Italy ISTAT Forecast: Population data was reported at 53.825 Person mn in 2066. This records a decrease from the previous number of 54.087 Person mn for 2065. Italy ISTAT Forecast: Population data is updated yearly, averaging 59.475 Person mn from Dec 2017 (Median) to 2066, with 50 observations. The data reached an all-time high of 60.591 Person mn in 2020 and a record low of 53.825 Person mn in 2066. Italy ISTAT Forecast: Population data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.G003: Population: by Age: Forecast: National Institute of Statistics.

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.

Statistical data about immigration in Italy and related topics. Original data comes from the National Statistical Institute of Italy (ISTAT, dati.istat.it) and has been put in RDF Data Cube format by Linked Open Data Italia association.

This dataset (ISTAT_absolute_poverty_thresholds_2005_2021_V1.xlsx) contains the absolute poverty thresholds for Italy between 2005 and 2021 distributed by ISTAT, by geographical macro-area, household type and municipality type. Together with the dataset, a data report is provided: "Data_report_ISTAT_absolute_poverty_thresholds_IT_2005-2021_V1.pdf" as well as tables from the ISTAT official annual poverty reports ("ISTAT_absolute_poverty_thresholds_IT_from official reports 2005-2021.pdf").

The table contains data on the main variables that describe the habits of citizens towards ICT technologies. The data, extracted from the Multi-purpose household survey - aspects of Istat’s daily life, have been available in historical series since 2016 for the regional level of detail. The continuity of the data is not always guaranteed, due to changes / deletions to the variables detected.

266 Global exporters importers export import shipment records of Istat troponin with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Context

Due to the coronavirus epidemic, and following the measures adopted by the Government to contain it, Istat has implemented a series of actions to ensure the continuity and quality of statistical production even in the emergency situation.

Content

TheThe Italian National Institute of Statistics has reorganized data collection by sustainable acquisition techniques, innovative methodologies and use of data sources; it also provided most appropriate solutions to support statistical production processes, in full protection of workers’ health.

Official statistics are fundamental for measuring the evolution of economy and society; their production and dissemination at the service of institutions, policy-makers, families and businesses, therefore, cannot be stopped, but need to be rethought to be ready to provide the country with all necessary answers, and above all to support and monitor the future country’s recovery.

Reference period: 01/01-04/04, Years 2015-2020. Collected data thanks to Istat Survey Deaths of resident population, that uses administrative source to collect main individual characteristics of deaths, and to processing ANPR (National Resident Population Register) source data for deaths referring to the 2020 year.

Processing data of municipalities (1,689) where ANPR data are considered reliable and migrated in ANPR database before January 1st, 2020.

Record: 1. CODES NUTS2 = Istat code of NUTS2
2. CODES NUTS3 = Istat code of NUTS3 3. CODES_NUTS3_LAU2 = Istat code of LAU2 4. NUTS 2 = Region of residence 5. NUTS 3 = Province of residence 6. LAU 2 = Municipality of residence 7. DATA_INIZIO_DIFF = Date of first dissemination of data in 2020 8. WEEK= Week of death (first considered period, from January 1st to January 11th, is 11 days) 9. AGE CLASS = Age class at the time of death 10. MALES_2015: total male deaths in 2015 11. MALES_2016: total male deaths in 2016 12. MALES_2017: total male deaths in 2017 13. MALES_2018: total male deaths in 2018 14. MALES_2019: total male deaths in 2019 15. MALES_2020: total male deaths in 2020 16. FEMALES_2015: total female deaths in 2015 17. FEMALES_2016: total female deaths in 2016 18. FEMALES_2017: total female deaths in 2017 19. FEMALES_2018: total female deaths in 2018 20. FEMALES_2019: total female deaths in 2019 21. FEMALES_2020: total female deaths in 2020 22. TOTAL_2015: total deaths in 2015 23. TOTAL_2016: total deaths in 2016 24. TOTAL_2017: total deaths in 2017 25. TOTAL_2018: total deaths in 2018 26. TOTAL_2019: total deaths in 2019 27. TOTAL_2020: total deaths in 2020

Acknowledgements

https://www.istat.it

https://www.istat.it/en/archivio/240106

Inspiration

These data also provides most appropriate solutions to support statistical production processes, in full protection of workers’ health.

Please note: for a correct view and use of this dataset it is advisable to consult it at original page on the Grosseto Portal. At the same address there are also, for the enabled datasets, additional access formats, the preview of the visualization via API call, the consultation of the fields in DCAT-AP IT format, the possibility to express an evaluation and comment on the dataset itself.

All resource formats available for this dataset can be downloaded as ZIP packages: inside the package sarà available the resource in the chosen format, complete with all the information on the metadata and the license associated with it.

Polygonal dataset with ISTAT census stations dated to 2011

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

dati ict provincia pubblica-amministrazione regione

Italy ISTAT Forecast: Population: Women data was reported at 27.115 Person mn in 2065. This records a decrease from the previous number of 27.266 Person mn for 2064. Italy ISTAT Forecast: Population: Women data is updated yearly, averaging 30.079 Person mn from Dec 2017 (Median) to 2065, with 49 observations. The data reached an all-time high of 31.144 Person mn in 2017 and a record low of 27.115 Person mn in 2065. Italy ISTAT Forecast: Population: Women data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.G003: Population: by Age: Forecast: National Institute of Statistics.

Istat has released, in shapefile format, the territorial bases for the 1991 census (CENSUS Project). The CENSUS project has created an information layer consisting of the polygons of the census sections resulting from the elaboration of the territorial bases approved by the Italian municipalities and acquired by Istat.

Vengono calcolate le previsioni per genere, anno di previsione, tipo di scenario (centrale, alto, basso), fino all'anno 2051 per la Regione Lombardia

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.

The file "dataset_regression_income.csv" contains a dataset developed in the analysis of inflation heterogeneity for Italian Households in the period 2015-2023.The dataset is the outcome of merging the yearly Household Budget Surveys (HBS) conducted by the Italian National Institute of Statistics (Istat), the Harmonised Index of Consumer Prices (HICP) which is calculated monthly by Istat, according to EU regulations, and the Survey on Households Income and Wealth (SHIW) conducted by Bank of Italy.Mapping price information into consumption decisions and aggregating an individual price index for each household according to a Laspeyres Formula leads to the computation of household-level inflation rates.Furthermore, we compute non-durable equivalent expenditure for each household as a proxy of living standards. The variable is obtained by subtracting durable expenditure from total aggregate expenditure and scaling down by an household equivalent scale (in the benchmark specification, the square root of the household size). The decile distribution of the variable is also computed.Finally, we apply a statistical matching procedure to integrate income information from SHIW data sources. The output is a synthetic dataset containing both expenditure and income information that preserves the joint distribution and correlation structures of the original datasets.The file "ISTAT_MFR_HBS_EUR.csv" is a conversion table that maps ECOICOP items to HBS expenditure voices.

ISTAT Forecast: Foreign Exchange Rate: US Dollar data was reported at 1.230 EUR/USD in 2018. This records an increase from the previous number of 1.130 EUR/USD for 2017. ISTAT Forecast: Foreign Exchange Rate: US Dollar data is updated yearly, averaging 1.180 EUR/USD from Dec 2013 (Median) to 2018, with 6 observations. The data reached an all-time high of 1.330 EUR/USD in 2014 and a record low of 1.110 EUR/USD in 2016. ISTAT Forecast: Foreign Exchange Rate: US Dollar data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.M007: Foreign Exchange Rate: Forecast: National Institute of Statistics.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly

Sampling procedure

Sample size:

Demographic Report 1971-2016 Municipality of Brescia ISTAT data processing

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.

AbstractIn Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies. Methods For a given locality, year, and cause of death, the SMR is the ratio between the observed number of deaths (Om) and the number of expected deaths (Em): SMR = Om/Em (1) where Om should be an available observational data and Em is estimated as the weighted sum of age-specific population size for the given locality (ni) per age-specific death rates of the reference population (MRi): Em = sum(MRi x ni) (2) MRi could be provided by a public health organization or be estimated as the ratio between the age-specific number of deaths of reference population (Mi) to the age-specific reference population size (Ni): MRi = Mi/Ni (3) Thus, the value of Em is weighted by the age distribution of deaths and population size. SMR assumes value 1 when the number of observed and expected deaths are equal. Following eqns. (1-3), the SMR was computed for single years of the period 2009-2018 and for single cause of death as defined by the International ICD-10 classification system by using the following data: age-specific number of deaths by cause of reference population (i.e., Mi) from the Italian National Institute of Statistics (ISTAT, (http://www.istat.it/en/, last access: 26/01/2022)); age-specific census data on reference population (i.e., Ni) from ISTAT; the observed number of deaths by cause (i.e., Om) from ISTAT; the age-specific census data on population (ni); the SMR was estimated at three different level of aggregation: municipal, provincial (equivalent to the European classification NUTS 3) and regional (i.e., NUTS2). The SMR was also computed for the broad category of malignant tumors (i.e. C00-C979, hereinafter cancer macro-type C), and for the broad category of malignant tumor plus non-malignant tumors (i.e. C00-C979 plus D0-D489, hereinafter cancer macro-type CD). Lower 90% and 95% confidence intervals of 10-year average values were computed according to the Byar method.