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VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

A list of fast facts on the performance of each sector of the UK economy.

These models (xls, Numbers for Mac OS X, csv) compare the Capital costs (CAPEX), Operating costs (OPEX) and revenue generated for a single household. The aim primarily is to compare the upfront and continuing costs and revenues of a household connected to FTTN (Fibre to the Node) and FTTP (Fibre to the Premises). Original analysis in OSX Numbers (one page), translated into XLS (multi-page), CSV (multi-file). Variables include: (1) CAPEX, (2) annual OPEX, (3) annual revenue, (4) Life of asset.The model also compares FTTP not starting until (5) Year X, where X is supplied by the user. The model also allows (in Numbers) to set yearly period of output e.g. annual, each decade, half-decade etc.V2 Now updated with discounted cash flow and discounted GDP impact in DCF files. 08.01.16V3 Now updated with GDP boost (externality 1%, 2% variable) in DCF_Externality files. 25.01.16.V4 Now included graphical heat map showing assumptions favouring FTTN or FTTP. Blog post 6 describes further. Javascript, in html file added within.V5 Updated model to include Delta FTTP/FTTN calc as used in Heatmap.V6 Added heat map image, so shows up in preview.V7 Add image of raw data; from Optus HFC Overbuild doc.Original source (Delimiter): see link below.V9 Add Numbers, Xls of FTTN replacement cost, discounted from Yr 10, 20, with various labour inflation rates (0,2,3,5%) [FTTNreplacecostwithFTTP]The model calculates breakeven; based on CAPEX, OPEX and Revenue. The model calculates yearly Cash balance (net costs and revenues), profit (adding depreciation and subtracting CAPEX), and GDP impact i.e. Revenue, plus costs, plus profit/loss of NBN Operator.Current issues with model:- life span of FTTN (est = 10 years; FTTP set conservatively to 25 years)- current Revenue and OPEX figures are assumed annual with no changes over time- FTTN figures after ten years, especially for revenue are not likely to be stable- customer satisfaction for FTTN likely to decline as relative speed compared to FTTP declines, not accounted for- does not account for HFCFurther description in blog post attached.NBN is the National Broadband Network, a 2007 project to connect all Australians to faster broadband. The 2009 ALP Government proposed connecting 93% to FTTP, while the 2013 Liberal National Coalition proposed connecting 25% of household to FTTN, 25% to FTTP and 40% to HFC. Remainder is wireless and satellite like the ALP proposal. The NBN is expected to complete in 2020 under the Coalition and 2025 under ALP proposals.Discussion published at: Ferrers, R. (2016). The NBN Brownfields Debate: valuing FTTN and FTTP. Journal of Telecommunications and Digital Economy, 4, 2, 31-65. (link below).