Graph and download economic data for Existing Home Sales: Months Supply (HOSSUPUSM673N) from May 2024 to May 2025 about supplies, sales, housing, and USA.

Graph and download economic data for Monthly Supply of New Houses in the United States (MSACSR) from Jan 1963 to May 2025 about supplies, new, housing, and USA.

Total Housing Inventory in the United States increased to 1540 Thousands in May from 1450 Thousands in April of 2025. This dataset includes a chart with historical data for the United States Total Housing Inventory.

Moldova PPI: NACE 2: Same Month PY=100: ES: Steam and Air Conditioning Supply data was reported at 100.000 Same Mth PY=100 in Oct 2018. This stayed constant from the previous number of 100.000 Same Mth PY=100 for Sep 2018. Moldova PPI: NACE 2: Same Month PY=100: ES: Steam and Air Conditioning Supply data is updated monthly, averaging 100.921 Same Mth PY=100 from Jan 2012 (Median) to Oct 2018, with 82 observations. The data reached an all-time high of 123.066 Same Mth PY=100 in Jan 2012 and a record low of 93.906 Same Mth PY=100 in Apr 2014. Moldova PPI: NACE 2: Same Month PY=100: ES: Steam and Air Conditioning Supply data remains active status in CEIC and is reported by National Bureau of Statistics of the Republic of Moldova. The data is categorized under Global Database’s Moldova – Table MD.I011: Producer Price Index: Same Month Previous Year=100.

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Jun 2025 about median and USA.

United States Months of Supply: Townhouse: Fairmont, MN data was reported at 2.000 Month in Jul 2012. This stayed constant from the previous number of 2.000 Month for Apr 2012. United States Months of Supply: Townhouse: Fairmont, MN data is updated monthly, averaging 2.000 Month from Apr 2012 (Median) to Jul 2012, with 2 observations. The data reached an all-time high of 2.000 Month in Jul 2012 and a record low of 2.000 Month in Jul 2012. United States Months of Supply: Townhouse: Fairmont, MN data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB029: Months of Supply: by Metropolitan Areas.

United States Months of Supply: Townhouse: Des Moines, IA data was reported at 0.500 Month in Aug 2019. This records a decrease from the previous number of 1.000 Month for Apr 2019. United States Months of Supply: Townhouse: Des Moines, IA data is updated monthly, averaging 0.750 Month from Apr 2019 (Median) to Aug 2019, with 2 observations. The data reached an all-time high of 1.000 Month in Apr 2019 and a record low of 0.500 Month in Aug 2019. United States Months of Supply: Townhouse: Des Moines, IA data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB029: Months of Supply: by Metropolitan Areas.

The U.S. Geological Survey is developing national water-use models to support water resources management in the United States. Model benefits include a nationally consistent estimation approach, greater temporal and spatial resolution of estimates, efficient and automated updates of results, and capabilities to forecast water use into the future and assess model uncertainty. The term “reanalysis” refers to the process of reevaluating and recalculating water-use data using updated or refined methods, data sources, models, or assumptions. In this data release, water use refers to water that is withdrawn by public and private water suppliers and includes water provided for domestic, commercial, industrial, thermoelectric power, and public water uses, as well as water that is consumed or lost within the public supply system. Consumptive use refers to water withdrawn by the public supply system that is evaporated, transpired, incorporated into products or crops, or consumed by humans or livestock. This data release contains data used in a machine learning model (child item 2) to estimate monthly water use for communities that are supplied by public-supply water systems in the conterminous United States for 2000-2020. This data release also contains associated scripts used to produce input features (child items 4 - 8) as well as model water use estimates by 12-digit hydrologic unit code (HUC12) and public supply water service area (WSA). HUC12 boundaries are in child item 3. Public supply delivery and consumptive use estimates are in child items 1 and 9, respectively. First posted: November 1, 2023 Revised: August 8, 2024 This version replaces the previous version of the data release: Luukkonen, C.L., Alzraiee, A.H., Larsen, J.D., Martin, D.J., Herbert, D.M., Buchwald, C.A., Houston, N.A., Valseth, K.J., Paulinski, S., Miller, L.D., Niswonger, R.G., Stewart, J.S., and Dieter, C.A., 2023, Public supply water use reanalysis for the 2000-2020 period by HUC12, month, and year for the conterminous United States: U.S. Geological Survey data release, https://doi.org/10.5066/P9FUL880 Version 2.0 This data release has been updated as of 8/8/2024. The previous version has been replaced because some fractions used for downscaling WSA estimates to HUC12 did not sum to one for some WSAs in Virginia. Updated model water use estimates by HUC12 are included in this version. A change was made in two scripts to check for this condition. Output files have also been updated to preserve the leading zero in in the HUC12 codes. Additional files are also included to provide information about mapping the WSAs and groundwater and surface water fractions to HUC12 and to provide public supply water-use estimates by WSA. The 'Machine learning model that estimates total monthly and annual per capita public supply water use' child item has been updated with these corrections and additional files. A new child item 'R code used to estimate public supply consumptive water use' has been added to provide estimates of public supply consumptive use. This page includes the following files: PS_HUC12_Tot_2000_2020.csv - a csv file with estimated monthly public supply total water use from 2000-2020 by HUC12, in million gallons per day PS_HUC12_GW_2000_2020.csv - a csv file with estimated monthly public supply groundwater use for 2000-2020 by HUC12, in million gallons per day PS_HUC12_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by HUC12, in million gallons per day PS_WSA_Tot_2000_2020.csv - a csv file with estimated monthly public supply total water use from 2000-2020 by WSA, in million gallons per day PS_WSA_GW_2000_2020.csv - a csv file with estimated monthly public supply groundwater use for 2000-2020 by WSA, in million gallons per day PS_WSA_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by WSA, in million gallons per day Note: 1) Groundwater and surface water fractions were determined using source counts as described in the 'R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units' child item. 2) Some HUC12s have estimated water use of zero because no public-supply water service areas were modeled within the HUC. change_files_format.py - A Python script used to change the water use estimates by WSA and HUC12 files from wide format to the thin and long format version_history.txt - a txt file describing changes in this version The data release is organized into these items: 1. Machine learning model that estimates public supply deliveries for domestic and other use types - The public supply delivery model estimates total delivery of domestic, commercial, industrial, institutional, and irrigation (CII) water use for public supply water service areas within the conterminous United States. This item contains model input datasets, code used to build the delivery machine learning model, and output predictions. 2. Machine learning model that estimates total monthly and annual per capita public supply water use - The public supply water use model estimates total monthly water use for 12-digit hydrologic units within the conterminous United States. This item contains model input datasets, code used to build the water use machine learning model, and output predictions. 3. National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020 - Spatial data consisting of a shapefile with 12-digit hydrologic units for the conterminous United States retrieved 10/26/2020. 4. Python code used to determine average yearly and monthly tourism per 1000 residents for public-supply water service areas - This code was used to create a feature for the public supply model that provides information for areas affected by population increases due to tourism. 5. Python code used to download gridMET climate data for public-supply water service areas - The climate data collector is a tool used to query climate data which are used as input features in the public supply models. 6. Python code used to download U.S. Census Bureau data for public-supply water service areas - The census data collector is a geographic based tool to query census data which are used as input features in the public supply models. 7. R code that determines buying and selling of water by public-supply water service areas - This code was used to create a feature for the public supply model that indicates whether public-supply systems buy water, sell water, or neither buy nor sell water. 8. R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units - This code was used to determine source water fractions (groundwater and/or surface water) for public supply systems and HUC12s. 9. R code used to estimate public supply consumptive water use - This code was used to estimate public supply consumptive water use using an assumed fraction of deliveries for outdoor irrigation and estimates of evaporative demand. This item contains estimated monthly public supply consumptive use datasets by HUC12 and WSA.

This data release contains the output from an ecological analysis modeling the exposure of 214 fish taxa across the conterminous US (CONUS) to an index of surface water supply and use imbalances (SUI), the proportion of monthly gross average water supply available after accounting for climate variation and consumptive use, during their spawning months, hereafter referred to as spawning exposure. SUI were calculated in Miller and others (2024) by combining the monthly water balance from water supply and human consumptive uses for CONUS from water years 2010-2020 at the HUC12 scale. Water supply inputs were generated from two physically-based hydrologic models, and consumptive water use was calculated from three separate national models for agricultural irrigation, thermoelectric power generation, and public supply. Water budgets were routed through the surface water flow network (to allow for upstream consumptive uses to affect downstream water availability) and used to determine potential water limitations for human populations and fish taxa. We overlaid water supply imbalances with the modeled ranges of 241 fish taxa, including Species of Greatest Conservation Need, recreationally important, and common native taxa. SUI were evaluated within each HUC12 and specifically mean weighted based on the probability of spawning in each month for each taxa. Our analyses indicated multiple taxa having notable proportions of their habitats exposed to high or severe water imbalances during spawning, especially the federally-listed Arkansas River shiner. This analysis can be used to identify fish taxa particularly exposed to water availability issues, specifically from surface water supply and use imbalances, during the physiologically important spawning period. However, this analysis did not consider specific taxa-level differences as to the sensitivity of different taxa to limited water supply. This data release contains five tabular datasets in comma-separated values (.csv), covering a tabular data dictionary, input data supporting analysis, raw analysis output, and summarized versions at two spatial scales for convenience. They are: 1) data_dictionary.csv - A data dictionary containing entity and attribute information about variable names, descriptions, types, ranges, and unique values for easy access. 2) SpawningExposure_TaxaSpawningWeights.csv - Dataset used to weigh spawning months for each taxon in calculation of the spawning exposure. Derived from Frimpong and Angermeier, 2011. 3) SpawningExposure_SUI_HUC12.csv - CONUS level dataset of spawning exposure to SUI from 2010-2020 for each fish taxa reported for each HUC12 where they are present. 4) SpawningExposure_SUI_CONUS_Summary.csv - A summary of spawning exposure to SUI by fish taxa, for the entire habitat range in CONUS, the range-averaged SUI exposure and percentage of habitat in each SUI category class. 5) SpawningExposure_SUI_Regional_Summary.csv - Summaries of spawning exposure to SUI by fish taxa, for each Van Metre (2020) hydrologic region, the region range-average exposure and percentage of the region's habitat range in each SUI category class.

United States Months of Supply: Townhouse: Indiana data was reported at 0.000 Month in Apr 2020. This records a decrease from the previous number of 1.000 Month for Mar 2020. United States Months of Supply: Townhouse: Indiana data is updated monthly, averaging 0.500 Month from Mar 2020 (Median) to Apr 2020, with 2 observations. The data reached an all-time high of 1.000 Month in Mar 2020 and a record low of 0.000 Month in Apr 2020. United States Months of Supply: Townhouse: Indiana data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB028: Months of Supply: by States.

Number of affordable housing starts (seasonally adjusted)

How the figure is calculated:

Total reported numbers of starts under the relevant programmes within the reporting period. Because delivery is seasonal and reflects funding profiles, with more starts and completions being reported in the second six months than are reported in the first six months, the current figures are compared back to the equivalent period of the year before rather than the preceding six months.

Why is this indicator in the business plan?

These are the most timely indicators on affordable housing delivery. Increasing the supply of affordable housing is a key part of DCLG policy.

How often is it updated?

Bi-annually, approximately June and November.

Where does the data come from?

Homes and Communities Agency (HCA) - Investment Management System and other programme information. Published figures are at http://www.homesandcommunities.co.uk/housing-statistics.

Greater London Authority (GLA) - Investment Management System and other programme information. Published figures are at http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics.

What area does the headline figure cover?

England

Are further breakdowns of the data available?

Yes, can be split by type (social rent, affordable rent, intermediate rent, Low Cost Home Ownership) and by local authority area.

What does a change in this indicator show?

An increase in this indicator is good and shows more new affordable houses are being started through the HCA and GLA.

Time Lag

Published within two months of the end of the reporting period.

Next available update

June 2015.

Type of Data

Official Statistics.

Robustness and data limitations

• Does not include all affordable housing starts and completions because some will be delivered outside the HCA and GLA roles.
• Delivery is seasonal and reflects funding profiles. Delivery tends to be lower in the first six months than the last six months of the year and therefore comparisons with the previous six-monthly period are not usually appropriate.
• A small number of the affordable housing starts reported by the HCA over this period are actually located in London (the Get Britain Building programme in London is administered by the HCA on behalf of the GLA).

With effect from 1 April 2014, affordable housing starts on site include the starts on site for new build homes purchased at completion. These have not been reported historically

Links to Further Information

http://www.homesandcommunities.co.uk/housing-statistics

http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics

Contact Details

CorporatePerformance@communities.gsi.gov.uk

This data release contains the output from an ecological analysis modeling the exposure of 214 fish taxa across the conterminous US (CONUS) to an index of surface water supply and use imbalances (SUI), the proportion of monthly gross average water supply available after accounting for climate variation and consumptive use, during their spawning months, hereafter referred to as spawning exposure. SUI were calculated in Miller and others (2024) by combining the monthly water balance from water supply and human consumptive uses for CONUS from water years 2010-2020 at the HUC12 scale. Water supply inputs were generated from two physically-based hydrologic models, and consumptive water use was calculated from three separate national models for agricultural irrigation, thermoelectric power generation, and public supply. Water budgets were routed through the surface water flow network (to allow for upstream consumptive uses to affect downstream water availability) and used to determine potential water limitations for human populations and fish taxa. We overlaid water supply imbalances with the modeled ranges of 241 fish taxa, including Species of Greatest Conservation Need, recreationally important, and common native taxa. SUI were evaluated within each HUC12 and specifically mean weighted based on the probability of spawning in each month for each taxa. Our analyses indicated multiple taxa having notable proportions of their habitats exposed to high or severe water imbalances during spawning, especially the federally-listed Arkansas River shiner. This analysis can be used to identify fish taxa particularly exposed to water availability issues, specifically from surface water supply and use imbalances, during the physiologically important spawning period. However, this analysis did not consider specific taxa-level differences as to the sensitivity of different taxa to limited water supply. This data release contains five tabular datasets in comma-separated values (.csv), covering a tabular data dictionary, input data supporting analysis, raw analysis output, and summarized versions at two spatial scales for convenience. They are: 1) data_dictionary.csv - A data dictionary containing entity and attribute information about variable names, descriptions, types, ranges, and unique values for easy access. 2) SpawningExposure_TaxaSpawningWeights.csv - Dataset used to weigh spawning months for each taxon in calculation of the spawning exposure. Derived from Frimpong and Angermeier, 2011. 3) SpawningExposure_SUI_HUC12.csv - CONUS level dataset of spawning exposure to SUI from 2010-2020 for each fish taxa reported for each HUC12 where they are present. 4) SpawningExposure_SUI_CONUS_Summary.csv - A summary of spawning exposure to SUI by fish taxa, for the entire habitat range in CONUS, the range-averaged SUI exposure and percentage of habitat in each SUI category class. 5) SpawningExposure_SUI_Regional_Summary.csv - Summaries of spawning exposure to SUI by fish taxa, for each Van Metre (2020) hydrologic region, the region range-average exposure and percentage of the region's habitat range in each SUI category class.

Number of affordable housing completions (seasonally adjusted)

How the figure is calculated:

Total reported numbers of completions under the relevant programmes within the reporting period. Because delivery is seasonal and reflects funding profiles, with more starts and completions being reported in the second six months than are reported in the first six months, the current figures are compared back to the equivalent period of the year before rather than the preceding six months.

Why is this indicator in the business plan?

These are the most timely indicators on affordable housing delivery. Increasing the supply of affordable housing is a key part of DCLG policy.

How often is it updated?

Bi-annually, approximately June and November.

Where does the data come from?

Homes and Communities Agency (HCA) - Investment Management System and other programme information. Published figures are at http://www.homesandcommunities.co.uk/housing-statistics.

Greater London Authority (GLA) - Investment Management System and other programme information. Published figures are at http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics.

What area does the headline figure cover?

England

Are further breakdowns of the data available?

Yes, can be split by type (social rent, affordable rent, intermediate rent, Low Cost Home Ownership) and by local authority area.

What does a change in this indicator show?

An increase in this indicator is good and shows more new affordable houses are being completed through the HCA and GLA.

Time Lag

Published within two months of the end of the reporting period.

Next available update

June 2015.

Type of Data

Official Statistics.

Robustness and data limitations

• Does not include all affordable housing starts and completions because some will be delivered outside the HCA and GLA roles.
• Delivery is seasonal and reflects funding profiles. Delivery tends to be lower in the first six months than the last six months of the year and therefore comparisons with the previous six-monthly period are not usually appropriate.
• A small number of the affordable housing starts reported by the HCA over this period are actually located in London (the Get Britain Building programme in London is administered by the HCA on behalf of the GLA).

Links to Further Information

http://www.homesandcommunities.co.uk/housing-statistics

http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics

Contact Details

CorporatePerformance@communities.gsi.gov.uk

Monthly reports of water use and conservation activities by urban retail water suppliers, which are generally defined as agencies serving over 3,000 service connections or deliveries 3,000 acre-feet of water annually for municipal purposes.

The most recent reporting period generally lags by about 2 months, due to the reporting deadline and the necessary subsequent dataset preparation. The full dataset that spans June 2014 to the most recent reporting period is the Per-Supplier Water Supply and Demand resource, which is an updated version of the dataset previously released on the Water Board's Water Conservation Portal. Other datasets include the per-water-system supply and demand, representing a subset of the SAFER Clearinghouse dataset, and the conservation actions datasets.

See the documentation PDF for data dictionaries and an explanation of the data flag methodology.

The number of home sales in the United States peaked in 2021 at almost ************* after steadily rising since 2018. Nevertheless, the market contracted in the following year, with transaction volumes falling to ***********. Home sales remained muted in 2024, with a mild increase expected in 2025 and 2026. A major factor driving this trend is the unprecedented increase in mortgage interest rates due to high inflation. How have U.S. home prices developed over time? The average sales price of new homes has also been rising since 2011. Buyer confidence seems to have recovered after the property crash, which has increased demand for homes and also the prices sellers are demanding for homes. At the same time, the affordability of U.S. homes has decreased. Both the number of existing and newly built homes sold has declined since the housing market boom during the coronavirus pandemic. Challenges in housing supply The number of housing units in the U.S. rose steadily between 1975 and 2005 but has remained fairly stable since then. Construction increased notably in the 1990s and early 2000s, with the number of construction starts steadily rising, before plummeting amid the infamous housing market crash. Housing starts slowly started to pick up in 2011, mirroring the economic recovery. In 2022, the supply of newly built homes plummeted again, as supply chain challenges following the COVID-19 pandemic and tariffs on essential construction materials such as steel and lumber led to prices soaring.

1. The forecast of electricity supply and demand for the next two months is based on our company's load forecast and the condition of power generating units, and is adjusted based on long-term weather forecasts from the Central Weather Bureau.2. Peak load refers to the estimated highest instantaneous peak load for each ten-day period.3. The data is updated on the first day of each ten-day period (1st, 11th, and 21st).4. For the calculation method and explanations, please refer to the Taiwan Power Company's official website homepage (https://www.taipower.com.tw/) Information Disclosure Electricity Supply and Demand Information Recent Electricity Information Forecast of Electricity Supply and Demand for the Next Two Months.

Graph and download economic data for Housing Inventory: Median Days on Market in Florida (MEDDAYONMARFL) from Jul 2016 to Jun 2025 about FL, median, and USA.

Business or organization change in supply chain challenges over the last three months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.