For the past decade, buying a home in the UK has been more affordable than renting one, when only considering the monthly costs. The renting versus buying gap fluctuated during the period and in 2016, it reached its highest value of 131 British pounds. In 2023, the monthly costs for a first-time buyer were 1,231 British pounds, compared to 1,258 British pounds for renters. Rental growth vs house price growth Housing costs in the UK have been on an uprise, with both renting and buying a home increasingly unreachable. Though the monthly costs of buying have consistently been lower in the past decade, house price growth has been much stronger than rental growth since the beginning of the pandemic. Additionally, buyers have been affected by the aggressive mortgage rate hikes, making acquiring their first home even less affordable. Barriers to homeownership Buying a home is not straightforward. For younger (18-40) potential first-time buyers, there are a number of barriers. Approximately one in three first-time buyers point out that raising a deposit was the main obstacle. Other reasons stopping buyers were not being able to take out a mortgage on their current income and poor credit ratings. Unsurprisingly, the highest share of people who buy a home with a mortgage was in the age group of 45 to 55-year-olds.

Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up but remained stable throughout 2024. In the second quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

Description

This data set represents thousands of loans made through the Lending Club platform, which is a platform that allows individuals to lend to other individuals. Of course, not all loans are created equal. Someone who is a essentially a sure bet to pay back a loan will have an easier time getting a loan with a low interest rate than someone who appears to be riskier. And for people who are very risky? They may not even get a loan offer, or they may not have accepted the loan offer due to a high interest rate. It is important to keep that last part in mind, since this data set only represents loans actually made, i.e. do not mistake this data for loan applications!

Format

A data frame with 10,000 observations on the following 55 variables.

emp_title

Job title.

emp_length

Number of years in the job, rounded down. If longer than 10 years, then this is represented by the value 10.

state

Two-letter state code.

homeownership

The ownership status of the applicant's residence.

annual_income

Annual income.

verified_income

Type of verification of the applicant's income.

debt_to_income

Debt-to-income ratio.

annual_income_joint

If this is a joint application, then the annual income of the two parties applying.

verification_income_joint

Type of verification of the joint income.

debt_to_income_joint

Debt-to-income ratio for the two parties.

delinq_2y

Delinquencies on lines of credit in the last 2 years.

months_since_last_delinq

Months since the last delinquency.

earliest_credit_line

Year of the applicant's earliest line of credit

inquiries_last_12m

Inquiries into the applicant's credit during the last 12 months.

total_credit_lines

Total number of credit lines in this applicant's credit history.

open_credit_lines

Number of currently open lines of credit.

total_credit_limit

Total available credit, e.g. if only credit cards, then the total of all the credit limits. This excludes a mortgage.

total_credit_utilized

Total credit balance, excluding a mortgage.

num_collections_last_12m

Number of collections in the last 12 months. This excludes medical collections.

num_historical_failed_to_pay

The number of derogatory public records, which roughly means the number of times the applicant failed to pay.

months_since_90d_late

Months since the last time the applicant was 90 days late on a payment.

current_accounts_delinq

Number of accounts where the applicant is currently delinquent.

total_collection_amount_ever

The total amount that the applicant has had against them in collections.

current_installment_accounts

Number of installment accounts, which are (roughly) accounts with a fixed payment amount and period. A typical example might be a 36-month car loan.

accounts_opened_24m

Number of new lines of credit opened in the last 24 months.

months_since_last_credit_inquiry

Number of months since the last credit inquiry on this applicant.

num_satisfactory_accounts

Number of satisfactory accounts.

num_accounts_120d_past_due

Number of current accounts that are 120 days past due.

num_accounts_30d_past_due

Number of current accounts that are 30 days past due.

num_active_debit_accounts

Number of currently active bank cards.

total_debit_limit

Total of all bank card limits.

num_total_cc_accounts

Total number of credit card accounts in the applicant's history.

num_open_cc_accounts

Total number of currently open credit card accounts.

num_cc_carrying_balance

Number of credit cards that are carrying a balance.

num_mort_accounts

Number of mortgage accounts.

account_never_delinq_percent

Percent of all lines of credit where the applicant was never delinquent.

tax_liens

a numeric vector

public_record_bankrupt

Number of bankruptcies listed in the public record for this applicant.

loan_purpose

The category for the purpose of the loan.

application_type

The type of application: either individual or joint.

loan_amount

The amount of the loan the applicant received.

term

The number of months of the loan the applicant received.

interest_rate

Interest rate of the loan the applicant received.

installment

Monthly payment for the loan the applicant received.

grade

Grade associated with the loan.

sub_grade

Detailed grade associated with the loan.

issue_month

Month the loan was issued.

loan_status

Status of the loan.

initial_listing_status

Initial listing status of the loan. (I think this has to do with whether the lender provided the entire loan or if the loan is across multiple lenders.)

disbursement_method

Dispersement method of the loan.

balance

Current...

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.

There is more to housing affordability than the rent or mortgage you pay. Transportation costs are the second-biggest budget item for most families, but it can be difficult for people to fully factor transportation costs into decisions about where to live and work. The Location Affordability Index (LAI) is a user-friendly source of standardized data at the neighborhood (census tract) level on combined housing and transportation costs to help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest. Compare eight household profiles (see table below) —which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.*$11,880 for a single person household in 2016 according to US Dept. of Health and Human Services: https://aspe.hhs.gov/computations-2016-poverty-guidelinesThis layer is symbolized by the percentage of housing and transportation costs as a percentage of income for the Median-Income Family profile, but the costs as a percentage of income for all household profiles are listed in the pop-up:Also available is a gallery of 8 web maps (one for each household profile) all symbolized the same way for easy comparison: Median-Income Family, Very Low-Income Individual, Working Individual, Single Professional, Retired Couple, Single-Parent Family, Moderate-Income Family, and Dual-Professional Family.An accompanying story map provides side-by-side comparisons and additional context.--Variables used in HUD's calculations include 24 measures such as people per household, average number of rooms per housing unit, monthly housing costs (mortgage/rent as well as utility and maintenance expenses), average number of cars per household, median commute distance, vehicle miles traveled per year, percent of trips taken on transit, street connectivity and walkability (measured by block density), and many more.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/. There you will find some background and an FAQ page, which includes the question:"Manhattan, San Francisco, and downtown Boston are some of the most expensive places to live in the country, yet the LAI shows them as affordable for the typical regional household. Why?" These areas have some of the lowest transportation costs in the country, which helps offset the high cost of housing. The area median income (AMI) in these regions is also high, so when costs are shown as a percent of income for the typical regional household these neighborhoods appear affordable; however, they are generally unaffordable to households earning less than the AMI.Date of Coverage: 2012-2016 Date Released: March 2019Date Downloaded from HUD Open Data: 4/18/19Further Documentation:LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation_**The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updates**

Title: Location Affordability Index - NMCDC Copy

Summary: This layer contains the Location Affordability Index from U.S. Dept. of Housing and Urban Development (HUD) - standardized household, housing, and transportation cost estimates by census tract for 8 household profiles.

Notes: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas.

Prepared by: dianaclavery_uo, copied by EMcRae_NMCDC

Source: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas. Check the source documentation or other details above for more information about data sources.

Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=447a461f048845979f30a2478b9e65bb

UID: 73

Data Requested: Family income spent on basic need

Method of Acquisition: Search for Location Affordability Index in the Living Atlas. Make a copy of most recent map available. To update this map, copy the most recent map available. In a new tab, open the AGOL Assistant Portal tool and use the functions in the portal to copy the new maps JSON, and paste it over the old map (this map with item id

Date Acquired: Map copied on May 10, 2022

Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 6

Tags: PENDING

Following the FCA's Policy Statement on the changes to the responsible lending rules, it has published further data on the mortgage prisoner population. The FCA's Mortgage Market Study estimated that around 140,000 borrowers were unable to switch to a better deal even though they were up-to-date with their payments. To help fix this it changed its rules late last year to allow lenders to assess affordability based on a borrower’s track record of making mortgage payments. The charts show analysis of the entire dataset which includes all borrowers in closed mortgage books and those who have mortgages owned by unregulated firms regardless of their eligibility to switch because of our new rules. The FCA conducted a data gathering exercise which collected details on all mortgage accounts owned by unregulated firms. This data was combined with details of mortgage accounts held in closed books of regulated firms.

In 2024, there were approximately **** million housing units occupied by renters in the United States. This number has been gradually increasing since 2010 as part of a long-term upward swing since 1975. Meanwhile, the number of unoccupied rental housing units has followed a downward trend, suggesting a growing demand and supply failing to catch up. Why are rental homes in such high demand? This high demand for rental homes is related to the shortage of affordable housing. Climbing 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. How many owner occupied homes are there in the U.S.? In 2023, there were over ** million owner occupied homes. Owner occupied housing is when 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.

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.

The Global Financial Crisis of 2008-09 was a period of severe macroeconomic instability for the United States and the global economy more generally. The crisis was precipitated by the collapse of a number of financial institutions who were deeply involved in the U.S. mortgage market and associated credit markets. Beginning in the Summer of 2007, a number of banks began to report issues with increasing mortgage delinquencies and the problem of not being able to accurately price derivatives contracts which were based on bundles of these U.S. residential mortgages. By the end of 2008, U.S. financial institutions had begun to fail due to their exposure to the housing market, leading to one of the deepest recessions in the history of the United States and to extensive government bailouts of the financial sector.

Subprime and the collapse of the U.S. mortgage market

The early 2000s had seen explosive growth in the U.S. mortgage market, as credit became cheaper due to the Federal Reserve's decision to lower interest rates in the aftermath of the 2001 'Dot Com' Crash, as well as because of the increasing globalization of financial flows which directed funds into U.S. financial markets. Lower mortgage rates gave incentive to financial institutions to begin lending to riskier borrowers, using so-called 'subprime' loans. These were loans to borrowers with poor credit scores, who would not have met the requirements for a conventional mortgage loan. In order to hedge against the risk of these riskier loans, financial institutions began to use complex financial instruments known as derivatives, which bundled mortgage loans together and allowed the risk of default to be sold on to willing investors. This practice was supposed to remove the risk from these loans, by effectively allowing credit institutions to buy insurance against delinquencies. Due to the fraudulent practices of credit ratings agencies, however, the price of these contacts did not reflect the real risk of the loans involved. As the reality of the inability of the borrowers to repay began to kick in during 2007, the financial markets which traded these derivatives came under increasing stress and eventually led to a 'sudden stop' in trading and credit intermediation during 2008.

Market Panic and The Great Recession

As borrowers failed to make repayments, this had a knock-on effect among financial institutions who were highly leveraged with financial instruments based on the mortgage market. Lehman Brothers, one of the world's largest investment banks, failed on September 15th 2008, causing widespread panic in financial markets. Due to the fear of an unprecedented collapse in the financial sector which would have untold consequences for the wider economy, the U.S. government and central bank, The Fed, intervened the following day to bailout the United States' largest insurance company, AIG, and to backstop financial markets. The crisis prompted a deep recession, known colloquially as The Great Recession, drawing parallels between this period and The Great Depression. The collapse of credit intermediation in the economy lead to further issues in the real economy, as business were increasingly unable to pay back loans and were forced to lay off staff, driving unemployment to a high of almost 10 percent in 2010. While there has been criticism of the U.S. government's actions to bailout the financial institutions involved, the actions of the government and the Fed are seen by many as having prevented the crisis from spiraling into a depression of the magnitude of The Great Depression.

Armut und Arbeitsplatzverlust in der Wirtschaftskrise. Themen: Einschätzung der Veränderung der Armut in der Wohngegend im eigenen Land und in der EU; geschätzter Anteil der Armen im eigenen Land; Schwierigkeiten mit der Bewältigung der anfallenden Kosten im Haushalt; Veränderung der Möglichkeit, sich medizinische Versorgung, Kinderbetreuung und Langzeit-Pflege leisten zu können; Einschätzung der Entwicklung der Rente; Beunruhigung über eigene Armut im Alter (Skalometer); Zahlungsschwierigkeiten in den letzten 12 Monaten; Einschätzung der Entwicklung der wirtschaftlichen Situation des Haushalts; Einschätzung des Risikos, die Miete, Kreditraten, tägliche Konsumartikel sowie Rechnungen und eine unerwartete Ausgabe von 1000 € nicht bezahlen zu können; Wahrscheinlichkeit des Zwangsauszugs aus der Wohnung aufgrund mangelnder Geldmittel; Arbeitsplatzsicherheit; Wahrscheinlichkeit nach angenommener Kündigung innerhalb von sechs Monaten einen neuen Arbeitsplatz zu bekommen (Skalometer). Demographie: Geschlecht; Alter; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad; Haushaltszusammensetzung und Haushaltsgröße; Selbsteinstufung des Lebensstandards (Skala). Zusätzlich verkodet wurde: Befragten-ID; Interviewer-ID; Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region; Gewichtungsfaktor. Social impact of the crisis. Topics: development of poverty in the last twelve months in: residential area, own country, European Union; estimated share of poor people in the own country (in percent); financial difficulties of the own household; changes in the last six months with regard to the affordability of: personal healthcare, childcare, long-term care; expected impact of economic and financial events on personal future pension; concern regarding the appropriateness of personal income in old age (scale); financial difficulties during the last year; expected development of the own financial situation in the next twelve months; assessment of the risk to not being able to: pay rent or mortgage on time, cope with unexpected expense of 1,000 €, repay consumer loans, pay daily consumer items; likelihood to be obliged to leave current accommodation within the next twelve months due to financial reasons; confidence to keep current job in the next twelve months; likelihood to find a new job within six months (scale). Demography: sex; age; age at end of education; occupation; professional position; type of community; household composition and household size; current living standard (scale). Additionally coded was: respondent ID; interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region; weighting factor.

Population of the respective nationalities of the European Union Member States, resident in each of the 27 Member States and aged 15 years and over. The survey covers the national population of citizens (in these countries) as well as the population of citizens of all the European Union Member States that are residents in these countries and have a sufficient command of the national languages to answer the questionnaire.

Social impact of the crisis.
Topics: development of poverty in the last twelve months in: residential area, own country, European Union; estimated share of poor people in the own country (in percent); financial difficulties of the own household; changes in the last six months with regard to the affordability of: personal healthcare, childcare, long-term care; expected impact of economic and financial events on personal future pension; concern regarding the appropriateness of personal income in old age (scale); financial difficulties during the last year; expected development of the own financial situation in the next twelve months; assessment of the risk to not being able to: pay rent or mortgage on time, cope with unexpected expense of 1,000 €, repay consumer loans, pay daily consumer items; likelihood to be obliged to leave current accommodation within the next twelve months due to financial reasons; confidence to keep current job in the next twelve months; likelihood to find a new job within six months (scale).

Demography: sex; age; age at end of education; occupation; professional position; type of community; household composition and household size; current living standard (scale).

Additionally coded was: interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; call history; region; weighting factor.

The drastic need for apartments has led to an expansion for apartment and condominium construction contractors over the past five years. Still, changing interest rates have led to years of expansion and contractions for contractors. Overall, revenue has been increasing at a CAGR of 4.3% to total an estimated $94.1 billion through the end of 2025, including an estimated 0.2% increase in 2025. Low interest rates amid the pandemic led residential investment to swell, which included apartment complexes. As inflationary concerns and interest rate hikes lingered, many contractors delayed construction, leading to slower growth in 2023 and 2024 as housing starts sank. Profit has risen slightly as materials price inflation has cooled and contractors have been able to adjust their rates, passing along higher prices to customers. This has also been a driver of revenue growth. Multifamily complexes are still very much needed as young professionals and immigrants move to major cities, leading to growth in 2025. Home prices are set to see slower growth in the coming years than in the previous five, causing a shift in the housing market back to homeownership. Also, continued rate cuts will incentivize home construction. Mortgage rates have remained stubbornly high in the face of cuts to the federal funds rate, however. Elevated mortgage rates will keep buying a house out of reach for many, pushing more people to rent. Apartment construction is set to continue to account for the growing population in the US. Affordable housing complexes remain crucial in many large cities and will be needed as more people enter. Rental vacancies will continue threatening contractors, as many consumers may split housing with roommates and fulfill current stock to save money. Overall, industry revenue is forecast to expand at a CAGR of 1.4% to total an estimated $101.0 billion through the end of 2030.

In Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania and Slovakia also 300 face-to-face interviews have been conducted.

Sozialer Einfluss der Krise. Finanzielle Schwierigkeiten. Bezahlbarkeit der Wohnung und Beschäftigungssituation. Sorge über die Einkommenssituation im Alter. Themen: Anzahl der Kinder im Haushalt unter 15 Jahren; Einschätzung des Lebensstandards des Haushalts (Skalometer); geschätzter Anteil armer Menschen im eigenen Land; Einschätzung der Finanzsituation des Haushalts hinsichtlich des verfügbaren Einkommens; Veränderungen im Gesundheits- und Sozialwesen im letzten Jahr (medizinische Versorgung , Kinderbetreuung und Langzeitpflege); erwarteter Einfluss wirtschaftlicher und finanzieller Ereignisse auf die eigene Rente; Besorgnis über unzureichendes Einkommen im höheren Alter (Skalometer); finanzieller Engpass in den letzten zwölf Monaten; erwartete Entwicklung der Finanzsituation des Haushalts; Einschätzung des Risikos von Zahlungsschwierigkeiten im nächsten Jahr betreffend Miete, Hypothek, unerwartete Ausgaben, Rückzahlung von Konsumkrediten, Rechnungen für Nahrungsmittel und andere Verbrauchsgüter; Einschätzung der Wahrscheinlichkeit des Wohnungsverlusts durch Zahlungsschwierigkeiten; Einschätzung der eigenen Arbeitsplatzsicherheit; Einschätzung der Wahrscheinlichkeit bei Arbeitslosigkeit innerhalb von sechs Monaten einen Job zu finden (Skalometer). Demographie: Alter; Geschlecht; Staatsangehörigkeit; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad; Besitz eines Mobiltelefons; Festnetztelefon im Haushalt; Haushaltszusammensetzung und Haushaltsgröße. Zusätzlich verkodet wurde: Befragten-ID; Interviewmodus (Mobiltelefon oder Festnetz); Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Region; Gewichtungsfaktor. Social impact of the crisis. Topics: number of children under the age of 15 in own household; self-rated living standard of own household (scale); development of poverty in the last twelve months in: residential area, own country, European Union; estimated share of poor people in the own country (in percent); financial difficulties of the own household; changes in the last six months with regard to the affordability of: personal healthcare, childcare, long-term care; expected impact of economic and financial events on personal future pension; concern regarding the appropriateness of personal income in old age (scale); financial difficulties during the last year; expected development of the own financial situation in the next twelve months; assessment of the risk to not being able to: pay rent or mortgage on time, cope with unexpected expense of 1,000 €, repay consumer loans, pay daily consumer items; likelihood to be obliged to leave current accommodation within the next twelve months due to financial reasons; confidence to keep current job in the next twelve months; likelihood to find a new job within six months (scale). Demography: age; sex; nationality; age at end of education; occupation; professional position; type of community; own a mobile phone and fixed (landline) phone; household composition and household size. Additionally coded was: respondent ID; type of phone line; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; region; weighting factor.

About Employment ServiceEmployment Service (ES) is one component of the suite of services known as Employment Ontario (EO). ES provides Ontarians with access to all the employment services and supports they need in one location, so they can find and keep a job, apply for training, and plan a career that’s right for them. The goal of the ES program is to help Ontarians find sustainable employment.Employment Service is delivered by third-party service providers at service delivery sites (SDS) across Ontario on behalf of the Ministry of Labour, Training and Skills Development (MLTSD). The services provided by ES are tailored to meet the individual needs of each client and can be provided one-on-one or in a group format.Employment Service has two broad categories: unassisted and assisted services.Unassisted services, or the Resource and Information (RI) service component, provides individuals with information on local training and employment opportunities, community service supports, and resources to support independent or “unassisted” job search. These services can be delivered through structured orientation or information sessions (on or off site), e-learning sessions, or one-to-one sessions up to two days in duration. The RI component also helps employers to attract and recruit employees and skilled labour by posting positions and offering opportunities to participate in job fairs and other community events.This service component is available to all Ontarians as there are no eligibility or access requirements.Assisted services are offered to individuals who display the need for more intensive, structured, and/or one-on-one employment supports, and includes the following components:job search assistance (including individualized assistance in career goal setting, skills assessment, and interview preparation)job matching, placement and incentives (which match client skills and interested with employment opportunities, and include placement into employment, on-the-job training opportunities, and incentives to employers to hire ES clients), and job training/retention (which supports longer-term attachment to or advancement in the labour market or completion of training)The service provider will develop with the assisted services client an ES service plan – and will monitor, evaluate, and adjust this plan over the duration of the service plan.To be eligible for assisted services, clients must be unemployed (defined as working less than twenty hours a week) and not participating in full-time education or training. Clients are also assessed on a number of suitability indicators covering economic, social and other barriers to employment, and service providers are to prioritize serving those clients with multiple suitability indicators.About ES Service Provider FundingService providers that deliver Employment Service sign agreements with MLTSD that cover individual fiscal years (defined as April 1st to March 31st). These agreements specify at which service delivery site(s) the service provider agrees to provide ES, the performance expectations for each service delivery site (SDS), and the funding that MLTSD will provide to the service provider to deliver ES at each SDS. Funding for ES is provided through two budget categories: operating funds and flow-through funds, with the latter further divided between Employment and Training Incentives for Employers and Employment and Training Supports for Clients/Participants. These three budget lines cover the normal costs of delivering all aspects of ES for both unassisted and assisted clients; for exception one-off expenditures, such as relocation, service providers can apply for Field Supports, which is the fourth and final budget line. Please see below for additional details on each of these four budget lines:2. Operating Funds are for the direct delivery of all of the components of ES (unassisted and assisted). Costs related to the provision of the ES that would be considered part of a service delivery site’s day-to-day operations include, but are not limited to:staff and management salaries;hiring and training of staff (including professional development);marketing (signage, paper/web ads, outreach, etc.);facilities (rent);facilities (mortgage payments) ONLY the interest portion of a mortgage payment is allowed as an Operating cost;other direct operating expenditures related to the delivery of the Employment Service.Service delivery sites are able to attribute no more than 15% of their operating funds for administrative overhead. Administrative overhead recognizes costs necessary for operating an organization but not directly associated with the delivery of the Employment Service. For example, a portion of the salaries/benefits of the Executive Director, IT, and/or financial staff who work for the entire organization but may spend a portion of their time dedicated to administrative functions that support ES. Note that Operating Funds cannot be used for termination and severance costs.2. Employment and Training Incentives for Employers are funds for employers to provide employment and on-the-job training opportunities in ES (up to $8,000 per person. The $8,000 is made up of a maximum of $6,000 for training incentives and an additional $2,000 for the Apprenticeship Employer Signing Bonus, if applicable).3. Employment and Training Supports for Clients/Participants are funds for Clients/Participants in assisted components (up to $500 per Client/Participant). These supports are determined based on family income and are intended, on a temporary basis, to help Clients/Participants address any financial barriers to participation in ES. Client eligibility for these supports is determined on the basis of need and the Low-Income Cut-offs (LICO) income value for the locality. Supports can cover costs such as:transportation;work clothing or clothing/grooming needed to achieve credibility;special equipment, supplies and equipment;certification charges (that may be applied to some short term courses);short term training costs such as books, materials;emergency or infrequent child care;language skills assessment/academic credential assessment;translation of academic documents (for internationally trained individuals);workplace accommodation needs for persons with disabilities.4. Field Supports are funds that may be provided through a formal in-year request to support ES Recipients with one-time exceptional expenditures not normally included as part of ongoing operations. Requests will be reviewed on a case by case basis and approved at the sole discretion of the Ministry. Purchases related to Field Support cannot be made without prior written approval from the Ministry.Service providers have discretion over the use of their funds within the following parameters:Operating funds are allocated against an identified level of service;In situations of co-location of ES with other programs and services, ES funds must only be used to cover costs directly related to the delivery of ES;Operating funds cannot be used for major capital expenditures, such as the purchase or construction of facilities. Purchase of equipment and furniture directly related to the effective delivery of the contracted program is allowable;A service provider must obtain prior written approval from the Ministry to shift funds between service delivery sites or communities;A service provider must not transfer funds between the four budget lines given above unless it obtains the prior written consent of the Ministry; andA service provider should not anticipate additional funds, although the Recipient should discuss any issues with the Ministry.A funding model is used to determine funding levels for the Operating Funds budget line. This model is based on the target number of assisted services clients that each service delivery site agrees to serve in that fiscal year. Note that no targeted funds are provided to deliver unassisted services; these are to be funded out of the allocation provided to service delivery sites on the basis of their target number of assisted services clients.The ES funding model allocates resources in five ranges based on the target amount of assisted services client the service delivery site is to achieve. For each range there is a sliding scale of possible funding amounts per assisted services client, and service delivery sites with higher assisted service client targets generally receive lower per client funding, on the basis that larger service delivery sites are able to achieve economies of scale. Also note that because of this graduated approach to ES funding it is possible that a service delivery site that has its assisted services client target increase may actually receive less overall funding if the target increase shifts it from one range to the next.The five funding ranges are:A/S Client TargetFunding Range per A/S ClientUp to 399$1,000 to $2,950400 to 899$925 to $2,100900 to 1,499$850 to $1,2001,500 to 1,999$795 to $1,0002,000 and Above$795The actual funding amount per assisted services client within each range is determined by reference to two groups of indicators: Location and Labour Market Environment. A service delivery site is assessed against each indicator, and within each group the number of indicators that are assessed as valid/true is totaled. The value, along with the assisted services client target, is then compared to a table to determine the funding value for Location and Labour Market Environment. The average of these two values is then multiplied by the assisted services client target to determine the amount of Operating Funds the service delivery site is to receive.The indicators for each group are below. Note that the Labour Market Environment indicators compare 2009 data for the Consolidated Municipal Service Manager area or planning zone in which the service delivery site is located with the 2009 provincial average.LocationIs the service delivery

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

Rent prices per square meter in the largest Dutch cities have been on an upward trend after a slight decline in 2020. Amsterdam remained the most expensive city to live in, averaging a monthly rent of 27.6 euros per square meter for residential real estate in the private rental sector. Monthly rents in Utrecht were around six euros cheaper per square meter. Both cities were above the average rent price of residential property in the Netherlands overall, whereas Rotterdam and The Hague were slightly below that. Buying versus renting, what do the Dutch prefer? The Netherlands is one of Europe’s leading countries when it comes to homeownership, having funded this with a mortgage. In 2023, around 60 percent of people living in the Netherlands were homeowners with a mortgage. This is because Dutch homeowners were able to for many years to deduct interest paid from pre-tax income (a system known in the Netherlands as hypotheekrenteaftrek). This resulted in the Netherlands having one of the largest mortgage debts across the European continent. Total mortgage debt of Dutch households reached a value of approximately 803 billion euros in 2023. Is the Dutch housing market overheating? There are several indicators for the Netherlands that allow to investigate whether the housing market is overheating or not. House price indices corrected for inflation in the Netherlands suggest, for example, that prices have declined since 2022. The Netherlands’ house-price-to-rent-ratio, on the other hand, has exceeded the pre-crisis level in 2019. These figures, however, are believed to be significantly higher for cities like Amsterdam, as it was suggested for a long time that the prices of owner-occupied houses were increasing faster than rents in the private rental sector.

Evaluate Canada’s best mortgage rates in one place. RATESDOTCA’s Rate Matrix lets you compare pricing for all key mortgage types and terms. Rates are based on an average mortgage of $300,000

The average amount of non-mortgage debt held by consumers in the United States has been falling steadily during the past years, amounting to ****** U.S. dollars in 2023. While respondents had ****** U.S. dollars of debt in 2018, that volume decreased to ****** U.S. dollars in 2019, which constituted the largest year-over-year decrease.What age groups are more indebted in the U.S.?The age group with the highest level of consumer debt in the U.S. was belonging to the Generation X with approximately ******* U.S. dollars of debt in 2022. The next generations with high consumer debt levels were baby boomers and millennials, whose debt levels were similar. In comparison, credit card debt is more equally distributed across all ages. There is an exception among people under 35 years old, who are significantly less burdened with credit card debt. However, most consumers expect to get rid of their debt in the short term. College expenses as a source of debtEducational expenses were not among the leading sources of debt among consumers in the U.S. in 2022. Instead, they made up about ** percent of the total. However, around ** percent of undergraduates from lower-income families had student loans, while over a fifth of undergraduates from higher-income families had student loans. Independently of how they cover these expenses, the confidence of students and parents about being able to pay these college costs was high in most cases.