Latterman Demographics and Voting Trends

San Francisco Demographics and Voting Trends: 

San Francisco Demographics and Voting Trends David Latterman October, 2004

Agenda: 

Agenda Description and methodology of demographic dataset Correlations to Rich DeLeon’s PVI Correlations to recent elections Turnout Identity Politics A look to the future

New SF demographic dataset: 

New SF demographic dataset Compiled from 2000 census Use blocks, block groups, and tracts to convert data to SF voting precincts Blocks are standard unit Much useful data come from block groups, too, though these are harder to convert Larger tract data is best for district analysis

Conversion techniques to SF precincts: 

Conversion techniques to SF precincts

Data from various census units: 

Data from various census units Blocks Race Age Gender Housing tenure (home ownership vs. renting) Block Groups Family data Education Employment Income Immigration status (especially useful in SF) Tracts LGBT (Same Sex Householders)

Example of block conversion - % Asian/Pacific Islander -: 

Example of block conversion - % Asian/Pacific Islander -

Example of block group conversion - Median HH Income -: 

Example of block group conversion - Median HH Income -

Using precinct data for analysis: 

Using precinct data for analysis Different than poll data – reflects how people actually voted Issues with data: n ~ 570 citywide n = much less for districts (45-60) “Ecological Fallacy” Difficult to establish which characteristics are important in heterogeneous parts of SF

Correlations to PVI: 

Correlations to PVI PVI: high score means a more liberal voting population; low score means a more conservative voting population Some stronger correlations to certain characteristics Varies within districts (this is important!) More liberal Hispanic Younger voters More conservative Asian Older voters Higher income Higher homeowner percentage

San Francisco PVI Map: 

San Francisco PVI Map

Good correlations with district variation (inverse slope): 

Good correlations with district variation (inverse slope) % voters over 50 vs. PVI % owned housing units vs. PVI

Good correlations with district variation (positive slope): 

Good correlations with district variation (positive slope) % voters 25-29 vs. PVI Correlations are consistently stronger with demographics that vote more conservatively!

Not a good correlation, but with some district variation: 

Not a good correlation, but with some district variation % Born in US vs. PVI

Not a good correlation with some district and neighborhood variation (1): 

Not a good correlation with some district and neighborhood variation (1) % Hispanic voters vs. PVI The Mission

Not a good correlation with some district and neighborhood variation (2): 

Not a good correlation with some district and neighborhood variation (2) % female voters vs. PVI The Castro The Tenderloin SOMA Thanks Rich! % Female Becomes a proxy for LGBT voters

Correlations to recent elections: 

Correlations to recent elections Turnout Identity Politics Potential future trends

Turnout – absentee and voting booth- is definitely affected by politics: 

Turnout – absentee and voting booth- is definitely affected by politics Dec ’03 Absentee Turnout

Dec ’03 Election Day Turnout: 

Dec ’03 Election Day Turnout

Similarly, TO is affected by demographic characteristics: 

Similarly, TO is affected by demographic characteristics Using average turnout of last three elections

Identity politics is alive and well in San Francisco: 

Identity politics is alive and well in San Francisco Look at African-Americans, Asians, Hispanic, LGBT Variation between and within districts

African-American Voting Trends: 

African-American Voting Trends Precinct >15% census pop

Asian-American Voting Trends: 

Asian-American Voting Trends Precinct >30% census pop

Hispanic Voting Trends: 

Hispanic Voting Trends Precinct >25% census pop

Racial politics in 2004 DCCC and beyond: 

Racial politics in 2004 DCCC and beyond Look at Asian, Af-Am, LGBT, Latino correlations Eye toward the future

DCCC ’04 – Asian (1): 

DCCC ’04 – Asian (1) Hsieh and Jung were the top two vote-getters in AD12 Hsieh Jung

DCCC ’04 – Asian (2): 

DCCC ’04 – Asian (2) Ow (AD13) and Yee (AD12) didn’t win Ow Yee

DCCC ’04 – African-American: 

DCCC ’04 – African-American

DCCC ’04 - Hispanics who did not win: 

DCCC ’04 - Hispanics who did not win Garcia – AD13 Trevino – AD13 Ramos – AD12

LGBT winners in AD13: 

LGBT winners in AD13 Haaland Wiener

Looking ahead: 

Looking ahead SF will see increased proportions of Hispanics and Asians, from many countries. They will have a huge impact on the electorate, especially as immigrants become naturalized and are able to vote If, in general, Asians are more moderate than Latinos…

SF Demographics Trends…: 

SF Demographics Trends…

Ethnicities vs. naturalized immigrants: 

Ethnicities vs. naturalized immigrants

% Naturalization vs. PVI: 

% Naturalization vs. PVI

For the future / other uses: 

For the future / other uses Subdivide racial groups to nation of origin Use data in policy debates (look for commonalities between Progs/Mods for compromises) City agencies like HHS, MUNI, PUC