In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

A breakdown of annual household incomes in Japan showed that around ***** percent of households earned less than *** million Japanese yen per year as of 2024. That year, the average annual household income of Japanese households was approximately *** million yen compared to a median household income of *** million yen.

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

Calculation of out-of-pocket cap based on five-level family income.

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

The poorest five percent of the population in Brazil received a monthly income of merely *** reals in 2024, with their jobs as their only source of income. By contrast, the average income of workers who fall within the 40 percent to 50 percent percentile, and from 50 percent to 60 percent are **** and **** Brazilian reals, respectively.

The bottom 50 percent in Argentina earned on average 15,057 U.S. dollars at purchasing power parity (PPP) before income taxes as of 2022, while individuals in the top one percent earned pre-tax more than 686,433 dollars. Looking at the percentage distribution of wealth in Argentina, the poorest half held 5.7 percent of the total in 2021. Moreover, the top one percent in the South American country accounted for 25.7 percent of the overall national wealth.

The graphing calculator market, while facing some headwinds, is poised for steady growth over the next decade. Driven by the continued importance of STEM education globally and the increasing complexity of mathematical and scientific curricula, demand for graphing calculators remains robust, particularly in schools and universities. The market is segmented by application (school, laboratory, companies) and type (color display, black and white), with color display calculators commanding a premium price point and capturing a larger share of the market due to their enhanced functionality and user-friendliness. While the rise of sophisticated smartphone apps and tablets offering similar functionalities presents a challenge, the dedicated features and reliability of standalone graphing calculators— particularly in exam settings where electronic devices are often restricted — continue to sustain market demand. The market's growth is further supported by the consistent advancements in calculator technology, with manufacturers like Texas Instruments, Casio, HP, and others continually improving features like processing power, memory, and connectivity. However, factors such as the increasing affordability of tablets and smartphones with advanced calculator capabilities act as a restraint on market expansion. The regional distribution of the graphing calculator market reflects global educational trends. North America and Europe currently hold significant market shares, owing to well-established educational systems and a strong focus on STEM education. However, Asia Pacific, particularly China and India, are expected to experience significant growth in the coming years due to their expanding educational infrastructure and a burgeoning middle class with increased disposable income. This growth will likely be fueled by government initiatives promoting STEM education and increased investment in educational technology. Competition among established manufacturers is intense, with a focus on innovation in functionalities and value-added features to maintain market share. Strategies involving partnerships with educational institutions and developing specialized software are likely to prove effective in the longer term. A conservative estimate suggests the market will see a Compound Annual Growth Rate (CAGR) of approximately 5% from 2025 to 2033, leading to substantial market expansion.

In Mexico, as of 2022, the bottom 50 percent, which represents the population whose income lied below the median, earned on average 2,076 euros at purchasing power parity (PPP) before income taxes. Meanwhile, the top ten percent had an average earning of 111,484 euros, 53 times over than the average earning of the bottom half. Further, the bottom 50 percent accounted for -0.3 percent of the overall national wealth in Mexico, that is, they have on average more debts than assets.

The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income (LMI) persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency. Most activities funded by the CDBG program are designed to benefit low- and moderate-income (LMI) persons. That benefit may take the form of housing, jobs, and services. Additionally, activities may qualify for CDBG assistance if the activity will benefit all the residents of a primarily residential area where at least 51 percent of the residents are low- and moderate-income persons, i.e. area-benefit (LMA). [Certain exception grantees may qualify activities as area-benefit with fewer LMI persons than 51 percent.]The Office of Community Planning and Development (CPD) provides estimates of the number of persons that can be considered Low-, Low- to Moderate-, and Low-, Moderate-, and Medium-income persons based on special tabulations of data from the 2016-2020 ACS 5-Year Estimates and the 2020 Island Areas Census. The Low- and Moderate-Income Summary Data may be used by CDBG grantees to determine whether or not a CDBG-funded activity qualifies as an LMA activity. The LMI percentages are calculated at various principal geographies provided by the U.S. Census Bureau. CPD provides the following datasets:Geographic Summary Level "150": Census Tract-Block Group.The block groups are associated with the HUD Unit-of-Government-Identification-Code for the CDBG grantee jurisdiction by fiscal year that is associated with each block group.Local government jurisdictions include; Summary Level 160: Incorporated Cities and Census-Designated Places, i.e. "Places", Summary Level 170: Consolidated Cities, Summary Level 050: County, and Summary Level 060: County Subdivision geographies.In the data files, these geographies are identified by their Federal Information Processing Standards (FIPS) codes and names for the place, consolidated city, or block group, county subdivision, county, and state.The statistical information used in the calculation of estimates identified in the data sets comes from the 2016-2020 ACS, 2020 Island Areas Census, and the Income Limits for Metropolitan Areas and for Non Metropolitan Counties. The data necessary to determine an LMI percentage for an area is not published in the publicly-available ACS data tables. Therefore, the Bureau of Census matches family size, income, and the income limits in a special tabulation to produce the estimates.Estimates are provided at three income levels: Low Income (up to 50 percent of the Area Median Income (AMI)); Moderate Income (greater than 50 percent AMI and up to 80 percent AMI), and Medium Income (greater than 80 percent AMI and up to 120 AMI). HUD is publishing the margin of error (MOE) data for all block groups and all places in the 2020 ACS LMISD. These data are provided within the LMISD tables.The MOE does not provide an expanded range for compliance. For example, a service area of 50 percent LMI with a 2 percent MOE would still be just 50 percent LMI for compliance purposes. However, the 2 percent MOE would inform the grantee about the accuracy of the ACS data before undergoing the effort and cost of conducting a local income survey, which is the alternative to using the HUD-provided data.CPD Notice 24-04 announced the publication of LMISD based on the 2020 ACS, and updated CPD Notice 19-02 as well as explains policy about the accuracy of surveys conducted pursuant to CPD Notice 14-013.Questions about the calculation of the estimates may be directed to Formula Help Desk.Questions about the use of the data should be directed to the staff of the CPD Field Office.

The average pre-tax income of the top ten percent earners in Spain was over 120,000 euros at purchasing power parity (PPP) as of 2024, almost nine times more than the average income of the bottom half earners. Looking at the distribution of national income in Spain, the earnings of the least affluent half of the population equated to 21 percent of the total country income in 2024, 0.1 percentage points less than one decade earlier. Moreover, the top one percent of earners in Spain accounted for over ten percent of the overall national income.

Physical Graphing Calculators Sales Market Outlook

The global physical graphing calculators sales market size was valued at approximately $900 million in 2023 and is expected to reach around $1.3 billion by 2032, growing at a CAGR of 4.1% over the forecast period. The increasing emphasis on STEM (Science, Technology, Engineering, and Mathematics) education and the indispensability of graphing calculators in various professional fields are key growth factors driving the market.

The growing focus on STEM education across the globe is a significant growth factor for the physical graphing calculators market. Governments and educational institutions are investing heavily in STEM education to help students develop essential skills in mathematics and science. Graphing calculators are often required for coursework in subjects like algebra, calculus, and statistics, making them a staple in both high school and college classrooms. The emphasis on STEM education is expected to grow, thereby driving the demand for physical graphing calculators.

Technological advancements in graphing calculators are also contributing to market growth. Modern graphing calculators are equipped with advanced features such as color displays, touchscreens, and the ability to connect to other devices via Bluetooth or USB. These features make the calculators more versatile and user-friendly, enhancing their appeal to both students and professionals. Additionally, the integration of software that allows for the visualization of complex mathematical functions and data analysis further adds to their utility, thereby boosting sales.

Another significant growth driver is the increasing requirement for graphing calculators in standardized testing. Many standardized tests, such as the SAT, ACT, and various state-specific exams, permit or even require the use of graphing calculators. This trend is not limited to the United States but extends to other regions as well. The requirement for these devices in exams ensures a steady demand from students who need to be adequately equipped to perform well in these tests.

Regionally, North America and Asia Pacific are expected to be key markets for physical graphing calculators. North America, led by the United States, has a well-established education system that mandates the use of graphing calculators in high schools and colleges. In Asia Pacific, countries like China and India are focusing on improving their education systems, including the implementation of advanced learning tools like graphing calculators. The growing middle-class population and increasing disposable income in these regions are also contributing to the market's growth.

Product Type Analysis

The physical graphing calculators market is segmented into three main product types: Scientific Graphing Calculators, Programmable Graphing Calculators, and Financial Graphing Calculators. Each of these segments caters to different needs and applications, which are driving their respective demands.

Scientific graphing calculators are predominantly used in educational settings, particularly in subjects like mathematics and physics. These calculators offer functionalities that are essential for solving complex equations, plotting graphs, and performing algebraic manipulations. The demand for scientific graphing calculators is driven by their widespread use in high schools and universities. As educational curriculums continue to evolve to include more complex mathematical concepts, the need for these calculators will likely increase, sustaining the demand in this segment.

Programmable graphing calculators are another important segment, primarily used in engineering and advanced scientific applications. These calculators allow users to write custom programs and algorithms, making them highly versatile and useful for solving specialized problems. The growing emphasis on computer science and programming in education and professional fields is boosting the demand for programmable graphing calculators. Additionally, their application in engineering tasks such as circuit design and structural analysis makes them indispensable tools for professionals in these fields.

Financial graphing calculators cater to the needs of finance professionals and students. These calculators are equipped with functionalities that are essential for financial planning, investment analysis, and accounting. The increasing complexity of financial markets and the need for accurate financial analysis are driving the demand for financial graphing calculators. F

This dataset contains all the different possible combinations for employee benefits offered at HRM. The benefits account for all position and employee group combinations. These benefit options include health, dental, and income replacement coverage.

This dataset is used to support HRM's Benefit Estimate Calculator. This dataset is for estimation only, rates and options are subject to change without notice. For additional information about employment benefits at HRM please visit https://www.halifax.ca/abouthalifax/ employment/employee-benefits.

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The analysis of real wages has a long tradition in Germany. The focus of the acquisition is on company wages, on wages of certain branches or for categories of workers as well as on the investigation of long term aggregated nominal and real wages. The study of Ashok V. Desai on the development of real wages in the German Reich between 1871 and 1913 is an important contribution to historical research on wages. The study is innovative and methodically on an exemplary level. But mainly responsible for the upswing in the historical research on wages in the 50s and 60s is an extraordinary publication by Jürgen Kuczynski. “The new historical research on wages in Germany is insolubly connected with Jürgen Kuczynski. In his broad researches the history of wages is only one section among many other themes but it is a very important one can be seen as the core piece of his work.” (Kaufhold, K.H., 1987: Forschungen zur deutschen Preis- und Lohngeschichte (seit 1930). In: Historia Socialis et Oeconomica. Festschrift für Wolfgang Zorn zum 65. Geburtstag. Stuttgart: Franz Steiner Verlag, S, 83). In his first study on long series on nominal and real wages in Germany he used a broad empirical basis and encouraged more research in this area. His weaknesses are methodological inconsistencies and a restricted representativeness. For example he includes tariff wages but also actually paid wages. Some important industries like food or textile industry are not taken into account. Wages in agriculture were often estimated but without enough material necessary for a good estimation. Wages for work at home are not regraded in the calculation of the index. The weight of cities in the calculation of the index is relatively too high compared to rural regions and therefor it leaks regional representativeness.In his study Desai uses the reports of trade associations for the Reich´s insurance office on the persons who are insured in the accident insurance and their wages as a basis for the calculation of annual nominal average wages. Desais focusses on industrial wages because only for them long term series are available. As the insurance premiums are calculated according to the income level the documents of the trade associations can be used for the calculation of an index for wages development. Desais study is also very useful regarding the calculation of a new index for costs of living based the model of a typical worker family. „F. Grumbach and H. König have used the same sources to derive indices of industrial earnings. The main differences between their series and ours are: (a) we have adopted the industrial classification followed by the Reichsversicherungsamt, while Grumbach and König have made larger industrial groups, (b) we have calculated average annual earnings, while they claim to have calculated average daily earnings (i.e. to have adjusted the annual figures for the average number of days worked per year per worker), and (c) they have failed to correct distortions in the original data” (Desai, A.V., 1968: Real Wages in Germany 1871–1913. Oxford. Clarendon Press, S. 4). Register of tables in HISTAT:A. OverviewsA.1 Overview: Different estimations of the real and nominal gross wages in the German Reich, index 1913 = 100 (1871-1913)A.2 Overview: Development of costs of living, index 1913 = 100 (1871-1913)A.3 Overview: Development of nominal and real wages, index 1913=100 (1844-1937) D. Study by Ashok V. DesaiD.01 Different estimations of real wages in the German Reich, index 1895 = 100 (1871-1913)D.02 Annual average wage (1871-1886)D.03 Annual gross wages in chosen production segments (1887-1913)D.04 Annual average wage in industry, transportation and trade (1871-1913)D.05 Construction of an index for costs of living, 1895 = 100 (1871-1913)D.06 Real wages, in constant prices from 1895 (1871-1913)D.07 Wheat prices and prices for wheat bread (1872-1913)D.08 Rye prices and prices for rye bread (1872-1913)D.09 Average export prices by product groups, index 1895 = 100 (1872-1913)D.10 Average import prices by product groups, index 1895 = 100 (1872-1913)D.11 Average export prices, import prices and terms of trade, index 1895 = 100 (1872-1913) O. Study by Thomas J. OrsaghO. Adjusted indices for costs of living and real wages after Orsgah, index 1913 = 100 (1871-1913)

Low income measure (LIM) thresholds by household size for market income, total income and after-tax income, in current and constant dollars, annual.

A dataset of car tax calculations for company cars by operating cycle, manufacturer, model, and derivative.

BackgroundCoronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global pandemic affecting millions worldwide. This study aims to bridge the knowledge gap between acute and chronic symptoms, vaccination impact, and associated factors in patients across different low- and middle-income countries (LMICs).Materials and methodsThe study included 2,445 participants aged 18 years and older, testing positive for COVID-19. Data collection involved screening for medical histories, testing records, symptomatology, and persistent symptoms. Validated instruments, including the DePaul Symptom Questionnaire (DSQ-2) and the Patient Health Questionnaire-9 (PHQ-9), were used. We applied a self-supervised and unsupervised deep neural network to extract features from the questionnaire. Gradient boosted machines (GBM) model was used to build a risk calculator for chronic fatigue syndrome (CFS), depression, and prolonged COVID-19 symptoms.ResultsOut of the study cohort, 68.1% of the patients had symptoms lasting longer than 2 weeks. The most frequent symptoms were loss of smell (46.8%), dry cough (40.1%), loss of taste (37.8%), headaches (37.2%), and sore throat (28.9%). The patients also reported high rates of depression (47.7%), chronic fatigue (6.5%), and infection after vaccination (23.7%). Factors associated with CFS included sex, age, and smoking. Vaccinated individuals demonstrated lower odds of experiencing prolonged COVID-19 symptoms, CFS, and depression. The predictive models achieved a high area under the curve (AUC) scores of 0.87, 0.82, and 0.74, respectively.ConclusionThe findings underscore the significant burden of long-term symptoms such as chronic fatigue and depression, affecting a considerable proportion of individuals post-infection. Moreover, the study reveals promising insights into the potential benefits of vaccination in mitigating the risk of prolonged COVID-19 symptoms, CFS, and depression. Overall, this research contributes valuable knowledge towards comprehensive management and prevention efforts amidst the ongoing global pandemic.Clinical trial registrationClinical trials.gov, NCT05059184.

Calculation of indicators of the "affordability" category of GFSI.