This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.

Purpose:

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

A dataset of car tax calculations for company cars by operating cycle, manufacturer, model, and derivative.

Abstract copyright UK Data Service and data collection copyright owner. One of the most important series of medieval and early modern records of central government in the Public Record Office is the collection of tax records with the reference E 179. It includes all the surviving detailed records of taxation of lay people in England from about 1190 to 1690, well over 30,000 in all, covering a variety of taxes levied by the monarchs. The records comprise a wide variety of types of document, from summaries of accounts, exemptions, abatements, petitions, receipts, inquisitions and schedules of arrears to long, detailed assessments giving the names of taxpayers and the sums with which they were charged. As well as being a prime source for the history of taxation, E 179 records are used for a wide variety of other purposes by social, economic and local historians, historical geographers and others. Before 1995 the documents in the collection had never been systematically examined, and accurate information about their date, type and tax never recorded, so the catalogue used by researchers to access them was woefully inadequate. From 1995, as part of the Records of Central Government Taxation Project, work was done on fourteen counties, and this project was begun to make a comprehensive and detailed examination and re-appraisal of the records in respect of six further counties (Cambridgeshire, Huntingdonshire, Bedfordshire, Buckinghamshire, Berkshire and Oxfordshire), and as before to record the information in a database and output the data in several different formats, to facilitate the use of the records by researchers in a number of fields. Within each county the procedure was to systematically examine the surviving documents in chronological order, as far as it was already known, recording the details discovered about them in a database. The first step was to examine each one to establish and record its physical characteristics: the material of which it was made; its format, whether a roll, a file, a volume or one of the large number of other lesser document types; the number of membranes, pages or folios it contained. Next, the attempt was made to establish as far as possible the tax which led to its creation, using a list of taxes already created as part of the database during an earlier stage of the project, but which was added to or modified if the document provided new information about a tax. Finally, a repertory of all places mentioned in the document, arranged in their hierarchy as given, was compiled, and included where appropriate corporate bodies and other units other than places which were the units of taxation.

If you download/use the data set I'd appreciate an up vote, cheers.

Updated

Scraped data of used cars listings. 100,000 listings, which have been separated into files corresponding to each car manufacturer. I collected the data to make a tool to predict how much my friend should sell his old car for compared to other stuff on the market, and then just extended the data set. Then made a more general car value regression model.

previous version

Picked two fairly common cars on the British market for analysis (Ford Focus and Mercedes C Class). The hope is to find info such as: when is the ideal time to sell certain cars (i.e. at what age and mileage are there significant drops in resale value). Also can make comparisons between the two, and make a classifier for a ford or Mercedes car. Can easily add more makes and models, so comment for any request e.g. if you want a big data set of all Mercedes makes and models.

Content

The cleaned data set contains information of price, transmission, mileage, fuel type, road tax, miles per gallon (mpg), and engine size. I've removed duplicate listings and cleaned the columns, but have included a notebook showing the process and the original data for anyone who wants to check/improve my work.

Inspiration

It'd be cool to have some insights and visualisations of the data. Also, am open to ideas on how to expand the data set.

Abstract copyright UK Data Service and data collection copyright owner. The New Earnings Survey (NES) is an annual survey of the earnings of employees in Great Britain. Its primary purpose is to obtain information about the levels, distribution and make-up of earnings, and for the collective agreements that cover them. The NES is designed to represent all categories of employees in businesses of all kinds and sizes. It provides a large amount of information on earnings and hours (including bonuses, overtime, etc) as well as industry information derived from the Inter-Departmental Business Register. It provides no information on personal characteristics of the employee apart from age and gender. Most variables are collected each year, although a few additional questions asked each year may or may not be asked in other years. The earnings, hours of work and other information relate to a specified week in April of each year. The NES sampling frame is mainly supplied by Inland Revenue records. It is based largely on a one per cent sample of employees who are members of Pay-As-You-Earn (PAYE) income tax schemes. The PAYE sample is supplemented by data provided by large employers, using extracts from their payroll systems. A survey form is sent to employers, and completion is compulsory under the Statistics of Trade Act 1947. Some large businesses make automatic submissions direct from their electronic records. Certain categories of employees are not selected: for example the Armed Forces, those employed in Enterprise Zones, private domestic service workers, occupational pensioners, non-salaried directors, those employed oversees, those working for their spouses, and clergymen holding pastoral appointments. The NES was replaced by the Annual Survey of Hours and Earnings (UK Data Archive SN 6689) in 2004. Further information on the NES can be found on the Office for National Statistics' (ONS) New Earnings Survey web page. There are a number of issues and inconsistencies associated with the NES data. Users are advised to read the documentation carefully before using the dataset. For example, ONS advise for safety reasons that only data from 1998 onwards should be used because 1998 was the first year that annual earnings were validated properly and published. Geographical references: postcodes The postcodes available in these data from 1996 are pseudo-anonymised postcodes. The real postcodes are not available due to the potential risk of identification of the observations. However, these replacement postcodes retain the inherent nested characteristics of real postcodes, and will allow researchers to aggregate observations to other geographic units, e.g. wards, super output areas, etc. In the dataset, the variable of the replacement postcode is 'new_PC'. Main Topics: The NES collects the following data for employees in all industries and occupations and for the major national collective agreements:levels, distributions and make-up of earningshours workedindustryoccupationplace of workgender age Simple random sample One per cent sample of individuals from National Insurance records

The Government is releasing public data to become more transparent and foster innovation. Some of this data was available before, but data.gov.uk brings it together in one searchable website. Making this data easily available means it will be easier for people to make decisions and suggestions about government policies based on detailed information. Hear more about the Government's Transparency agenda from the Prime Minister in this video. There are datasets available from all central government departments and a number of other public sector bodies and local authorities. Is data just public information? Not really. From data.gov.uk, you can access the raw data driving government forward. This can then be used by people to build useful applications that help society, or investigate how effective policy changes have been over time. General public information - such as how to find out if you are entitled to tax credits, or how to tax your car - can be found at gov.uk. You can use the data in all sorts of ways. This may be simply to analyse trends over time from one policy area, or to compare how different parts of government go about their work. Technical users will be able to create useful applications out of the raw data files, which can then be used by everyone. data.gov.uk provides a mini-site of guidance for publishers, including step-by-step process for including your data on data.gov.uk. Please see: Data.gov.uk is a key part of the Government's work on Transparency and Data. The data.gov.uk implementation is being led by the Data team in the Cabinet Office, working across government departments to ensure that data is released in a timely and accessible way. This work is being supported by Sir Tim-Berners Lee & Professor Nigel Shadbolt. There are a number of technical partners involved in the project to date. These include the CKAN, which runs the catalogue at data.gov.uk/data as well as a growing number of open data registries around the world. It is a project originally created by the Open Knowledge Foundation to make it easy to find, share and reuse open content and data. The CKAN software provides a web interface, programmer's API, feeds notifying of changes, and a browsable history of all changes. The API is documented here: http://data.gov.uk/datametadata-api-docs. There are a number of ways of getting involved in the project, dependent on your background or interest. For example: If you wish to get involved in working with data you can check this very brief primer, you can also check out organisations such as the Open Data Institute and the Open Knowledge Foundation. To find out technical details about the setup of data.gov.uk go here. Hear more about the Government's Transparency agenda from the Prime Minister.

The excel file contains a row per subject who undertook the experiment. This includes the values they entered for each of the four elements of the main incentivised choice within the experiment, the treatment the subject was randomly allocated to, derived measures as to the nature of their compliant (or non-compliant) behaviour and timings associated with each of the stages of the experiment.There is additional data in relation to the classification of their behaviour in the experiment.The primary research questions were to see if compliance would be reduced in treatments were incorrect information was used to pre-populate tax forms compared to conditions of no or correct information and which, if any, of a series of prompts might be able to improve levels of compliance.Good tax design and administration are central to the functioning of the economy. Taxes are important determinants of economic behaviour, and good implementation can significantly increase economic and social welfare. The role of the Tax Administration Research Centre is to deliver research that enhances tax policy and provides lasting benefit to the economy. There are many research tools that can contribute to this goal but the greatest success will be achieved by combining a range of research methodologies and disciplines. The Centre will unite researchers from two institutions with distinguished reputations for research into tax administration and tax design. Complementary abilities and methodologies will be brought together to address a wide range of intersecting research projects. The research methodologies will include economic modelling, econometric analysis, experimentation, numerical simulation, and qualitative analysis. In undertaking its work the Centre will make extensive use of the HMRC/HMT Datalab to permit innovative empirical work to be undertaken. Some examples of the research projects to be conducted at the Centre are: Risk-based auditing and taxpayers' responses will investigate the reaction of taxpayers to audits, and how this will change the pattern of compliance behaviour. The project will study whether taxpayers learn about the audit strategy over time, and how a risk-based strategy should be updated to take this into account. The project will link with laboratory experiments on compliance and with research on the role of tax advisers. The results will increase the return on resources allocated to auditing. Decomposing the elasticity of taxable income will determine how the response of individuals to taxes summarised by the "elasticity of taxable income" can be separated into the channels through which individuals respond (e.g. reduced work effort, increased pension contributions or charitable contributions, moving income abroad, taking income in other forms). The results will enable greater focus of tax interventions and improved design of tax structure. Consequences of pre-population will study the implications of pre-populated tax returns for compliance. If the pre-populated form shows an income level below actual income this might convey an impression to the taxpayer that they can successfully evade. The research will implement an experiment that randomises the allocation of pre-populated returns. The outcome will advise on how best to proceed with the implementation of pre-population. Large business (Intermediaries) relationship with HMRC will use qualitative depth interviews address the extent to which new initiatives have altered working practices in intermediary firms and their clients' businesses, the HMRC understanding of tax avoidance practices, and the appropriateness of current policy strategies currently. This will enhance understanding of the effects of HMRC operational policy and improve administration. Understanding the determinants of customer experience will link HMRC survey data on customer experience with objective measures of service delivery standards, third-party information, and tax return data in Datalab. The linked data will be used to analyse the systematic determinants of subjective customer experience and will show which aspects of HMRC delivery generate a positive customer experience, and which do not. The Centre will enhance tax administration and tax design. It has ambitious plans to become the leading international centre with a central role in research and in building research capability in tax analysis through the training of PhD students and training of research staff. Subjects were recruited from the general UK population by a market research agency (ICM). ICM sent an invitation e-mail to its participant pool to take part in an online decision-making experiment. When registering their interest in the experiment, participants were asked to fill out a questionnaire comprising a series of standard demographic questions. ICM included only participants who stated that they were over 18 years old and were either self-employed or employed full-time; this meant that they were U.K. tax residents. ICM then invited at random 755 people from those who met our sampling criteria.Out of the 755 people invited, 554 completed the experiment. The experiment was conducted through a bespoke on-line website hosted by the University of Exeter. ICM sent a unique username and password to each subject for them to access the experiment. We could not match usernames to actual participant data, and ICM did not have access to participant decisions, making this a double-blind experimental design. This was made explicit to participants when they were invited to participate. After logging in, each participant read an on-screen set of instructions that detailed the task they were required to perform. Participants were also told that they would be paid a fixed £5 sum for completing the experiment and would have the opportunity to earn more in line with their decisions in the experiment. The instructions detailed several examples of the potential outcomes from various declaration choices.

We report on data from a real-effort tax compliance experiment using three subject pools: students, who do not pay income tax; company employees, whose income is reported by a third party; and self-employed taxpayers, who are responsible for filing and payment. While compliance behaviour is unaffected by changes in the level of, or information about the audit probability, higher fines increase compliance. We found there are subject pool differences, where self-assessed taxpayers are the most compliant, while students are the least compliant. Through a simple framing manipulation, we show that such differences are driven by norms of compliance from outside the lab.Good tax design and administration are central to the functioning of the economy. Taxes are important determinants of economic behaviour, and good implementation can significantly increase economic and social welfare. The role of the Tax Administration Research Centre is to deliver research that enhances tax policy and provides lasting benefit to the economy. There are many research tools that can contribute to this goal but the greatest success will be achieved by combining a range of research methodologies and disciplines. The Centre will unite researchers from two institutions with distinguished reputations for research into tax administration and tax design. Complementary abilities and methodologies will be brought together to address a wide range of intersecting research projects. The research methodologies will include economic modelling, econometric analysis, experimentation, numerical simulation, and qualitative analysis. In undertaking its work the Centre will make extensive use of the HMRC/HMT Datalab to permit innovative empirical work to be undertaken. Some examples of the research projects to be conducted at the Centre are: Risk-based auditing and taxpayers' responses will investigate the reaction of taxpayers to audits, and how this will change the pattern of compliance behaviour. The project will study whether taxpayers learn about the audit strategy over time, and how a risk-based strategy should be updated to take this into account. The project will link with laboratory experiments on compliance and with research on the role of tax advisers. The results will increase the return on resources allocated to auditing. Decomposing the elasticity of taxable income will determine how the response of individuals to taxes summarised by the elasticity of taxable income; can be separated into the channels through which individuals respond (e.g. reduced work effort, increased pension contributions or charitable contributions, moving income abroad, taking income in other forms). The results will enable greater focus of tax interventions and improved design of tax structure. Consequences of pre-population will study the implications of pre-populated tax returns for compliance. If the pre-populated form shows an income level below actual income this might convey an impression to the taxpayer that they can successfully evade. The research will implement an experiment that randomises the allocation of pre-populated returns. The outcome will advise on how best to proceed with the implementation of pre-population. Large business (Intermediaries) relationship with HMRC will use qualitative depth interviews address the extent to which new initiatives have altered working practices in intermediary firms and their clients' businesses, the HMRC understanding of tax avoidance practices, and the appropriateness of current policy strategies currently. This will enhance understanding of the effects of HMRC operational policy and improve administration. Understanding the determinants of customer experience will link HMRC survey data on customer experience with objective measures of service delivery standards, third-party information, and tax return data in Datalab. The linked data will be used to analyse the systematic determinants of subjective customer experience and will show which aspects of HMRC delivery generate a positive customer experience, and which do not. The Centre will enhance tax administration and tax design. It has ambitious plans to become the leading international centre with a central role in research and in building research capability in tax analysis through the training of PhD students and training of research staff. The student sample was recruited from a pool of voluntary undergraduate student subjects. The majority of the PAYE sample was recruited from a pool of voluntary subjects from across the UK run by a market research company, Saros Research. We also recruited PAYE taxpayers from businesses in the local area, as well as employees of the university. The self-assessed sample was recruited from a pool of voluntary subjects from across the UK run by a market research company, ICM Research.

These datasets contain aggregated expenditure and demographic variables, that are derived from the Family Expenditure Survey (GN 33057), the Expenditure and Food Survey/Living Costs and Food Survey (GN 33334), the General Household Survey (GN 33090) and the Health Survey for England (GN 33261). These files can be used to replicate the results in the paper Banks, J., Blundell, R., Levell, P. and Smith, J. "Life-Cycle Consumption Patterns at Older Ages in the US and the UK: Can Medical Expenditures Explain the Difference?", AEJ: Economic Policy (August, 2019) (see related resources). This proposal sets out a major new programme of research that will lead to significant scientific progress and policy impact. Building on the expertise developed at the Centre and at IFS, we will use the developments in econometric techniques and data availability, including linked survey and administrative data, to push our research agenda in exciting new directions. The focus of the work will be on: a) Consumers and markets. We will use insights from behavioural economics and robust methods to understand within-household behaviour and we will explore the relationships between government policy, firm behaviour and outcomes for consumers. This work has the potential to transform our understanding of the effects of policy interventions that either change the relative prices of the goods consumers buy (e.g. taxes on alcohol, green levies, sugar taxes) or try to change consumers' preferences (e.g. through information campaigns or restrictions on advertising). b) Inequality, risk and insurance. Understanding the determinants of inequality is central to our agenda. We will focus on understanding inequality across the life cycle and across and within generations. We will explore the role of housing, of insurance and of market and non-market mechanisms in managing risk and uncertainty. The availability of new administrative data linked to existing surveys will allow us to examine the dynamics of inequality and the impact of alternative policies. In particular, we will focus on the role of wealth and bequests in generating within-cohort inequality among the younger generations and we will investigate how uncertainty is resolved over the life cycle and how this affects the degree of insurance provided by taxes and benefits at different ages. c) Public finances and taxation. Focusing on high earners and multinational companies, we will use newly-available data to throw new light on risks to the public finances in the UK from these vital but increasingly risky sources of revenue. We will also develop a programme of work that focuses on the particular issues facing tax design in middle-income countries. d) Evolution of human capital over the life cycle. We aim to make major strides in understanding the process of formation of human capital from the early years to young adulthood, how human capital is rewarded in the labour market, how it is linked to labour supply and productivity, and how the evolution of health and well-being interacts with labour supply and other outcomes in later years. These issues are intricately related and we envisage a joined-up programme of work that will provide new answers to some of the most important questions currently facing policymakers. How do people make decisions over savings, nutrition, education and labour supply and how can government influence those decisions? What is driving increased levels of income inequality and how might interventions in education and through the tax and welfare system ameliorate them, and at what cost? How should governments respond to the pressures on corporate and individual tax revenues created by increasing globalisation? What drives decisions over pension savings, health behaviours and retirement decisions and how should governments design policy in the face of an ageing population? In answering these questions, we will make use of the unique expertise and data resources brought together at the Centre. Crucially, our intention is also to take a consistent approach in which we will model the determinants of individual decisions over the life course and the interactions between economic actors; we will model behavioural 'biases' and market frictions; we will use a combination of available data, randomised controlled trials and structural modelling to understand not just the effect of policies but also what drives that effect and hence what might be the effect of other policies; and we will develop new data and measurement tools. Derived dataset using data collected from household surveys of the UK population. The LCFS collects detailed data on household expenditure which we were able to use to separate out spending into different categories for comparison with spending in the United States (as measured in the Consumer Expenditure Survey). The HSE and GHS were chosen as they have household level data on self-reported health which we were able to compare across different cohorts and also with measures from similar surveys in the US.