According to a survey among Chinese consumers in July 2021, ** percent of respondents from China's fourth- and fifth-tier cities believed it is not good to live paycheck to paycheck, slightly higher than those in larger cities. Among surveyed first-tier city residents, ***** percent of respondents thought that there was nothing wrong with having no savings.

In a survey conducted in Australia in 2021, over half of the respondents with an annual household income of between ****** and ****** Australian dollars indicated that they live paycheck to paycheck. Generally, households with higher annual incomes were less likely to live paycheck to paycheck, with the exception of households earning ****** Australian dollars or less, who were slightly less likely than those earning between ****** and ****** Australian dollars to live paycheck to paycheck.

According to a survey, ** percent of members of Generation Z lived paycheck to paycheck. This figure amounted to ** percent for Millennials.

This statistic shows the share of rural Americans who could not afford an unexpected expense in 2019, by income. During the survey, 54 percent of rural Americans who had an income of 25,000 U.S. dollars to 50,000 U.S. dollars reported that they would not be able to pay off an unexpected expense of 1,000 U.S. dollars right away.

Between April 2008 and March 2024, households from the Pakistani and Bangladeshi ethnic groups were the most likely to live in low income out of all ethnic groups, before and after housing costs.

This statistic shows the total personal income in the United States from 1990 to 2023. The data are in current U.S. dollars not adjusted for inflation or deflation. According to the BEA, personal income is the income that is received by persons from all sources. It is calculated as the sum of wage and salary disbursements, supplements to wages and salaries, proprietors' income with inventory valuation and capital consumption adjustments, rental income of persons with capital consumption adjustment, personal dividend income, personal interest income, and personal current transfer receipts, less contributions for government social insurance. Personal income increased to about 23 trillion U.S. dollars in 2023.Personal income Personal income in the United States has risen steadily over the last decades from 5.07 trillion U.S. dollars in 1991 to 23 trillion U.S. dollars in 2023. Personal income includes all earnings including wages, investments, and other sources. Personal income also varied widely across the U.S., where those living in the District of Columbia, on the higher scale, earned an average of 96,873 U.S. dollars per capita and on the lower end of the spectrum, people in Mississippi earned 45,438 U.S. dollars per capita. In the District of Columbia, disposable income averaged some 81,193 U.S. dollars. In total, California earned the most personal income followed by Texas, receiving three trillion U.S. dollars and 1.76 trillion U.S. dollars, respectively. Income tends to vary widely between demographics in the United States. Those with higher education levels tend to earn more money. However, only 25.7 percent of persons with a disability that had a Bachelor's degree or higher were employed in 2020. The Social Security and Supplemental Security Income disability programs provide monetary benefits to the disabled and certain family members.

Check Cashing Service Market Outlook

The global check cashing service market size was valued at approximately USD 11 billion in 2023 and is projected to reach USD 16.5 billion by 2032, growing at a CAGR of 4.5% during the forecast period. This growth is primarily driven by the increasing demand for convenient and quick access to cash, particularly among unbanked and underbanked populations. The check cashing industry is essential for providing financial services to individuals and businesses who lack access to traditional banking facilities.

One of the primary growth factors driving the check cashing service market is the significant portion of the global population that remains unbanked or underbanked. According to recent estimates, over 1.7 billion people worldwide do not have access to traditional banking services. This demographic relies heavily on alternative financial service providers, such as check cashing services, to meet their financial needs. The convenience and immediacy offered by these services make them a popular choice, particularly for individuals living paycheck to paycheck or in remote areas where banking infrastructure may be limited.

Another critical growth factor is the increasing prevalence of gig economy jobs and freelance work. With more people working independently and receiving payments via checks, there is a rising need for quick and reliable check cashing services. This trend is further supported by the growing number of small and medium-sized enterprises (SMEs) that prefer check payments for various transactions. As the gig economy continues to expand, the demand for check cashing services is expected to rise correspondingly, thereby driving market growth.

The integration of technology into check cashing services is also propelling market growth. Innovations such as mobile check cashing apps and online check cashing platforms offer enhanced convenience and accessibility to customers. These technological advancements are particularly appealing to tech-savvy younger generations who value the ability to perform financial transactions on-the-go. Furthermore, the implementation of security measures and verification processes within these digital platforms ensures that customers' transactions are safe and secure, thereby increasing their trust and reliance on these services.

Cash Flow Management Service plays a crucial role in the financial ecosystem, particularly for businesses and individuals who rely on check cashing services. These services help manage the inflow and outflow of cash, ensuring that there is sufficient liquidity to meet immediate financial obligations. For businesses, effective cash flow management can mean the difference between thriving and struggling, as it allows them to maintain operations smoothly and invest in growth opportunities. Individuals, especially those who are unbanked or underbanked, benefit from cash flow management services by gaining better control over their finances, reducing the risk of financial shortfalls, and planning for future expenses. The integration of cash flow management services with check cashing solutions can provide a comprehensive financial strategy that enhances financial stability and security.

In terms of regional outlook, North America is expected to dominate the check cashing service market, owing to the substantial unbanked population and the widespread acceptance of alternative financial services. The Asia Pacific region is also anticipated to witness significant growth, driven by the increasing adoption of digital financial services and the expanding middle-class population seeking convenient banking alternatives. Europe, Latin America, and the Middle East & Africa are projected to experience steady growth, supported by ongoing efforts to improve financial inclusion and the rising demand for quick access to cash.

Service Type Analysis

Payroll Check Cashing

Payroll check cashing services represent a significant segment of the overall check cashing service market. This service type is particularly popular among workers who receive their wages in the form of paper checks. The convenience of being able to cash a payroll check immediately after receiving it, often without the need for a bank account, makes this service highly valuable. Many employees, especially those in low-income brackets or those employed in temporary or part-time positions, rely on payroll check cashing services to access the

More than half of the respondents in a global survey were at least slightly struggling with paying for basic needs as of September 2022. The single commodity that most people were struggling with was energy and utilities, followed by food. On the other hand, fewest were affected by credit card repayments. Rising inflation rates have seen cost of living surge in 2022, which has especially affected energy and certain types of food.

The 2025 State Employee Pay page provides a comprehensive breakdown of salary structures, cost-of-living adjustments (COLAs), pay raises, and classification changes for state employees across various departments and positions. It includes information on:

Updated salary schedules by classification and grade

Annual cost-of-living adjustments (if approved by legislature)

Bonus or incentive pay (where applicable)

Pay equity adjustments

Job title and classification updates

Agency-specific pay plans

This resource is essential for current state workers, HR professionals, policy analysts, and those considering employment in the public sector.

Whether you're a classified employee, exempt worker, or part of a unionized workforce, this guide outlines how your pay may be affected throughout 2025 based on legislation, union negotiations, and state budget allocations.

Estimates of the number and proportion of UK employee jobs with hourly pay below the living wage, by region, work geography, local authority and Parliamentary constituency, as defined by the Living Wage Foundation.

A structured overview of the average, net, median, and minimum wage in Germany for 2025. This dataset combines original market research conducted by KUMMUNI GmbH with publicly available data from the German Federal Statistical Office. It includes values with and without bonuses, hourly minimum wage, and take-home pay after tax.

Median earnings of residents - Gross Weekly Pay (£)

This measure is the median weekly earnings for full-time employees (working 39.1 hours per week – 2017 average) where half the workers earn above that amount, and half earn below that amount This gives an indication of living standards people are able to enjoy through their disposable income.

Changes in the composition of the workforce, demonstrated by changes in median earnings, can show the effect of council’s Economic Strategy. For example, creation of lower paid jobs, or loss of highly-paid jobs, can both act to reduce the median.

In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.

Between 2018 and 2022, people in households in the ‘other’, Asian and black ethnic groups were the most likely to be in persistent low income, both before and after housing costs, out of all ethnic groups.

Average monthly disposable salary Years: 2013-2014 DEFINITION: Average Monthly Disposable Salary (After Tax). Based on 0-50 contributions for Afghanistan, Aland Islands, Andorra and 81 more countries and 50-100 contributions for Albania, Algeria, Armenia and 19 more countries and over 100 contributions for Argentina, Australia, Austria and 82 more countries. The surveys were conducted by numbeo.com from May, 2011 to February, 2014. See this sample survey for the United States, respondents were asked "Average Monthly Disposable Salary (After Tax)". Prices in current USD.

Source: https://www.nationmaster.com/country-info/stats/Cost-of-living/Average-monthly-disposable-salary/After-tax#

This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

Abstract

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Nauru. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people.

Some more specific outputs from the survey are listed below: a) To obtain expenditure weights and other useful data for the revision of the consumer price index; b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts; c) To supply basic data needed for policy making in connection with social and economic planning; d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption; e) To gather information on poverty lines and incidence of poverty throughout Nauru.

Geographic coverage

National

Analysis unit

• Household
• Person
• Expenditure Commodity

Universe

The survey covered all private households on the island of Nauru. When the survey was in the field, interviewers were further required to reduce the scope by removing those households which had not been residing in Nauru for the last 12 months and did not intend to stay in Nauru for the next 12 months.

Persons living in special dwellings (Hospital, Prison, etc) were not included in the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size adopted for the survey was 500 households which allowed for expected sample loss, whilst still maintaining a suitable responding sample for the analysis.

Before the sample was selected, the population was stratified by constituency in order to assist with the logistical issues associated with the fieldwork. There were eight constituencies in total, along with "Location" which stretches across the districts of Denigamodu and Aiwo, forming nine strata in total. Although constituency level analysis was not a priority for the survey, sample sizes within each stratum were kept to a minimum of 40 households, to enable some basic forms of analysis at this level if required.

The sample selection procedure within each stratum was then to sort each household on the frame by household size (number of people), and then run a systematic skip through the list in order to achieve the desirable sample size.

Sampling deviation

No deviations from the sample design took place.

Mode of data collection

Face-to-face [f2f] for questionnaires, self-enumeration for the diaries

Research instrument

The survey schedules adopted for the HIES included the following: · Expenditure questionnaire · Income questionnaire · Miscellaneous questionnaire · Diary (x2)

Whilst a Household Control Form collecting basic demographics is also normally included with the survey, this wasn't required for this HIES as this activity took place for all households in the mini census.

Information collected in the four schedules covered the following:

Expenditure questionnaire: Covers basic details about the dwelling structure and its access to things like water and sanitation. It was also used as the vehicle to collect expenditure on major and infrequent expenditures incurred by the household.

Income questionnaire: Covers each of the main types of household income generated by the household such as wages and salaries, business income and income from subsistence activities.

Miscellaneous questionnaire: Covers topics relating to health access, labour force status and education.

Diary: Covers all day to day expenditures incurred by the household, consumption of items produced by the household such as fish and crops, and gifts both received and given by the household.

Cleaning operations

There were 3 phases to the editing process for the 2006 Nauru HIES which included: 1. Data Verification operations 2. Data Editing operations 3. Data Auditing operations

For more information on what each phase entailed go the document HIES Processing Instructions attached to this documentation.

Response rate

The survey response rates were a lot lower than expected, especially in some districts. The district of Aiwo, Uaboe and Denigomodu had the lowest response rates with 16.7%, 20.0% and 34.8% respectively. The area of Location was also extremely low with a responses rate of 32.2%. On a more positive note, the districts of Yaren, Ewa, Anabar, Ijuw and Anibare all had response rates at 80.0% or better.

The major contributing factor to the low response rates were households refusing to take part in the survey. The figures for responding above only include fully responding households, and given there were many partial responses, this also brought the values down. The other significant contributing factor to the low response rates was the interviewers not being able to make contact with the household during the survey period.

Unfortunately, not only do low response rates often increase the sampling error of the survey estimates, because the final sample is smaller, it will also introduce response bias into the final estimates. Response bias takes place when the households responding to the survey possess different characteristics to the households not responding, thus generating different results to what would have been achieved if all selected households responded. It is extremely difficult to measure the impact of the non-response bias, as little information is generally known about the non-responding households in the survey. For the Nauru 2006 HIES however, it was noted during the fieldwork that a higher proportion of the Chinese population residing in Nauru were more likely to not respond. Given it is expected their income and expenditure patterns would differ from the rest of the population, this would contribute to the magnitude of the bias.

Sampling error estimates

To determine the impact of sampling error on the survey results, relative standard errors (RSEs) for key estimates were produced. When interpreting these results, one must remember that these figures don't include any of the non-sampling errors discussed in other sections of this documentation

To also provide a rough guide on how to interpret the RSEs provided in the main report, the following information can be used:

Category  Description
RSE < 5%  Estimate can be regarded as very reliable
5% < RSE < 10% Estimate can be regarded as good and usable
10% < RSE < 25% Estimate can be considered usable, with caution
RSE > 25%  Estimate should only be used with extreme caution

The actual RSEs for the key estimates can be found in Section 4.1 of the main report

As can be seen from these tables, the estimates for Total Income and Total Expenditure from the HIES can be considered to be very good, from a sampling error perspective. The same can also be said for the Wage and Salary estimate in income and the Food estimate in expenditure, which make up a high proportion of each respective group.

Many of the other estimates should be used with caution, depending on the magnitude of their RSE. Some of these high RSEs are to be expected, due to the expected degree of variability for how households would report for these items. For example, with Business Income (RSE 56.8%), most households would report no business income as no household members undertook this activity, whereas other households would report large business incomes as it's their main source of income.

Data appraisal

Other than the non-response issues discussed in this documentation, other quality issues were identified which included: 1) Reporting errors Some of the different aspects contributing to the reporting errors generated from the survey, with some examples/explanations for each, include the following:

a) Misinterpretation of survey questions: A common mistake which takes place when conducting a survey is that the person responding to the questionnaire may interpret a question differently to the interviewer, who in turn may have interpreted the question differently to the people who designed the questionnaire. Some examples of this for a HIES can include people providing answers in dollars and cents, instead of just dollars, or the reference/recall period for an “income” or “expenditure” is misunderstood. These errors can often see reported amounts out by a factor of 10 or even 100, which can have major impacts on final results.

b) Recall problems for the questionnaire information: The majority of questions in both of the income and expenditure questionnaires require the respondent to recall what took place over a 12 month period. As would be expected, people will often forget what took place up to 12 months ago so some information will be forgotten.

c) Intentional under-reporting for some items: For whatever reasons, a household may still participate in a survey but not be willing to provide accurate responses for some questions. Examples for a HIES include people not fully disclosing their total income, and intentionally under-reporting expenditures on items such as alcohol and tobacco.

d) Accidental under-reporting in the household diaries: Although the two diaries are left with the household for a period of two weeks, it is easy for the household to forget to enter all expenditures throughout this period - this problem most likely increases as the two

Abstract copyright UK Data Service and data collection copyright owner.

To examine public attitudes to an incomes policy, undertaken in January 1974.
Main Topics:

Attitudinal/Behavioural Questions
First asking for the respondent's definition of an incomes policy, the survey then concentrates on the effects of such a policy, asking for agreement or disagreement with a series of statements concerning wages and incomes, respondent's choice of most acceptable reason for a pay rise from a given list of nine reasons and the respondent's attitude towards 'special cases'. Concerning the effect of an incomes policy on the respondent himself, information is obtained on whether respondent feels that such a policy would make him better off or not, what income level the respondent feels necessary to maintain a proper standard of living, whether the present government is doing enough for 'people like yourself', and, finally, what is understood by the phrase 'people like yourself', eliciting a subjective assessment of class.
The effect of an incomes policy on the country's economy, on a capable and hardworking person's chances of getting on, on Britain as a place to live and on the amount of government interference in everyday life is also assessed. All those in full-time employment were asked whether they would, unconditionally, accept a pay increase of 7p in the $ or less and whether they would accept the following if the government was thereby able to keep prices steady: such a limitation on their annual pay rise (if they would not accept it unconditionally), the imposition of fines on unions making strikes for wage claims above the level allowed by the incomes policy, or a total wage freeze. Two final questions ask for the respondent's opinion as to whether any government could keep prices steady and for his attitude to the pay freeze of 1973. Some questions in this survey were taken from W G Runciman's Relative Deprivation and Social Justice (data held as Survey 028).
Background Variables
Age, sex, party membership and support, union membership (and whether active member or not), geographical region, whether employed or not, type of job (manual, non-manual) and occupational class according to a four-point scale.

In 2024, around 1.75 million people received unemployment benefits, known as Arbeitslosengeld II (ALG II) in Germany. ALG II, also called Hartz IV, is social benefit payments to people without an income who cannot work to make a living. Whether a claimant is eligible for Arbeitslosengeld II depends on his or her assets, savings, life insurance and the income of a spouse or partner. If all of these assets are below a threshold level, a claimant can get money from the state.

🇬🇧 영국 English Average pay is based on full-time equivalent annual salary olus additional payments for Chief Officers. It excludes election fees "Lowest paid staff" is defined as those paid on National 'living wage' - please click the link for officer pay policy.