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

Inflation Expectations in the United States decreased to 3.20 percent in May from 3.60 percent in April of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The IMF has a great inflation database, but it relies on countries to provide their latest data to the IMF, and as such, it can be temporarily out of date. This database will keep the IMF inflation database up to date for African countries by scraping data from individual countries' websites as soon as they release their data and combining it with the latest IMF data. This Africa inflation database powers the ADH Inflation Observer. All 3 datasets found here contain the same data, but in different shapes to suit different applications.

Core consumer prices in the United States increased 2.80 percent in April 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.

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

This data package includes the underlying data to replicate the charts, tables, and calculations presented in Labor market tightness and inflation before and after the COVID-19 pandemic, PIIE Working Paper 24-23.

If you use the data, please cite as:

Bloesch, Justin. 2024. Labor market tightness and inflation before and after the COVID-19 pandemic. PIIE Working Paper 24-23. Washington: Peterson Institute for International Economics.

Inflation Rate in Argentina decreased to 47.30 percent in April from 55.90 percent in March of 2025. This dataset provides the latest reported value for - Argentina Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Core consumer prices in Egypt increased 13.10 percent in May of 2025 over the same month in the previous year. This dataset provides - Egypt Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

R Core Team. (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

Supplement to Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness (https://philpapers.org/rec/PEROAL-2).

Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness move from the features of the ERP characterized in Occipital and Left Temporal EEG Correlates of Phenomenal Consciousness (Pereira, 2015, https://doi.org/10.1016/b978-0-12-802508-6.00018-1, https://philpapers.org/rec/PEROAL) towards the instantaneous amplitude and frequency of event-related changes correlated with a contrast in access and in phenomenology.

Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness proceed as following.

In the first section, empirical mode decomposition (EMD) with post processing (Xie, G., Guo, Y., Tong, S., and Ma, L., 2014. Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm. BMC medical research methodology, 14, 35) Ensemble Empirical Mode Decomposition (postEEMD) and Hilbert-Huang Transform (HHT).

In the second section, calculated the variance inflation factor (VIF).

In the third section, partial least squares regression (PLSR): the minimal root mean squared error of prediction (RMSEP).

In the last section, partial least squares regression (PLSR): significance multivariate correlation (sMC) statistic.

Cost of food in the United States increased 2.80 percent in April of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Turkey decreased to 35.41 percent in May from 37.86 percent in April of 2025. This dataset provides the latest reported value for - Turkey Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

View data of PCE, an index that measures monthly changes in the price of consumer goods and services as a means of analyzing inflation.

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Apr 2025 about savings, personal, rate, and USA.

Michigan 5 Year Inflation Expectations in the United States decreased to 4.20 percent in May from 4.40 percent in April of 2025. This dataset includes a chart with historical data for the United States Michigan 5-Year Inflation Expectations.

This dataset provides information about 277 UK learned societies that published peer reviewed journals in 2015, illustrating how the nature of their publishing activities had changed by 2023. The dataset includes information such as outsourced publishing partners, number of journals published (1, 2 or 3+), incoming resources, publishing revenues and publishing models.

Learned society publishers represent a critical part of the publishing and scholarly communications ecosystem and the impact of changes in the landscape on this group of stakeholders as a whole is not well studied or understood. This dataset provides important insights into how learned society publishing in the UK has changed over time, showing that the number of self-published societies has reduced by 35% since 2015, that outsourcing relationships have become more complex and that societies' revenues from publishing have, in the main, failed to keep pace with inflation.

If you have any questions or comments, or wish to propose amendments to the information included in the dataset, please contact Rob Johnson at rob.johnson@research-consulting.com.

Understanding how organisms distribute themselves in response to interacting species, ecosystems, climate, human development and time is fundamental to ecological study and practice. A measure to quantify the relationship among organisms and their environments is intensity of use: the rate of use of a specific resource in a defined unit of time. Estimating the intensity of use differs from estimating probabilities of occupancy or selection, which can remain constant even when the intensity of use varies. We describe a method to evaluate the intensity of use across conditions that vary in both space and time. We demonstrate its application on a large mammal community where linear developments and human activity are conjectured to influence the interactions between white‐tailed deer (Odocoileus virginianus) and wolves (Canis lupus) with possible consequences on threatened woodland caribou (Rangifer tarandus caribou). We collect and quantify intensity of use data for multiple, interacting species with the goal of assessing management efficacy, including a habitat restoration strategy for linear developments. We test whether blocking linear developments by spreading logs across a 200‐m interval can be applied as an immediate mitigation to reduce the intensities of use by humans, predator and prey species in a boreal caribou range. We deployed camera traps on linear developments with and without restoration treatments in a landscape exposed to both timber and oil development. We collected a three‐year dataset and employed spatial recurrent event models to analyse intensity of use by an interacting human and large mammal community across a range of environmental and climatic conditions. Spatial recurrent event models revealed that intensity of use by humans influenced the intensity of use by all five large mammal species evaluated, and the intensities of use by wolves and deer were inextricably linked in space and time. Conditions that resist travel on linear developments had a strong negative effect on the intensity of human and large mammal use. Mitigation strategies that resist, or redirect, animal travel on linear developments can reduce the effects of resource development on interacting human and predator–prey interactions. Our approach is easily applied to other continuous time point‐based survey methodologies and shows that measuring the intensity of use within animal communities can help scientists monitor, mitigate and understand ecological states and processes.

This dataset provides information about 277 UK learned societies that published peer reviewed journals in 2015, illustrating how the nature of their publishing activities had changed by 2023. The dataset includes information such as outsourced publishing partners, number of journals published (1, 2 or 3+), incoming resources, publishing revenues and publishing models.

Learned society publishers represent a critical part of the publishing and scholarly communications ecosystem and the impact of changes in the landscape on this group of stakeholders as a whole is not well studied or understood. This dataset provides important insights into how learned society publishing in the UK has changed over time, showing that the number of self-published societies has reduced by 35% since 2015, that outsourcing relationships have become more complex and that societies' revenues from publishing have, in the main, failed to keep pace with inflation.

If you have any questions or comments, or wish to propose amendments to the information included in the dataset, please contact Rob Johnson at rob.johnson@research-consulting.com.

Predator-prey dynamics are a fundamental part of ecology, but directly studying interactions has proven difficult. The proliferation of camera trapping has enabled the collection of large datasets on wildlife, but researchers face hurdles inferring interactions from observational data. Recent advances in hierarchical co-abundance models infer species interactions while accounting for two species’ detection probabilities, shared responses to environmental covariates, and propagate uncertainty throughout the entire modelling process. However, current approaches remain unsuitable for interacting species whose natural densities differ by an order of magnitude and have contrasting detection probabilities, such as predator-prey interactions, which introduce zero-inflation and overdispersion in count histories. Here we developed a Bayesian hierarchical N-mixture co-abundance model that is suitable for inferring predator-prey interactions. We accounted for excessive zeros in count histories using an informed zero-inflated Poisson distribution in the abundance formula and accounted for overdispersion in count histories by including a random effect per sampling unit and sampling occasion in the detection probability formula. We demonstrate that models with these modifications outperform alternative approaches, improve model goodness-of-fit, and overcome parameter convergence failures. We highlight its utility using 20 camera trapping datasets from 10 tropical forest landscapes in Southeast Asia and estimate four predator-prey relationships between tigers, clouded leopards, and muntjac and sambar deer. Tigers had a negative effect on muntjac abundance, providing support for top-down regulation, while clouded leopards had a positive effect on muntjac and sambar deer, likely driven by shared responses to unmodelled covariates like hunting. This Bayesian co-abundance modelling approach to quantify predator-prey relationships is widely applicable across species, ecosystems, and sampling approaches, and may be useful in forecasting cascading impacts following widespread predator declines. Taken together, this approach facilitates a nuanced and mechanistic understanding of food-web ecology. Methods This dataset is a subset of 20 large systematic camera trapping sessions conducted across 10 landscapes in Southeast Asian primary tropical forests. The manuscript describes a new method of analyzing camera trap data to infer predator-prey species interactions and is well described in the manuscript. The camera trap data has already been converted to count history matrices and spatial covariates have already been generated, and both are saved as .csv files. The repository also contains completed co-abundance modes which are saved as .RDS files.

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.