Background Widespread scepticism persists on the use of the Under-Privileged Area (UPA8) score of Jarman in distributing supplementary resources to so-attributed 'deprived' UK general practices. The search for better 'needs' markers continues. Having already shown that Council Tax Valuation Band (CTVB) is a predictor of UK GP workload, we compare, here, CTVB of residence of a random sample of patients with their respective 'Jarman' scores. Methods Correlation coefficient is calculated between (i) the CTVB of residence of a randomised sample of patients from an English general practice and (ii) the UPA8 scores of the relevant enumeration districts in which they live. Results There is a highly significant correlation between the two measures despite modest study size of 478 patients (85% response). Conclusions The proposal that CTVB is a marker of deprivation and of clinical demand should be examined in more detail: it correlates with 'Jarman', which is already used in NHS resource allocation. But unlike 'Jarman', CTVB is simple, objective, and free of the problems of Census data. CTVB, being household-based, can be aggregated at will.

Background All current UK indices of socio-economic status have inherent problems, especially those used to govern resource allocation to the health sphere. The search for improved markers continues: this study proposes and tests the possibility that Council Tax Valuation Band (CTVB) might match requirements. Presentation of the hypothesis To determine if there is an association between CTVB of final residence and mortality risk using the death registers of a UK general practice. Testing the hypothesis Standardised death rates and odds ratios (ORs) for groups defined by CTVB of dwelling (A – H) were calculated using one in four denominator samples from the practice lists. Analyses were repeated three times – between number of deaths and CTVB of residence of deceased 1992 – 1994 inclusive, 1995 – 1997 inc., 1998 – 2000 inc. In 856 deaths there were consistent and significant differences in death rates between CTVBs: above average for bands A and B residents; below average for other band residents. There were significantly higher ORs for A, B residents who were female and who died prematurely (before average group life expectancy). Implications of the hypothesis CTVB of final residence appears to be a proxy marker of mortality risk and could be a valuable indicator of health needs resource at household level. It is worthy of further exploration.

Net additions to dwelling stock within the area measure the absolute change in stock between one year and the next. Each self-contained unit is counted as a dwelling. This includes:

New builds Conversions Changes of use (e.g., residential house to office) Demolitions

Net additions are calculated as: 'New build completions' + 'Conversions' + 'Change of use' + 'Other net gains' - 'Demolitions'

This metric does not include new delivery and acquisitions to the existing stock. As this is an absolute value for each area, care should be taken when comparing with other areas.

A dwelling can consist of:

One self-contained household space Two or more non self-contained household spaces at the same address

Special cases:

Hostels with more than one bed space that are not managed are counted as one self-contained dwelling (e.g., single council tax payer). Ancillary dwellings such as 'granny annexes' should be included if they are self-contained and access is not shared by outside residents.

Sources of net additions data:

Housing Flows Reconciliation (HFR) Greater London Authority (GLA) Regional Assembly joint returns

Historical data collection:

2000-01 to 2003-04: All local authorities submitted data to CLG via HFR form. 2004-05 to 2008-09: CLG worked with Regional Planning bodies in the south and midlands on joint data returns to ensure consistency between regional Annual Monitoring Reports (AMRs) and central government figures. Post-2010: After abolition of Regional Planning Bodies, all regions except London returned to HFR submissions from 2009-10. London data is supplied by the GLA.

New build data for net additions is more comprehensive due to:

Longer collection period Use of multiple evidence sources (site visits, council tax records, planning databases, building control records, etc.) Capturing elements missing from quarterly P2 and AIR collections (which rely only on building control reported completions)

This metric was formerly published as NI 154.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Council Tax database, including addresses, characteristics and attributes of properties. Property attribute and transactions data underpin the information base necessary for the VOA to value properties correctly for property tax (Non-Domestic Rates and Council Tax) and for valuation work carried out for other public sector clients (e.g. Inheritance Tax and Capital Gains Tax). By statute non-domestic properties are revalued every 5 years and then appeals and material changes of circumstances are dealt with thereafter. There is no single source of information and the valuation process involves bringing together various data sources. However the Form of Return is a key compenent to allow VOA to establish a fair market rent for properties, which is the basis of rating assessments. Updated: Continuously as and when properties are built, altered or removed and when occupations are re-organised

The count of all dwellings that are charged Council Tax and the number of those that are classed as second homes, for August 2021.

Houseboat and caravan dwellers form part of our local housing market. This dataset aims to bring together some information to help us see the scale of the issue in our local area. This includes Cambridge East Cambridgeshire Fenland Huntingdonshire South Cambridgeshire Forest Heath St Edmundsbury Peterborough This data is simply a starting point, being launched in April 2017, and at this stage is looking to bring existing data together to shed some light on the scale of this part of our housing market.There are two source of data: Council Tax records identifying the number of houseboat dwellers in 2015 and 2016. The government data is published in response to an external request for information seeking a record of the number of households who are boat dwellers in each local authority in England. They note that: "Caseworkers use Dwelling Type “TH” and Dwelling Group “72” when they identify a houseboat, captured as part of the property attributes on the VOA administrative database. Total counts for each local authority district in England are provided. Counts are rounded to the nearest 10. However, counts of zero are reported as “0” and counts between one and four (inclusive) are reported as negligible and denoted by “-“. Totals may not sum due to rounding." As the figures are rounded to the nearest 10, we can see this only gives an indication of the number of houseboats in each local authority area; in addition, a local correspondent informs us that this is "not an accurate way of calculating the numbers of houseboats since houseboats are not liable to pay council tax if the land they are moored on is not a hereditment". A web search for local marinas and moorings in the local area, undertaken in April 2017. We are very pleased to have now uploaded geo-coded data on the location of some of the marinas and moorings across the area in 2017, which has enabled us to produce a local map. We continue to seek new and improved sources of data, and updates to the goverment figures, as time progresses.

Number of dwellings by Council Tax band, and percentage of dwellings in each Council Tax band.

Number of dwellings by Council Tax band. Higher geographies are aggregated from 2011 Data Zones.

United Kingdom State Support: BU:MO: Council Tax Benefit data was reported at 11.000 % in 2017. This records an increase from the previous number of 10.000 % for 2015. United Kingdom State Support: BU:MO: Council Tax Benefit data is updated yearly, averaging 11.000 % from Mar 2011 (Median) to 2017, with 6 observations. The data reached an all-time high of 13.000 % in 2011 and a record low of 10.000 % in 2015. United Kingdom State Support: BU:MO: Council Tax Benefit data remains active status in CEIC and is reported by Department for Work and Pensions. The data is categorized under Global Database’s UK – Table UK.H026: Contribution of State Support: Benefit Unit by Family Type.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of assessed property values for each zip code in Council Bluffs, Iowa. It's important to understand that assessed property values can vary greatly and can change yearly.

United Kingdom State Support: BU:FO: Council Tax Benefit data was reported at 11.000 % in 2017. This stayed constant from the previous number of 11.000 % for 2015. United Kingdom State Support: BU:FO: Council Tax Benefit data is updated yearly, averaging 11.500 % from Mar 2011 (Median) to 2017, with 6 observations. The data reached an all-time high of 12.000 % in 2013 and a record low of 11.000 % in 2017. United Kingdom State Support: BU:FO: Council Tax Benefit data remains active status in CEIC and is reported by Department for Work and Pensions. The data is categorized under Global Database’s UK – Table UK.H026: Contribution of State Support: Benefit Unit by Family Type.

Exploring Potential Tax and Water Liens in NYC

Investigating Geographic Distribution and Effects of Local Policies

By data.world's Admin [source]

About this dataset

This dataset captures properties in New York City that have tax and/or water liens potentially eligible to be included in the next lien sale. Explore the city's fiscal landscape with information about borough, lot, tax class code, building classes, community board, council district, house number street name and zip code. This data is updated monthly with new liens being added from the most current month back to 12 months prior. By analyzing this data you can gain greater insight into New York City’s financial conditions over time as well as how this affects individual properties throughout the city. This data is provided by the New York City open data portal is subject to terms of use outlined on its website so please refer to it for any additional information regarding usage rights

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How to use the dataset

This data is sourced from New York City's Open Data portal. By exploring this dataset you can search for properties with possible tax and/or water liens located in a particular area or neighborhood or by a specific attribute such as the house number or street name. You can also take a look at particular subsections of potential eligible lien sale records over time – for example you could look at all potential water debt liens only during a certain month – to get some more specific insights into what tax and water liens may be available at certain points in time. To use this dataset please note the following important tips: • Start by familiarizing yourself with each column’s field meaning (using our table above); • When searching for records use quotation marks if you are looking up something which is two words (e.g “construction”) ;
• Use an underscore _for replacing spaces if necessary e.g “west_village”;
• Be aware that Boroughs are referenced by their full names (e.g Manhattan, Queens, etc);
• If using wild cards (*) make sure not to put them on either side of your query - e.g instead of Lastname * use Lastname*.
We hope this guide was helpful and good luck exploring!

Research Ideas

• Real Estate Investment Analysis: Create a platform or tool using this dataset to assist individuals looking to invest in properties with potential tax and water liens. The platform/tool should provide insights into the best locations for purchasing real estate based on location, tax class code, building class and council district data points from this dataset.
• Tax Foreclosure Notifications: Use this dataset to create an automated notification system which informs registered users when a property they are interested in is coming up for sale with a lien in the next sale date.
• Local Planning Solutions: Leverage data from this dataset to identify areas where there might be concentration of properties with tax liens that could potentially benefit from local planning solutions such as community grants, affordable housing initiatives etc.. This could help municipalities deploy resources more effectively towards restoring distressed properties instead of letting them slip out of their control via foreclosure at lien sales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: tax-lien-sale-lists-1.csv | Column name | Description | |:---------------------|:-----------------------------------------------------------------| | Month | The month in which the lien sale is eligible. (String) | | Borough | The borough in which the property is located. (String) | | Lot | The lot number of the property. (Integer) | | Tax Class Code | The tax class code of the property. (Integer) | | Building Class | The building class of the property. (String) | | Community Board | The community board in which the property is located. (Integer) | | Council District | The council district in which the property is located. (Integer) | | House Number | The house number of the property. (Integer) | | Street Name | The street name of the property. (String) | | Zip Code | The zip code of the p...

This dataset provides information for Cambridgeshire, West Suffolk and Peterborough, showing the age of homes as provided by the Valuation Office Agency, based on council tax records. The first file of data is specifically focussed on identifying homes with solid walls, as part of the Warm Homes project, so the data has been grouped to highlight the small areas (known as Lower Super Output Areas) where homes fall into three specific age bands: Built before 1929 Built between 1930 to 1939 Built between 1945 and 2015 Some build dates are unknown, there are also counted in the data. Homes built before 1929 all tend to have solid walls, as cavity walls had not been invented. Homes built between 1930 and 1939 may or may not have solid walls, in the period when cavity walls were becoming more popular but not yet "the norm". Few homes were built 1939 to 1945. On the whole, homes built since 1945 tend to have cavity walls. So this data set helps us identify where we can find homes which are most likely to have solid walls, and therefore where a solid wall insulation project might want ot focus its attention. The second data file is more detailed and adds further information on the date homes were built, grouped into ten-year bands, and adds the number of homes in each LSO which falls into council tax bands A to H as well.