Core consumer prices in the United States increased 2.80 percent in May of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset is about books. It has 3 rows and is filtered where the book subjects is Unemployment-Effect of inflation on-Econometric models. It features 9 columns including author, publication date, language, and book publisher.

Inflation Rate in India decreased to 2.82 percent in May from 3.16 percent in April of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In this paper we use GARCH-M methods to test four hypotheses about the effects of real and nominal uncertainty on average inflation and output growth in the United States from 1948 to 1996. We find no evidence that higher inflation uncertainty or higher output growth uncertainty raises the average inflation rate. We also find no support for the idea that more risky output growth is associated with a higher average real growth rate. Our key result is that in a variety of models and sample periods, inflation uncertainty significantly lowers real output growth.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Truth Or Consequences, NM, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Truth Or Consequences did not include 5, 6, or 7-person households. Across the different household sizes in Truth Or Consequences the mean income is $56,928, and the standard deviation is $38,611. The coefficient of variation (CV) is 67.82%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $20,161. It then further increased to $110,968 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/truth-or-consequences-nm-median-household-income-by-household-size.jpeg" alt="Truth Or Consequences, NM median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Truth Or Consequences median household income. You can refer the same here

Inflation Rate in Russia decreased to 9.40 percent in June from 9.90 percent in May of 2025. This dataset provides - Russia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data-set cited sources that helped assess the interrelationship between savings, spending, and inflation expectations among undergraduate students. It was directed towards discovering the difficulties students may face with their finances because of inflation. A web-based survey was administered to 315 undergraduate students in Nigeria. Data obtained was analyzed using descriptive statistics such as percentage and frequency. The results revealed inflation expectations had a significant negative impact on the spending habits of students. The results further revealed that individual savings attitudes were reduced with an increase in inflation, but overall savings did not.

It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1-year inflation expectations. Assessing this view empirically requires the use of dynamic structural models to quantify the cumulative effect of gasoline price shocks on household inflation expectations at each point in time. We find that, on average, gasoline price shocks account for 42% of the variation in these expectations. The cumulative increase in household inflation expectations from early 2009 to early 2013, in particular, is almost entirely explained by unexpectedly rising gasoline prices. However, there is no support for the view that the improved fit of the Phillips curve augmented by household inflation expectations during 2009 2013 is mainly explained by rising gasoline prices.

Analysis of ‘🚊 Consumer Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/consumer-price-indexe on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

9The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods.(1) It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.(1)

The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas.(1) To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date.(1) In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays.(1)

The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (Consumer Price Index for All Urban Consumers: All Items Less Food & Energy [CPILFESL]) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs.(1) Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average.(1)

Attribution: US. Bureau of Labor Statistics from The Federal Reserve Bank of St. Louis

For more information on the consumer price indexes, see:

• (1) Bureau of Economic Analysis. “CPI Detailed Report.” 2013
• (2) Handbook of Methods
• (3) Understanding the CPI: Frequently Asked Questions

This dataset was created by Finance and contains around 900 samples along with Consumer Price Index For All Urban Consumers: All Items, Title:, technical information and other features such as: - Consumer Price Index For All Urban Consumers: All Items - Title: - and more.

How to use this dataset

• Analyze Consumer Price Index For All Urban Consumers: All Items in relation to Title:
• Study the influence of Consumer Price Index For All Urban Consumers: All Items on Title:
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

This panel dataset contains quarterly series on inflation targets, bands, and track records for 41 inflation targeting countries from 1990 to 2024. Data on inflation targets and bands are collected through each central bank’s historical documents and rules-based track record measures are calculated by the author to assess actual inflation outcomes with respect to the central banks’ stated policy objectives. The dataset supports research work in Zhang (2025), Zhang and Wang (2022), and Zhang (2021). Please cite the papers when using the data.

Z. Zhang, Does inflation targeting track record matter for asset prices? Evidence from stock, bond, and foreign exchange markets, Journal of International Financial Markets, Institutions and Money, Volume 101, 2025, 102141. Z. Zhang, S. Wang, Do actions speak louder than words? Assessing the effects of inflation targeting track records on macroeconomic performance, 2022, IMF Working Papers 2022/227.
Z. Zhang, Stock returns and inflation redux: An explanation from monetary policy in advanced and emerging markets, 2021, IMF Working Papers 2021/219.

About this dataset

Context

The dataset illustrates the median household income in Truth Or Consequences, 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 Truth Or Consequences decreased by $1,573 (5.12%), 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 5 years and declined for 8 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 Truth Or Consequences median household income. You can refer the same here

This dataset supports the research exploring the impact of monetary policy instruments on the Colombian economy, focusing on the classical dichotomy and monetary neutrality. The analysis delves into how monetary policy, including instruments such as interest rates and money supply, influences both nominal and real variables in the economy. It also highlights the relationship between monetary policy and economic stability, particularly how central banks manage inflation and economic growth. Key sections explore the separation between nominal and real variables as explained by the classical dichotomy, and the principle of monetary neutrality, which argues that changes in money supply affect nominal variables without impacting real economic factors.

The dataset is structured around a combination of theoretical insights and simulations that analyze the effectiveness of monetary neutrality in the Colombian context, given both domestic and international economic challenges such as the war in Ukraine and agricultural sector disruptions. Through simulations, the dataset demonstrates the effects of monetary expansion on variables like inflation, production, and employment, providing a framework for understanding current economic trends and proposing solutions to socio-economic challenges in Colombia.

This data package contains underlying data to replicate the calculations, charts, and tables in Low Inflation Bends the Phillips Curve around the World: Extended Results, PIIE Working Paper 21-15.

If you use the data, please cite as: Forbes, Kristin, Joseph E. Gagnon, and Christopher G. Collins, Low Inflation Bends the Phillips Curve around the World: Extended Results, PIIE Working Paper 21-15, September 2021, Peterson Institute for International Economics.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Truth Or Consequences. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Truth Or Consequences. 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 2022

In terms of income distribution across age cohorts, in Truth Or Consequences, the median household income stands at $74,421 for householders within the 25 to 44 years age group, followed by $28,310 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 $24,772.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-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 Truth Or Consequences median household income by age. You can refer the same here

The present study investigated whether inhibition of deiodinase, the enzyme which converts thyroxine (T4) to the more biologically-active form, 3,5,3'-triiodothyronine (T3), would impact inflation of the posterior and/or anterior chamber of the swim bladder, processes previously demonstrated to be thyroid-hormone regulated. Two experiments were conducted using a model deiodinase inhibitor, iopanoic acid (IOP). In the first study, fathead minnow (Pimephales promelas) embryos were exposed to 0.6, 1.9, or 6.0 mg IOP/L or control water in a flow-through system until reaching 6 days post-fertilization (dpf) at which time posterior swim bladder inflation was assessed. To examine effects on anterior swim bladder inflation, a second study was conducted with 6 dpf larvae exposed to the same IOP concentrations until reaching 21 dpf. Fish from both studies were sampled for T4/T3 measurements, gene transcription analyses, and thyroid histopathology. In the embryo study, incidence and length of inflated posterior swim bladders were significantly reduced in the 6.0 mg/L treatment at 6 dpf. Incidence of inflation and length of anterior swim bladder in larval fish were significantly reduced in all IOP treatments at 14 dpf, but inflation recovered by 18 dpf. Throughout the larval study, whole body T4 concentrations were significantly increased and T3 concentrations were significantly decreased in all IOP treatments. Consistent with hypothesized compensatory responses, significant up-regulation of deiodinase-2 mRNA was observed in the larval study, and down-regulation of thyroperoxidase mRNA was observed in all IOP treatments in both studies. Taken together, these results support the hypothesized adverse outcome pathways linking inhibition of deiodinase activity to impaired swim bladder inflation. This dataset is associated with the following publication: Cavallin, J., G. Ankley, B. Blackwell, C. Blanksma, K. Fay, K. Jensen, M. Kahl, D. Knapen, P. Kosian, S. Poole, E. Randolph, A. Schroeder, L. Vergauwen, and D. Villeneuve. Impaired swim bladder inflation in early-life stage fathead minnows exposed to a deiodinase inhibitor, iopanoic acid (article). ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(11): 2942-2952, (2017).

Inflation Rate in Vietnam increased to 3.57 percent in June from 3.24 percent in May of 2025. This dataset provides the latest reported value for - Vietnam Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The data set provides all data that were reported in results, tables, and figures associated with Stinckens et al., "The effect of thyroperoxidase and deiodinase inhibition on anterior swim bladder inflation in the zebrafish". The data set includes: 1) Effects of three test chemicals on thyroperoxidase enzyme activity 2) Effects of three test chemicals on deiodinase enzyme activity 3) Thyroid hormone (T3 and T4) concentrations measured in exposed larvae 4) Measures of posterior and anterior swimbladder chamber inflation and surface areas. 5) Data on swimming behavior (distance) of exposed fish. 6) Measured concentrations of the test chemicals in the test media and tissues. This dataset is associated with the following publication: Stinckens, E., L. Vergauwen, B. Blackwell, G. Ankley, D. Villeneuve, and D. Knapen. Effect of thyroperoxidase and deiodinase inhibition on anterior swim bladder inflation in the zebrafish. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(10): 6213-6223, (2020).

About this dataset

Context

The dataset presents the median household income across different racial categories in Truth Or Consequences. 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 Truth Or Consequences population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 75.30% of the total residents in Truth Or Consequences. Notably, the median household income for White households is $30,806. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $138,205. This reveals that, while Whites may be the most numerous in Truth Or Consequences, Two or More Races households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/truth-or-consequences-nm-median-household-income-by-race.jpeg" alt="Truth Or Consequences median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Truth Or Consequences.
• Median household income: Median household income, adjusting for inflation, presented in 2022-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 Truth Or Consequences median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the Truth Or Consequences median household income by race. The dataset can be utilized to understand the racial distribution of Truth Or Consequences income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Truth Or Consequences, NM median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Truth Or Consequences, NM (2021, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Truth Or Consequences median household income by race. You can refer the same here