About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in China, Maine, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 21,283, while the mean income for the highest quintile (20% of households with the highest income) is 236,557. This indicates that the top earners earn 11 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 401,757, which is 169.84% higher compared to the highest quintile, and 1887.69% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for China town median household income. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Mexico, MO, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 10,617, while the mean income for the highest quintile (20% of households with the highest income) is 160,507. This indicates that the top earners earn 15 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 284,944, which is 177.53% higher compared to the highest quintile, and 2683.85% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mexico median household income. You can refer the same here

This map is visualizing the changes in average household income (in 2023 dollars) for individuals at the county level, based on their parents' income level (see table below). Changes are defined by the mean household income earned by individuals born in 1978 and individuals born in 1992 (measured at age 27). Income is an important measure of economic mobility, which is the ability to improve economic status over time. The data is sourced from the Opportunity Atlas, a comprehensive dataset developed through a collaboration between researchers at the U.S. Census Bureau and Opportunity Insights at Harvard University. It includes data from the 2000 and 2010 decennial Census, Federal Income Tax returns, and the 2005-2015 American Community Surveys (ACS).Parent income percentileAverage household income (2023 dollars)Lowest (1st percentile)$1,150Low (25th percentile)$33,320Middle (50th percentile)$69,520High (75th percentile)$122,040Highest (100th percentile)$1,840,000 The table outlines the approximate dollar values for each parent percentile group that are referenced in the datasets. See more information on the Opportunity Insights FAQ page.

Abstract

The Health Inequality Project uses big data to measure differences in life expectancy by income across areas and identify strategies to improve health outcomes for low-income Americans.

Section 7

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution. Both race-adjusted and unadjusted estimates are reported.

Source

Section 13

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution separately by year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 6

This dataset was created on 2020-01-10 18:53:00.508 by merging multiple datasets together. The source datasets for this version were:

Commuting Zone Life Expectancy Estimates by year: CZ-level by-year life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy: Commuting zone (CZ)-level life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy Trends: CZ-level estimates of trends in life expectancy for men and women, by income quartile

Commuting Zone Characteristics: CZ-level characteristics

Commuting Zone Life Expectancy for larger populations: CZ-level life expectancy estimates for men and women, by income ventile

Section 15

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by state of residence and year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 11

This table reports US mortality rates by gender, age, year and household income percentile. Household incomes are measured two years prior to the mortality rate for mortality rates at ages 40-63, and at age 61 for mortality rates at ages 64-76. The “lag” variable indicates the number of years between measurement of income and mortality.

Observations with 1 or 2 deaths have been masked: all mortality rates that reflect only 1 or 2 deaths have been recoded to reflect 3 deaths

Source

Section 3

This table reports coefficients and standard errors from regressions of life expectancy estimates for men and women at age 40 for each quartile of the national income distribution on calendar year by commuting zone of residence. Only the slope coefficient, representing the average increase or decrease in life expectancy per year, is reported. Trend estimates for both race-adjusted and unadjusted life expectancies are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 9

This table reports life expectancy estimates at age 40 for Males and Females for all countries. Source: World Health Organization, accessed at: http://apps.who.int/gho/athena/

Source

Section 10

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by county of residence. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for counties with populations larger than 25,000 only

Source

Section 2

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by commuting zone of residence and year. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 8

This table reports US population and death counts by age, year, and sex from various sources. Counts labelled “dm1” are derived from the Social Security Administration Data Master 1 file. Counts labelled “irs” are derived from tax data. Counts labelled “cdc” are derived from NCHS life tables.

Source

Section 12

This table reports numerous county characteristics, compiled from various sources. These characteristics are described in the county life expectancy table.

Two variables constructed by the Cen

Household income statistics by household type (couple family, one-parent family, non-census family households) and household size for Canada, provinces and territories, census divisions and census subdivisions.

Upper income limit, income share and average of market, total and after-tax income by economic family type and income decile, annual.

The Distributional Financial Accounts (DFAs) provide a quarterly measure of the distribution of U.S. household wealth since 1989, based on a comprehensive integration of disaggregated household-level wealth data with official aggregate wealth measures. The data set contains the level and share of each balance sheet item on the Financial Accounts' household wealth table (Table B.101.h), for various sub-populations in the United States. In our core data set, aggregate household wealth is allocated to each of four percentile groups of wealth: the top 1 percent, the next 9 percent (i.e., 90th to 99th percentile), the next 40 percent (50th to 90th percentile), and the bottom half (below the 50th percentile). Additionally, the data set contains the level and share of aggregate household wealth by income, age, generation, education, and race. The quarterly frequency makes the data useful for studying the business cycle dynamics of wealth concentration--which are typically difficult to observe in lower-frequency data because peaks and troughs often fall between times of measurement. These data will be updated about 10 or 11 weeks after the end of each quarter, making them a timely measure of the distribution of wealth.

This map is visualizing the changes in average household income (in 2023 dollars) for individuals at the commuting zone level, based on their parents' income level (see table below). Changes are defined by the mean household income earned by individuals born in 1978 and individuals born in 1992 (measured at age 27). Income is an important measure of economic mobility, which is the ability to improve economic status over time. The data is sourced from the Opportunity Atlas, a comprehensive dataset developed through a collaboration between researchers at the U.S. Census Bureau and Opportunity Insights at Harvard University. It includes data from the 2000 and 2010 decennial Census, Federal Income Tax returns, and the 2005-2015 American Community Surveys (ACS).Parent income percentileAverage household income (2023 dollars)Lowest (1st percentile)$1,150Low (25th percentile)$33,320Middle (50th percentile)$69,520High (75th percentile)$122,040Highest (100th percentile)$1,840,000The table outlines the approximate dollar values for each parent percentile group that are referenced in the datasets. See more information on the Opportunity Insights FAQ page.

Families of tax filers; Distribution of total income by census family type and age of older partner, parent or individual (final T1 Family File; T1FF).

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

China % of Household grouped by Annual Income: Urban:RMB65000-70000 data was reported at 4.920 % in 2011. This records an increase from the previous number of 4.420 % for 2010. China % of Household grouped by Annual Income: Urban:RMB65000-70000 data is updated yearly, averaging 3.480 % from Dec 2005 (Median) to 2011, with 7 observations. The data reached an all-time high of 4.920 % in 2011 and a record low of 1.500 % in 2005. China % of Household grouped by Annual Income: Urban:RMB65000-70000 data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Household Income Distribution: Urban.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Lexington town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 9(0.07%) households where the householder is under 25 years old, 2,355(19.09%) households with a householder aged between 25 and 44 years, 5,931(48.07%) households with a householder aged between 45 and 64 years, and 4,042(32.76%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Lexington town, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lexington town median household income by age. You can refer the same here

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_1f57cbc6cc41d72fb1b96c7c266c2eaf/view

Information on farm household income and farm household composition. Source agency: Environment, Food and Rural Affairs Designation: National Statistics Language: English Alternative title: Farm Household Income and Household Composition, England If you require the datasets in a more accessible format, please contact fbs.queries@defra.gsi.gov.uk Background and guidance on the statistics Information on farm household income and farm household composition was collected in the Farm Business Survey (FBS) for England for the first time in 2004/05. Collection of household income data is restricted to the household of the principal farmer from each farm business. For practical reasons, data is not collected for the households of any other farmers and partners. Two-thirds of farm businesses have an input only from the principal farmer’s household (see table 5). However, details of household composition are collected for the households of all farmers and partners in the business, but not employed farm workers. Data on the income of farm households is used in conjunction with other economic information for the agricultural sector (e.g. farm business income) to help inform policy decisions and to help monitor and evaluate current policies relating to agriculture in the United Kingdom by Government. It also informs wider research into the economic performance of the agricultural industry. This release gives the main results from the income and composition of farm households and the off-farm activities of the farmer and their spouse (Including common law partners) sections of the FBS. These sections include information on the household income of the principal farmer’s household, off-farm income sources for the farmer and spouse and incomes of other members of their household and the number of working age and pensionable adults and children in each of the households on the farm (the information on household composition can be found in Appendix B). This release provides the main results from the 2013/14 FBS. The results are presented together with confidence intervals. Survey content and methodology The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2013 there were just over 58 thousand farm businesses meeting this criteria. Since 2009/10 a sub-sample of around 1,000 farms in the FBS has taken part in both the additional surveys on the income and composition of farm households and the off-farm activities of the farmer and their spouse. In previous years, the sub-sample had included over 1,600 farms. As such, caution should be taken when comparing to earlier years. The farms that responded to the additional survey on household incomes and off-farm activities of the farmer and spouse had similar characteristics to those farms in the main FBS in terms of farm type and geographical location. However, there is a smaller proportion of very large farms in the additional survey than in the main FBS. Full details of the characteristic of responding farms can be found at Appendix A of the notice. For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey Data analysis The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. Completion of the additional survey on household incomes and off-farm activities of the farmer and spouse was voluntary and a sample of around 1,000 farms was achieved. In order to take account of non-response, the results have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income). Accuracy and reliability of the results We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval. The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years. Availability of results This release contains headline results for each section. The full set of results can be found at: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey#publications Defra statistical notices can be viewed on the on the statistics pages of the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates. Data Uses Data from the Farm Business Survey (FBS) are provided to the EU as part of the Farm Accountancy Data Network (FADN). The data have been used to help inform policy decisions (e.g. Reform of Pillar 1 and Pillar 2 of Common Agricultural Policy) and to help monitor and evaluate current policies relating to agriculture in England (and the EU). It is also widely used by the industry for benchmarking and informs wider research into the economic performance of the agricultural industry. User engagement As part of our ongoing commitment to compliance with the Code of Practice for Official Statistics http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html, we wish to strengthen our engagement with users of these statistics and better understand the use made of them and the types of decisions that they inform. Consequently, we invite users to make themselves known, to advise us of the use they do, or might, make of these statistics, and what their wishes are in terms of engagement. Feedback on this notice and enquiries about these statistics are also welcome. Definitions Household income of the principal farmer Principal farmer’s household income has the following components: (1) The share of farm business income (FBI) (including income from farm diversification) attributable to the principal farmer and their spouse. (2) Principal farmer’s and spouse’s off farm income from employment and self-employment, investment income, pensions and social payments. (3) Income of other household members. The share of farm business income and all employment and self-employment incomes, investment income and pension income are recorded as gross of income tax payments and National Insurance contributions, but after pension contributions. In addition, no deduction is made for council tax. Household A household is defined as a single person or group of people living at the same address as their only or main residence, who either share one meal a day together or share the living accommodation. A household must contain at least one person who received drawings from the farm business or who took a share of the profit from the business. Drawings Drawings represent the monies which the farmer takes from the business for their own personal use. The percentage of total drawings going to each household is collected and is used to calculate the total share of farm business income for the principal farmer’s household. Mean Mean household income of individuals is the ”average”, found by adding up the weighted household incomes for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean. Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. household income or net worth), into 100 equal-sized groups. E.g. twenty five per cent of the population would have incomes below the 25th percentile. Median Median household income divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. The term is also used for the midpoint of the subsets of the income distribution Quartiles Quartiles are values which divide the population, when ranked by an output variable, into four equal-sized groups. The lowest quartile is the same as the 25th percentile. The divisions of a population split by quartiles are referred to as quarters in this publication. Quintiles Quintiles are values which divide the population, when ranked by an output variable, into five equal-sized groups. The divisions of a population split by quintiles are referred to as fifths in this publication. Assets Assets include milk and livestock quotas, as well as land, buildings (including the farm house), breeding livestock, and machinery and equipment. For tenanted farmers,

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 geography-specific; 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% income threshold of Nova Scotian tax filers. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

This dataset contains indicators of household-level income and wealth inequality and residential segregation in the Netherlands. This information is derived from restricted geo-coded register microdata provided by Statistics Netherlands and used in the analyses published in the referenced paper, where the methodology for calculating these data is included. It includes measures of income and wealth inequality at the household level for 2022, adjusted for the number of household members and distinguishing between financial wealth and real estate wealth; residential segregation of income and wealth, computed with adjustments both for household members and adults, and likewise distinguishing between financial and real estate wealth, for the 2011-2022 period and for different geographic scales of spatial computation of segregation; demographic data for 500 m × 500 m grid cells covering the entire Dutch territory for 2022; information on the income and wealth percentiles of households, disaggregated into financial and real estate wealth; and detailed wealth distribution data for the Netherlands, distinguishing between financial and real estate wealth, between households headed by individuals born in the Netherlands and those born abroad, and for all years of the population distribution, for the year 2022. Together, these indicators provide a comprehensive view of economic inequality and residential segregation in the Netherlands, capturing both levels (inequality and percentiles) and spatial patterns (segregation across multiple scales). This dataset also contains the R scripts used for the computation of the data and its visualization in the referenced paper.

A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.

Singapore Monthly Hsehold Income fr Work Per Hsehold Member at 20th Percentile data was reported at 1,311.000 SGD in 2017. This records an increase from the previous number of 1,280.000 SGD for 2016. Singapore Monthly Hsehold Income fr Work Per Hsehold Member at 20th Percentile data is updated yearly, averaging 828.000 SGD from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 1,311.000 SGD in 2017 and a record low of 628.000 SGD in 2000. Singapore Monthly Hsehold Income fr Work Per Hsehold Member at 20th Percentile data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.H051: Household Income from Work: Resident Employed Households.

This dataset contains replication files for "The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility" by Raj Chetty, John Friedman, Nathaniel Hendren, Maggie R. Jones, and Sonya R. Porter. For more information, see https://opportunityinsights.org/paper/the-opportunity-atlas/. A summary of the related publication follows. We construct a publicly available atlas of children’s outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children’s earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children’s outcomes vary sharply across nearby tracts: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $5,000 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, we show that the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child’s own Census tract, characteristics of tracts that are one mile away have little predictive power for a child’s outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods’ causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi-experimental research design analyzing movers’ outcomes. We then identify high-opportunity neighborhoods that are affordable to low-income families, providing an input into the design of affordable housing policies. Our measures of children’s long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets. Click here to view the Opportunity Atlas Any opinions and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. The statistical summaries reported in this paper have been cleared by the Census Bureau’s Disclosure Review Board release authorization number CBDRB-FY18-319.