The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in China was last recorded at 3 percent. This dataset provides the latest reported value for - China Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Brazil was last recorded at 15 percent. This dataset provides - Brazil Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the Cut Bank population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Cut Bank across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Cut Bank was 3,017, a 0.43% decrease year-by-year from 2022. Previously, in 2022, Cut Bank population was 3,030, a decline of 0.69% compared to a population of 3,051 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cut Bank decreased by 73. In this period, the peak population was 3,161 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Cut Bank is shown in this column.
• Year on Year Change: This column displays the change in Cut Bank population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Cut Bank Population by Year. You can refer the same here

The benchmark interest rate in Canada was last recorded at 2.75 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Tobacco tax rates were last changed on March 29, 2018. The current rates are:

• 18.475¢ per cigarette
• 18.475¢ per gram or part gram of cut tobacco
• Tax on cigars is 56.6% of the taxable price

Tobacco tax is:

• $3.70 on a pack of 20 cigarettes
• $4.62 on a pack of 25 cigarettes
• $36.95 on a carton of 200 cigarettes

You can download the dataset to view the historical price points for this tax.

About tobacco tax

About this dataset

Context

The dataset tabulates the Cut And Shoot population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Cut And Shoot across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Cut And Shoot was 1,184, a 0.17% decrease year-by-year from 2022. Previously, in 2022, Cut And Shoot population was 1,186, an increase of 4.31% compared to a population of 1,137 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cut And Shoot increased by 85. In this period, the peak population was 1,449 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Cut And Shoot is shown in this column.
• Year on Year Change: This column displays the change in Cut And Shoot population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Cut And Shoot Population by Year. You can refer the same here

The Community Rating System (CRS) is a voluntary incentive program that recognizes and encourages community floodplain management practices that exceed the minimum requirements of the National Flood Insurance Program (NFIP). Active CRS community flood insurance premium rates are discounted to reflect the reduced flood risk resulting from the community’s efforts that address the three goals of the program: 1. Reduce and avoid flood damage to insurable property; 2. Strengthen and support the insurance aspects of the National Flood Insurance Program; and 3. Foster comprehensive floodplain management. rnrnThe Flood insurance premium rates in Community Rating System communities are discounted in increments of 5%. A Class 10 community is not participating in the CRS and receives no discount. A Class 9 community receives a 5% discount for all policies in its Special Flood Hazard Areas, a Class 8 community receives a 10% discount, all the way to a Class 1 community, which receives a 45% premium discount. Classifications are based on 19 creditable activities, organized in four categories: Public Information, Mapping and Regulations, Flood Damage Reduction, Warning and Response. Quantitative CRS datasets are avaialble about community floodplain mangament practices that validates the CRS community rating classifications and credit points. The abridged public dataset is available at https://www.fema.gov/floodplain-management/community-rating-system. CRS dataset is updated semiannually in CIS.

Monetary policy is generally regarded as a central element in the attempts of policy makers to attenuate business-cycle fluctuations. According to the New Keynesian paradigm, central banks are able to stimulate or depress aggregate demand in the short run by adjusting their nominal interest rate targets. The effects of interest rate changes on aggregate consumption, the largest component of aggregate demand, are well understood in the context of this paradigm, on which the canonical "workhorse'' model used in monetary policy analysis is grounded. A key feature of the model is that aggregate consumption is fully described by the amount of goods consumed by a representative household. A decline in the policy rate for instance implies that the real interest rate declines, the representative household saves less and hence increase its demand for consumption. At the same time, general equilibrium effects let labour income grow causing consumption to increase further. However, the mechanism outlined above ignores a considerable amount of empirically-observed heterogeneity among households. For example, households with a higher earnings elasticity to interest rate changes benefit more from a rate cut than those with a lower elasticity; households with large debt positions are at a relative advantage over households with large bond holdings; and households with low exposure to inflation are relatively better off than those holding a sizeable amount of nominal assets. As a result, the contribution to the aggregate consumption response differs substantially across households, implying that monetary expansions and tightenings produce relative "winners'' and relative "losers''. The aim of the project laid out in this proposal is to give a disaggregated account of the heterogeneous effects of monetary-policy induced interest rate changes on household consumption and a detailed analysis of the channels underlying them. Additionally, it seeks to draw conclusions about the determinants of the strength of the transmission mechanism of monetary policy. To do so, it relies on a large panel comprising detailed data from the universe of all households residing in Norway between 1993 and 2015 supplemented with additional micro-data provided by the European Commission. I will be assisted by two project partners, Pascal Paul who is a member of the Research Department of the Federal Reserve Bank of San Francisco and Martin Holm who is affiliated with the Research Unit of Statistics Norway and the University of Oslo. In addition, I would like to collaborate with and help train a doctoral student based at the University of Lausanne on this project. Existing empirical studies of the consumption response to monetary policy at the micro level rely on survey data. Therefore, they are subject to a number of severe data limitations. The surveys employed typically have either no or only a short panel dimension, suffer from attrition, include only limited information on income and wealth, are top-coded, and contain a significant amount of measurement error. The administrative data set provided to us by Statistics Norway suffers from none of these issues, implying that we are in a unique position to evaluate the household-level effects of policy rate changes. In a first step, we use forecasts published by the Norwegian central bank to derive monetary policy shocks that are robust to the simultaneity problem inherent in the identification of the effects of monetary policy following Romer and Romer (2004). We then confront the micro-data with the estimated shocks to study the consumption response along different segments of the income and wealth distribution and to test the importance of heterogeneity in labour earnings, financial income, liquid assets, inflation exposure and interest rate exposure among others. The findings will be of high relevance as they will not only allow us to evaluate channels hypothesised in the analytical literature, improve our understanding of the monetary policy transmission mechanism and its distributional consequences but also serve as a benchmark for structural models built both by theorists and practitioners.

The variable examined is graduation status after four years of high school. Early and summer graduates are considered graduates after four years. The "other" rate includes students who dropped out of high school, enrolled in a GED program, transferred to post-secondary education, or have unknown status. Special education students in school after four years but subsequently graduated are not included in the "still enrolled" rate due to Individuals with Disabilities Education Act (IDEA) restrictions. The subgroups reported are gender, race/ethnicity, English language learners, special education students, and students eligible for free or reduced-price meals (FRPM). The data replace the rate of students enrolled in 12th grade in September who graduated the following June. Connecticut State Department of Education (SDE) collects data longitudinally by four-year cohorts. SDE reports and CTdata.org carries graduation rates of four-year cohorts annually.

New Zonage “A/B/C” applicable from 01/10/2014 (Ministerial Decree of 01 August 2014).

The “A/B/C” zoning, created in 2003 at the time when Robien’s rental investment scheme was introduced, characterises the tension of the local real estate market, i.e. the adequacy of the demand for and the supply of available housing on a territory. It consists of five modalities ranging from the most tense (Abis) to the most relaxed (C).Franche-Comté is only affected by zones B2 and C. Several financial schemes use this zoning to determine the eligibility of territories for aid or to adjust their parameters (level of aid, ceiling of rents, etc.). These include the Intermediate Rental Investment Facility for Individuals (see Duflot Zoning), the Old Borloo, the Intermediate Rental Loan (PLI), the Zero Rate Loan (PTZ), the Social Accession Rental Loan (PSLA) and the Social Access Loan (PAS) to property, and the reduced rate VAT in the ANRU area.Some ANAH aid to social lenders is also linked to a ceiling on rent and the amount of resources of the tenant, which varies according to the zoning A/B/C. Following a consultation conducted by the Regional Prefect with the local authorities in the 4th quarter of 2013, the new zoning A/B/C was adopted by the Minister in charge of Housing on 1 August 2014. For Franche-Comté, 19 new municipalities were reclassified from C to B2, while no decommissioning was recorded. Its entry into force varies between 1 October 2014 and 1 February 2015 depending on the arrangements attached to it:

as of 1 October 2014 for: — the zero-rate loan; — the guarantee scheme of the FGAS; — the reduced rate VAT scheme for intermediate rental accommodation (279-0a A of the CGI); — the aid scheme for intermediate rental investment for private individuals (199 novitiies of the General Tax Code (CGI); — promises of sales of public land, pursuant to Article R. 3211-15 of the General Code of Ownership of Public Persons;

on 1 January 2015 for: — the benefit of aid from the National Housing Agency, the ‘old Borloo’ tax scheme; — the intermediate rental loan; — reduced VAT in ANRU area; — devices related to HLM promotion; — the assessment of resources for new intermediate dwellings held by HLML bodies in the context of their service of general economic interest;

as of 1 February 2015 for: — approvals of social loans for leasing-accession.

Data sources: order of the Minister of Housing dated 01 August 2014

The benchmark interest rate in Mexico was last recorded at 7.75 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data set provides energetic (MeV) ion count rates and events measured by the Heavy Ion Counter (HIC) instrument on the Galileo spacecraft. These data are derived from high time resolution raw data that were recorded to tape and then played back later in the orbit. There are two basic types of data files associated with the full-rate reduced data: Detector Count Rates and Events (Pulse Heights).

Gasoline tax rates were last changed on July 1, 2022. The current rates are: * unleaded gasoline - 9¢ per litre Effective July 1, 2022 until June 30, 2025, the gasoline tax rate on unleaded gasoline will be reduced from 14.7 cents per litre to 9.0 cents per litre, representing a cut of 5.7 cents per litre. * leaded gasoline - 17.7¢ per litre The Aviation fuel tax rate was last changed on April 1, 2017. The current rate is 6.7¢ per litre. Effective January 1, 2020, a new rate was established for Northern Ontario. The rate for Northern Ontario is 2.7¢ per litre. The Propane tax rate was last changed on January 1, 1990. The current rate is 4.3¢ per litre. You can download the dataset to view the historical price points for these taxes.

This data set provides energetic (MeV) ion count rates and events measured by the Heavy Ion Counter (HIC) instrument on the Galileo spacecraft. The data are derived from the raw real-time science (RTS) data. There are two basic types of data files associated with the full-rate reduced data: Detector Count Rates and Events (Pulse Heights).

A dataset providing GP recorded chronic obstructive pulmonary disease rates. Chronic Obstructive Pulmonary Disease (COPD) is a serious long-term lung disease in which the flow of air into the lungs is gradually reduced by inflammation of the air passages and damage to the lung tissue. Chronic Bronchitis and emphysema are common types of COPD. Chronic Obstructive Pulmonary Disease (COPD) is the fifth biggest killer disease in the UK, killing approximately 25,000 people a year in England. Further information For more information on public health, please visit: http://www.leeds.gov.uk/phrc/Pages/default.aspx

The benchmark interest rate in the United Kingdom was last recorded at 4 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Virulence, the degree to which a pathogen harms its host, is an important but poorly understood aspect of host-pathogen interactions. However it is not a static trait, instead depending on ecological context and potentially evolving over short periods of time (e.g., during the course of an epidemic). At the start of an epidemic, when susceptible hosts are plentiful, pathogens may evolve increased virulence, maximizing their intrinsic growth rate. However, if host density declines during an epidemic, theory predicts evolution of reduced virulence. Although well-studied theoretically, there is still little empirical evidence for virulence evolution in epidemics, especially in natural settings with native host and pathogen species. Here, we used a combination of field observations and lab experiments in the Daphnia-Pasteuria model system to look for evidence of virulence evolution in nature. Controlling for environmental conditions, we found that there was no change in parasite virulence when measured in terms of host lifespan or the number of clutches produced. There also was no evidence for evolution of host resistance or parasite infectivity. However, over the epidemic, the parasite evolved to produce significantly fewer spores in infected hosts, perhaps as a result of trade-offs quantified in earlier studies. Future studies that track evolution of parasite spore yield in more populations, and that link those changes with genetic changes and with predation rates, will yield better insight into the drivers of parasite evolution in the wild.