5 datasets found
  1. o

    Data and Code for: Importing Political Polarization? The Electoral...

    • openicpsr.org
    stata
    Updated May 20, 2020
    + more versions
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    David Autor; David Dorn; Gordon Hanson; Kaveh Majlesi (2020). Data and Code for: Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure [Dataset]. http://doi.org/10.3886/E119547V2
    Explore at:
    stataAvailable download formats
    Dataset updated
    May 20, 2020
    Dataset provided by
    American Economic Association
    Authors
    David Autor; David Dorn; Gordon Hanson; Kaveh Majlesi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Dec 31, 2016
    Area covered
    U.S. and China
    Dataset funded by
    Swiss National Science Foundation
    Smith Richardson Foundation
    National Science Foundation
    Andrew Carnegie Fellows Program
    Accenture LLP
    IBM Global Universities Program
    Russell Sage Foundation
    Center on Global Transformation at UC San Diego
    Schmidt Sciences
    Description
    Has rising import competition contributed to the polarization of U.S. politics? Analyzing multiple measures of political expression and results of congressional and presidential elections spanning the period 2000 through 2016, we find strong though not definitive evidence of an ideological realignment in trade-exposed local labor markets that commences prior to the divisive 2016 U.S. presidential election. Exploiting the exogenous component of rising import competition by China, we find that trade exposed electoral districts simultaneously exhibit growing ideological polarization in some domains—meaning expanding support for both strong-left and strong-right views—and pure rightward shifts in others. Specifically, trade-impacted commuting zones or districts saw an increasing market share for the FOX News channel (a rightward shift), stronger ideological polarization in campaign contributions (a polarized shift), and a relative rise in the likelihood of electing a Republican to Congress (a rightward shift). Trade-exposed counties with an initial majority white population became more likely to elect a GOP conservative, while trade-exposed counties with an initial majority-minority population become more likely to elect a liberal Democrat, where in both sets of counties, these gains came at the expense of moderate Democrats (a polarized shift). In presidential elections, counties with greater trade exposure shifted towards the Republican candidate (a rightward shift). These results broadly support an emerging political economy literature that connects adverse economic shocks to sharp ideological realignments that cleave along racial and ethnic lines and induce discrete shifts in political preferences and economic policy.
  2. H

    Replication Data for "The Last Shall Be Last: Ethnic, Racial, and Nativist...

    • data.niaid.nih.gov
    • dataverse.harvard.edu
    • +1more
    tsv
    Updated Dec 30, 2022
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    Kousser, Thad (2022). Replication Data for "The Last Shall Be Last: Ethnic, Racial, and Nativist Bias in Distributive Politics" [Dataset]. http://doi.org/10.7910/DVN/F0QNW3
    Explore at:
    tsvAvailable download formats
    Dataset updated
    Dec 30, 2022
    Dataset provided by
    (UC San Diego)
    Authors
    Kousser, Thad
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This is a dataset on district spending, demographics, and legislator characteristics for 2,517 state legislative districts in six American states in the years 1921, 1941, and 1961.

  3. H

    The Pacific Poll 01-2: San Diego Voter Priorities for 2001,The Energy...

    • dataverse.harvard.edu
    Updated Aug 12, 2010
    + more versions
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    Ph.D. Christian Collet (2010). The Pacific Poll 01-2: San Diego Voter Priorities for 2001,The Energy Crisis, Opening the Mexican Border [Dataset]. http://doi.org/10.7910/DVN/UHXMVX
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 12, 2010
    Dataset provided by
    Harvard Dataverse
    Authors
    Ph.D. Christian Collet
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2001
    Area covered
    United States, California, Orange County
    Description

    The purpose of this study was to assess voter attitudes towards the energy crisis in California, opening the Mexican border and general policy priorities for 2001 in San Diego County. Respondents were asked about their top priorities for local officials in 2001, whether or not they have heard of Governor Gray Davis, the Public Utilities Commission, Southern California Edison, San Diego Gas and Electric, the San Diego County Board of Supervisors, The San Diego City Council, State Senator Steve Peace, San Diego Mayor Dick Murphy and Mexican President Vicente Fox and were asked if they had a favorable or unfavorable attitude toward each. Respondents were also asked who they felt was the most responsible for the energy crisis and how worried they were about electricity shortages or blackouts in their area. Respondents were asked how seriously they viewed the possibility of utility bankruptcy, and whether or not they felt the state should allow the utilities to go bankrupt. Further, respondents were asked a series of possible solutions to the energy crisis and how much of a difference they thought it would have on the current energy crisis. They were asked how much they spent last month on their electricity bill. A series of questions were asked about proposals to open the border between the U.S. and Mexico: whether or not respondents favor doing so, who they felt would benefit the most from an open border, and perceived impact of an open border on the local economy. Demographic variables include the length of time the respondent has been living in San Diego County and the United States, political party identification, strength of party identification, actual party registration of the respondent (from county election sources), education, the number of individuals over the age of 18 living in the respondent's household, date of birth, marital status, ethnicity (if they identified Hispanic, a sub-category is included), household income, and gender. There are also geographic variables including city of the respondent and a recoded variable for region of the county (North County, City of San Diego/La Jolla and the El Cajon/Chula Vista/Border area) and a dummy variable for whether or not the respondent lives in the City of San Diego.

  4. Anti-Displacement Toolkit Policy Briefs

    • opendata.sandag.org
    csv, xlsx, xml
    Updated Jan 25, 2024
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    SANDAG and Lesar Development Consultants (2024). Anti-Displacement Toolkit Policy Briefs [Dataset]. https://opendata.sandag.org/Land-and-People-/Anti-Displacement-Toolkit-Policy-Briefs/m34u-kg3q
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Jan 25, 2024
    Dataset provided by
    San Diego Association Of Governmentshttps://www.sandag.org/
    Authors
    SANDAG and Lesar Development Consultants
    Description

    The Anti-Displacement Toolkit Policy Briefs describe 10 policies that were chosen as priorities based on stakeholder engagement with community-based organizations, local jurisdiction staff, and affordable and market rate housing developers. The policy briefs detail each policy and its goals, target population, key stakeholders, impact timeframe, special considerations (i.e., potential benefits/drawbacks and financial/political considerations), implementation steps, and case studies.

  5. Government Hill, San Antonio, TX, US Demographics 2025

    • point2homes.com
    html
    Updated 2025
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    Point2Homes (2025). Government Hill, San Antonio, TX, US Demographics 2025 [Dataset]. https://www.point2homes.com/US/Neighborhood/TX/San-Antonio/Government-Hill-Demographics.html
    Explore at:
    htmlAvailable download formats
    Dataset updated
    2025
    Dataset authored and provided by
    Point2Homeshttps://plus.google.com/116333963642442482447/posts
    Time period covered
    2025
    Area covered
    Government Hill, Texas, San Antonio, United States
    Variables measured
    Asian, Other, White, 2 units, Over 65, Median age, Blue collar, Mobile home, 3 or 4 units, 5 to 9 units, and 70 more
    Description

    Comprehensive demographic dataset for Government Hill, San Antonio, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

  6. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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David Autor; David Dorn; Gordon Hanson; Kaveh Majlesi (2020). Data and Code for: Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure [Dataset]. http://doi.org/10.3886/E119547V2

Data and Code for: Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure

Explore at:
stataAvailable download formats
Dataset updated
May 20, 2020
Dataset provided by
American Economic Association
Authors
David Autor; David Dorn; Gordon Hanson; Kaveh Majlesi
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 1, 2000 - Dec 31, 2016
Area covered
U.S. and China
Dataset funded by
Swiss National Science Foundation
Smith Richardson Foundation
National Science Foundation
Andrew Carnegie Fellows Program
Accenture LLP
IBM Global Universities Program
Russell Sage Foundation
Center on Global Transformation at UC San Diego
Schmidt Sciences
Description
Has rising import competition contributed to the polarization of U.S. politics? Analyzing multiple measures of political expression and results of congressional and presidential elections spanning the period 2000 through 2016, we find strong though not definitive evidence of an ideological realignment in trade-exposed local labor markets that commences prior to the divisive 2016 U.S. presidential election. Exploiting the exogenous component of rising import competition by China, we find that trade exposed electoral districts simultaneously exhibit growing ideological polarization in some domains—meaning expanding support for both strong-left and strong-right views—and pure rightward shifts in others. Specifically, trade-impacted commuting zones or districts saw an increasing market share for the FOX News channel (a rightward shift), stronger ideological polarization in campaign contributions (a polarized shift), and a relative rise in the likelihood of electing a Republican to Congress (a rightward shift). Trade-exposed counties with an initial majority white population became more likely to elect a GOP conservative, while trade-exposed counties with an initial majority-minority population become more likely to elect a liberal Democrat, where in both sets of counties, these gains came at the expense of moderate Democrats (a polarized shift). In presidential elections, counties with greater trade exposure shifted towards the Republican candidate (a rightward shift). These results broadly support an emerging political economy literature that connects adverse economic shocks to sharp ideological realignments that cleave along racial and ethnic lines and induce discrete shifts in political preferences and economic policy.
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