Monetary policy is generally regarded as a central element in the attempts of policy makers to attenuate business-cycle fluctuations. According to the New Keynesian paradigm, central banks are able to stimulate or depress aggregate demand in the short run by adjusting their nominal interest rate targets. The effects of interest rate changes on aggregate consumption, the largest component of aggregate demand, are well understood in the context of this paradigm, on which the canonical "workhorse'' model used in monetary policy analysis is grounded. A key feature of the model is that aggregate consumption is fully described by the amount of goods consumed by a representative household. A decline in the policy rate for instance implies that the real interest rate declines, the representative household saves less and hence increase its demand for consumption. At the same time, general equilibrium effects let labour income grow causing consumption to increase further. However, the mechanism outlined above ignores a considerable amount of empirically-observed heterogeneity among households. For example, households with a higher earnings elasticity to interest rate changes benefit more from a rate cut than those with a lower elasticity; households with large debt positions are at a relative advantage over households with large bond holdings; and households with low exposure to inflation are relatively better off than those holding a sizeable amount of nominal assets. As a result, the contribution to the aggregate consumption response differs substantially across households, implying that monetary expansions and tightenings produce relative "winners'' and relative "losers''. The aim of the project laid out in this proposal is to give a disaggregated account of the heterogeneous effects of monetary-policy induced interest rate changes on household consumption and a detailed analysis of the channels underlying them. Additionally, it seeks to draw conclusions about the determinants of the strength of the transmission mechanism of monetary policy. To do so, it relies on a large panel comprising detailed data from the universe of all households residing in Norway between 1993 and 2015 supplemented with additional micro-data provided by the European Commission. I will be assisted by two project partners, Pascal Paul who is a member of the Research Department of the Federal Reserve Bank of San Francisco and Martin Holm who is affiliated with the Research Unit of Statistics Norway and the University of Oslo. In addition, I would like to collaborate with and help train a doctoral student based at the University of Lausanne on this project. Existing empirical studies of the consumption response to monetary policy at the micro level rely on survey data. Therefore, they are subject to a number of severe data limitations. The surveys employed typically have either no or only a short panel dimension, suffer from attrition, include only limited information on income and wealth, are top-coded, and contain a significant amount of measurement error. The administrative data set provided to us by Statistics Norway suffers from none of these issues, implying that we are in a unique position to evaluate the household-level effects of policy rate changes. In a first step, we use forecasts published by the Norwegian central bank to derive monetary policy shocks that are robust to the simultaneity problem inherent in the identification of the effects of monetary policy following Romer and Romer (2004). We then confront the micro-data with the estimated shocks to study the consumption response along different segments of the income and wealth distribution and to test the importance of heterogeneity in labour earnings, financial income, liquid assets, inflation exposure and interest rate exposure among others. The findings will be of high relevance as they will not only allow us to evaluate channels hypothesised in the analytical literature, improve our understanding of the monetary policy transmission mechanism and its distributional consequences but also serve as a benchmark for structural models built both by theorists and practitioners.

I use a field experiment in rural Kenya to study how temporary incentives to save impact long-run economic outcomes. Study participants randomly selected to receive large temporary interest rates on an individual bank account had significantly more income and assets 2.5 years after the interest rates expired. These changes are much larger than the short-run impacts on experimental bank account use and almost entirely driven by growth in entrepreneurship. Temporary Interest rates directed to joint bank accounts had no detectable long-run impacts on entrepreneurship or income, but increased investment in household public goods and spousal consensus over finances.

This dataset contains an history of nearly all of the real estate transactions concerning a single house/appartment in France from 2014 to today. Some variables likely to have an impact on the price of real estate are also provided as time series: the households income levels per city, the average debt level of french peoples, the average amount of savings of french people, the interest rates of loans, the price of the rent per city, the number of houses and number of vacant houses per city.

This dataset is provided under a permissive licence, and is free to use for commercial uses. It has a vocation of helping research concerning the dynamics of real estate prices.

The dataset consist in extraction from several openly available datasets put together in a practical format: The DVF+ database of real estate transactions, the IRCOM dataset of household incomes and income taxes, average interest rates of real estate loans from the banque de france website, the LOVAC dataset of number of vacant and occupied housings per city, the OECD dataset of financial assets per capita, the "carte des loyers" dataset of 2018 and 2022 which list the average price of the rent per square meter, the Indice de Référence des Loyers (IRL) time series which is an index defining the maximum rent increase that can be applied to an already rented housing and is calculated every 3 months as the inflation adjusted buying power of 100€ in 1998, the TEC00104 eurostat dataset of debt levels.

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Financial capability (Module 336): this module was asked on behalf of the Financial Services Authority. The purpose of the module was to gain a general view of how respondents who have a mortgage or rent their property would cope with a change to their circumstances, such as an increase to their mortgage or rent payment or a rise in interest rates. It also asks all respondents about type and amount of debt and how the individual or family who have a mortgage or rent their property would cope with 'shock' changes to income. Disability monitoring (Module 363): the Special Licence version of this module is held under SN 6470. Use of HRT (Module 368): the National Health Service is interested in women's use of cancer screening services, in particular breast cancer screening and cervical cancer screening. The module also asks about the use of hormone replacement therapy (HRT). Older workers (Module MAW): this module was asked on behalf of the Centre for Research into the Older Workforce (CROW) and examines work based training opportunities for older workers. Multi-stage stratified random sample Face-to-face interview

Housing costs can represent a substantial financial burden to households, especially low-income households. The median of the ratio of housing costs over income gives an indication of the financial pressure that households face from housing costs. Another common measure of housing affordability presented in this indicator is the housing cost overburden rate, which measures the proportion of households or population that spend more than 40% of their disposable income on housing costs (in line with Eurostat methodology). For a discussion of different measures of housing affordability and their advantages and limits, please see indicator HC1.5 Overview of affordable housing indicators in the OECD Affordable Housing Database. For policy measures aiming to support households with housing costs, please see indicators in the PH2, PH3 and PH4 series. Housing costs can refer to: (1) a narrow definition based on rent and mortgage costs (principal repayment and mortgage interest); or (2) a wider definition that also includes the costs of mandatory services and charges, regular maintenance and repairs, taxes and utilities, which are referred to as “total housing costs” below. Housing costs are considered as a share of household disposable income, which includes social transfers (such as housing allowances) and excludes taxes. Income is equivalised for household size based on a common equivalence elasticity (the square root of household size) which implies that a household’s economic needs increase less than proportionally with its size. Housing costs refer to the primary residence. The data presented here are based on household survey microdata and concern national household or population level data.

By the middle of the 1990s, Indonesia had enjoyed over three decades of remarkable social, economic, and demographic change and was on the cusp of joining the middle-income countries. Per capita income had risen more than fifteenfold since the early 1960s, from around US$50 to more than US$800. Increases in educational attainment and decreases in fertility and infant mortality over the same period reflected impressive investments in infrastructure. In the late 1990s the economic outlook began to change as Indonesia was gripped by the economic crisis that affected much of Asia. In 1998 the rupiah collapsed, the economy went into a tailspin, and gross domestic product contracted by an estimated 12-15%-a decline rivaling the magnitude of the Great Depression. The general trend of several decades of economic progress followed by a few years of economic downturn masks considerable variation across the archipelago in the degree both of economic development and of economic setbacks related to the crisis. In part this heterogeneity reflects the great cultural and ethnic diversity of Indonesia, which in turn makes it a rich laboratory for research on a number of individual- and household-level behaviors and outcomes that interest social scientists. The Indonesia Family Life Survey is designed to provide data for studying behaviors and outcomes. The survey contains a wealth of information collected at the individual and household levels, including multiple indicators of economic and non-economic well-being: consumption, income, assets, education, migration, labor market outcomes, marriage, fertility, contraceptive use, health status, use of health care and health insurance, relationships among co-resident and non- resident family members, processes underlying household decision-making, transfers among family members and participation in community activities. In addition to individual- and household-level information, the IFLS provides detailed information from the communities in which IFLS households are located and from the facilities that serve residents of those communities. These data cover aspects of the physical and social environment, infrastructure, employment opportunities, food prices, access to health and educational facilities, and the quality and prices of services available at those facilities. By linking data from IFLS households to data from their communities, users can address many important questions regarding the impact of policies on the lives of the respondents, as well as document the effects of social, economic, and environmental change on the population. The Indonesia Family Life Survey complements and extends the existing survey data available for Indonesia, and for developing countries in general, in a number of ways. First, relatively few large-scale longitudinal surveys are available for developing countries. IFLS is the only large-scale longitudinal survey available for Indonesia. Because data are available for the same individuals from multiple points in time, IFLS affords an opportunity to understand the dynamics of behavior, at the individual, household and family and community levels. In IFLS1 7,224 households were interviewed, and detailed individual-level data were collected from over 22,000 individuals. In IFLS2, 94.4% of IFLS1 households were re-contacted (interviewed or died). In IFLS3 the re-contact rate was 95.3% of IFLS1 households. Indeed nearly 91% of IFLS1 households are complete panel households in that they were interviewed in all three waves, IFLS1, 2 and 3. These re-contact rates are as high as or higher than most longitudinal surveys in the United States and Europe. High re-interview rates were obtained in part because we were committed to tracking and interviewing individuals who had moved or split off from the origin IFLS1 households. High re-interview rates contribute significantly to data quality in a longitudinal survey because they lessen the risk of bias due to nonrandom attrition in studies using the data. Second, the multipurpose nature of IFLS instruments means that the data support analyses of interrelated issues not possible with single-purpose surveys. For example, the availability of data on household consumption together with detailed individual data on labor market outcomes, health outcomes and on health program availability and quality at the community level means that one can examine the impact of income on health outcomes, but also whether health in turn affects incomes. Third, IFLS collected both current and retrospective information on most topics. With data from multiple points of time on current status and an extensive array of retrospective information about the lives of respondents, analysts can relate dynamics to events that occurred in the past. For example, changes in labor outcomes in recent years can be explored as a function of earlier decisions about schooling and work. Fourth, IFLS collected extensive measures of health status, including self-reported measures of general health status, morbidity experience, and physical assessments conducted by a nurse (height, weight, head circumference, blood pressure, pulse, waist and hip circumference, hemoglobin level, lung capacity, and time required to repeatedly rise from a sitting position). These data provide a much richer picture of health status than is typically available in household surveys. For example, the data can be used to explore relationships between socioeconomic status and an array of health outcomes. Fifth, in all waves of the survey, detailed data were collected about respondents¹ communities and public and private facilities available for their health care and schooling. The facility data can be combined with household and individual data to examine the relationship between, for example, access to health services (or changes in access) and various aspects of health care use and health status. Sixth, because the waves of IFLS span the period from several years before the economic crisis hit Indonesia, to just prior to it hitting, to one year and then three years after, extensive research can be carried out regarding the living conditions of Indonesian households during this very tumultuous period. In sum, the breadth and depth of the longitudinal information on individuals, households, communities, and facilities make IFLS data a unique resource for scholars and policymakers interested in the processes of economic development.

Abstract copyright UK Data Service and data collection copyright owner.The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP. The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage. The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage. Safe Room Access FRS data In addition to the standard End User Licence (EUL) version, Safe Room access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 7196, where the extra contents are listed. The Safe Room version also includes secure access versions of the Households Below Average Income (HBAI) and Pensioners' Incomes (PI) datasets. The Safe Room access data are currently only available to UK HE/FE applicants and for access at the UK Data Archive's Safe Room at the University of Essex, Colchester. Prospective users of the Safe Room access version of the FRS/HBAI/PI will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503 respectively. The secure access versions are held within the Safe Room FRS study under SN 7196 (see above). The FRS aims to: support the monitoring of the social security programme; support the costing and modelling of changes to national insurance contributions and social security benefits; provide better information for the forecasting of benefit expenditure. From April 2002, the FRS was extended to include Northern Ireland. Detailed information regarding anonymisation within the FRS can be found in User Guide 2 of the dataset documentation. Edition History: For the second edition (July 2009), correction was made to variables TOTCAPBU and TOTCAPB2. Edits made to the PENPROV table were reviewed and new edits, based on revised criteria, applied to the dataset (see Penprov note for details). For the third edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 has been added to the dataset. Main Topics: Household characteristics (composition, tenure type); tenure and housing costs including Council Tax, mortgages, insurance, water and sewage rates; welfare/school milk and meals; educational grants and loans; children in education; informal care (given and received); childcare; occupation and employment; health restrictions on work; travel to work; children's health; wage details; self-employed earnings; personal and occupational pension schemes; income and benefit receipt; income from pensions and trusts, royalties and allowances, maintenance and other sources; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; children's earnings; interest and dividends; investments; National Savings products; assets. Standard Measures Standard Occupational Classification Multi-stage stratified random sample Face-to-face interview Computer Assisted Personal Interviewing 2006 2007 ABSENTEEISM ACADEMIC ACHIEVEMENT ADMINISTRATIVE AREAS AGE APARTMENTS APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BANK ACCOUNTS BEDROOMS BONDS BUILDING SOCIETY AC... BUSES BUSINESS RECORDS CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CARS CHARITABLE ORGANIZA... CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD MINDERS CHILD MINDING CHILD SUPPORT PAYMENTS CHILD WORKERS CHILDREN CHRONIC ILLNESS CIVIL PARTNERSHIPS COHABITATION COLOUR TELEVISION R... COMMERCIAL BUILDINGS COMMUTING CONCESSIONARY TELEV... CONSUMPTION COUNCIL TAX CREDIT UNIONS Consumption and con... DAY NURSERIES DEBILITATIVE ILLNESS DEBTS DISABILITIES DISABILITY DISCRIMI... DISABLED CHILDREN DISABLED PERSONS DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATION EDUCATIONAL BACKGROUND EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... EDUCATIONAL VOUCHERS ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ETHNIC GROUPS EXPENDITURE EXTRACURRICULAR ACT... FAMILIES FAMILY MEMBERS FINANCIAL DIFFICULTIES FINANCIAL INSTITUTIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FREE SCHOOL MEALS FRIENDS FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION Family life and mar... GENDER GIFTS GRANDPARENTS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH SERVICES HEARING IMPAIRED PE... HEARING IMPAIRMENTS HIGHER EDUCATION HOLIDAY LEAVE HOME BASED WORK HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE INCOME INCOME TAX INDUSTRIES INSURANCE INSURANCE PREMIUMS INTEREST FINANCE INVESTMENT INVESTMENT RETURN Income JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LEAVE LOANS LODGERS MANAGERS MARITAL STATUS MARRIED WOMEN MARRIED WOMEN WORKERS MATERNITY LEAVE MATERNITY PAY MEDICAL PRESCRIPTIONS MORTGAGE PROTECTION... MORTGAGES MOTORCYCLES NEIGHBOURS Northern Ireland OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS ONE PARENT FAMILIES ONLINE BANKING OVERTIME PARENTS PART TIME COURSES PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PASSENGERS PATERNITY LEAVE PENSION CONTRIBUTIONS PENSIONS PHYSICALLY DISABLED... PHYSICIANS POVERTY PRIVATE EDUCATION PRIVATE PERSONAL PE... PRIVATE SCHOOLS PROFITS QUALIFICATIONS RATES REBATES REDUNDANCY REDUNDANCY PAY REMOTE BANKING RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOM SHARING ROOMS ROYALTIES SAVINGS SAVINGS ACCOUNTS AN... SCHOLARSHIPS SCHOOL MILK PROVISION SCHOOLCHILDREN SCHOOLS SEASONAL EMPLOYMENT SECONDARY EDUCATION SECONDARY SCHOOLS SELF EMPLOYED SEWAGE DISPOSAL AND... SHARES SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SOCIAL CLASS SOCIAL HOUSING SOCIAL SECURITY SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPECIAL EDUCATION SPECTACLES SPOUSES STATE EDUCATION STATE HEALTH SERVICES STATE RETIREMENT PE... STUDENT HOUSING STUDENT LOANS STUDENTS STUDY SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS Social stratificati... TAXATION TELEPHONES TELEVISION LICENCES TELEVISION RECEIVERS TEMPORARY EMPLOYMENT TENANCY AGREEMENTS TENANTS HOME PURCHA... TERMINATION OF SERVICE TIED HOUSING TIME TOP MANAGEMENT TRAINING TRANSPORT FARES TRAVEL CONCESSIONS TRAVEL PASSES UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS VISION IMPAIRMENTS VISUALLY IMPAIRED P... VOCATIONAL EDUCATIO... VOLUNTARY WORK WAGES WATER RATES WIDOWED WORKING MOTHERS WORKING WOMEN property and invest...

• Acquisition for the home of some good: car or motorbike, home furnishings, household appliances or computers and small household appliances.
• Monthly savings capacity at home.
• Retrospective assessment of the household's economic situation (6 months). Reason for the positive and negative assessment.
• Number of unemployed and job-seeking people in the surrounding area. Its evolution since 6 months.
• Retrospective and prospective assessment of the possibility of improving or finding employment in Spain (6 months).
• Retrospective and prospective assessment of the economic situation in Spain (6 months).
• Prospective assessment of the probability of acquiring durable goods for the household (1 year).
• Evolution of the saving capacity of the household (1 year).
• Prospective assessment of the household's economic situation (6 months). Reason for the positive and negative assessment.
• Prospective assessment of inflation in Spain (1 year).
• Evolution of interest rates and house prices in Spain (1 year). Intention to buy a home in the next year.
• Level of studies completed by obtaining a degree and in progress from the person interviewed.
• Household size. Family relationship between household members. Number of persons in the household with income.
• Ideology scale of the interviewee.
• Time of acquisition of Spanish nationality. Level of knowledge of Spanish of the interviewee. Country of origin.
• Participation and remembrance of vote in the 2016 general election.
• Housing tenure regime.

Abstract copyright UK Data Service and data collection copyright owner.Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991. The Understanding Society Spending Study 2 was conducted by the Institute for Social and Economic Research (ISER) at the University of Essex. The purpose of the study was to test ways to increase participation in mobile data collection. The study comprised two separate sample groups: adult sample members of the Understanding Society Innovation Panel (see SN 6849) and members of the Lightspeed UK Online Access Panel. Respondents in both sample groups were invited to download an app on their smartphone to provide daily updates on their spending for 31 days. Those who did not download the app were invited to complete a daily browser-based online diary. Data for the Innovation Panel sample were collected between May 2018 and February 2019. Data for the Lightspeed UK Online Access Panel sample were collected between July 2018 and January 2019.Further information about the Spending Study, including links to publications and documents, can be found on the ISER Understanding household finance through better measurement webpage. Main Topics: Household expenditure; Survey methods experiment. Convenience sample Multi-stage stratified random sample Mobile app-based data collection Self-administered questionnaire: Web-based (CAWI) 2018 2019 ACADEMIC ACHIEVEMENT ACCIDENTS ACCOUNTS ADOLESCENTS ADOPTED CHILDREN ADOPTIVE PARENTS ADULTS AGE ALCOHOL USE ALCOHOLIC DRINKS APPLICATION FOR EMP... ASPIRATION ASSAULT ATTITUDES BEDROOMS BEREAVEMENT BIRTH WEIGHT BREAST FEEDING BRITISH POLITICAL P... BROADBAND BULLYING BUSINESSES CABLE TELEVISION CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CENTRAL HEATING CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD SUPPORT PAYMENTS CHILDBIRTH CHILDREN CITIZENSHIP CIVIL PARTNERSHIPS CLEANING CLINICAL TESTS AND ... CLOTHING COHABITATION COHABITING COLOUR TELEVISION R... COMMUNITY BEHAVIOUR COMMUTING COMPACT DISC PLAYERS COMPUTERS CONFECTIONERY CONSUMER GOODS COSTS COUNCIL TAX CRIME AND SECURITY CRIME VICTIMS CRIMINAL DAMAGE CULTURAL GOODS Consumption and con... DEBILITATIVE ILLNESS DEBTS DEGREES DEPRESSION DIGITAL GAMES DISABILITIES DISABLED PERSONS DISCRIMINATION DISEASES DIVORCE DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL EXPECTA... ELECTRIC POWER SUPPLY EMOTIONAL STATES EMPLOYEES EMPLOYERS EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT OPPORTUN... EMPLOYMENT PROGRAMMES ENERGY CONSUMPTION ENVIRONMENTAL CONSE... ENVIRONMENTAL DEGRA... ENVIRONMENTAL ISSUES ENVIRONMENTAL MOVEM... ETHNIC GROUPS ETHNIC MINORITIES EXAMINATIONS EXPENDITURE FAMILIES FAMILY COHESION FAMILY ENVIRONMENT FAMILY LIFE FAMILY MEMBERS FAMILY SIZE FATHER S ECONOMIC A... FATHER S PLACE OF B... FATHERS FINANCIAL DIFFICULTIES FINANCIAL EXPECTATIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FOOD AND NUTRITION FOSSIL FUELS FRIENDS FRUIT FUEL OILS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURNITURE FURTHER EDUCATION GAS SUPPLY GENDER GRANDPARENTS Great Britain HAPPINESS HEALTH HEATING SYSTEMS HEIGHT PHYSIOLOGY HIGHER EDUCATION HOLIDAYS HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOURS OF WORK HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD INCOME HOUSEHOLDS HOUSES HOUSEWORK HOUSING HOUSING BENEFITS HOUSING CONDITIONS HOUSING FACILITIES HOUSING FINANCE HOUSING NEEDS HOUSING TENURE ILL HEALTH INCOME INFORMAL CARE INSURANCE INTEREST FINANCE INTERNET ACCESS INTERNET USE INVESTMENT JOB CHANGING JOB HUNTING JOB SATISFACTION JUVENILE DELINQUENCY LANDLORDS LANGUAGES LEAVING HOME YOUTH LEISURE TIME ACTIVI... LIFE SATISFACTION LIVING ABROAD LOANS MANAGERS MARITAL HISTORY MARITAL STATUS MARRIAGE MARRIAGE DISSOLUTION MEALS MOBILE PHONES MORTGAGE ARREARS MORTGAGES MOTHER S ECONOMIC A... MOTHER S PLACE OF B... MOTHERS MOTOR PROCESSES MOTOR VEHICLES NATIONALISM NATIONALITY NEIGHBOURHOODS NEIGHBOURS OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONAL TRAINING OCCUPATIONS ONE PARENT FAMILIES OVERTIME PAIN PARENT CHILD RELATI... PARENT RESPONSIBILITY PARENTAL ROLE PARENTAL SUPERVISION PART TIME EMPLOYMENT PARTICIPATION PATIENTS PAYMENTS PERSONAL DEBT REPAY... PHYSICAL MOBILITY PLACE OF BIRTH PLACE OF RESIDENCE POLITICAL ALLEGIANCE POLITICAL ATTITUDES POLITICAL INTEREST PRIVATE PERSONAL PE... PRIVATE SCHOOLS PRIVATE SECTOR PROFITS PUBLIC SECTOR QUALIFICATIONS QUALITY OF LIFE RECREATIONAL FACILI... RECYCLING RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RELIGIOUS DOCTRINES RENEWABLE ENERGY RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOMS RURAL AREAS SATELLITE RECEIVERS SATISFACTION SAVINGS SCHOOL LEAVING AGE SCHOOL PUNISHMENTS SCHOOLS SEASONAL EMPLOYMENT SELF EMPLOYED SELF ESTEEM SHOPPING SIBLINGS SLEEP SMOKING SOCIAL ATTITUDES SOCIAL CAPITAL SOCIAL CLASS SOCIAL HOUSING SOCIAL INEQUALITY SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIO ECONOMIC STATUS SOLAR ENERGY SOLID FUEL HEATING SPOUSES STANDARD OF LIVING STATE EDUCATION STATE RETIREMENT PE... STEPCHILDREN STUDENT TRANSPORTATION STUDENTS SUBCONTRACTING SUBSIDIARY EMPLOYMENT SUPERVISORS Social behaviour an... TELEPHONES TELEVISION RECEIVERS TELEVISION VIEWING TEMPORARY EMPLOYMENT THEFT TIED HOUSING TIME TRAINING TRAVELLING TIME TRUANCY UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... URBAN AREAS VEGETABLES VOTING BEHAVIOUR VOTING INTENTION WAGES WEIGHT PHYSIOLOGY WELSH LANGUAGE WIDOWED WIND ENERGY WORKING WOMEN WORKPLACE YOUTH

ABSTRACT This paper makes an empirical evaluation of the relationship between financialisation and the Portuguese private consumption by performing a time series econometric analysis from the first quarter of 1996 to the third quarter of 2019. Framed within the post-Keynesian literature, financialisation has two contradictory effects on private consumption. The first one corresponds to the fall in the households’ labour income, which favours a deceleration of private consumption. The second one corresponds to the increase of households’ debt and the increase of households’ financial and housing wealth, which favours an acceleration of private consumption. The global net effect of financialisation tends to be positive because the beneficial wealth effect suppresses the harmful income effect. We estimated a private consumption equation that includes four control variables (unemployment rate, inflation rate, short-term interest rate and long-term interest rate) and three variables linked to financialisation (labour income, net financial wealth and housing wealth). Our results confirm that labour income, net financial wealth and housing wealth are positive determinants of Portuguese private consumption. Our results also show that financialisation has represented an important driver of Portuguese private consumption, particularly due to the beneficial effects of net financial wealth.

Abstract copyright UK Data Service and data collection copyright owner.The English Housing Survey (EHS) is a continuous national survey commissioned by the Ministry of Housing, Community and Local Government (MHCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures. The information obtained through the survey provides an accurate picture of people living in the dwelling, and their views on housing and their neighbourhoods. The survey is also used to inform the development and monitoring of the Ministry's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public. The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 12,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC). The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire. End User Licence and Special Licence Versions: From 2014 data onwards, the End User Licence (EUL) versions of the EHS will only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS will be deposited later in the year, which will be of a similar nature to previous EHS EUL datasets and will include derived and raw datasets. Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages. The English Housing Survey, 2012: Housing Stock Data is available for all cases where a physical survey has been completed. For occupied cases the data comprises information from the household interview and from the physical survey. For vacant properties only, data from the physical survey are provided. The data are made available for a two-year rolling sample i.e. approximately 16,000 cases together with the appropriate two-year weights. For example, the EHS Housing Stock results presented here are for 2012, but cover the period April 2011 to March 2013. The Housing Stock dataset should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income. Latest edition information For the fourth edition (March 2017), a new cavity wall insulation variable wins95x was added to the physical file. This variable was introduced for the latest EHS Headline Report. From the submission of the 2015 EHS, wins95x will replace wins90x; it has been added to EHS physical files from 2007/8 onwards. Main Topics: The EHS Housing Stock survey consists of two components. Interview Survey An interview is first conducted with the householder. The interview topics include: household characteristics, satisfaction with the home and the area, disability and adaptations to the home, ownership and rental details and income details. Physical Survey Where interviews are achieved (the 'full household sample'), each year all rented properties and a sub-sample of owner occupied properties are regarded as eligible for the physical survey and the respondent's consent is sought. A proportion of vacant properties are also sub-sampled. For these cases a visual inspection of the property, both internal and external is carried out by a qualified surveyor. Data collected cover: stock profile; amenities; services and the local environment; dwelling condition and safety; energy performance; energy-inefficient dwellings. Multi-stage stratified random sample Face-to-face interview Physical measurements House inspection; Surveyor property inspection. 2012 2013 AGE AIDS FOR THE DISABLED APARTMENTS ATTITUDES BATHROOMS BEDROOMS BIOFUELS BOILERS BUILDING MAINTENANCE CAR PARKING AREAS CARS CEILINGS CENTRAL HEATING CHIMNEYS COHABITATION COMMUNAL ESTABLISHM... COOKING FACILITIES COSTS COUNCIL TAX DISABLED ACCESSIBILITY DISABLED FACILITIES DISABLED PERSONS DOORS ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATIONAL BACKGROUND ELECTRIC POWER SUPPLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENERGY CONSUMPTION ENERGY EFFICIENCY ENVIRONMENT ETHNIC GROUPS England FAMILIES FINANCIAL RESOURCES FLOORS FOSSIL FUELS FREEHOLD FURNISHED ACCOMMODA... GARAGES GAS SUPPLY GENDER HEADS OF HOUSEHOLD HEATING SYSTEMS HIGH RISE FLATS HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSE PRICES HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSES HOUSING HOUSING AGE HOUSING BENEFITS HOUSING CONDITIONS HOUSING FACILITIES HOUSING IMPROVEMENT HOUSING SHORTAGES HOUSING TENURE HUMAN SETTLEMENT Housing ILL HEALTH INCOME INTEREST RATES KITCHENS LANDLORDS LAVATORIES LEASEHOLD LOANS LOCAL TAX BENEFITS LODGERS MARITAL STATUS METHODS OF PAYMENT MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES OWNERSHIP AND TENURE PHYSICAL MOBILITY PLACE OF BIRTH POVERTY PRIVATE GARDENS PROPERTY RADIATORS RATES RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RESIDENTIAL MOBILITY RESPONSIBILITY ROOFS ROOMS RURAL AREAS SATISFACTION SAVINGS SELF EMPLOYED SEWAGE DISPOSAL AND... SHELTERED HOUSING SINGLE OCCUPANCY HO... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SOLAR ENERGY SPOUSES STANDARD OF LIVING STATUS IN EMPLOYMENT STRUCTURAL ELEMENTS... STUDENT HOUSING SUPERVISORY STATUS TENANCY AGREEMENTS THERMAL INSULATION TIED HOUSING TRAFFIC NOISE UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS URBAN AREAS VACANT HOUSING WALLS WASHING FACILITIES WHEELCHAIRS WINDOWS

Quality of life, housing situation and urban image of Halle. Topics: Satisfaction with the home and the living environment; owner and building type of the inhabited property; number of residential spaces; number of square meters of the apartment; housing equipment; monthly rent or cost; modernisation levy; ancillary costs included; year of construction of the building; duration of residence in this apartment; wish to relocate in the next two years; preferred place of residence as moving destination; possible reasons for relocation or move out of Halle; preferred status of the new apartment; preferred nature of the new apartment; solidarity with the city and the district; image and specific characteristics of the city of Halle; future direction of the city image; importance of civic participation and satisfaction with the opportunities for civic participation; awareness and use of these opportunities (district conference, citizens´ meeting); most important municipal tasks; sources of information on urban redevelopment; satisfaction with the information about the urban redevelopment and personal interest in urban redevelopment; advantages and annoyances of the residential area; frequency of visits to the city centre; preferred means of transport for the route to the city centre; satisfaction with selected structural institutions; political interests in general and in municipalities; Interest in party activity; intention to vote; party preference (Sunday question); assessment of the current and future economic situation as well as the economic situation in the East German federal states and in the city of Halle; worries about the future by: increased cost of living, ruthlessness, violent crime, fraud, possible apartment loss, Pollution, immigration of foreigners, right-wing radicalism, left-wing radicalism, illness, and unemployment (scale); importance of selected living conditions, communal institutions and municipal services (scale); satisfaction with these municipal facilities and services; importance of selected life goals, principles of life and value orientation (scale); current work area and at the time of the fall of the Berlin Wall; assessment of one´s own job security; place of work; duration of the commuting time; means of transport used to get to work; number of children; life satisfaction; assessment of personal future. Unemployed people were also asked: duration of unemployment; sources of livelihoods; plans for the future professional activity. Demography: duration of residence in Halle; sex; age (year of birth), grouped); marital status; flatmate; school-leaving certificate; professional qualification; professional activity; current occupational status; household size; household composition: number of children under the age of 6, from 6 to 9 and from 10 to 18 years; handicapped persons or persons in need of care in the household and their degree of kinship; household net income; sources of household income. Additionally coded was: participation in the 1993 citizens´ surveys, 1994, 1995, 1997 and 1999; respondent commented on the survey; municipality; household type; weighting factors. Lebensqualität, Wohnsituation und Stadtimage von Halle. Themen: Zufriedenheit mit der Wohnung und der Wohnumgebung; Eigentümer und Bautyp der bewohnten Immobilie; Anzahl der Wohnräume; Quadratmeteranzahl der Wohnung; Wohnausstattung; monatliche Miete bzw. Belastung; Modernisierungsumlage; enthaltene Nebenkosten; Baujahr der bewohnten Immobilie; Wohndauer in dieser Wohnung; Umzugswunsch in den folgenden zwei Jahren; präferierter Wohnort als Umzugsziel; mögliche Umzugsgründe bzw. Wegzug aus Halle; präferierter Status der neuen Wohnung; präferierte Beschaffenheit der neuen Wohnung; Verbundenheit mit der Stadt und dem bewohnten Stadtteil; Image und spezifische Charakteristika der Stadt Halle; zukünftige Ausrichtung des Stadtimages; Wichtigkeit von Bürgerbeteiligung und Zufriedenheit mit den Möglichkeiten der Bürgerbeteiligung; Bekanntheit und Nutzung dieser Möglichkeiten (Stadtteilkonferenz, Bürgerversammlung); wichtigste kommunale Aufgaben; Informationsquellen über den Stadtumbau; Zufriedenheit mit den Informationen über den Stadtumbau und eigenes Interesse am Stadtumbau; Vorteile und Ärgernisse des Wohnviertels; Besuchsfrequenz der Innenstadt; bevorzugte Verkehrsmittel für den Weg in die Innenstadt; Zufriedenheit mit ausgewählten Struktureinrichtungen; Politikinteresse allgemein und kommunal sowie Interesse an der Mitarbeit in einer Partei; Wahlbeteiligungsabsicht; Parteipräferenz (Sonntagsfrage); Beurteilung der derzeitigen und erwarteten eigenen wirtschaftlichen Situation sowie der in den ostdeutschen Bundesländern und in der Stadt Halle; Zukunftssorgen durch: Verteuerung des Lebensunterhaltes, Rücksichtslosigkeit, Gewaltkriminalität, Betrüger, möglichen Wohnungsverlust, Umweltverschmutzung, Einwanderung von Ausländern, Rechtsradikalismus, Linksradikalismus, Krankheit und mögliche Arbeitslosigkeit (Skala); Wichtigkeit ausgewählter Lebensbedingungen, kommunaler Einrichtungen und städtischer Leistungen (Skala); Zufriedenheit mit diesen kommunalen Einrichtungen und Leistungen; Wichtigkeit ausgewählter Lebensziele, Lebensprinzipien und Werteorientierungen (Skala); derzeitiger Arbeitsbereich und zur Zeit der Wende; Einschätzung der eigenen Arbeitsplatzsicherheit; Ort des Arbeitsplatzes; Dauer des Arbeitsweges; genutzte Verkehrsmittel zum Arbeitsplatz; Kinderzahl; Lebenszufriedenheit; Einschätzung der persönlichen Zukunft. Arbeitslose wurden zusätzlich gefragt: Dauer der Arbeitslosigkeit; Quellen der Lebensunterhaltssicherung; Pläne bezüglich der weiteren Berufstätigkeit. Demographie: Wohndauer in Halle; Geschlecht; Alter (Geburtsjahr, gruppiert); Familienstand; Mitbewohner in der Wohnung; Schulabschluss; berufliche Qualifikation; Berufstätigkeit; derzeitige berufliche Stellung; Haushaltsgröße; Haushaltszusammensetzung: Anzahl Kinder unter 6 Jahren bzw. von 6 bis 9 Jahren und von 10 bis 18 Jahren; behinderte oder pflegebedürftige Personen im Haushalt und deren Verwandtschaftsgrad; Haushaltsnettoeinkommen; Quellen des Haushaltseinkommens. Zusätzlich verkodet wurde: Teilnahme an den Bürgerbefragungen 1993, 1994, 1995, 1997 und 1999; Befragter gab einen Kommentar zur Befragung ab; Stadtbezirk; Haushaltstyp; Gewichtungsfaktoren. Simple disproportional random sample from the register of the residents´ registration office, stratified by sex and age. In urban districts with low population numbers an increased number of cases was obtained. Einfache disproportionale Zufallsauswahl aus der Kartei des Einwohnermeldeamtes, nach Alter und Geschlecht geschichtet. In Stadtbezirken mit geringen Einwohnerzahlen wurde eine erhöhte Fallzahl bezogen.