of Income Before Taxes: Seventh 10 Percent (61st to 70th Percentile) (CXU980230LB1508M) from 2014 to 2023 about consumer unit, homeownership, percentile, mortgage, tax, percent, income, and USA.

United States - Mortgage Debt Service Payments as a Percent of Disposable Personal Income was 5.84% in January of 2025, according to the United States Federal Reserve. Historically, United States - Mortgage Debt Service Payments as a Percent of Disposable Personal Income reached a record high of 8.95 in October of 2007 and a record low of 4.37 in January of 1980. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Mortgage Debt Service Payments as a Percent of Disposable Personal Income - last updated from the United States Federal Reserve on August of 2025.

In 2023, Italians paid a lower percentage of their monthly income towards mortgage payment compared to the year before. On average, mortgage installments amounted to **** percent of the monthly household income in 2023, down from **** percent the previous year.

The mortgage debt service ratio in the United States remained fairly stable in 2024, after recovering from a dip in 2020 and 2021. The ratio measures the mortgage debt service payments as a percentage of disposable personal income during a specific quarter and shows the financial burden placed on households by mortgage borrowing. In the fourth quarter of 2024, the total required mortgage payments amounted to approximately **** percent of disposable personal income. This was substantially lower than the spike recorded during the subprime mortgage crisis.

According to a survey conducted between April and May 2023, around **** percent of respondents in Japan who took out variable-rate home loans had a household income of ******************** Japanese yen. The majority of home loan borrowers had a yearly household income of *************************************** yen, regardless of the type of interest rate selected.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner with Mortgage by Income Before Taxes: $150,000 and over (CXU980230LB0217M) from 2003 to 2015 about consumer unit, homeownership, mortgage, tax, percent, income, and USA.

In 2023, the average monthly home loan repayments of working households with housing loan debt in Japan accounted for **** percent of their disposable income. The share of mortgage repayments to disposable income per month increased by *** percentage points.

According to a survey conducted from April to May 2025, the largest share of home loan borrowers in Japan, around ** percent, had a debt-to-income ratio of between ** to ** percent. Around ** percent of respondents had a debt-to-income ratio of over 30 percent.

Around ** percent of people who have mortgage pay 10 to 14 percent of the net income of their household. A share of ** percent of people who plan to get a mortgage stated that their monthly payment will be more than 40 percent of the household's net income.

Mortgage Status By Selected Monthly Owner Costs As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner without Mortgage by Income Before Taxes: $40,000 to $49,999 (CXU980240LB0208M) from 1984 to 2023 about consumer unit, homeownership, mortgage, tax, percent, income, and USA.

Mortgage repayments as a percentage of monthly equivalised disposable household income, throughout the house price and income distribution.

This statistic shows the share of income spent on mortgage payments in selected metro areas in the Unites States in 2018. In 2018, Los Angeles, California was the third least affordable metro area because **** percent of the median household income was spent on median mortgage payments. For comparison, this is higher than the **** percent homeowners spent, on average, on mortgage payments in the United States in 2018.

This graph shows the answers to a survey conducted in Italy in 2018. Individuals were asked which proportion of their monthly income they spend on their mortgage/rent. Some ** percent of the respondents said that their mortgage/rent accounts for ********** of their monthly income. Moreover, *** in *** respondents declared that they do not pay any mortgage or rent.

In the fiscal year 2024, around **** percent of Flat 35 home loan borrowers in Japan had a debt-to-income ratio of 25 to under 30 percent. This was followed by **** percent of borrowers who had a debt-to-income ratio of 20 to under 25 percent.Flat 35 loans are long-term fixed interest rate housing loans for up to 35 years that are offered by private financial institutions and securitized or insured by the Japan Housing Finance Agency.

Negative Equity in U.S. Housing Market

Measuring Home Values, Debt, and Credit Risk

By Zillow Data [source]

About this dataset

This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.

Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.

Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith

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Research Ideas

• Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
• Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
• Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...