Inflation Rate in Norway decreased to 2.50 percent in April from 2.60 percent in March of 2025. This dataset provides - Norway Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Global developments play an important role for domestic inflation rates. Earlier literature has found that a substantial amount of the variation in a large set of national inflation rates can be explained by a single global factor. However, inflation volatility has been typically neglected, although it is clearly relevant both from a policy point of view and for structural analysis and forecasting. We study the evolution of inflation rates in several countries, using a novel model that allows for commonality in both levels and volatilities, in addition to country-specific components. We find that inflation volatility is indeed important, and a substantial fraction of it can be attributed to a global factor that is also driving inflation levels and their persistence. The extent of commonality among core inflation rates and volatilities is substantially smaller than for overall inflation, which leaves scope for national monetary policies. Finally, we show that the point and density forecasting performance of the model is good relative to standard benchmarks, which provides additional evidence on its reliability.

Interest rates and inflation are two critical economic indicators that profoundly influence each other and impact broader economic health. Typically, central banks use interest rates as a primary monetary policy tool to control inflation. When inflation rises above target levels, central banks may increase interest rates to reduce spending and borrowing, thereby stabilizing prices. Conversely, lowering interest rates usually stimulates economic activity but risks driving inflation higher. Understanding and predicting the relationship between these indicators can help policymakers, economists, investors, and businesses anticipate economic conditions, make informed decisions, and develop strategies for risk management. This dataset provides historical yearly data on interest rates and corresponding inflation levels, offering a valuable resource to explore, analyze, and model this fundamental economic relationship.

Inflation Rate in Mexico increased to 4.42 percent in May from 3.93 percent in April of 2025. This dataset provides - Mexico Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data package includes the underlying data files to replicate the calculations and charts presented in Soaring demand is driving double-digit import price inflation in the United States, PIIE Policy Brief 22-12.

If you use the data, please cite as: Freund, Caroline (2022). Soaring demand is driving double-digit import price inflation in the United States, PIIE Policy Brief 22-12. Peterson Institute for International Economics.

Inflation Rate in China remained unchanged at -0.10 percent in April. This dataset provides - China Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset illustrates the median household income in Airport Drive, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Airport Drive decreased by $5,170 (7.43%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Airport Drive median household income. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Airport Drive. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Airport Drive. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2021

In terms of income distribution across age cohorts, in Airport Drive, householders within the 45 to 64 years age group have the highest median household income at $117,324, followed by those in the 25 to 44 years age group with an income of $97,861. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $58,099. Notably, householders within the under 25 years age group, had the lowest median household income at $47,290.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 Airport Drive median household income by age. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Airport Drive. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Airport Drive, the median income for all workers aged 15 years and older, regardless of work hours, was $48,125 for males and $26,200 for females.

These income figures highlight a substantial gender-based income gap in Airport Drive. Women, regardless of work hours, earn 54 cents for each dollar earned by men. This significant gender pay gap, approximately 46%, underscores concerning gender-based income inequality in the village of Airport Drive.

- Full-time workers, aged 15 years and older: In Airport Drive, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,375, while females earned $41,111, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Airport Drive.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Airport Drive median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Airport Drive. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Airport Drive population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 92.61% of the total residents in Airport Drive. Notably, the median household income for White households is $76,250. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $76,250.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Airport Drive.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Airport Drive median household income by race. You can refer the same here

Inflation Rate in Pakistan increased to 3.50 percent in May from 0.30 percent in April of 2025. This dataset provides the latest reported value for - Pakistan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Shoal Creek Drive. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Shoal Creek Drive. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2021

In terms of income distribution across age cohorts, in Shoal Creek Drive, the median household income stands at $111,521 for householders within the 25 to 44 years age group, followed by $96,831 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $45,770.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 Shoal Creek Drive median household income by age. You can refer the same here

The canonical inflation specification in sticky-price rational expectations models (the new-Keynesian Phillips curve) is often criticized for failing to account for the dependence of inflation on its own lags. In response, many studies employ a "hybrid" specification in which inflation depends on its lagged and expected future values, together with a driving variable such as the output gap. We consider some simple tests of the hybrid model that are derived from its closed form. We find that the hybrid model describes inflation dynamics poorly, and find little empirical evidence for the type of rational, forward-looking behavior that the model implies.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Airport Drive, 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 17,151, while the mean income for the highest quintile (20% of households with the highest income) is 200,759. This indicates that the top earners earn 12 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 309,536, which is 154.18% higher compared to the highest quintile, and 1804.77% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 2022 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 Airport Drive median household income. You can refer the same here

About this dataset

Context

The dataset illustrates the median household income in Shoal Creek Drive, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Shoal Creek Drive increased by $41,779 (75.76%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 8 years and declined for 5 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Shoal Creek Drive median household income. You can refer the same here

Inflation Rate in Ghana decreased to 18.40 percent in May from 21.20 percent in April of 2025. This dataset provides - Ghana Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Kenya decreased to 3.80 percent in May from 4.10 percent in April of 2025. This dataset provides the latest reported value for - Kenya Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Techsalerator’s Location Sentiment Data for Syria

Techsalerator’s Location Sentiment Data for Syria offers a comprehensive collection of information vital for businesses, researchers, and technology developers. This dataset provides profound insights into location-based sentiment, mood, and emotional patterns across different regions of Syria.

For access to the full dataset, contact us at info@techsalerator.com or visit Techsalerator Contact Us.

Techsalerator’s Location Sentiment Data for Syria

Techsalerator’s Location Sentiment Data for Syria provides a structured analysis of sentiment-related data across urban, rural, and conflict-affected regions. This dataset is essential for social science research, crisis management, political analysis, and local community development.

Top 5 Key Data Fields

• Location of Sentiment Capture – Identifies the geographic area where the sentiment data was collected, enabling region-specific sentiment analysis.
• Sentiment Intensity – Measures the strength of positive or negative sentiment in different locations, important for understanding emotional responses to events.
• Time of Capture – Records the exact time and date when sentiment was captured, allowing for temporal analysis of emotional trends.
• Sentiment Category – Categorizes sentiment into various themes, such as political, social, economic, and cultural sentiments.
• Sentiment Source Identification – Categorizes data based on the source of sentiment, including social media, news outlets, public forums, and interviews.

Top 5 Sentiment Trends in Syria

• Impact of Conflict on Emotional Well-being – Increasing negative sentiment related to ongoing conflicts, highlighting the psychological toll on affected populations.
• Economic Sentiment Fluctuations – Growing concerns over inflation and unemployment are driving negative sentiment across major urban centers.
• Political Sentiment Analysis – Divided political sentiments in urban and rural regions reflect differing perspectives on governance and security policies.
• Youth Sentiment – Younger populations exhibit a mix of frustration and hope, with a desire for greater opportunities and stability.
• Humanitarian Sentiment – Sentiment data reveals increasing empathy and support for displaced populations, shaping international aid efforts.

Top 5 Applications of Location Sentiment Data in Syria

• Crisis Management – Sentiment analysis helps humanitarian organizations respond effectively by understanding local emotional states during crises.
• Political Strategy – Political analysts use sentiment data to gauge public opinion and adjust campaigns accordingly in different regions of Syria.
• Community Development – Local governments and NGOs utilize sentiment data to address community concerns and tailor development programs to meet emotional and social needs.
• Media and Journalism – Journalists use sentiment data to report on public reactions and shifts in national and local moods.
• Market Research – Businesses analyze sentiment to assess customer perceptions, preferences, and reactions to products and services in Syria.

Accessing Techsalerator’s Location Sentiment Data

To obtain Techsalerator’s Location Sentiment Data for Syria, contact info@techsalerator.com with your specific requirements. Techsalerator offers customized datasets based on requested fields, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Location of Sentiment Capture
• Sentiment Intensity
• Time of Capture
• Sentiment Category (Political, Economic, Social, etc.)
• Sentiment Source Identification
• Geographic Region (Urban, Rural, Conflict Zones)
• Demographic Segmentation (Age, Gender, etc.)
• Emotion Type (Fear, Hope, Frustration, etc.)
• Political Affiliation Sentiment
• Cultural Sentiment Trends

For deep insights into sentiment patterns and emotional landscapes in Syria, Techsalerator’s dataset is an invaluable resource for political analysts, researchers, NGOs, and businesses.

Persistent virus infection can drive CD8+ T-cell responses which are markedly divergent in terms of frequency, phenotype, function, and distribution. On the one hand viruses such as Lymphocytic Choriomeningitis Virus (LCMV) Clone 13 can drive T-cell “exhaustion”, associated with upregulation of checkpoint molecules, loss of effector functions, and diminished control of viral replication. On the other, low-level persistence of viruses such as Cytomegalovirus and Adenoviral vaccines can drive memory “inflation,” associated with sustained populations of CD8+ T-cells over time, with maintained effector functions and a distinct phenotype. Underpinning these divergent memory pools are distinct transcriptional patterns—we aimed to compare these to explore the regulation of CD8+ T-cell memory against persistent viruses at the level of molecular networks and address whether dysregulation of specific modules may account for the phenotype observed. By exploring in parallel and also merging existing datasets derived from different investigators we attempted to develop a combined model of inflation vs. exhaustion and investigate the gene expression networks that are shared in these memory pools. In such comparisons, co-ordination of a critical module of genes driven by Tbx21 is markedly different between the two memory types. These exploratory data highlight both the molecular similarities as well as the differences between inflation and exhaustion and we hypothesize that co-ordinated regulation of a key genetic module may underpin the markedly different resultant functions and phenotypes in vivo—an idea which could be tested directly in future experiments.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Airport Drive, MO, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Airport Drive, MO reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Airport Drive households based on income levels.

Key observations

• For Family Households: In Airport Drive, the majority of family households, representing 30.84%, earn $125,000 to $149,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $200,000 or more, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Airport Drive, the majority of non-family households, accounting for 19.26%, have income $50,000 to $59,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $200,000 or more, representing a smaller, yet notable, portion of non-family households in the community.

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:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Airport Drive, MO (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Airport Drive, MO
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Airport Drive, MO
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Airport Drive, MO

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 Airport Drive median household income. You can refer the same here