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Vital Signs: Transit Cost-Effectiveness – by operator
data.bayareametro.gov | Last Updated 2018-07-06T18:04:51.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Rent Payments – by metro
data.bayareametro.gov | Last Updated 2019-10-25T20:17:20.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED August 2019 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments 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.
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Vital Signs: Housing Affordability - County Overall
data.bayareametro.gov | Last Updated 2019-10-25T20:43:28.000ZHousing Affordability (EQ2) FULL MEASURE NAME Housing Affordability LAST UPDATED October 2018 DATA SOURCE U.S Census Bureau: Decennial Census Form STF3 – https://nhgis.org (1980-1990) Form SF3a – https://nhgis.org (2000) U.S. Census Bureau: American Community Survey Form B25074 (2009-2017) Form B25095 (2009-2017) http://api.census.gov Image: Flickr (Creative Commons license), Photographer: Frank Kehren, https://www.flickr.com/photos/fkehren/8481894011 CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The share of income brackets used for different Census and ACS forms varied over time. To allow for historical comparisons, the Census Bureau merges housing expenditure brackets into three consistent bins (less than 20 percent, 20 percent to 34 percent, and more than 35 percent) that work for all years. The highest income bracket for renters in the ACS data was $100,000 or more, while the homeowner dataset included brackets for $100,000 to $149,999 and $150,000 and above. These brackets were merged together to allow for uniform comparison across tenure. While some studies use 30 percent as the affordability threshold, Vital Signs uses 35 percent as this is the closest break point using the standardized affordability brackets above. Historical data for Napa County is unavailable due to an insufficient sample size for renters in a number of years, making it impossible to calculate affordability for all households. All ACS data is for a single year, rather than a rolling average. Income breakdown data is only provided for one year as it is not possible to compare consistent inflation-adjusted income brackets over time given Census data limitations.
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Vital Signs: Jobs – by subcounty
data.bayareametro.gov | Last Updated 2020-04-13T23:19:44.000ZVITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED March 2020 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/ U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/ U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/ Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma
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Vital Signs: Rent Payments – Bay Area
data.bayareametro.gov | Last Updated 2019-10-25T20:17:35.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED September 2016 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2015 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2015 http://data.bls.gov Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments 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.
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Vital Signs: Transit Cost-Effectiveness – by metro
data.bayareametro.gov | Last Updated 2018-07-06T18:04:53.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Housing Affordability - County by Income
data.bayareametro.gov | Last Updated 2019-10-25T20:43:10.000ZHousing Affordability (EQ2) FULL MEASURE NAME Housing Affordability LAST UPDATED October 2018 DATA SOURCE U.S Census Bureau: Decennial Census Form STF3 – https://nhgis.org (1980-1990) Form SF3a – https://nhgis.org (2000) U.S. Census Bureau: American Community Survey Form B25074 (2009-2017) Form B25095 (2009-2017) http://api.census.gov Image: Flickr (Creative Commons license), Photographer: Frank Kehren, https://www.flickr.com/photos/fkehren/8481894011 CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The share of income brackets used for different Census and ACS forms varied over time. To allow for historical comparisons, the Census Bureau merges housing expenditure brackets into three consistent bins (less than 20 percent, 20 percent to 34 percent, and more than 35 percent) that work for all years. The highest income bracket for renters in the ACS data was $100,000 or more, while the homeowner dataset included brackets for $100,000 to $149,999 and $150,000 and above. These brackets were merged together to allow for uniform comparison across tenure. While some studies use 30 percent as the affordability threshold, Vital Signs uses 35 percent as this is the closest break point using the standardized affordability brackets above. Historical data for Napa County is unavailable due to an insufficient sample size for renters in a number of years, making it impossible to calculate affordability for all households. All ACS data is for a single year, rather than a rolling average. Income breakdown data is only provided for one year as it is not possible to compare consistent inflation-adjusted income brackets over time given Census data limitations.
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Vital Signs: Home Prices – by county
data.bayareametro.gov | Last Updated 2019-10-25T20:29:56.000ZVITAL 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.
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Vital Signs: Jobs – Bay Area
data.bayareametro.gov | Last Updated 2020-04-13T23:21:14.000ZVITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED October 2019 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/ U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/ U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/ Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma
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Vital Signs: Home Prices – by city
data.bayareametro.gov | Last Updated 2019-10-25T20:29:41.000ZVITAL 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.