In the United States, interest rates for all mortgage types started to increase in 2021. This was due to the Federal Reserve introducing a series of hikes in the federal funds rate to contain the rising inflation. In the second quarter of 2025, the 30-year fixed rate dropped slightly, to **** percent. The rate remained below the peak of **** percent in the fourth quarter of 2023. Why have U.S. home sales decreased? Cheaper mortgages normally encourage consumers to buy homes, while higher borrowing costs have the opposite effect. As interest rates increased in 2022, the number of existing homes sold plummeted. Soaring house prices over the past 10 years have further affected housing affordability. Between 2014 and 2024, the median price of an existing single-family home risen by about ** percent. On the other hand, the median weekly earnings have risen much slower. Comparing mortgage terms and rates Between 2008 and 2024, the average rate on a 15-year fixed-rate mortgage in the United States stood between **** and **** percent. Over the same period, a 30-year mortgage term averaged a fixed-rate of between **** and **** percent. Rates on 15-year loan terms are lower to encourage a quicker repayment, which helps to improve a homeowner’s equity.

Mortgage interest rates worldwide varied greatly in June 2025, from less than ******percent in many European countries to as high as ***percent in Turkey. The average mortgage rate in a country depends on the central bank's base lending rate and macroeconomic indicators such as inflation and forecast economic growth. Since 2022, inflationary pressures have led to rapid increases in mortgage interest rates. Which are the leading mortgage markets? An easy way to estimate the importance of the mortgage sector in each country is by comparing household debt depth, or the ratio of the debt held by households compared to the county's GDP. In 2024, Switzerland, Australia, and Canada had some of the highest household debt to GDP ratios worldwide. While this indicator shows the size of the sector relative to the country’s economy, the value of mortgages outstanding allows to compare the market size in different countries. In Europe, for instance, the United Kingdom, Germany, and France were the largest mortgage markets by outstanding mortgage lending. Mortgage lending trends in the U.S. In the United States, new mortgage lending soared in 2021. This was largely due to the growth of new refinance loans that allow homeowners to renegotiate their mortgage terms and replace their existing loan with a more favorable one. Following the rise in interest rates, the mortgage market cooled, and refinance loans declined.

Mortgage rates surged at an unprecedented pace in 2022, with the average 10-year fixed rate doubling between March and December of that year. In response to mounting inflation, the Bank of England implemented a series of rate hikes, pushing borrowing costs steadily higher. By October 2025, the average 10-year fixed mortgage rate stood at **** percent. As financing becomes more expensive, housing demand has cooled, weighing on market sentiment and slowing house price growth. How have the mortgage hikes affected the market? After surging in 2021, the number of residential properties sold fell significantly in 2023, dipping to just above *** million transactions. This contraction in activity also dampened mortgage lending. Between the first quarter of 2023 and the first quarter of 2024, the value of new mortgage loans declined year-on-year for five consecutive quarters. Even as rates eased modestly in 2024 and housing activity picked up slightly, volumes remained well below the highs recorded in 2021. How are higher mortgages impacting homebuyers? For homeowners, the impact is being felt most acutely as fixed-rate deals expire. Mortgage terms in the UK typically range from two to ten years, and many borrowers who locked in historically low rates are now facing significantly higher repayments when refinancing. By the end of 2026, an estimated five million homeowners will see their mortgage deals expire. Roughly two million of these loans are projected to experience a monthly payment increase of up to *** British pounds by 2026, putting additional pressure on household budgets and constraining affordability across the market.

The mortgage interest rate in Sweden rose dramatically in 2022, following a long period of mortgages maintaining rates below two percent. In the first quarter of 2025, the average weighted interest rate stood at **** percent, more than one percentage point below the rate in the first quarter of 2024. In Europe, Sweden's mortgage interest rate ranked alongside Germany and Portugal.  Homeownership in Sweden  The homeownership rate in Sweden did not vary significantly over the period from 2008 to 2019. It peaked in 2010 and slightly fluctuated the following years. The rate was lowest in 2019, amounting to roughly **** percent. Profile of the European homeowner  Swedes, Germans, Austrians, Turks, and Danes are the European citizens for who homeownership was the least common. Romania was the country with the highest homeownership rate among selected European countries in 2021, followed by Slovakia. Both countries had a rate higher than ** percent. In general, it seemed to be more common to own a home in Eastern European countries than in the Western part of the continent.

Mortgage interest rates in Spain soared in 2022, after falling below *** percent at the end of 2021. In the first quarter of 2025, the average weighted interest rate stood at **** percent. That was lower than the rate in the same period the previous year. Despite the increase, Spain had a considerably lower mortgage interest rate than many other European countries. The aftermath of the property bubble Before the bursting of the real estate bubble, the housing market experienced a period of intense activity. A context marked by economic growth, high employment rate, low interest rates, skyrocketing house prices and land speculation, among others, encourage massive lending for the acquisition of property; in 2005 alone, more than *** million home mortgages were granted in Spain. When the bubble burst and the financial crisis hit the country, residential real estate transactions plummeted and households’ non-performing loans jumped to nearly ** billion euros as countless families were not able to cope with their debts. Over a decade after the onset of the crisis, and despite falling mortgage rates, the volume of mortgage loans keeps decreasing every year. A homeowner country Traditionally, Spain has been a country of homeowners; in 2021, the homeownership rate was roughly ** percent. While nearly half of Spanish households own their property with no outstanding payment, the percentage of households that have loan or mortgage pending has been decreasing in recent years. Despite ownership remaining as the preferred tenure option, cultural changes, job insecurity and mounting house prices are prompting Spaniards to opt more and more to become tenants instead of owners, as shown in the changing dynamics of the Spanish residential rental market.

Graph and download economic data for Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks (DRSFRMACBS) from Q1 1991 to Q3 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

Mortgage lenders are dealing with the RBA's shift to a tighter monetary policy, as it fights heavy inflation. Since May 2022, the RBA has raised the benchmark cash rate, which flows to interest rates on home loans. This represents a complete reversal of the prevailing approach to monetary policy taken in recent years. Over the course of the pandemic, subdued interest rates, in conjunction with government incentives and relaxed interest rate buffers, encouraged strong mortgage uptake. With the RBA's policy reversal, authorised deposit-taking institutions will need to balance their interest rate spreads to ensure steady profit. A stronger cash rate means more interest income from existing home loans, but also steeper funding costs. Moreover, increasing loan rates mean that prospective homeowners are being cut out of the market, which will slow demand for new home loans. Overall, industry revenue is expected to rise at an annualised 0.4% over the past five years, including an estimated 2.2% jump in 2023-24, to reach $103.4 billion. APRA's regulatory controls were updated in January 2023, with new capital adequacy ratios coming into effect. The major banks have had to tighten up their capital buffers to protect against financial instability. Although the ‘big four’ banks control most home loans, other lenders have emerged to foster competition for new loanees. Technological advances have made online-only mortgage lending viable. However, lenders that don't take deposits are more reliant on wholesale funding markets, which will be stretched under a higher cash rate. Looking ahead, technology spending isn't slowing down, as consumers continue to expect secure and user-friendly online financial services. This investment is even more pressing, given the ongoing threat of cyber-attacks. Industry revenue is projected to inch upwards at an annualised 0.8% over the five years through 2028-29, to $107.7 billion.

The mortgage prevalence among homeowners in the 30 European countries in the ranking varied widely in 2024. About ** percent of the total population in Norway was a homeowner, with **** percent paying out a mortgage loan. Conversely, only *** percent of households in Romania had a mortgage, with nearly **** percent being homeowners. Meanwhile, an average of **** percent of the total population within the EU-27 was an owner-occupant with a mortgage or housing loan. Homeownership depends on multiple factors, such as housing policy, the macroeconomic situation, the state of the housing sector, and the availability of finance. Countries with more developed mortgage markets tend to have lower mortgage interest rates.

DESCRIPTION

A banking institution requires actionable insights into mortgage-backed securities, geographic business investment, and real estate analysis. The mortgage bank would like to identify potential monthly mortgage expenses for each region based on monthly family income and rental of the real estate. A statistical model needs to be created to predict the potential demand in dollars amount of loan for each of the region in the USA. Also, there is a need to create a dashboard which would refresh periodically post data retrieval from the agencies. The dashboard must demonstrate relationships and trends for the key metrics as follows: number of loans, average rental income, monthly mortgage and owner’s cost, family income vs mortgage cost comparison across different regions. The metrics described here do not limit the dashboard to these few. Dataset Description

Variables

Description Second mortgage Households with a second mortgage statistics Home equity Households with a home equity loan statistics Debt Households with any type of debt statistics Mortgage Costs Statistics regarding mortgage payments, home equity loans, utilities, and property taxes Home Owner Costs Sum of utilities, and property taxes statistics Gross Rent Contract rent plus the estimated average monthly cost of utility features High school Graduation High school graduation statistics Population Demographics Population demographics statistics Age Demographics Age demographic statistics Household Income Total income of people residing in the household Family Income Total income of people related to the householder Project Task: Week 1

Data Import and Preparation:

Import data.

Figure out the primary key and look for the requirement of indexing.

Gauge the fill rate of the variables and devise plans for missing value treatment. Please explain explicitly the reason for the treatment chosen for each variable.

Exploratory Data Analysis (EDA):

Perform debt analysis. You may take the following steps:

Explore the top 2,500 locations where the percentage of households with a second mortgage is the highest and percent ownership is above 10 percent. Visualize using geo-map. You may keep the upper limit for the percent of households with a second mortgage to 50 percent

Use the following bad debt equation:

Bad Debt = P (Second Mortgage ∩ Home Equity Loan) Bad Debt = second_mortgage + home_equity - home_equity_second_mortgage Create pie charts to show overall debt and bad debt

Create Box and whisker plot and analyze the distribution for 2nd mortgage, home equity, good debt, and bad debt for different cities

Create a collated income distribution chart for family income, house hold income, and remaining income

Perform EDA and come out with insights into population density and age. You may have to derive new fields (make sure to weight averages for accurate measurements):

Use pop and ALand variables to create a new field called population density

Use male_age_median, female_age_median, male_pop, and female_pop to create a new field called median age

Visualize the findings using appropriate chart type

Create bins for population into a new variable by selecting appropriate class interval so that the number of categories don’t exceed 5 for the ease of analysis.

Analyze the married, separated, and divorced population for these population brackets

Visualize using appropriate chart type

Please detail your observations for rent as a percentage of income at an overall level, and for different states.

Perform correlation analysis for all the relevant variables by creating a heatmap. Describe your findings.

Project Task: Week 2

Data Pre-processing:

The economic multivariate data has a significant number of measured variables. The goal is to find where the measured variables depend on a number of smaller unobserved common factors or latent variables.

Each variable is assumed to be dependent upon a linear combination of the common factors, and the coefficients are known as loadings. Each measured variable also includes a component due to independent random variability, known as “specific variance” because it is specific to one variable. Obtain the common factors and then plot the loadings. Use factor analysis to find latent variables in our dataset and gain insight into the linear relationships in the data.

  Following are the list of latent variables:

Highschool graduation rates

Median population age

Second mortgage statistics

Percent own

Bad debt expense

Data Modeling :

Build a linear Regression model to predict the total monthly expenditure for home mortgages loan.

  Please refer deplotment_RE.xlsx. Column hc_mortgage_mean is predicted variable. This is the mean monthly mortgage and owner costs of specified geographical location.

  Note: Exclude loans from prediction model which have NaN (Not a Numb...

Fannie Mae and Freddie Mac Loan-Level Dataset

Borrower Demographics, Loan-to-Value Ratios, and Census Tract Location

By Natarajan Krishnaswami [source]

About this dataset

The FHFA Public Use Databases provide an unprecedented look into the flow of mortgage credit and capital in America's communities. With detailed information about the income, race, gender and census tract location of borrowers, this database can help lenders, planners, researchers and housing advocates better understand how mortgages are acquired by Fannie Mae and Freddie Mac.

This data set includes 2009-2016 single-family property loan information from the Enterprises in combination with corresponding census tract information from the 2010 decennial census. It allows for greater granularity in examining mortgage acquisition patterns within each MSA or county by combining borrower/property characteristics, such as borrower's race/ethnicity; co-borrower demographics; occupancy type; Federal guarantee program (conventional/other versus FHA-insured); age of borrowers; loan purpose (purchase, refinance or home improvement); lien status; rate spread between annual percentage rate (APR) and average prime offer rate (APOR); HOEPA status; area median family income and more.

In addition to demographic data on borrowers and properties, this dataset also provides insight into affordability metrics such as median family incomes at both the MSA/county level as well as functional owner occupied bankrupt tracts using 2010 Census based geography while taking into account American Community Survey estimates available at January 1st 2016. This allows us to calculate metrics that are important for assessing inequality such as tract income ratios which measure what portion of an area’s median family income is made up by a single borrows earnings or the ratio between borrows annual income compared to an area’s average median family iincome for those year’s reporting period. Finally each record contains Enterprise Flags associated with whether loans were purchased my Fannie Mae or Freddie Mac indicating further insights regarding who is financing policies affecting undocumented immigrant labor access as well affordable housing legislation targeted towards first time home buyers

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For more datasets, click here.

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How to use the dataset

This guide will provide you with all the information needed to use the Fannie Mae and Freddie Mac Loan-Level Dataset for 2016. The dataset contains loan-level data for both Fannie Mae and Freddie Mac, including loans acquired in 2016. It includes details such as homeowner demographics, loan-to-value ratio, census tract location, and affordability of mortgage.

The first step to using this dataset is understanding how it is organized. There are 38 fields that make up the loan level data set, making it easy to understand what is being looked at. For each field there is a description of what the field represents and potential values it can take on (i.e., if it’s an integer or float). Having an understanding of the different fields will help when querying certain data points or comparing/contrasting.

Once you understand what type of information is available in this dataset you can start to create queries or visualizations that compare trends across Fannie Mae & Freddie Mac loans made in 2016. Depending on your interest areas such as homeownership rates or income disparities certain statistics may be pulled from the dataset such as borrower’s Annual Income Ratio per area median family income by state code or a comparison between Race & Ethnicity breakdown between borrowers and co-borrowers from various states respective MSAs, among other possibilities based on your inquiries . Visualizations should then be created so that clear comparisons and contrasts could be seen more easily by other users who may look into this same dataset for additional insights as well .

After creating queries/visualization , you can dive deeper into research about corresponding trends & any biases seen within these datasets related within particular racial groupings compared against US Postal & MSA codes used within the 2010 Census Tract locations throughout the US respectively by further utilizing publicly available research material that looks at these subjects with regards housing policies implemented through out years one could further draw conclusions depending on their current inquiries

Research Ideas

• Use the dataset to analyze borrowing patterns based on race, nationality and gender, to better understand the links between minority groups and access to credit...

Mortgage rates in the Netherlands increased sharply in 2022 and 2023, after declining gradually between 2008 and 2021. In December 2021, the average interest rate for new mortgage loans stood at **** percent, and by the end of 2023, it had risen to **** percent. In May 2025, mortgage rates decreased slightly, falling to **** percent on average. Mortgages with a 10-year fixed rate were the most affordable, at **** percent. Are mortgage rates in the Netherlands different from those in other European countries? When comparing this ranking to data that covers multiple European countries, the Netherlands’ mortgage rate was similar to the rates found in Spain, the United Kingdom, and Sweden. It was, however, a lot lower than the rates in Eastern Europe. Hungary and Romania, for example, had some of the highest mortgage rates. For more information on the European mortgage market and how much the countries differ from each other, please visit this dedicated research page. How big is the mortgage market in the Netherlands? The Netherlands has overall seen an increase in the number of mortgage loans sold and is regarded as one of the countries with the highest mortgage debt in Europe. The reason behind this is that Dutch homeowners were able to for many years to deduct interest paid from pre-tax income (a system known in the Netherlands as hypotheekrenteaftrek). Total mortgage debt of Dutch households has been increasing year-on-year since 2013.

Zillow Home Value Index (ZHVI): A measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. Available as a smoothed, seasonally adjusted measure and as a raw measure.

Zillow publishes top-tier ZHVI ($, typical value for homes within the 65th to 95th percentile range for a given region) and bottom-tier ZHVI ($, typical value for homes within the 5th to 35th percentile range for a given region).

Zillow also publishes ZHVI for all single-family residences ($, typical value for all single-family homes in a given region), for condo/coops ($), for all homes with 1, 2, 3, 4 and 5+ bedrooms ($).

Note: Starting with the January 2023 data release, and for all subsequent releases, the full ZHVI time series has been upgraded to harness the power of the neural Zestimate.

More information about what ZHVI is and how it’s calculated is available on this overview page. Here’s a handy ZHVI User Guide for information about properly citing and making calculations with this metric.

Mortgage Payment: An estimate of the monthly mortgage payment on a new home purchase with the average interest rate of that month. The home value is estimated using smoothed and seasonally adjusted ZHVI. If the down payment is less than 20%, the monthly mortgage payment includes 1% mortgage insurance.
Total Monthly Payment: An estimate of the total monthly payment on a new home purchase with current interest rates. The total monthly payment includes the mortgage payment, homeowner’s insurance, property taxes, and maintenance costs worth 0.5% of the home’s value. The home value is estimated using smoothed and seasonally adjusted ZHVI. If the down payment is less than 20%, the monthly mortgage payment includes 1% mortgage insurance. Homeowners insurance rates and property tax rate estimates vary by region.

The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at **** percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to **** percent in 2021 due to government interventions during the COVID-19 pandemic. In 2024, the rate stood slightly higher at **** percent but remained well below historical averages, indicating a relatively stable housing market. Impact of economic conditions on foreclosures The foreclosure rate is closely tied to broader economic trends and housing market conditions. During the aftermath of the 2008 financial crisis, the share of non-performing mortgage loans climbed significantly, with loans 90 to 180 days past due reaching *** percent. Since then, the share of seriously delinquent loans has dropped notably, demonstrating a substantial improvement in mortgage performance. Among other things, the improved mortgage performance has to do with changes in the mortgage approval process. Homebuyers are subject to much stricter lending standards, such as higher credit score requirements. These changes ensure that borrowers can meet their payment obligations and are at a lower risk of defaulting and losing their home. Challenges for potential homebuyers Despite the low foreclosure rates, potential homebuyers face significant challenges in the current market. Homebuyer sentiment worsened substantially in 2021 and remained low across all age groups through 2024, with the 45 to 64 age group expressing the most negative outlook. Factors contributing to this sentiment include high housing costs and various financial obligations. For instance, in 2023, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

This statistic illustrates the average house price for equity release plan customers in the United Kingdom (UK) from the second half of 2015 to the second half of 2019, by type of lifetime mortgage. Equity release plans are designed to allow homeowners to access some of the value of their property without the need to sell their house and move out. A lump sum equity release plan facilities a one-off payment, whilst a drawdown equity release plan enables a homeowner to receive an initial advance, alongside an agreed amount cash facility that can be used when required. It can be seen that the average house price for both lump sum and drawdown customers increased steadily during this period, reaching over *** thousand British pounds in lump sum plans, and *** thousand British pounds in the drawdown plans, as of the second half of 2019.

About 36 percent of homeowners in England were aged 65 and above, which contrasts sharply with younger age groups, particularly those under 35. Young adults between 25 and 35, made up 15 percent of homeowners and had a dramatically lower homeownership rate. The disparity highlights the growing challenges faced by younger generations in entering the property market, a trend that has significant implications for wealth distribution and social mobility. Barriers to homeownership for young adults The path to homeownership has become increasingly difficult for young adults in the UK. A 2023 survey revealed that mortgage affordability was the greatest obstacle to property purchase. This represents a 39 percent increase from 2021, reflecting the impact of rising house prices and mortgage rates. Despite these challenges, one in three young adults still aspire to get on the property ladder as soon as possible, though many have put their plans on hold. The need for additional financial support from family, friends, and lenders has become more prevalent, with one in five young adults acknowledging this necessity. Regional disparities and housing supply The housing market in England faces regional challenges, with North West England and the West Midlands experiencing the largest mismatch between housing supply and demand in 2023. This imbalance is evident in the discrepancy between new homes added to the housing stock and the number of new households formed. London, despite showing signs of housing shortage, has seen the largest difference between homes built and households formed. The construction of new homes has been volatile, with a significant drop in 2020, a rebound in 2021 and a gradual decline until 2024.

The distribution of all owner-occupier households in England in 2024 varied per age group, as well as the type of home financing. The older the age group, the larger the share of owner-occupier homeowners who purchased their home outright. A share of 2.1 percent of own outright homeowners were between the ages of 25 to 34, whereas a share of 62.1 percent of own outright homeowners were aged 65 and over. Although this is the case, the largest share of homeowners who purchased their house with a mortgage was in the age range of 35 to 44 years old.

The Housing Affordability Index value in the United States plummeted in 2022, surpassing the historical record of ***** index points in 2006. In 2024, the housing affordability index measured **** index points, making it the second-worst year for homebuyers since the start of the observation period. What does the Housing Affordability Index mean? The Housing Affordability Index uses data provided by the National Association of Realtors (NAR). It measures whether a family earning the national median income can afford the monthly mortgage payments on a median-priced existing single-family home. An index value of 100 means that a family has exactly enough income to qualify for a mortgage on a home. The higher the index value, the more affordable a house is to a family. Key factors that drive the real estate market Income, house prices, and mortgage rates are some of the most important factors influencing homebuyer sentiment. When incomes increase, consumer power also increases. The median household income in the United States declined in 2022, affecting affordability. Additionally, mortgage interest rates have soared, adding to the financial burden of homebuyers. The sales price of existing single-family homes in the U.S. has increased year-on-year since 2011 and reached ******* U.S. dollars in 2023.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

Despite the Office for National Statistics (ONS) reporting that the actual average deposit required to buy a home was ** thousand British pounds (GBP), Santander's survey of potential first-time homeowners found the average target deposit was in some cases much lower. Even in London, where the average property price in early 2019 was over *** thousand British pounds, potential first-time homeowners had a target deposit of around **** percent of the property price (**** thousand GBP).

The issue with having a lower deposit for a new home is that it puts buyers into a higher loan-to-value mortgage ratio. Those in the North East looked to achieve the highest deposit to property price ratio at ******* percent.

Following a period of stagnation over most of the 2010s, the number of owner-occupied housing units in the United States started to grow in 2017. In 2024, there were over 86.9 million owner-occupied homes. Owner-occupied housing is where the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing, and social housing. Homeownership sentiment in the U.S. Though homeownership is still a cornerstone of the American dream, an increasing share of people see themselves as lifelong renters. Millennials have been notoriously late to enter the housing market, with one in four reporting that they would probably continue to always rent in the future, a 2022 survey found. In 2017, just five years before that, this share stood at about 13 percent. How many renter households are there? Renter households are roughly half as few as owner-occupied households in the U.S. In 2024, the number of renter-occupied housing units amounted to over 45 million. Climbing on the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home.