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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21 to 30 of 191 Results
Replication Data for: Rescuing Intuitions: Income Inequality Begets Liberal Shifts in Public Mood
Replication Data for: Rescuing Intuitions: Income Inequality Begets Liberal Shifts in Public Mood
Jan 12, 2022
Downey, Leah, 2022, "Replication Data for: Rescuing Intuitions: Income Inequality Begets Liberal Shifts in Public Mood", https://doi.org/10.7910/DVN/VELPR2, Harvard Dataverse, V1, UNF:6:g1dfEkUxmHy/KPX3yD7i6w== [fileUNF]
Included here are: PDF of the paper PDF of the codebook, mostly from the original paper, with a couple of additions PDF of the original paper data set from the original paper 2 additional data sets
Replication Data for: Testing the Bounds of the Knowledge Burden Hypothesis: The Fall of the Iron Curtain and Collaboration in Mathematics
Replication Data for: Testing the Bounds of the Knowledge Burden Hypothesis: The Fall of the Iron Curtain and Collaboration in Mathematics
Jan 12, 2022
Ghosh, Sourobh; Hashemian, Mahdi; Kearney, Casey, 2022, "Replication Data for: Testing the Bounds of the Knowledge Burden Hypothesis: The Fall of the Iron Curtain and Collaboration in Mathematics", https://doi.org/10.7910/DVN/EKLKCR, Harvard Dataverse, V1, UNF:6:511CCEHjCfgc3Zf/p19Fwg== [fileUNF]
Prior literature explains increasing team-sizes in academic collaboration as a result of the knowledge burden hypothesis, which broadly asserts that the continuously accumulating stock of scientific knowledge requires increased specialization in academic work. In this paper, we replicate Agrawal et al. (2016)’s analysis of the differential increase...
Replication Data for: "Polarization and the Religious Floating Voter: Exploring Mechanisms for the Decline"
Replication Data for: "Polarization and the Religious Floating Voter: Exploring Mechanisms for the Decline"
Jan 12, 2022
Uden, Amy, 2022, "Replication Data for: "Polarization and the Religious Floating Voter: Exploring Mechanisms for the Decline"", https://doi.org/10.7910/DVN/FBWTGO, Harvard Dataverse, V1, UNF:6:YODB3w3geIJSf38RkyMrCA== [fileUNF]
This dataset provides replication data for "Polarization and the Religious Floating Voter: Exploring Mechanisms for the Decline," prepared as a requirement for Gov 2001 at Harvard University, exploring Corwin Smidt's 2015 "Polarization and the Decline of the Floating Voter".
Replication Data For: Gini in the Model
Jan 12, 2022
Donahue, Kate; Rosenblatt, Lizzy, 2022, "Replication Data For: Gini in the Model", https://doi.org/10.7910/DVN/ACBKIY, Harvard Dataverse, V1, UNF:6:HhLR1IfSCQEsm6VYEANdNw== [fileUNF]
Replication data for final Gov 2001 paper
Replication Data for: Mortality Impacts of Medicaid Expansion: Revisiting Sommers, et al. 2012
Replication Data for: Mortality Impacts of Medicaid Expansion: Revisiting Sommers, et al. 2012
Jan 12, 2022
Brault, Matthew; Munshi, Vidit; Ward, Zachary, 2022, "Replication Data for: Mortality Impacts of Medicaid Expansion: Revisiting Sommers, et al. 2012", https://doi.org/10.7910/DVN/7MKJ1J, Harvard Dataverse, V1, UNF:6:5CqQIX67NZPyvB1+e/POlA== [fileUNF]
Here we provide replication data and code for our analysis of Medicaid expansion's effects on mortality.
Replication Data for: Myran and Williams, "Heterogeneous Effects of Religion on Voter Overconfidence in Model-Dependent Political Behavior Inferences"
Jan 12, 2022
Myran, Aaron and Williams, Basil, 2022, "Replication Data for: Myran and Williams, "Heterogeneous Effects of Religion on Voter Overconfidence in Model-Dependent Political Behavior Inferences"", https://doi.org/10.7910/DVN/HG8MB8, Harvard Dataverse, V1, UNF:6:RvjlE9W+m3o9wV7rXqyZTg== [fileUNF]
Contents: replication data and code, graphs, tables, original tables and code to be replicated from Ortoleva and Snowberg (2015)
Replication Data for: College Does Matter: Exploring the Changing Impact of Formal Education on Political Success
Jan 12, 2022
Gao, Jenny; Peterson, Aticus, 2022, "Replication Data for: College Does Matter: Exploring the Changing Impact of Formal Education on Political Success", https://doi.org/10.7910/DVN/N3GMXX, Harvard Dataverse, V1
R Code for Original Paper Replication R Code for Model Improvements Datasets for replication and model improvements
Replication Data for: Words of Wisdom, Wars of Words
Replication Data for: Words of Wisdom, Wars of Words
Jan 12, 2022
Awad, Edmond; Dsouza, Sohan, 2022, "Replication Data for: Words of Wisdom, Wars of Words", https://doi.org/10.7910/DVN/5T4NUN, Harvard Dataverse, V1, UNF:6:q/ROfzfWrC7Cox77oobIPw== [fileUNF]
This is a dataset that was used for a course project.
Replication Data for: Mechanisms of Persistence
Replication Data for: Mechanisms of Persistence
Jan 12, 2022
Mazumder, Soumyajit; Bowles, Jeremy; Bullock, Jessie, 2022, "Replication Data for: Mechanisms of Persistence", https://doi.org/10.7910/DVN/BPWMMN, Harvard Dataverse, V1, UNF:6:xIfGYT8jADjH7mQzBwX5eA== [fileUNF]
#README #Introduction This directory contains all of the necessary datasets and R scripts to replicate the analysis in Besley and Reynal-Querol (2014) as well as Bowles, Bullock, and Mazumder (2016). To replicate the results, we recommend that you use RStudio. If you have any questions, please contact either Jeremy Bowles (jbowles[at]g.harvard.edu)...
Replication Data for: Media Density and (Non-)Violence: An Extension of “Not by the Sword Alone”
Replication Data for: Media Density and (Non-)Violence: An Extension of “Not by the Sword Alone”
Jan 12, 2022
Averell Schmidt; Kala Viswanathan; Bradley Dewees, 2022, "Replication Data for: Media Density and (Non-)Violence: An Extension of “Not by the Sword Alone”", https://doi.org/10.7910/DVN/ZKXPIE, Harvard Dataverse, V1
This paper extends and replicates “Not by the Sword Alone: Soft Power, Mass Media, and the Production of State Sovereignty” by T. Camber Warren.
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