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Household wealth. What we can learn from micro data registers Gitte Frej Knudsen Søren Brodersen. Household wealth. The use of micro based registers. Explaining variables at micro level. Registers. Use. Individuals Income Social status Family type Education Working place.
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Household wealth What we can learn from micro data registers Gitte Frej Knudsen Søren Brodersen
Household wealth The use of micro based registers Explaining variables at micro level Registers Use • Individuals • Income • Social status • Family type • Education • Working place • Micro based registers in • the wealth project • Dwellings • Household cars Research Statistics Analysis • Enterprises • Activity code • Number of employees • Turnover • Other micro based • registers • Debt • Financial assets Example: Analysis of owner occupiers’ net wealth
Household wealth Main results Share of households’ real assets 95,5% 4,2% 0,3% + Households’ real assets
Household wealth Register: Market value for owner occupied dwellings 1. Geography dimension Merging Key: Real estate no. • Building and estate register • Real estate no. • Postal code • Municipal code • Region • Real estate value register • Real estate no. • Official real estate valuation (tax value) 2. Real estate sales • Official valuation and • geography dimension • Real estate no. • Official real estate valuation • Postal code, municipality, region • Estate sales register • Real estate no. • Actual sale values Merging Key: Real estate no.
Household wealth Register: Market value for owner occupied dwellings 3. Sector delimitation: Household sector • Business register • Business register no. • Type of ownership • Owners of real estate • Real estate no. • Personal ID no. • Business register no. • Owner share • Owners belonging to the • household sector • Real estate no. • Personal ID no. • Business register no. • Owner share Filter: Persons and sole proprietorships 4. Official estate valuations broken down by individuals and geography • Official real estate valuations • Real estate no. • Official estate valuations • Postal code, municipality, region • Actual sale values Merging (basic register) Key: Real estate no. • Owners belonging to the • household sector • Real estate no. • Personal ID no. • Business register no. • Owner share
Household wealth Estimation of actual market values for owner occupied dwellings 1. Estimation of coefficients relating actual sale values to official real estate valuations k is a geographical area, e.g. a postal code j is an owner occupied dwelling (type j), traded in the geographical area k 2. Estimation of market value at micro level Market value = Official estate value * market value coefficient
Household wealth Estimation of market values for owner occupied dwellings One family houses only Coefficients of actual sales values to official real estate values
Household wealth Market values for co-operative dwellings Challenges • No central registration of owners • No official real estate valuation of co-operative dwellings Assumptions for estimation of market values at micro level • All adults at the same address own equal shares of the co-operative dwelling • The total real estate value owned by the co-operative is distributed proportionally among dwellings according to square meters • Coefficients between actual sales values and official estate value are estimated at regional level only Conclusion Estimates suffer from incomplete information for ownership and actual sales values unlike register information on owner occupied dwellings
Household wealth Comparison between micro based market value and national accounts data on household real estate. Note: Real estate of households includes dwellings and business real estate of household sector enterprises.
Households’ real assets Register: Market value for household cars 1. Sector delimitation: Household sector • Vehicle register • Owners: Personal ID no. Business reg. no. • Vehicle key number • Manufacturer • Model, variant, age • … other technical data • Business register • Business register no. • Type of ownership • Owners belonging to the • household sector • Personal ID no., • Business reg. no. • Vehicle key number • Manufacturer • Model, variant, age • … other technical data Filter: Persons and sole proprietorships 2. Market value Imputation programme Impute market value when no match is found • Owners belonging to the • household sector • Personal ID no., • Business reg. no. • Vehicle key number • Manufacturer • Model, variant, age • … other technical data • Price register from • Danish Motorcar Society • Vehicle key number • Age • Market value Merging Keys: Vehicle key number, age
Households’ real assets Register: Market value for household cars • 3. Challenges • The Price register from Danish Motorcar Society contains only cars • No prices for cars older than 20 years • 10 percent of the household cars have no match between the Price register and the Vehicle register • 4. Assumptions for estimation of market values at micro level • No market value for household vans, motor cycles, mobile homes etc. • All cars older than 20 years have a market value equal to zero. • Imputed market values for 10 percent of the household cars • 5. Explaining variables • Registers with explaining • variables (Statistics Denmark) • Geographical localisation • Composition of the owner's family • Family income • Housing condition …other explaining variables • Merged Vehicle register • with market value • Owner • Manufacturer • Model, variant, age etc. • Market value Merging Keys: Personal ID no. Business reg. no.
Household wealth Household wealth 2008 * Excl. land ** Only Cars
Household wealth Summary • Households’ real assets estimated at micro level amounts at the end of 2009 to approximately 2.4 times GDP • Micro registers can be used for distribution analysis (by income, gender, age, family size, occupation etc.) • Reliable estimates of market values for owner occupied dwellings at micro and macro level • Estimates for co-operative dwellings are less reliable but still useful
