The United Nations Standard Products and Services Code (UNSPSC) is a hierarchical convention that is used to classify all products and services.

This dataset contains the ICD-10 code lists used to test the sensitivity and specificity of the Clinical Practice Research Datalink (CPRD) medical code lists for dementia subtypes. The provided code lists are used to define dementia subtypes in linked data from the Hospital Episode Statistic (HES) inpatient dataset and the Office of National Statistics (ONS) death registry, which are then used as the 'gold standard' for comparison against dementia subtypes defined using the CPRD medical code lists. The CPRD medical code lists used in this comparison are available here: Venexia Walker, Neil Davies, Patrick Kehoe, Richard Martin (2017): CPRD codes: neurodegenerative diseases and commonly prescribed drugs. https://doi.org/10.5523/bris.1plm8il42rmlo2a2fqwslwckm2 Complete download (zip, 3.9 KiB)

Tax code rates for Tax Years 2006 through 2013. Data is updated yearly. For more information on Tax codes visit the Cook County Clerk's website at: http://www.cookcountyclerk.com/tsd/Pages/default.aspx

This dataset was created to facilitate the conversion of Uniform Crime Reporting (UCR) Program state and county codes to Federal Information Processing Standards (FIPS) state and county codes. The four UCR agency-level data files archived at ICPSR in Uniform Crime Reporting Program Data: United States contain UCR state and county codes as geographic identifiers. Researchers who wish to use these data with other sources, such as Census data, may want to convert these UCR codes to FIPS codes in order to link the different data sources. This file was created to facilitate this linkage. It contains state abbreviations, UCR state and county codes, FIPS state and county codes, and county names for all counties present in the UCR data files since 1990. These same FIPS codes were used to create the UCR County-Level Detailed Arrest and Offense files from 1990-1996.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2010 Census.

This dataset contains statewide counts for every diagnosis, procedure, and external cause of injury/morbidity code reported on the hospital emergency department data. Diagnosis codes are reported using ICD-9-CM or ICD-10-CM. Procedure codes are reported using CPT-4. External cause of injury/morbidity codes are reported using ICD-9-CM or ICD-10-CM. ICD-10 replaced ICD-9, effective October 1, 2015.

Auxiliary data and codes, example data for scPlant (https://github.com/compbioNJU/scPlant).

List of currencies and their 3 digit codes as defined by ISO 4217. The data provided here is the consolidation of Table A.1 "Current currency & funds code list" and Table A.3 "Historic denominations".Note that the ISO page offers pay-for PDFs but also links to http://www.currency-iso.org/en/home/tables.html which does provide them in machine readable form freely.

In 2021, an international goods and services classification for procurement called the United Nations Standard Products and Services Code (UNSPSC, v21) was implemented to replace the Government of Canada’s Goods and Services Identification Numbers (GSIN) codes for categorizing procurement activities undertaken by the Government of Canada. For the transition from GSIN to UNSPSC, a subset of the entire version 21 UNSPSC list was created. The Mapping of GSIN-UNSPSC file below provides a suggested linkage between the subset of UNSPSC and higher levels of the GSIN code list. As procurement needs evolve, this file may be updated to include other UNSPSC v21 codes that are deemed to be required. In the interim, if the lowest level values within the UNSPSC structure does not relate to a specific category of goods or services, the use of the higher (related) level code from within the UNSPSC structure is appropriate. --- >Please note: This dataset is offered as a means to assist the user in finding specific UNSPSC codes, based on high-level comparisons to the legacy GSIN codes. It should not be considered a direct one-to-one mapping of these two categorization systems. For some categories, the linkages were only assessed at higher levels of the two structures (and then simply carried through indiscriminately to the related lower categories beneath those values). But given that the two systems do not necessarily group items in the same way throughout their structures, this could result in confusing connections in some cases. Please always select the UNSPSC code that best describes the applicable goods or services, even if the associated GSIN value as shown in this file is not directly relevant. --- The data is available in Comma Separated Values (CSV) file format and can be downloaded to sort, filter, and search information. The United Nations Standard Products and Services Code (UNSPSC) page on CanadaBuys offers a comprehensive guide on how to use this reference file. The Finding and using UNSPSC Codes page from CanadaBuys also contains additional information which may be of use. This dataset was originally published on June 22, 2016. The format and contents of the CSV file were revised on May 12, 2021. A copy of the original file was archived as a secondary resource to this dataset at that time (labelled ARCHIVED - Mapping of GSIN-UNSPSC in the resource list below). --- As of March 23, 2023, the data dictionary linked below includes entries for both the current and archived versions of the datafile, as well as for the datafiles of Goods and Services Identification Number (GSIN) dataset and the archived United Nations Standard Products and Services Codes (v10, released 2007) dataset.

We show that the conditional distribution of forecasted GDP growth depends on financial conditions in a panel of 11 advanced economies. Financial conditions have a larger effect on the lower 5th percentile of conditional growth—which we call growth-at-risk (GaR)—than the median. In addition, the term structure of GaR reflects that when initial financial conditions are loose, downside risks are lower in the near-term but increase in later quarters. This intertemporal tradeoff for loose financial conditions is amplified when credit-to-GDP growth is rapid. Using granular instrumental variables, we also provide evidence that the relationship from loose financial conditions to future downside risks is causal. Our results suggest that models of macrofinancial linkages should incorporate the endogeneity of higher-order moments to systematically account for downside risks to growth in the medium run.

Files included are original data inputs on stream fishes (fish_data_OEPA_2012.csv), water chemistry (OEPA_WATER_2012.csv), geographic data (NHD_Plus_StreamCat); modeling files for generating predictions from the original data, including the R code (MVP_R_Final.txt) and Stan code (MV_Probit_Stan_Final.txt); and the model output file containing predictions for all NHDPlus catchments in the East Fork Little Miami River watershed (MVP_EFLMR_cooc_Final). This dataset is associated with the following publication: Martin, R., E. Waits, and C. Nietch. Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 613(614): 1228-1239, (2018).

van den Berg, Gerard J., Bonev, Petyo, and Mammen, Enno, (2020) “Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation.” Review of Economics and Statistics 102:2, 355–367.

This reference table contains data elements for the 58 Counties in California that can be used to join to other data sets. This data includes the following fields:DHCS County CodeCounty NameCounty Region CodeCounty Region DescriptionFIPS County Code (xxx)FIPS State Code + FIPS County Code (06xxx)North/South Indicator

Data and Code to accompany the paper "Correlation Neglect in Student-to-School Matching."Abstract: We present results from three experiments containing incentivized school-choice scenarios. In these scenarios, we vary whether schools' assessments of students are based on a common priority (inducing correlation in admissions decisions) or are based on independent assessments (eliminating correlation in admissions decisions). The quality of students' application strategies declines in the presence of correlated admissions: application strategies become substantially more aggressive and fail to include attractive ``safety'' options. We provide a battery of tests suggesting that this phenomenon is at least partially driven by correlation neglect, and we discuss implications for the design and deployment of student-to-school matching mechanisms.

78 Global import shipment records of Bar Code with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The units of geography used for the 2010 Census maps displayed here are the Zip Code Tabulation Area (ZCTA). ZCTAs are statistical geographic areas produced by the Census Bureau by aggregating census blocks to create generalized areas closely resembling the U.S. Postal Service's postal zip codes. The data collected on the short form survey are general demographic characteristics such as age - race - ethnicity - household relationship - housing vacancy and tenure (owner/renter).Feature Service Link:http://geodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer/1 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports using the Hi-Tech classification system. The Hi-Tech endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

Find the updated imports data of 40169330 HS code with product name, description, pricing, Indian import port, and importers in India.

Online Supplemental Material 2 (OSM 2) contains the data and code necessary to generate Figures 3-6, 8-9, S1 and S5-S6 presented in Sinensky et al. (2022). The R Markdown document (OSM 2.0) will render these figures using the data provided in OSM 2.1-2.6.

ACRIS Collateral Type mapping for Codes in the ACRIS Personal Property Master Dataset