201 to 210 of 274 Results
Jun 25, 2021 - Harvard Dataverse
Quinlan, Dr Stephen; Schnaudt, Dr Christian; Lewis-Beck, Prof Michael S., 2021, "Replication Data for Forecasting Bloc Support in German Federal Elections: A Political History Model", https://doi.org/10.7910/DVN/CZLJS6, Harvard Dataverse, V1, UNF:6:lxQgO9D2UWw4swxNdfsZtA== [fileUNF]
This deposit contains replication materials for the paper "Forecasting Bloc Support in German Federal Elections: A Political History Model" by Quinlan, Schnaudt, and Lewis-Beck published in the journal Political Science & Politics. |
Jun 25, 2021
Mark A. Kayser; Arndt Leininger; Anastasiia Vlasenko, 2021, "Replication Data for: A Länder-based Forecast of the 2021 German Bundestag Election", https://doi.org/10.7910/DVN/KCMSB0, Harvard Dataverse, V1, UNF:6:yQ2cz9TZieoMN/GN+3Dnpw== [fileUNF]
Polls are poor forecasts when elections are distant because they are sensitive to events and conditions that can change before election day. Structural approaches, which fit models on previous elections and fundamentals such as economic performance, are less influenced by idiosyncratic events and can establish baseline expectations about election o... |
Jun 24, 2021
Grossman, Jonathan, 2021, "Replication Data for: Cite the Good Cite: Making Citations in Political Science More Transparent", https://doi.org/10.7910/DVN/KHLK5S, Harvard Dataverse, V1, UNF:6:PobJo7O6p5lsVdNDlaqyLg== [fileUNF]
Replication data for "Cite the Good Cite: Making Citations in Political Science More Transparent". These data can also be accessed at https://github.com/jonathan-grossman/Cite-the-Good-Cite. |
Thomas König; Ropers, Guido, 2021, "Replication Data for: How Gendered is the Peer Review Process? A Mixed-Design Analysis of Reviewer Feedback", https://doi.org/10.7910/DVN/LMDUEQ, Harvard Dataverse, V1, UNF:6:RNTzncHDn2bFHpi8Q+E2bw== [fileUNF]
A fair peer review process is essential for the integrity of a discipline's scholarly standards. However, underrepresentation of scholarly groups casts doubt on fairness, which is currently raising concerns about a gender bias in the peer review process of premier scholarly journals such as the American Political Science Review (APSR). In this stud... |
Jun 24, 2021
Graefe, Andreas, 2021, "Replication Data for: Combining forecasts for the 2021 German federal election: The PollyVote", https://doi.org/10.7910/DVN/KWTJJV, Harvard Dataverse, V1, UNF:6:DNUxz5O4KALklLwmK5Pamw== [fileUNF]
Forecasts of the PollyVote and its components over time for the German federal election 2021, May 1st to June 21. |
Murr, Andreas; Lewis-Beck, Michael S., 2021, "Replication Data for: Citizen Forecasts of the 2021 German Election", https://doi.org/10.7910/DVN/WVTI2K, Harvard Dataverse, V1, UNF:6:afA01PHEeaX3/jW3cPwCxQ== [fileUNF]
Systematic methods of forecasting elections vary and include reliance on polls, models, and markets. For the German case, most of the work has utilized models or polls. With respect to the use of polls, those efforts have focused almost exclusively on voter intention polling. Here we turn to voter expectation polling, i.e., citizen forecasting, to... |
Neunhoeffer, Marcel; Gschwend, Thomas; Müller, Klara; Munzert, Simon; Stoetzer, Lukas F., 2021, "Replication Data for: The Zweitstimme Model: A Dynamic Forecast of the 2021 German Federal Election", https://doi.org/10.7910/DVN/EDTKNW, Harvard Dataverse, V1
We present the Zweitstimme Model to forecast the outcome of the 2021 German federal election. The dynamic Bayesian forecasting model combines data from published pre-election public opinion polls with information from fundamentals-based forecasting models. The model takes care of the multiparty nature of the setting and generates probability statem... |
Jun 17, 2021 - Harvard Dataverse
He, Zhaochen, 2021, "Replication Data for: The Party-Line Pandemic: A Closer Look at the Partisan Response to COVID-19", https://doi.org/10.7910/DVN/GGMW0H, Harvard Dataverse, V1
Data in .rds format; use readRDS in R to open. |
Gilardi, Fabrizio; Baumgartner, Lucien; Dermont, Clau; Donnay, Karsten; Gessler, Theresa; Kubli, Maël; Leemann, Lucas; Müller, Stefan, 2021, "Replication Data for: Building Research Infrastructures to Study Digital Technology and Politics: Lessons from Switzerland", https://doi.org/10.7910/DVN/BSQWOU, Harvard Dataverse, V1
The effects of digital technology on political processes are an important phenomenon that, due to several structural problems, remains poorly understood. A key issue is the lack of adequate research infrastructures, or the lack of access. We first discuss the challenges many social scientists face and then present the infrastructure we built in Swi... |
Fraga, Bernard L.; Juenke, Eric Gonzalez; Shah, Paru, 2021, "Candidate Characteristics Cooperative (C3) 2018 Data", https://doi.org/10.7910/DVN/VHAPHV, Harvard Dataverse, V2, UNF:6:xIhBPOhz4IjhD/x3KsR4rw== [fileUNF]
The Candidate Characteristics Cooperative (C3) 2018 Data is the result of a collaborative, hand-coded effort to code the race/ethnicity and gender of state legislative primary and general election candidates from 2018. Covering approximately 14,500 unique major-party and minor-party candidates, contributors were able to identify the race/ethnicity... |
