Annual average net outlays for vehicle purchases came to above ***** U.S. dollars for all U.S. consumers in 2023, ranging between around ***** U.S. dollars for those in the lowest income bracket to nearly ****** U.S. dollars for consumers in the highest income group.

This statistic shows the percentage share of total weekly household expenditure going on new car and van purchases in the United Kingdom (UK) in 2023. Households in the ninth decile group spent an average of *** percent of their weekly household expenditure on new cars and/or vans. The average expenditure on new vehicles across all households was *** percent.

The statistics shows the brands of cars used primarily by American households in 2024. The results were sorted by income tier. As of **********, ** percent of respondents who stated their income was high said they used a BMW. The survey was conducted in 2024, among ***** respondents.Want to know more about the topic of mobility? Check out share of car owners in selected countries worldwide to see how car ownership varies across the globe. You can access millions of exclusive survey results with Statista Consumer Insights.

Graph and download economic data for Expenditures: Vehicle Purchases: Cars and Trucks, New by Quintiles of Income Before Taxes: Second 20 Percent (21st to 40th Percentile) (CXUNEWCARSLB0103M) from 1984 to 2023 about purchase, trucks, percentile, tax, vehicles, expenditures, new, income, and USA.

Average weekly household expenditure on goods and services in the UK. Data are shown by region, age, income (including equivalised) group (deciles and quintiles), economic status, socio-economic class, housing tenure, output area classification, urban and rural areas (Great Britain only), place of purchase and household composition.

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

This statistic shows the average household expenditure per week on purchases of vehicles in the United Kingdom (UK) in 2023, by gross income decile group. Households in the fourth decile group spent an average of **** British pounds a week on vehicle purchases, including cars, vans and motorcycles (new or second hand). The income group with the highest weekly expenditure on vehicle purchases is the highest ten percent, who spend ***** British pounds on average.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation. The HIECS 2010/2011 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2010/2011, among a long series of similar surveys that started back in 1955. The survey main objectives are:

• To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials.

• To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates.

• To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period.

• To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation.

• To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands.

• To define average household and per-capita income from different sources.

• To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey.

• To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas.

• To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure.

• To study the relationships between demographic, geographical, housing characteristics of households and their income.

• To provide data necessary for national accounts especially in compiling inputs and outputs tables.

• To identify consumers behavior changes among socio-economic groups in urban and rural areas.

• To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas.

• To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services.

• To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index.

• To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which :

1- The total sample of the current survey (26.5 thousand households) is divided into two sections:

a- A new sample of 16.5 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, etc.

b- A panel sample with 2008/2009 survey data of around 10 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2- The number of enumeration area segments is reduced from 2526 in the previous survey to 1000 segments for the new sample, with decreasing the number of households selected from each segment to be (16/18) households instead of (19/20) in the previous survey.

3- Some additional questions that showed to be important based on previous surveys results, were added, such as:

a- Collect the expenditure data on education and health on the person level and not on the household level to enable assessing the real level of average expenditure on those services based on the number of beneficiaries.

b- The extent of health services provided to monitor the level of services available in the Egyptian society.

c- Smoking patterns and behaviors (tobacco types- consumption level- quantities purchased and their values).

d- Counting the number of household members younger than 18 years of age registered in ration cards.

e- Add more details to social security pensions data (for adults, children, scholarships, families of civilian martyrs due to military actions) to match new systems of social security.

f- Duration of usage and current value of durable goods aiming at estimating the service cost of personal consumption, as in the case of imputed rents.

4- Quality control procedures especially for fieldwork, are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

National

Analysis unit

1- Household/family

2- Individual/Person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS, 2010-2011 is a self-weighted two-stage stratified cluster sample, of around 26500 households. The main elements of the sampling design are described in the following:

1- Sample Size It has been deemed important to collect a smaller sample size (around 26.5 thousand households) compared to previous rounds due to the convergence in the time period over which the survey is conducted to be every two years instead of five years because of its importance. The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 26500 households has been considered, and was distributed between urban and rural with the percentages of 47.1 % and 52.9, respectively. This sample is divided into two parts: a- A new sample of 16.5 thousand households selected from main enumeration areas. b- A panel sample with 2008/2009 survey data of around 10 thousand households.

2- Cluster size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 16 households (that was increased to 18 households in urban governorates and Giza, in addition to urban areas in Helwan and 6th of October, to account for anticipated non-response in those governorates: in view of past experience indicating that non-response may almost be nil in rural governorates). While the cluster size for the panel sample was 4 households.

3- Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area

There is a sharp increase in vehicle ownership once income surpasses ****** U.S. dollars. The high running costs of owning a car makes it very difficult for low-income earners to have their own vehicle. The annual salary of those in the lowest income group shown would not cover the cost of the average second hand car.

A record 4.7 million passenger cars and commercial vehicles were sold in India in 2022. This figure then increased by close to one million units from the previous year.

Great expectations   

With a population of around 1.4 billion people, the addressable market for vehicle sales is more than twice as big as that of South Korea. It is expected that an increased number of women and young people will join the workforce and drive the demand for mobility.

Bills, bills, bills 

India’s gross domestic product is expected to double in size between 2015 and 2024, but fuel prices continue to weigh heavily on the population: The average worker needs to spend 70 percent of his or her daily income to buy a gallon of gas. This is one of the reasons why the average per capita use of gasoline comes to only 6.4 gallons annually. This compares to almost 432 gallons in the United States per motorist per year.

Net income attributable to Tesla’s common stockholders was nearly **** billion U.S. dollars, while net income related to noncontrolling interests amounted to ** million U.S. dollars in 2024. This was the fourth year the company turned a full-year profit, after reaching that goal in 2020. The fiscal year end of the company is December, 31st. Focus on innovation drives costs 2020 was the first time that Tesla turned a full-year profit. Previously, net losses had begun to accelerate in 2014, and so did research and development (R&D) expenses. Between 2014 and 2024, Tesla’s research and development expenses increased more than nine-fold from about *** million to over *** billion U.S. dollars. The company's R&D intensity peaked at ** percent in 2017, a striking value compared to GM's **** percent. Tesla's high R&D spending was largely due to the focus on innovative technologies, including electric vehicle batteries and charging infrastructure. In addition to these costs, the company also had to invest significantly more capital than expected towards ramping up production of its Model 3 and Model Y. As a result of increasing demand for Model 3 batteries, Tesla has also begun pouring money into Gigafactory plants in Shanghai, Texas, and Berlin-Brandenburg. Tesla's earnings topped estimates in 2023 with net income reaching nearly ** billion U.S. dollars for the first time. Cost trend   Tesla's selling, general, and administrative (SG&A) expenses jumped from *** billion U.S. dollars in 2016 to more than *** billion U.S. dollars in the following year. SG&A expenses increased moderately to reach around **** billion U.S. dollars the most recent fiscal year.

Motor vehicle sales grew by some 11.9 percent worldwide between 2022 and 2023. Passenger vehicles increased by around 11.3 percent compared to the previous year when some 58.6 million cars were sold worldwide. The current state of the market In 2023, motor vehicle sales reached over 92.7 million units worldwide. China was the largest automobile market worldwide, making up close to 25.8 million of the new car registrations that same year. The United States and Europe ranked second and third, with light vehicle sales reaching approximately 15.5 million units in the U.S. market. The German-based Volkswagen Group and Japanese Toyota Motor were the global leading automakers, with revenues reaching around 348.6 and 311.9 billion U.S. dollars respectively as of May 2024. The path to recovery The automotive chip shortage led to around 11.3 million vehicles being cut from worldwide production in 2021, and forecasts estimate that these disruptions in the automotive supply chain will contribute to the removal of another seven million units from production in 2022. However, despite these challenges, the demand for passenger cars increased in 2021 and 2022, as car sales slowly started to increase. This is partly due to consumers' interest in electric vehicles. Autonomous,electrified, and battery electric vehicles are also forecast to gain popularity in the next decades. Electrified vehicles are projected to make up close to a quarter of car sales worldwide by 2025. By 2040, China is forecast to be one of the largest market for autonomous vehicle sales.

Global new vehicle sales grew by 11.9 percent between 2022 and 2023. In detail, commercial vehicle sales increased by about 13.3 percent, while passenger car sales were up by 11.3 percent.

In 2018, manufacturing labor costs in China were estimated to be **** U.S. dollars per hour. This is compared to an estimated **** U.S. dollars per hour in Mexico, and **** U.S. dollars in Vietnam. Manufacturing jobs in the United States Many people in the United States believe manufacturing jobs to be the backbone of the U.S. economy, despite employment in the manufacturing sector decreasing since 1997, and the monthly change in manufacturing employment being highly variable. Although manufacturing added a value of about ** percent to the U.S. gross domestic product (GDP) in 2018, employment in the United States has been moving away from manufacturing to other means of employment. A difference in earnings Part of this steering away from manufacturing could be due to a difference in labor costs. While hourly wages in Vietnam were less than * U.S. dollars in 2018, hourly wages in the U.S. manufacturing sector hovered around ** U.S. dollars in 2018. The labor costs in the U.S. could simply be too high for companies, who look to countries such as China, Mexico, and Vietnam for cheaper labor.