Information about the Department of Primary Industries (formerly called Department of Agriculture and Fisheries). Find out more about the department by visiting https://www.daf.qld.gov.au.

Complaints Reporting received by Primary Industries and Regions South Australia for the period 2011-12 to 2023-24 for annual reporting purposes.

The Strategic Plan for the Department of Primary Industries, formerly known as the Department of Agriculture and Fisheries, sets a clear direction for working towards a productive and profitable agriculture, fisheries and forestry sector.

Annual Reports of the Department of Primary Industries, formerly known as the Department of Agriculture and Fisheries. Produced at the end of each financial year, these reports demonstrate our achievements and provide information about our corporate governance, financial performance, organisational development and future directions.

Description

Estimates of the markup for the Primary Foods industry (comprised of agriculture, hunting, fishing, and logging) using the De Loecker et al. (2020) methodology. Instead of using micro-based, firm-level data, we calculate the markups using aggregate, macro-data. The database contains information on 170 countries for the years 1995 - 2015.

Our sources of data are two-fold; the first is the EORA input-output database, and the second is the UN FAO-Stat database. Our paper Rodriguez del Valle and Fernández-Vázquez (2024), explains in more detail the estimation technique based on Generalized Maximum Entropy employed to derive these estimates.

The dataset can be used to explore and research a myriad of topics, including the impact globalization has on markups, the role of institutional quality, and even climate. We have found strong evidence that the percentage share of value added required for production originating from abroad is significantly connected to lower markups. We have also found compelling empirical evidence that institutional quality can impact the evolution of markups.

Please note that we make a strong assumption that each industry is produced by one "firm" consistent with input-output theory. For this industry, we believe the assumption will not bias results too strongly, particularly when analyzing developing countries. Results may be biased in countries where large farms exist.

Categories

Industrial Organization, Macroeconomics, Microeconomics, Agriculture Industry

Acknowledgements & Source

Adrian Rodriguez del Valle,Esteban Fernandez-Vazquez

Institutions

Universidad de Oviedo

Data Source

Please don't forget to upvote if you find this useful.

The dataset contains year- and state-wise compiled data on the value of industries in major industries by their principal characteristics such as number of factories, employment, wages, invested capital, capital formation, input, output, depreciation and value added, etc.

Note:

The Annual Survey of Industries (ASI) provides data on various vital aspects of the registered factories for use in the estimation of national income, studies of industrial structure and policy formulation.

Get data on Ontario gross domestic product (GDP) by manufacturing industries. The GDP is a monetary measure of the value of all final goods and services produced in a period. This dataset shows Ontario’s GDP by manufacturing industries, including: * food, beverage and tobacco * chemical and petroleum products * primary metal products * fabricated metal products * machinery * electrical and electronic products * transportation equipment * paper products and printing * plastic and rubber products * other manufacturing

Access API

Metadata Portal Metadata Information

Contractors Reporting Primary Industries and Regions SA for the period 2017-18 to 2023-24 for annual reporting purposes

Consultants Reporting received by Primary Industries and Regions South Australia for annual reporting purposes.

GDP from Agriculture in Maldives decreased to 2840.40 MVR Million in 2024 from 4584 MVR Million in 2023. This dataset provides - Maldives Gdp From Agriculture- actual values, historical data, forecast, chart, statistics, economic calendar and news.

A list of all Impact analysis statements for the Department of Primary Industries (formerly the Department of Agriculture and Fisheries). Under the Queensland Government Better regulation policy (the policy), agencies are required to publish impact analysis statements (the statements) for regulatory proposals, following final approval by the relevant decision-making body. The policy outlines the Queensland Government requirements for the development and review of regulations and a statement is an assessment of a regulatory proposal under the policy. On this page, we will publish links to our statements for each calendar year.

GDP from Agriculture in China decreased to 11712.80 CNY Hundred Million in the first quarter of 2025 from 91413.90 CNY Hundred Million in the fourth quarter of 2024. This dataset provides - China Gdp From Agriculture- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Tagging programmes have been used to provide information on fish and fisheries to central government policy makers in New Zealand for many years. A wide variety of species have been the subject of such studies, including finfish, shellfish and rock lobsters. In New Zealand, the Ministry for Primary Industries (formerly the Ministry of Fisheries) has funded these programmes to aid with fisheries research and stock assessment. Data from these programme are held in the "tag" database, from which the data in this dataset are sourced.
Citation: Ministry for Primary Industries (2014). New Zealand research tagging database. Southwestern Pacific OBIS, National Institute of Water and Atmospheric Research (NIWA), Wellington, New Zealand, 411926 records.Online: http://nzobisipt.niwa.co.nz/resource.do?r=mpi_tag Released on November 5, 2014.Bibliographic Citations: http://www.fish.govt.nz/NR/rdonlyres/E827F55F-0779-4599-8223-92538AC61725/0/research_database_tag_2011.pdf_Item Page Created: 2016-06-09 02:17 Item Page Last Modified: 2025-04-05 18:54Owner: NIWA_OpenDataMPI_tagNo data edit dates availableFields: id,type,modified,language,license,rightsHolder,accessRights,bibliographicCitation,institutionCode,collectionCode,datasetName,ownerInstitutionCode,basisOfRecord,dynamicProperties,occurrenceID,catalogNumber,occurrenceRemarks,individualCount,sex,lifeStage,occurrenceStatus,samplingProtocol,eventDate,startDayOfYear,year,month,day,fieldNumber,waterBody,country,stateProvince,county,locality,minimumDepthInMeters,maximumDepthInMeters,decimalLatitude,decimalLongitude,geodeticDatum,coordinateUncertaintyInMeters,footprintWKT,scientificNameID,scientificName,kingdom,phylum,class,order_,family,genus,subgenus,specificEpithet,infraspecificEpithet,scientificNameAuthorship,FID

Forecasts and trends in Queensland agricultural, fisheries and forestry value chain, from the Department of Primary Industries (DPI) data platform DataFarm and from publications AgTrends and previously Prospects.

The Rural Economic Development team within the Department of Agriculture and Fisheries delivers its services and operations through three regions that collectively cover the state - North, Central and South. This dataset shows these region boundaries and their area in hectare.Updates16-Mar-2020: South-East region and South region merged into a single region (known now as South).22-Feb-2021: Minor edit to match LGA boundaries dataset

Manufacturing industries, annual 21 principal statistics (revenues, expenses, salaries, employment, stocks, etc.), by North American Industry Classification System (NAICS), total and 3-digit level.

About this dataset

Context

The dataset tabulates the Industry town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Industry town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Industry town was 801, a 0.50% increase year-by-year from 2022. Previously, in 2022, Industry town population was 797, an increase of 0.63% compared to a population of 792 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Industry town increased by 16. In this period, the peak population was 928 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Industry town is shown in this column.
• Year on Year Change: This column displays the change in Industry town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry town Population by Year. You can refer the same here

Abstract

[x[This dataset was superseded by GIP AssetList Database v1.3 20150212

GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

on 12/2/2015]x]

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains the spatial and non-spatial (attribute) components of the Gippsland bioregion Asset List as two .mdb files, which are readable as an MS Access database or as an ESRI Personal Geodatabase.

Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. All reports received associated with the WAIT process for Gippsland are included in the zip file as part of this dataset.

Elements are initially included in the preliminary assets database if they are partly or wholly within the bioregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Gippsland bioregion are found in the "AssetList" table of the database. In this version of the database only M1 has been assessed.

Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "AssetList_database_GIP_v1p2_20150130.doc", located in the zip file as part of this dataset.

The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset.

Detailed information describing the database structure and content can be found in the document "AssetList_database_GIP_v1p2_20150130.doc" located in the zip file.

Some of the source data used in the compilation of this dataset is restricted.

Purpose

[x[*****THIS IS NOT THE CURRENT ASSET LIST*****

This dataset was superseded by GIP AssetList Database v1.3 20150212

GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

on 12/2/2015

THIS DATASET IS NOT TO BE PUBLISHED IN ITS CURRENT FORM]x]

Dataset History

This dataset is an update of the previous version of the Gippsland asset list database: "Gippsland Asset List V1 20141210"; ID: 112883f7-1440-4912-8fc3-1daf63e802cb, which was updated with the inclusion of a number of additional datasets from the Victorian Department of the Environment and Primary Industries as identified in the "linkages" section and below.

Victorian Farm Dam Boundaries

https://data.bioregionalassessments.gov.au/datastore/dataset/311a47f9-206d-4601-aa7d-6739cfc06d61

Flood Extent 100 year extent West Gippsland Catchment Management Authority GIP v140701

https://data.bioregionalassessments.gov.au/dataset/2ff06a4f-fdd5-4a34-b29a-a49416e94f15

Irrigation District Department of Environment and Primary Industries GIP

https://data.bioregionalassessments.gov.au/datastore/dataset/880d9042-abe7-4669-be3a-e0fbe096b66a

Landscape priority areas (West)

West Gippsland Regional Catchment Strategy Landscape Priorities WGCMA GIP 201205

https://data.bioregionalassessments.gov.au/datastore/dataset/6c8c0a81-ba76-4a8a-b11a-1c943e744f00

Plantation Forests Public Land Management(PLM25) DEPI GIP 201410

https://data.bioregionalassessments.gov.au/datastore/dataset/495d0e4e-e8cd-4051-9623-98c03a4ecded

and additional data identifying "Vulnerable" species from the datasets:

Victorian Biodiversity Atlas flora - 1 minute grid summary

https://data.bioregionalassessments.gov.au/datastore/dataset/d40ac83b-f260-4c0b-841d-b639534a7b63

Victorian Biodiversity Atlas fauna - 1 minute grid summary

https://data.bioregionalassessments.gov.au/datastore/dataset/516f9eb1-ea59-46f7-84b1-90a113d6633d

A number of restricted datasets were used to compile this database. These are listed in the accompanying documentation and below:

• The Collaborative Australian Protected Areas Database (CAPAD) 2010

• Environmental Assets Database (Commonwealth Environmental Water Holder)

• Key Environmental Assets of the Murray-Darling Basin

• Communities of National Environmental Significance Database

• Species of National Environmental Significance

• Ramsar Wetlands of Australia 2011

Dataset Citation

Bioregional Assessment Programme (2015) GIP AssetList Database v1.2 20150130. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/6f34129d-50a3-48f7-996c-7a6c9fa8a76a.

Dataset Ancestors

• Derived From Flood Extent 100 year extent West Gippsland Catchment Management Authority GIP v140701

• Derived From Surface Water Economic Entitlements GIP 20141219

• Derived From West Gippsland Regional Catchment Strategy Landscape Priorities WGCMA GIP 20121205

• Derived From Irrigation District Department of Environment and Primary Industries GIP

• Derived From Surface Water and Groundwater Entitlement Data with Volumes - DEPI Regs Cat6 Victoria 20141218

• Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From Victorian Water Supply Protection Areas

• Derived From National Groundwater Information System (NGIS) v1.1

• Derived From Birds Australia - Important Bird Areas (IBA) 2009

• Derived From Southern Rural Water SW Locations with BOM Regulations Category 6 Volumes Gippsland 20150430

• Derived From Gippsland Project boundary

• Derived From Victorian Groundwater Management Areas

• Derived From Plantation Forests Public Land Management(PLM25) DEPI GIP 201410

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)

• Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only)

• Derived From Surface Water Entitlement Locations Gippsland Southern Rural Water 20141218

• Derived From Ramsar Wetlands of Australia

• Derived From National Groundwater Information System Victorian Extract (2014-03-21)

• Derived From GEODATA TOPO 250K Series 3

• Derived From Groundwater Licences Entitlement Volume To Bores Vic DEPI 20141021

• Derived From Groundwater Economic Elements Gippsland 20141120

• Derived From Commonwealth Heritage List Spatial Database (CHL)

• Derived From Potential Groundwater Dependent Ecosystems for West Gippsland Catchment Management Authority

• Derived From Victorian Biodiversity Atlas flora - 1 minute grid summary

• Derived From Unreg surface water licences DELWP Gippsland 20150301

• Derived From National Heritage List Spatial Database (NHL) (v2.1)

• Derived From Gippsland Basin bioregion Asset List v01 - 20141210

• Derived From Victorian Farm Dam Boundaries

• Derived From Gippsland Basin bioregion Preliminary Assessment Extent (PAE)

• Derived From [Victoria Regional CMA - Water Asset Information Tool - WAIT

Documents relating to disaster management in the Queensland agricultural sector, including fisheries and forestry. Our Disaster Management Plan outlines the roles and responsibilities of the department in disaster operations and disaster management, and details how we will prevent, prepare for, respond to and recover from disasters. We lead the Queensland Government's efforts to prevent, respond to and recover from pests and diseases that threaten agriculture. A response to this type of emergency may be entirely separate from a state disaster response, and may entail activating specific emergency response plans relative to the pest or disease. This plan touches briefly on these kinds of responses.