West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to 84.8 - well below the national benchmark of 100. Nevada - which had an index value of 100.1 - was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately 427,000 U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than 200,000 U.S. dollars. That makes living costs in these states significantly lower than in states such as Hawaii and California, where housing is much more expensive. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded 500 U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

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

At 8.07 U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the July 2024 Big Mac index. Concurrently, the cost of a Big Mac was 5.69 dollars in the U.S., and 6.06 U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2023. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 117.5 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.

According to a recent study, Colombia had the lowest monthly cost of living in Latin America with 546 U.S. dollars needed for basic living. In contrast, four countries had a cost of living above one thousand dollars, Costa Rica, Chile, Panama and Uruguay. In 2022, the highest minimum wage in the region was recorded by Ecuador with 425 dollars per month.

Can Latin Americans survive on a minimum wage? Even if most countries in Latin America have instated laws to guarantee citizens a basic income, these minimum standards are often not enough to meet household needs. For instance, it was estimated that almost 22 million people in Mexico lacked basic housing services. Salary levels also vary greatly among Latin American economies. In 2022, the average net monthly salary in Brazil was lower than Ecuador's minimum wage.

What can a minimum wage afford in Latin America? Latin American real wages have generally risen in the past decade. However, consumers in this region still struggle to afford non-basic goods, such as tech products. Recent estimates reveal that, in order to buy an iPhone, Brazilian residents would have to work more than two months to be able to pay for it. A gaming console, on the other hand, could easily cost a Latin American worker several minimum wages.

Abstract

The Measuring Living Standards in Cities (MLSC) survey is a new instrument designed to enhance understanding of cities in Africa and support evidence based policy design. The instrument was developed under the World Bank’s Spatial Development of African Cities Program, and was piloted in Dar es Salaam (Tanzania) and Durban (South Africa) over the course of 2014/15. These geo-referenced surveys provide information on urban living standards at an unprecedented level of granularity: they can be compared across different geographic levels within the cities, and between areas of ‘regular’ and ‘irregular’ settlement patterns. They also respond to the need to increased understanding of specifically ‘urban’ dimensions of quality of living: housing attributes, access to basic services, and commuting patterns, among others.

Geographic coverage

The survey covered households in Dar es Salaam, Tanzania.

Analysis unit

• Household

• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE FRAME

16,000 EAs generated by the Tanzania National Bureau of Statistics (NBS) for the 2012 Census.

STAGE ONE

200 EAs sorted into four strata. The central strata was divided into ‘central core, shanty’ and ‘central core, non-shanty’. Two EAs were replaced with reserve EAs as the original EAs were found to be inaccessible.

STAGE TWO

12 households randomly selected by systematic equal-probability from updated listing of each EA.

LISTING METHODOLOGY

The listing exercise took place between the first and the second stage of sampling. The household listing operations were implemented with computer assisted paperless interviewing (CAPI) techniques, which generates electronic files directly. Enumerators collected basic information about household: the name of the household head name, phone number and total number of household members living in the dwelling. Enumerators also recorded the GPS location of all structures,18 defined the type of structure, and aimed to provide measurement of structure size.

Listing was preceded by community sensitisation in both cities. In Dar es Salaam, enumerators visited the local chief (Mjumbe) of their assigned EA two days in advance of listing and on the day of listing.

Enumerators were equipped with maps created on Google My Maps to display shapefiles for the listing exercise. Hardcopies of their respective EA maps were also provided to be use in case of network failure. In Dar es Salaam, enumerators conducted a listing of all households in each of the selected EAs.

The listing exercise was conducted by 30 enumerators, each of which was assigned between 3 and 9 EAs for listing (enumerators were selected on the basis of performance from a group of 35 that were trained for listing). Enumerators were allocated EAs based on: (i) distance from enumerators’ homes in order to minimize transport time and cost; (ii) distance between the EAs; and (iii) safety and response rate considerations.

SURVEY IMPLEMENTATION

The surveys were fielded over the course of several months. The Dar es Salaam survey was implemented between November 2014 and January 2015.

Cases were assigned to interviewers using Survey Solutions. Interviewers were provided with both an electronic and hardcopy map, as well as a printed completion form, and could contact the listing manager through email, WhatsApp, or google hangouts if they were unable to find the assigned house.

Completing the survey often required repeat visits. This is because the survey required input from up to three separate respondents: the main respondent, who could be any present household member, and answered questions on household composition, basic information on members, assets, remittances, grants, housing, properties and consumption; the household head, who answered questions on residential history, satisfaction, employment, time use and commuting; and a random respondent, who was randomly selected from household members over the age of 12 (not including the head), who responded questions on satisfaction, employment, time use and commuting. Enumerators visited each house at least twice before a component could be marked as unavailable - in many cases, however, more than two visits were conducted.

Quality assurance procedures included: (i) In-interview feedback from CAPI, which provided a check that modules or questions were not missing, and alerted interviewers to mistakes and inconsistencies in given answers, so that these could be addressed while the interviewer was still with the respondent; (ii) Aggregate checks conducted using the Survey Solutions Supervisor application, which allows supervisors to identify common mistakes (applied to all initial interviews, and then through spot checks); interviewer performance and completion monitoring conducted by the implementing firm, through interviewer and EA level summaries of response rates, interview completion, and progress; (iii) weekly summaries of key indictors provided by the World Bank team (following each data delivery); (iv) direct observation of fieldwork; and (v) back check interviews. A key lesson learned is that the portion of back check interviews should be agreed in advance with the implementing firm: in Dar es Salaam back checks were conducted on 5% of the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

Non-response rate: 13%

Regarding the fourth edition: "Total consumption expenditure" is obtained by summing all COCIOP numbers for each of annual files. The total will differ from "Total consumption expenditure" that applies to the item and situated in the former criteria files provided from us. The reason is that in COCIOP is "Interest on housing" is replaced by "imputed rent".

Statistics Norway have used periodical consumption surveys as a basis for establishing and updating the weighting foundation for the reality price index. Detailed accounts of the consumption in private households have also established an important basis for the level of living statistics and for research on income, level of living and for example effects of the taxing system usage of direct and indirect taxes. The material is also so detailed that it constitutes an interesting groundwork for nutrition analyses. The data can also be applied in demand studies, in economical planning models or for specification of private consumption in the national financial statement.

In 1974 SSB converted to a system with annual surveys with somewhat smaller samples. From 1974-1976 data was published for 3 years at the time, and the annual gross samples of about 1500 households, net sample of 1100-1200 households. The aim was still to build a detailed overview of the consumption in private households, that constitutes a groundwork for updating the weighting basis in the reality price index. Another aim was to map out consumption in various types of households. The households are classified in accordance with such marks as household type, income, main income earners working status and age, neighborhood, size of total consumption spending, etc. The data are organized in several sections and contains background information about the household (gathered through an introductory interview that maps out the household composition), detailed consumption measured in value and amounts (registered by journal notation, for the household and the individual members of the household), the households purchase of durable consumer goods (lasting capital objects, gathered through a comprehensive finishing interview), consumption of self-produced goods, income and taxes.

The house price to income index in Europe declined in almost all European countries in 2023, indicating that income grew faster than house prices. Portugal, Luxembourg, and the Netherlands led the house price to income index ranking in 2023, with values exceeding 125 index points. Romania, Bulgaria, and Finland were on the other side of the spectrum, with less than 100 index points. The house price to income ratio is an indicator for the development of housing affordability across OECD countries and is calculated as the nominal house prices divided by nominal disposable income per head, with 2015 chosen as a base year. A ratio higher than 100 means that the nominal house price growth since 2015 has outpaced the nominal disposable income growth, and housing is therefore comparatively less affordable. In 2023, the OECD average stood at 117.4 index points.

The average transaction price of new housing in Europe was the highest in Norway, whereas existing homes were the most expensive in Austria. Since there is no central body that collects and tracks transaction activity or house prices across the whole continent or the European Union, not all countries are included. To compile the ranking, the source weighed the transaction prices of residential properties in the most important cities in each country based on data from their national offices. For example, in Germany, the cities included were Munich, Hamburg, Frankfurt, and Berlin. House prices have been soaring, with Sweden topping the ranking Considering the RHPI of houses in Europe (the price index in real terms, which measures price changes of single-family properties adjusted for the impact of inflation), however, the picture changes. Sweden, Luxembourg and Norway top this ranking, meaning residential property prices have surged the most in these countries. Real values were calculated using the so-called Personal Consumption Expenditure Deflator (PCE), This PCE uses both consumer prices as well as consumer expenditures, like medical and health care expenses paid by employers. It is meant to show how expensive housing is compared to the way of living in a country. Home ownership highest in Eastern Europe The home ownership rate in Europe varied from country to country. In 2020, roughly half of all homes in Germany were owner-occupied whereas home ownership was at nearly 97 percent in Romania or around 90 percent in Slovakia and Lithuania. These numbers were considerably higher than in France or Italy, where homeowners made up 65 percent and 72 percent of their respective populations.For more information on the topic of property in Europe, visit the following pages as a starting point for your research: real estate investments in Europe and residential real estate in Europe.

Geneva, Switzerland, was the most expensive city to buy an apartment in Europe in the first quarter of 2024. The square meter price in Geneva was nearly 15,650 euros in that quarter, about 2,000 euros higher than the second city in the ranking, Zurich. Cost of rent Rents across the major cities in Europe increased significantly in 2023. One of the main factors driving high rents across European cities is the same as any other consumer-driven business. If demand outweighs supply, prices will inflate. The drive for high paid professionals to be located centrally in prime locations, mixed with the low levels of available space, high land, and construction costs, all help keep rental prices increasing. Mortgage rates The average mortgage interest rates across Europe in 2023 were all under five percent, except in Czechia, Romania, Hungary, and Poland. On an individual level, a difference of one percent would most likely mean thousands of euros in interest on the mortgage a person is paying, making timing key in house purchasing. Mortgage interest rates tend to be lower in Nordic countries due to the financial stability and reliability of its borrowers. Other factors that influence the mortgage interest rates include inflation, economic growth, monetary policies, the bond market and the overall conditions of the housing market. More stable markets also tend to have higher average prices.

In the first quarter of 2024, Amsterdam was the most expensive city to rent a furnished one-bedroom apartment among the 23 leading European cities surveyed. At 2,300 euros per month, rent in Amsterdam was more than twice as high as in Brussels. Amsterdam was also the most expensive city to rent a private room.One of the main factors driving high rents across European cities is the same as any other consumer-driven business. If demand outweighs supply, prices will inflate. The drive for high paid professionals to be located centrally in prime locations, mixed with the low levels of available space, high land, and construction costs, all help keep rental prices increasing.

In December 2024, inflation amounted to 2.9 percent, while wages grew by 4.2 percent. The inflation rate has not exceeded the rate of wage growth since January 2023. Inflation in 2022 The high rates of inflation in 2022 meant that the real terms value of American wages took a hit. Many Americans report feelings of concern over the economy and a worsening of their financial situation. The inflation situation in the United States is one that was experienced globally in 2022, mainly due to COVID-19 related supply chain constraints and disruption due to the Russian invasion of Ukraine. The monthly inflation rate for the U.S. reached a 40-year high in June 2022 at 9.1 percent, and annual inflation for 2022 reached eight percent. Without appropriate wage increases, Americans will continue to see a decline in their purchasing power. Wages in the U.S. Despite the level of wage growth reaching 6.7 percent in the summer of 2022, it has not been enough to curb the impact of even higher inflation rates. The federally mandated minimum wage in the United States has not increased since 2009, meaning that individuals working minimum wage jobs have taken a real terms pay cut for the last twelve years. There are discrepancies between states - the minimum wage in California can be as high as 15.50 U.S. dollars per hour, while a business in Oklahoma may be as low as two U.S. dollars per hour. However, even the higher wage rates in states like California and Washington may be lacking - one analysis found that if minimum wage had kept up with productivity, the minimum hourly wage in the U.S. should have been 22.88 dollars per hour in 2021. Additionally, the impact of decreased purchasing power due to inflation will impact different parts of society in different ways with stark contrast in average wages due to both gender and race.

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.