Municipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities. The data contained in Indicators provides key financial and demographic information on municipalities in Connecticut. The data includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition. The majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. Unlike prior years' where the audited financial information was compiled by OPM, the FY 2020 and beyond information in this edition was based upon the self-reporting by municipalities of their own audited data. Note: This dataset includes annually reported data using three types of years: calendar year, fiscal year, and grand list year. The calendar year spans January 1 to December 31. In Connecticut, the state fiscal year runs from July 1 to June 30, with the numerical year indicating when the fiscal year ends (e.g., fiscal year 2022 ended on June 30, 2022). The grand list year refers to the year municipalities assess property values, which occurs annually on October 1. For example, the property values assessed on October 1, 2020, are referred to as "Grand List Year 2020." However, these values are used to levy property taxes for the next fiscal year, spanning July 1, 2021, to June 30, 2022. In this context, grand list year 2020 corresponds to fiscal year ending 2022. Similarly, mill rates for each year are based on the grand list from two years prior. The most recent edition is for the Fiscal Years Ended 2018-2022 published in September 2024. For additional data on net current expenditures per pupil, see the State Department of Education website here: https://portal.ct.gov/sde/fiscal-services/net-current-expenditures-per-pupil-used-for-excess-cost-grant-basic-contributions/documents For additional population data from the Department of Public Health, visit their website here: https://portal.ct.gov/dph/health-information-systems--reporting/population/annual-town-and-county-population-for-connecticut The most recent data on the Municipal Fiscal Indicators is included in the following datasets: Municipal-Fiscal-Indicators: Financial Statement Information, 2020-2022 https://data.ct.gov/d/d6pe-dw46 Municipal-Fiscal-Indicators: Uniform Chart of Accounts, 2020-2022 https://data.ct.gov/d/e2qt-k238 Municipal Fiscal Indicators: Pension Funding Information for Defined Benefit Pension Plans, 2020-2022 https://data.ct.gov/d/73q3-sgr8 Municipal Fiscal Indicators: Type and Number of Pension Plans, 2020-2022 https://data.ct.gov/d/i84g-vvfb Municipal Fiscal Indicators: Other Post-Employment Benefits (OPEB), 2020-2022 https://data.ct.gov/d/ei7n-pnn9 Municipal Fiscal Indicators: Economic and Grand List Data, 2019-2024 https://data.ct.gov/d/xgef-f6jp Municipal Fiscal Indicators: Benchmark Labor Data, 2020-2024 https://data.ct.gov/d/5ijb-j6bn Municipal Fiscal Indicators: Bond Ratings, 2019-2022 https://data.ct.gov/d/a65i-iag5 Municipal Fiscal Indicators: Individual Town Data, 2014-2022 https://data.ct.gov/d/ej6f-y2wf Municipal Fiscal Indicators: Totals and Averages, 2014-2022 https://data.ct.gov/d/ryvc-y5rf

United States - Commercial Paper Outstanding; Maturing After December 31 was 1053480.57400 Mil. of $ in December of 2024, according to the United States Federal Reserve. Historically, United States - Commercial Paper Outstanding; Maturing After December 31 reached a record high of 1740912.61490 in December of 2006 and a record low of 0.00000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Commercial Paper Outstanding; Maturing After December 31 - last updated from the United States Federal Reserve on July of 2025.

BackgroundThere is an increasing need to evaluate the production and impact of medical research produced by institutions. Many indicators exist, yet we do not have enough information about their relevance. The objective of this systematic review was (1) to identify all the indicators that could be used to measure the output and outcome of medical research carried out in institutions and (2) enlist their methodology, use, positive and negative points.MethodologyWe have searched 3 databases (Pubmed, Scopus, Web of Science) using the following keywords: [Research outcome* OR research output* OR bibliometric* OR scientometric* OR scientific production] AND [indicator* OR index* OR evaluation OR metrics]. We included articles presenting, discussing or evaluating indicators measuring the scientific production of an institution. The search was conducted by two independent authors using a standardised data extraction form. For each indicator we extracted its definition, calculation, its rationale and its positive and negative points. In order to reduce bias, data extraction and analysis was performed by two independent authors.FindingsWe included 76 articles. A total of 57 indicators were identified. We have classified those indicators into 6 categories: 9 indicators of research activity, 24 indicators of scientific production and impact, 5 indicators of collaboration, 7 indicators of industrial production, 4 indicators of dissemination, 8 indicators of health service impact. The most widely discussed and described is the h-index with 31 articles discussing it.DiscussionThe majority of indicators found are bibliometric indicators of scientific production and impact. Several indicators have been developed to improve the h-index. This indicator has also inspired the creation of two indicators to measure industrial production and collaboration. Several articles propose indicators measuring research impact without detailing a methodology for calculating them. Many bibliometric indicators identified have been created but have not been used or further discussed.

United States - Commercial Paper Outstanding, Tier-2; Maturing After December 31 was 76749.03200 Mil. of $ in December of 2024, according to the United States Federal Reserve. Historically, United States - Commercial Paper Outstanding, Tier-2; Maturing After December 31 reached a record high of 93629.80300 in December of 2023 and a record low of 0.00000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Commercial Paper Outstanding, Tier-2; Maturing After December 31 - last updated from the United States Federal Reserve on July of 2025.

This dataset provides spatially explicit crop performance indicators for agricultural fields across Europe for the period from May 1 to July 31, 2022. The indicators were derived for parcels with known crop types based on the EU-wide crop-type map developed under Task 5.7 of the OpenEarthMonitor project.

Key variables include:

• Cumulative NDVI (Normalized Difference Vegetation Index)

• Cumulative Chlorophyll Index (CHL)

• Cumulative Growing Degree Days (GDD)

All indicators were extracted at the centroid of each delineated field parcel.

A crop performance index was computed per country and crop type, enabling comparative analysis across European agricultural landscapes. The data is provided as a point-based spatial layer (GeoPackage format), with each point representing a parcel centroid and its associated performance metrics.

This dataset supports the development of a field-based crop performance and phenological monitoring service for Europe, which is currently under prototyping.

Graph and download economic data for OECD based Recession Indicators for Brazil from the Peak through the Period preceding the Trough (DISCONTINUED) (BRARECDP) from 1996-02-01 to 2022-07-31 about peak, trough, recession indicators, and Brazil.

Reason for Selection According to the Southeastern Freshwater Biodiversity Conservation Strategy, “the Southeastern United States is a global hotspot of freshwater biodiversity, supporting almost two-thirds of the country’s fish species, over 90% of the US total species of mussels and nearly half of the global total for crayfish species. More than a quarter of this region’s species are found nowhere else in the world. Unfortunately, this region is also a hotspot for imperilment. The number of imperiled freshwater fish species in the Southeast has risen 125% in the past 20 years” (RBC and TNACI 2023). This indicator identifies areas with abundant rare and endemic aquatic species that would benefit from conservation action. It captures patterns of rare and endemic species diversity not well-represented by other freshwater indicators.

The Southeast Aquatic Resources Partnership (SARP) tracks the number of aquatic animal species in different conservation categories, including Species of Greatest Conservation Need (SGCN), Regional SGCN (RSGCN), and threatened or endangered. To depict the aquatic priorities of state fish and wildlife agencies, this indicator previously used SGCN, which are identified in each State Wildlife Action Plan (SWAP) as most in need of conservation action. In 2024, this indicator switched to using RSGCN. RSGCN are regional priority species derived from all Southeast SWAPs using a set of consistent criteria, such as level of conservation concern, regional stewardship responsibility, and biological or ecological significance (Terwilliger Consulting 2019). Using RSGCN provides more clarity and focus for regional conservation and enhanced opportunities for multi-state collaboration. It also accounts for differences in the ways aquatic species are identified as SGCN in each SWAP, which caused the indicator to overprioritize some states because they had a more comprehensive SGCN list, but not necessarily more aquatic biodiversity. Input Data

Southeast Blueprint 2024 extent
Southeast Aquatic Resources Partnership (SARP) RSGCN HUC12 summaries

SARP provided these summaries on May 8, 2024 as a spreadsheet containing the ID number for each HUC12 watershed and an attribute for the number of aquatic animal RSGCN observed in that watershed. This dataset is based on state Natural Heritage Program occurrence records for fishes, mussels, snails, crayfish, and amphibians. It was last updated in April 2024. More information on this dataset is available in the appendix of the Blueprint development process pdf.

  Estimated Floodplain Map of the Conterminous U.S. from the Environmental Protection Agency’s (EPA) EnviroAtlas; see this factsheet for more information; download the data 

The EPA Estimated Floodplain Map of the Conterminous U.S. displays “...areas estimated to be inundated by a 100-year flood (also known as the 1% annual chance flood). These data are based on the Federal Emergency Management Agency (FEMA) 100-year flood inundation maps with the goal of creating a seamless floodplain map at 30-m resolution for the conterminous United States. This map identifies a given pixel’s membership in the 100-year floodplain and completes areas that FEMA has not yet mapped” (EPA 2018).

  National Hydrography Dataset Plus (NHDPlus) Version 2.1 medium resolution catchments (note: V2.1 is just the current sub-version of the dataset generally called NHDPlusV2); view the user guide

CatchmentsA catchment is the local drainage area of a specific stream segment based on the surrounding elevation. Catchments are defined based on surface water features, watershed boundaries, and elevation data. It can be difficult to conceptualize the size of a catchment because they vary significantly in size based on the length of a particular stream segment and its surrounding topography—as well as the level of detail used to map those characteristics.

To learn more about catchments and how they’re defined, check out these resources:

An article from USGS explaining the differences between various NHD products
The glossary at the bottom of this tutorial for an EPA water resources viewer, which defines some key terms



U.S. Geological Survey (USGS) Watershed Boundary Dataset (WBD), accessed 12-2-2021: HUC12s; download the data

Mapping Steps

Join the RSGCN count table to the HUC12 spatial data.
Convert to a 30 m raster, where the values represent the number of RSGCN.
Reclassify the species count values to the 1-9 indicator values below.
Mask the resulting raster to the EPA estimated floodplain. Assign a value of 0 to all areas outside the EPA floodplain. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.
Mask the resulting floodplain-masked raster to the NHDPlus medium resolution catchments layer to remove values in the nearshore environment.
As a final step, clip to the spatial extent of Southeast Blueprint 2024. 

Note: For more details on the mapping steps, code used to create this layer is available in the Southeast Blueprint Data Download under > 6_Code. Final indicator values Indicator values are assigned as follows: 9 = 8+ aquatic animal Regional Species of Greatest Conservation Need (RSGCN) observed 8 = 7 aquatic animal RSGCN observed 7 = 6 aquatic animal RSGCN observed 6 = 5 aquatic animal RSGCN observed 5 = 4 aquatic animal RSGCN observed 4 = 3 aquatic animal RSGCN observed 3 = 2 aquatic animal RSGCN observed 2 = 1 aquatic animal RSGCN observed 1 = 0 aquatic animal RSGCN observed 0 = Not identified as a floodplain Known Issues

As this indicator is based on occurrence records, poorly surveyed areas may be scored too low. Therefore, this data does not imply absence of species.
While this indicator generally includes the open water area of reservoirs, some open water portions of reservoirs (e.g., Kerr Lake in NC/VA) are missing from the estimated floodplain dataset.
Small headwaters and creeks are not included in this indicator because the EPA estimated floodplain dataset does not include them.
This indicator may underprioritize areas important for aquatic plants. A list of Southeastern plant Regional Species of Greatest Conservation Need has recently been developed, but at this point SARP is only collecting information on aquatic animal species. We will explore ways to incorporate aquatic plant species in the future.
In the area just south of Guadalupe Mountains National Park in West Texas, this indicator depicts the floodplain as a series of straight lines that poorly match the actual floodplain. This is due to an error in the EPA floodplain map used in this indicator.
The catchment boundaries are inconsistent in how far they extend toward the ocean. As a result, this indicator does not consistently apply to estuaries, coastal areas, and barrier islands.

Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email hilary_morris@fws.gov).Literature Cited EPA EnviroAtlas. 2018. Estimated Floodplain Map of the Conterminous U.S. [https://enviroatlas.epa.gov/enviroatlas/DataFactSheets/pdf/Supplemental/EstimatedFloodplains.pdf].

Southeast Aquatic Resources Partnership. Species Summaries by HUC12. Accessed May 2024.

Terwilliger Consulting, Inc. Regional Species of Greatest Conservation Need in the Southeastern United States. July 2019. [https://secassoutheast.org/pdf/SEAFWA_RSGCN_Final_Report_20190715.pdf].

The River Basin Center and The Tennessee Aquarium Conservation Institute. The Southeastern Freshwater Biodiversity Conservation Strategy. Accessed July 31, 2023. [https://southeastfreshwater.org/].

U.S. Environmental Protection Agency (USEPA) and the U.S. Geological Survey (USGS). 2012. National Hydrography Dataset Plus 2. [https://www.horizon-systems.com/nhdplus/].

Graph and download economic data for OECD based Recession Indicators for Australia from the Period following the Peak through the Trough (DISCONTINUED) (AUSRECD) from 1960-02-01 to 2022-07-31 about peak, trough, recession indicators, and Australia.

United States - Commercial Paper Outstanding, Tier-1; Maturing After December 31 was 346475.39600 Mil. of $ in December of 2024, according to the United States Federal Reserve. Historically, United States - Commercial Paper Outstanding, Tier-1; Maturing After December 31 reached a record high of 1595815.04030 in December of 2006 and a record low of 0.00000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Commercial Paper Outstanding, Tier-1; Maturing After December 31 - last updated from the United States Federal Reserve on July of 2025.

The indicator reports the number of employees working in industry (sections B, C, D and E of NACE rev.2) to the total number of employed jobs at 30 June and 31 December. This indicator illustrates the ‘industrial’ character of the entity. Series breaks: — as of 1 January 2011:output of statistics of inactive employees following the modification of the declaration of public sector staff (Capelo reform). — as of 1 January 2012: output of statistics of inactive employees following the amendment of the declaration of public sector staff (Capelo reform): continuation and end. — as of 1 January 2014: adjustment of the breakdown by work common following the exhaustive identification of establishment units See also: Other indicators relating to wage employment are available in the topic ‘Labour market’. — The 10 main sectors of activity (grouping A10) in the “\2” classification of national accounts, p. 16.The indicator reports the number of employees working in industry (sections B, C, D and E of NACE rev.2) to the total number of employed jobs at 30 June and 31 December. This indicator illustrates the ‘industrial’ character of the entity. Series breaks: — as of 1 January 2011: output of statistics of inactive employees following the modification of the declaration of public sector staff (Capelo reform). — as of 1 January 2012: output of statistics of inactive employees following the amendment of the declaration of public sector staff (Capelo reform): continuation and end. — as of 1 January 2014: adjustment of the breakdown by work common following the exhaustive identification of establishment units See also: Other indicators relating to wage employment are available in the topic ‘Labour market’. — The 10 main sectors of activity (grouping A10) in the “\2” classification of national accounts, p. 16.

This data set contains the JOSS quality controlled WVSS-I data. This data has consistent water vapor information (dewpoint, RH, and mixing ratio are consistent), and has the benefit of time continuity to check for changes in WVSS-I calibration. IMPORTANT NOTE: The sensor technology of the first generation Water Vapor Sensing System (WVSS-I) is Vaisala's thin-film capacitor. Though a better sensor than found on radiosondes, it still loses calibration over time. The data from WVSS-I gathered from July 1, 1999 to December 31, 1999 has been evaluated and a scientific article is being prepared. This data is useful with data from four of the six aircraft considered quite good. One aircraft (#376) appears approximately 5% too wet and one aircraft (#441) appears approximately 5% too dry (very dry in November and December 1999). See the README for further information.

This data is the source dataset for the Forestry Commissions Headline Performance Indicator: 'Percentage of woodland in active management (including the Public Forest Estate)'.

This Indicator forms part of the Forestry Commissions Corporate Plan Performance Indicators and Woodland Indicators 2012/13.

This FC website gives more information about the Performance Indicators: http://www.forestry.gov.uk/website/forestry.nsf/byunique/infd-8kmhu6

For the purposes of the corporate indicator, 'Actively Managed’ woodland is currently defined using the following FC administrative data sources. It is recognised that there are other woodlands that could be considered to be 'managed'.

1) Any English Woodland Grant Scheme (EWGS) Woodland Creation Grant (WCG) whose first instalment payment date was < 10 years ago at the end of the reporting period. 2) Any English Woodland Grant Scheme (EWGS) Woodland Management Grant (WMG) whose first instalment payment date was < 5 years ago at the end of the reporting period. 3) Any English Woodland Grant Scheme (EWGS) Woodland Planning Grant (WPG) whose first instalment payment date was < 10 years ago at the end of the reporting period. 4) Any English Woodland Grant Scheme (EWGS) Woodland Improvement Grant (WIG) whose first instalment payment date was < 5 years ago at the end of the reporting period. 5) Any Farm Woodland Premium Scheme (FWPS) and Farm Woodland Premium (FWP) whose scheme approval date was <30 years ago at the end of the reporting period. 6) Any Woodland Grants Scheme Mk3 (WGS3) schemes that have been in contract in the 15 years up until the end of the reporting period. 7) Any Felling Licence Applications (FLA) whose registration date was <10 years ago at the end of the reporting period. 8) All Public Forest Estate land owned and/or managed by the Forestry Commission at the end of the reporting period.

EXCLUDED: EWGS Woodland Assessment Grant (WAG), EWGS Woodland Regeneration Grant (WRG), Forest Plans, Dedication, WGS2, WGS1 and Natural England’s HLS.

The 'denominator' used for calculation of the indicator, i.e. the figure used as the entire woodland area in England, was that obtained from the most recent version of the National Forest Inventory (NFI) at the time of computation.

The administrative data sources are integrated to produce a single layer indicating woodland management status and this is provided as a georeferenced .tiff raster file here. Cell values: 0 = Unmanaged woodland, 1 = Actively managed woodland. Cell size: 25m.

Please ensure that the following acknowledgement is displayed on any hard copy: © Crown copyright and database right 'year'. Ordnance Survey Licence number 100021242. Attribution statement: Contains OS data © Crown copyright [and database right] [year].

The COVID-19 pandemic and its impact on crude oil prices created additional risks throughout the financial industry. To contribute to the ongoing debates, this paper empirically examined the risk contagion of COVID-19 to oil prices by incorporating a Markov-Switching GARCH (MS-GARCH) framework and the multivariate GARCH time series model, BEKK-GARCH model. The study examines data collected between 27 January 2020 and 31 December 2020. Further, we used principal component analysis (PCA) to find principal factors explaining the overall variability of the global economic indicators that contribute to the risk. Finally, to support the risk transmission effects between COVID-19 and oil prices, we conducted regression analysis, while controlling for the factors extracted from the PCA method.

Type of journals and area of research measured by indicators.

Business Climate Indicator in France remained unchanged at 96 points in July. This dataset provides - France Business Climate Composite Indicator- actual values, historical data, forecast, chart, statistics, economic calendar and news.