Gov 2020/2001 Dataverse

This website is a dataverse for GOV 2020, previously Gov 2001/Stat E200: Advanced Quantitative Research Methodology (Gary King). Here you can find replication archives for Gov 2020 and 2001 final papers, past and current. Students currently enrolled in Gov 2020 should use this Dataverse page to upload their replication archives for their replication papers.

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51 to 60 of 191 Results

Replication Data for: Does State Capacity Lead to Class Voting? Dec 15, 2020 Walters, Kirsten; Urteaga, Madai; Shenker, Noah Quinn, 2020, "Replication Data for: Does State Capacity Lead to Class Voting?", https://doi.org/10.7910/DVN/LSK097, Harvard Dataverse, V1, UNF:6:YsoXSpyasO8AY61qn9O/mw== [fileUNF] Data for replicating and extending Kimuli Kasara and Pavithra Suryanarayan's 2020 article, "Bureaucratic Capacity and Class Voting: Evidence from across the World and the United States,"
Democratic Credibility Revisited Dec 15, 2020 Opacic, Aleksei; Song, Lucy, 2020, "Democratic Credibility Revisited", https://doi.org/10.7910/DVN/OWMI64, Harvard Dataverse, V1, UNF:6:mJFklLtsygXLxKfW4KwHSw== [fileUNF] Replication data for Opacic and Song (2020): Democratic Credibility Revisited.
Replication Data for: Votes on Fire: Did Wildfires Influence Voter Turnout in the 2020 Presidential Election? Dec 15, 2020 Ballesteros, Maria; Conevska, Aleksandra; Miles, Ethan, 2020, "Replication Data for: Votes on Fire: Did Wildfires Influence Voter Turnout in the 2020 Presidential Election?", https://doi.org/10.7910/DVN/BCG5FO, Harvard Dataverse, V1, UNF:6:svkhN+te7vKx94a++VWjdw== [fileUNF] We study how exposure to the 2020 wildfires in Washington State influenced voter turnout in the 2020 presidential election. Using Modis Active Fire Detection Data and the USDA's Wildfire Hazard Potential map, we leverage measures of exposure to severe wildfires to estimate changes in voter turnout at the precinct level. When controlling for populat...
Replication Data for: Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy by De Benedictis-Kessner et al (2017) Dec 15, 2020 Geng, Fangli; Kuznetsowa, Masha, 2020, "Replication Data for: Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy by De Benedictis-Kessner et al (2017)", https://doi.org/10.7910/DVN/0YUSTJ, Harvard Dataverse, V1, UNF:6:DKP1SqzoU9WOutj+41PbMg== [fileUNF] This data and code replicate and extend the analysis conducted in "Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy" by De Benedictis-Kessner et al (2017). The original Stata datasets included here were graciously provided by De Benedictis-Kessner. (2019-05-11)
Replication Data for: To What Extent do Political Parties Influence Public Opinion? Dec 15, 2020 Cai, Evelyn; Waldorf, Genevieve; Yu, Yao, 2020, "Replication Data for: To What Extent do Political Parties Influence Public Opinion?", https://doi.org/10.7910/DVN/9YVKMA, Harvard Dataverse, V1, UNF:6:2h0bD8zSoOPK0IEMtPAOFw== [fileUNF] This paper replicates "How Political Parties Shape Public Opinion in the Real World" by Slothuus and Bisgaard (2020) and extends upon their results using coarsened exact matching.
Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy" Dec 15, 2020 Dagonel, Angelo; Hernandez, Kiara; Manevich, Dorothy, 2020, "Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy"", https://doi.org/10.7910/DVN/SBN9RU, Harvard Dataverse, V1 Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy" Pundits accredit Donald Trump’s victory in 2016 to his ability to speak to the economic dislo-cation and resentment faced by White working-class voters left behind by globalization. Reny,Collingwood, and Valenzuela (2019) put this claim to the test, e...
Ranges of Resistance: Terrain and the Incidence of Nonviolent Campaigns Dec 15, 2020 Ilavarasan, Uma M.; Irajpanah, Katherine; Troy, Kevin K., 2020, "Ranges of Resistance: Terrain and the Incidence of Nonviolent Campaigns", https://doi.org/10.7910/DVN/EOVECR, Harvard Dataverse, V1, UNF:6:Bg/c6asfFJvGb4L24jJt4Q== [fileUNF] We present the first analysis of the relationship between terrain and nonviolent civil resistance campaigns using cross-national data geocoded at the subnational level. We show that---unlike rugged terrain's well-established permissive effect on the incidence of civil wars---highly variable terrain is negatively associated with nonviolent resistanc...
Replication Data for "Measuring the Returns of Vote Buying: A Null Effect" Dec 15, 2020 Cayton, Frances; Fu, Chengyu; Hickey, Molly, 2020, "Replication Data for "Measuring the Returns of Vote Buying: A Null Effect"", https://doi.org/10.7910/DVN/T7ZZ0R, Harvard Dataverse, V1, UNF:6:pVP3dzGresNUUX7wrxRZ+Q== [fileUNF] Building on Francisco Cantú’s 2019 paper "Groceries for Votes: The Electoral Returns of Vote Buying,” we reconsider the efficacy of a vote buying scheme in the 2012 Mexican Presidential Elections in which voters were given gift cards in exchange for their support. The author’s initial analysis rests on the assumption that the distance between one’s...
Replication Data for: Health consequences of the US DACA immigration programme Dec 15, 2020 Dragan, Kacie; James, Lyndon, 2020, "Replication Data for: Health consequences of the US DACA immigration programme", https://doi.org/10.7910/DVN/FVNIBH, Harvard Dataverse, V1 This is the replication code and raw data for our replication/extension of Health consequences of the US Deferred Action for Childhood Arrivals (DACA) immigration programme
Replication Data for: Donor Influence, Polarization, and Representation in an Era of Nationalized Politics Dec 15, 2020 Beavers, David; Cha, Jeremiah; O'Donohue, Andrew, 2020, "Replication Data for: Donor Influence, Polarization, and Representation in an Era of Nationalized Politics", https://doi.org/10.7910/DVN/GMF3DQ, Harvard Dataverse, V1, UNF:6:PxSiJEre2Udrd2ZrVUI2Rg== [fileUNF] The following files replicate our findings in "Donor Influence, Polarization, and Representation in an Era of Nationalized Politics," prepared for Gov 2001, Quantitative Social Science Methods I, in Fall 2020.

Replication Data for: Does State Capacity Lead to Class Voting?

Dec 15, 2020

Walters, Kirsten; Urteaga, Madai; Shenker, Noah Quinn, 2020, "Replication Data for: Does State Capacity Lead to Class Voting?", https://doi.org/10.7910/DVN/LSK097, Harvard Dataverse, V1, UNF:6:YsoXSpyasO8AY61qn9O/mw== [fileUNF]

Data for replicating and extending Kimuli Kasara and Pavithra Suryanarayan's 2020 article, "Bureaucratic Capacity and Class Voting: Evidence from across the World and the United States,"

Democratic Credibility Revisited

Dec 15, 2020

Opacic, Aleksei; Song, Lucy, 2020, "Democratic Credibility Revisited", https://doi.org/10.7910/DVN/OWMI64, Harvard Dataverse, V1, UNF:6:mJFklLtsygXLxKfW4KwHSw== [fileUNF]

Replication data for Opacic and Song (2020): Democratic Credibility Revisited.

Replication Data for: Votes on Fire: Did Wildfires Influence Voter Turnout in the 2020 Presidential Election?

Dec 15, 2020

Ballesteros, Maria; Conevska, Aleksandra; Miles, Ethan, 2020, "Replication Data for: Votes on Fire: Did Wildfires Influence Voter Turnout in the 2020 Presidential Election?", https://doi.org/10.7910/DVN/BCG5FO, Harvard Dataverse, V1, UNF:6:svkhN+te7vKx94a++VWjdw== [fileUNF]

We study how exposure to the 2020 wildfires in Washington State influenced voter turnout in the 2020 presidential election. Using Modis Active Fire Detection Data and the USDA's Wildfire Hazard Potential map, we leverage measures of exposure to severe wildfires to estimate changes in voter turnout at the precinct level. When controlling for populat...

Replication Data for: Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy by De Benedictis-Kessner et al (2017)

Dec 15, 2020

Geng, Fangli; Kuznetsowa, Masha, 2020, "Replication Data for: Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy by De Benedictis-Kessner et al (2017)", https://doi.org/10.7910/DVN/0YUSTJ, Harvard Dataverse, V1, UNF:6:DKP1SqzoU9WOutj+41PbMg== [fileUNF]

This data and code replicate and extend the analysis conducted in "Concentrated Burdens: How Self-Interest and Partisanship Shape Opinion on Opioid Treatment Policy" by De Benedictis-Kessner et al (2017). The original Stata datasets included here were graciously provided by De Benedictis-Kessner. (2019-05-11)

Replication Data for: To What Extent do Political Parties Influence Public Opinion?

Dec 15, 2020

Cai, Evelyn; Waldorf, Genevieve; Yu, Yao, 2020, "Replication Data for: To What Extent do Political Parties Influence Public Opinion?", https://doi.org/10.7910/DVN/9YVKMA, Harvard Dataverse, V1, UNF:6:2h0bD8zSoOPK0IEMtPAOFw== [fileUNF]

This paper replicates "How Political Parties Shape Public Opinion in the Real World" by Slothuus and Bisgaard (2020) and extends upon their results using coarsened exact matching.

Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy"

Dec 15, 2020

Dagonel, Angelo; Hernandez, Kiara; Manevich, Dorothy, 2020, "Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy"", https://doi.org/10.7910/DVN/SBN9RU, Harvard Dataverse, V1

Replication Data for "Explaining the Trump Electorate: Immigration, Race and the National Economy" Pundits accredit Donald Trump’s victory in 2016 to his ability to speak to the economic dislo-cation and resentment faced by White working-class voters left behind by globalization. Reny,Collingwood, and Valenzuela (2019) put this claim to the test, e...

Ranges of Resistance: Terrain and the Incidence of Nonviolent Campaigns

Dec 15, 2020

Ilavarasan, Uma M.; Irajpanah, Katherine; Troy, Kevin K., 2020, "Ranges of Resistance: Terrain and the Incidence of Nonviolent Campaigns", https://doi.org/10.7910/DVN/EOVECR, Harvard Dataverse, V1, UNF:6:Bg/c6asfFJvGb4L24jJt4Q== [fileUNF]

We present the first analysis of the relationship between terrain and nonviolent civil resistance campaigns using cross-national data geocoded at the subnational level. We show that---unlike rugged terrain's well-established permissive effect on the incidence of civil wars---highly variable terrain is negatively associated with nonviolent resistanc...

Replication Data for "Measuring the Returns of Vote Buying: A Null Effect"

Dec 15, 2020

Cayton, Frances; Fu, Chengyu; Hickey, Molly, 2020, "Replication Data for "Measuring the Returns of Vote Buying: A Null Effect"", https://doi.org/10.7910/DVN/T7ZZ0R, Harvard Dataverse, V1, UNF:6:pVP3dzGresNUUX7wrxRZ+Q== [fileUNF]

Building on Francisco Cantú’s 2019 paper "Groceries for Votes: The Electoral Returns of Vote Buying,” we reconsider the efficacy of a vote buying scheme in the 2012 Mexican Presidential Elections in which voters were given gift cards in exchange for their support. The author’s initial analysis rests on the assumption that the distance between one’s...

Replication Data for: Health consequences of the US DACA immigration programme

Dec 15, 2020

Dragan, Kacie; James, Lyndon, 2020, "Replication Data for: Health consequences of the US DACA immigration programme", https://doi.org/10.7910/DVN/FVNIBH, Harvard Dataverse, V1

This is the replication code and raw data for our replication/extension of Health consequences of the US Deferred Action for Childhood Arrivals (DACA) immigration programme

Replication Data for: Donor Influence, Polarization, and Representation in an Era of Nationalized Politics

Dec 15, 2020

Beavers, David; Cha, Jeremiah; O'Donohue, Andrew, 2020, "Replication Data for: Donor Influence, Polarization, and Representation in an Era of Nationalized Politics", https://doi.org/10.7910/DVN/GMF3DQ, Harvard Dataverse, V1, UNF:6:PxSiJEre2Udrd2ZrVUI2Rg== [fileUNF]

The following files replicate our findings in "Donor Influence, Polarization, and Representation in an Era of Nationalized Politics," prepared for Gov 2001, Quantitative Social Science Methods I, in Fall 2020.

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