Graph and download economic data for Employment Cost Index: Wages and salaries for Private industry workers in the Northeast Census Region (CIU2020000000210I) from Q1 2001 to Q2 2025 about Northeast Census Region, ECI, salaries, workers, private industries, wages, private, industry, and USA.

Graph and download economic data for Producer Price Index by Industry: Ready-Mix Concrete Manufacturing: Ready-Mix Concrete for Northeast Census Region (PCU327320327320A) from Dec 2012 to Jul 2025 about Northeast Census Region, cement, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Abstract: This article aims to observe the evolution of the processing industry in the Northeast region, in particular to verify if the region suffers from a deindustrialization process. The manufacturing industry in Brazil has undergone a process of deindustrialization, from a 32% share of GDP in 1986 to about 10% in 2014. In the light of this, it is sought to analyze if the manufacturing industry in the Northeast region and its states Followed the trajectory of the national industry, that is, deindustrialization.

China Land Price: 36 City: Northeast Area: Industrial data was reported at 605.921 RMB/sq m in Sep 2021. This records an increase from the previous number of 604.591 RMB/sq m for Jun 2021. China Land Price: 36 City: Northeast Area: Industrial data is updated quarterly, averaging 568.000 RMB/sq m from Dec 2008 (Median) to Sep 2021, with 52 observations. The data reached an all-time high of 605.921 RMB/sq m in Sep 2021 and a record low of 499.000 RMB/sq m in Sep 2009. China Land Price: 36 City: Northeast Area: Industrial data remains active status in CEIC and is reported by Ministry of Natural Resources. The data is categorized under China Premium Database’s Price – Table CN.PF: Land Price: Regional: Key City.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Graph and download economic data for Employment Cost Index: Total compensation for Private industry workers in the Northeast Census Region (CIU2010000000210I) from Q1 2001 to Q2 2025 about Northeast Census Region, ECI, compensation, workers, private industries, private, industry, and USA.

Employment Cost Index: Total compensation for Private industry workers in the Northeast Census Region was 172.33600 Index: Dec 2005=100 in April of 2025, according to the United States Federal Reserve. Historically, Employment Cost Index: Total compensation for Private industry workers in the Northeast Census Region reached a record high of 172.33600 in April of 2025 and a record low of 84.30000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for Employment Cost Index: Total compensation for Private industry workers in the Northeast Census Region - last updated from the United States Federal Reserve on September of 2025.

Survey participants plotted activity points using an interactive mapping tool.The 2012 Northeast Recreational Boater Survey was conducted by SeaPlan, the Northeast Regional Ocean Council (NROC), states’ coastal agencies, marine trade associations composed of many private industry representatives, and the First Coast Guard District. The methodology for the 2012 Northeast Recreational Boater Survey follows a protocol similar to the 2010 Massachusetts Survey with modifications based on the lessons learned and recommendations suggested in the Massachusetts Survey Final Report.The methodology consists of surveying a random sample of selected boat owners throughout the Northeast through a series of monthly online surveys. The surveying period lasted throughout the 2012 boating season (May 1 through October 31, 2012), which was identified by the advisory committee (consisting of NROC and representatives from the recreational boating industry).The project team decided to use a random sample survey approach because it successfully gathered statistically robust economic and spatial data on recreational boating activity by Massachusetts registered boaters during the 2010 boating season. This was also the only approach that would allow for the calculation of statistically robust economic impact estimates for both the states and the region, which was identified as a priority (along withspatial data) by both NROC and the boating industry.

This dataset can be used by coastal planners in ocean planning activities to develop a better understanding of how and where humans use the ocean in the Northeast to inform regional ocean planning and minimize ocean use conflicts. This effort also fulfilled a recommendation from the 2010 Massachusetts Survey to expand the survey’s geographic range to the Northeast Region, allowing for the capture of interstate traffic between states in the Northeast. Furthermore, this dataset can also be used by the boating industry to show the importance of recreational boating to the region and to inform business planning.

Supplemental Information; SURVEY SAMPLING METHODOLOGY - The sample for this survey came from seven databases, including the U.S. Coast Guard Documented Vessel Database and databases of state registered boaters from New York, Connecticut, Rhode Island, Massachusetts, New Hampshire, and Maine. Recreational boaters who owned vessels that met the following criteria were eligible for the survey: * Registration: Currently registered with a state in the Northeast and/or registered as a documented vessel with the U.S. Coast Guard, with a hailing port in the Northeast * Primary Use: Recreational use designation * Length: At least 10 feet in length * Saltwater (if specified; only Maine and New Hampshire required this information) * Location: Located in a “coastal county”. The survey team defined “coastal counties” as those that border saltwater, or those that were highlighted by state coastal planners as likely containing large amount of saltwater boating activity. Based on the 2010 Massachusetts Survey and budgetary considerations, the project team determined an overall sample size that would provide sufficient spatial and economic data for both each state, as well as the whole Northeast. Because of the, at times, large discrepancies between the number of eligible boats in some states, the team decided that certain states with fewer eligible boats should also have a supplemental sample of boats in addition to the pure random sample. To ensure the sample represented the total population of registered boats in the Northeast, the sampling method included considerations of state, geography and size class. Of the 373,766 boats eligible for the survey, the base of randomly sampled boats included 50,000 boats from across all six states. In addition to this base, the survey team sampled 17,772 boats as a supplemental sample, including: 1,772 boats of 26 feet in length or more from across all six states to increase the number of large boats in the sample, and 16,000 additional boats to ensure each state had enough responses for the statistical analysis. These included 10,000 boats from Maine, 2,500 boats from Rhode Island, 2,000 boats from New Hampshire and 1,500 boats from Connecticut. This resulted in a total of 67,772 boaters invited to participate in the study. Boater Recruitment and Response: In the survey invitation package, the survey team also sent invited boaters a questionnaire to verify eligibility to participate in the survey. Eligibility requirements consist of: boat is used in saltwater; boat is used for recreational purposes; and boaters have access to the internet with a working email address. 12,218 boaters responded to the invitation; however only 7,800 of these respondents were found to meet all of the above criteria. From this sample, 4,297 individual boaters completed at least one monthly survey. Surveying Process: The study consisted of six monthly surveys and one end of season survey. The online monthly surveys gathered spatial and economic data on recreational boating activity that occurred during the previous month. The online survey had two parts: 1) a survey with questions about general boating activity during the previous month, and the boater’s last trip of the month (specifically focusing on spending), and 2) a mapping application developed by Ecotrust where boaters plotted their boating route and identified any areas where they participated in activities, such as fishing, diving, wildlife viewing, swimming and relaxing at anchor. The end of season survey gathered a variety of information that could not be gathered in the monthly surveys. The end of season survey contained questions about yearly boating-related expenditures (e.g., dockage, storage, taxes, yearly maintenance), feedback on the survey itself, and general boating-related questions (e.g. whether boaters have taken a boating safety course). Density Analysis: The density analysis described in the following paragraphs was vetted by a technical advisory team consisting of representatives from the Massachusetts Office of Coastal Zone Management (MA CZM), NROC, Maine Coastal Program and Applied Science Associates (ASA) and was based on mapping and analysis protocols from the 2010 Massachusetts Survey. To develop the density layer, vessel routes were drawn in WGS 1984 in the Ecotrust mapping application and were imported into Excel, then ArcMap using a data frame in that coordinate system. Routes from the random sample were selected from that data layer, and the data layer was re-projected into two separate shapefiles, one in UTM 18 and one in UTM 19. A line density analysis using a 250 m square grid cell with a 675 m neighborhood was applied to each shapefile. The 675 m neighborhood was applied to account for inherent user error in the mapping tool. The line density analysis resulted in a raster grid for each UTM zone. Each raster was clipped by the boundaries of its UTM zone, re-projected into the North American Albers Equal Area Conic Projection, and the separate rasters were mosaicked together. At the boundary of the two raster grids there was a line of cells with no data value. This was a result of mosaicking rasters that originated in different coordinate systems. To approximate values in the blank cells, each blank cell was populated by a value from a focal statistics calculation. The focal statistics expression took the mean of all cells in a 4x4 neighborhood around each blank cell. The values were then converted to Z-scores using the raster calculator by taking the log of the density values, subtracting the mean value, and dividing the resulting value by the standard deviation of the value. This layer was clipped again using the NOAA medium resolution shoreline dataset. DATA PROCESSING Processing environment: ArcGIS 10.05, Windows 7 Ultimate SP5, Intel Xeon CPU Process Steps Description 1 Raw routes from mapping application imported into ArcMap 2 Routes from random sample selected using select by attributes query 3 Routes projected into two separate shapefiles (UTM Zones 18 & 19) 4 LINE DENSITY tool in spatial analyst applied to each shapefile using a 250 m square grid with a 675 m neighborhood 5 Resulting rasters clipped to their respective UTM Zones using the EXTRACT BY MASK tool 6 Rasters reprojected to North America Albers Equal Area Conic Projection, using PROJECT tool 7 MOSAIC tool used to merge rasters 8 Focal mean expression (4x4 neighborhood) used to approximate and fill cells with no data at the boundary between mosaicked rasters 9 Raster calculator used to calculated Z-scores ([(Ln(Value))-Mean]/Std. Deviation) 10 Raster clipped by NOAA Medium Resolution Shoreline data using EXTRACT BY POLYGON tool QUALITY PROCESS Attribute Accuracy: The lines used to generate the density grid were derived from a mapping tool used by boaters to reconstruct their boating routes. To ensure that boaters included their round-trip route the mapping applications would send the user an error message asking them to re-plot the route or the program would automatically return the route to the starting point. This application also restricted the scale at which users could draw their routes, reducing the amount of error that could occur from plotting routes at too small a scale. Clipping this layer with a regional ocean shapefile derived from the NOAA medium resolution shoreline dataset excluded route density resulting from routes drawn over land, in freshwater, or outside of northeastern waters. Logical Consistency: None Completeness: Only reported routes from the random sample were included. Routes from the supplemental sample were excluded from this analysis. Route density occurring over land, freshwater areas, or outside northeastern waters was excluded by the final geoprocessing step. Positional Accuracy: The positional accuracy of the routes is dependent on the individual reporting routes through the

Financial overview and grant giving statistics of Northeast Ind Dev Assoc Inc

Financial overview and grant giving statistics of Goodwill Industries of Northeast Iowa Inc.

In 2023, there were approximately **** million households with internet connection in the northeastern region of Thailand. In that same year, around ***** million households across the country had access to internet connection.

Industrial Consumption: Northeast: Metallurgy data was reported at 7,460.280 GWh in 2023. This records an increase from the previous number of 4,442.350 GWh for 2022. Industrial Consumption: Northeast: Metallurgy data is updated yearly, averaging 3,566.735 GWh from Dec 2012 (Median) to 2023, with 12 observations. The data reached an all-time high of 9,547.930 GWh in 2012 and a record low of 3,022.460 GWh in 2017. Industrial Consumption: Northeast: Metallurgy data remains active status in CEIC and is reported by Energy Research Company. The data is categorized under Brazil Premium Database’s Energy Sector – Table BR.RBC098: Electricity Consumption: by Type: Industrial.

Brazil Construction Industry: Total Personal Expenses: 5 Persons or More: Northeast data was reported at 11,811,750.000 BRL th in 2017. This records a decrease from the previous number of 13,304,866.000 BRL th for 2016. Brazil Construction Industry: Total Personal Expenses: 5 Persons or More: Northeast data is updated yearly, averaging 11,811,750.000 BRL th from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 15,724,961.000 BRL th in 2014 and a record low of 3,438,825.000 BRL th in 2007. Brazil Construction Industry: Total Personal Expenses: 5 Persons or More: Northeast data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Construction and Properties Sector – Table BR.EH007: Construction Industry: CNAE 2.0: Total Personal Expenses: by Region and State.

Graph and download economic data for Producer Price Index by Industry: New Nonresidential Building Construction by Contractor Type/Region: Poured Concrete Foundation and Structure Contractors for Northeast Census Region (PCU2364002364002241) from Feb 2014 to Jun 2025 about Northeast Census Region, contractors, cement, nonresidential, buildings, construction, new, PPI, industry, price index, indexes, price, and USA.

Brazil Electricity Consumption: North East Region: Industry data was reported at 2,362.000 GWh in Feb 2025. This records a decrease from the previous number of 2,377.000 GWh for Jan 2025. Brazil Electricity Consumption: North East Region: Industry data is updated monthly, averaging 1,817.000 GWh from Jan 1979 (Median) to Feb 2025, with 554 observations. The data reached an all-time high of 2,575.000 GWh in Oct 2010 and a record low of 526.000 GWh in Apr 1979. Brazil Electricity Consumption: North East Region: Industry data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Global Database’s Brazil – Table BR.RB001: Electricity Consumption. [COVID-19-IMPACT]

Formal Employment: General Industry: Extractive Industries: Balance: Northeast: Alagoas data was reported at -9.000 Unit in Mar 2025. This records a decrease from the previous number of 12.000 Unit for Feb 2025. Formal Employment: General Industry: Extractive Industries: Balance: Northeast: Alagoas data is updated monthly, averaging 10.000 Unit from May 2020 (Median) to Mar 2025, with 59 observations. The data reached an all-time high of 380.000 Unit in Feb 2022 and a record low of -22.000 Unit in Oct 2024. Formal Employment: General Industry: Extractive Industries: Balance: Northeast: Alagoas data remains active status in CEIC and is reported by Ministry of Labor. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBB028: Formal Employment: by Region and State: General Industries: Extractive Industries: Balance.

Industrial Consumption: Northeast: Manufacture Of Rubber & Plastic Material Products data was reported at 1,537.050 GWh in 2023. This records a decrease from the previous number of 1,624.920 GWh for 2022. Industrial Consumption: Northeast: Manufacture Of Rubber & Plastic Material Products data is updated yearly, averaging 1,423.435 GWh from Dec 2012 (Median) to 2023, with 12 observations. The data reached an all-time high of 1,624.920 GWh in 2022 and a record low of 1,305.940 GWh in 2012. Industrial Consumption: Northeast: Manufacture Of Rubber & Plastic Material Products data remains active status in CEIC and is reported by Energy Research Company. The data is categorized under Brazil Premium Database’s Energy Sector – Table BR.RBC098: Electricity Consumption: by Type: Industrial.

Brazil Gross Value Added: Northeast: Pernambuco: Industrial: Manufacturing: Intermediate Consumption data was reported at 58,091.597 BRL mn in 2016. This records an increase from the previous number of 49,926.189 BRL mn for 2015. Brazil Gross Value Added: Northeast: Pernambuco: Industrial: Manufacturing: Intermediate Consumption data is updated yearly, averaging 19,053.175 BRL mn from Dec 2002 (Median) to 2016, with 15 observations. The data reached an all-time high of 58,091.597 BRL mn in 2016 and a record low of 7,499.397 BRL mn in 2002. Brazil Gross Value Added: Northeast: Pernambuco: Industrial: Manufacturing: Intermediate Consumption data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AG014: SNA 2008: Gross Value Added: Northeast: Pernambuco.

China VAI: YoY(Real): Northeast Area(3 Provinces: Liaoning, Jilin, Heilongjiang) data was reported at -7.100 % in Mar 2020. This records a decrease from the previous number of 9.000 % for Dec 2019. China VAI: YoY(Real): Northeast Area(3 Provinces: Liaoning, Jilin, Heilongjiang) data is updated monthly, averaging 1.100 % from Mar 2015 (Median) to Mar 2020, with 51 observations. The data reached an all-time high of 9.000 % in Dec 2019 and a record low of -7.100 % in Mar 2020. China VAI: YoY(Real): Northeast Area(3 Provinces: Liaoning, Jilin, Heilongjiang) data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BE: Value Added of Industry: Monthly.

Contains approximately 608 point locations of Wyoming Industrial and Miscellaneous Use Well Permit Locations (yields greater than 49 gpm) on file with the Wyoming State Engineer's Office (SEO). They range in dates from the early 1900s to 2000, but are located only to the nearest 40 acre parcel. All locational information and attributes were imported from the SEO Well Permits Database stored in a MS Access database.