Lall, Ranjit

Number of items: 9.
Article
  • Lall, Ranjit, Robinson, Thomas (2022). The MIDAS touch: accurate and scalable missing-data imputation with deep learning. Political Analysis, 30(2), 179 - 196. https://doi.org/10.1017/pan.2020.49 picture_as_pdf
  • Honig, Dan, Lall, Ranjit, Parks, Bradley C. (2022). When does transparency improve institutional performance? Evidence from 20,000 projects in 183 countries. American Journal of Political Science, https://doi.org/10.1111/ajps.12698 picture_as_pdf
  • Lall, Ranjit (2021). The financial consequences of rating international institutions: competition, collaboration, and the politics of assessment. International Studies Quarterly, 65(2), 343 - 359. https://doi.org/10.1093/isq/sqaa082 picture_as_pdf
  • Lall, Ranjit (2017). The missing dimension of the political resource curse debate. Comparative Political Studies, 50(10), 1291 - 1324. https://doi.org/10.1177/0010414016666861 picture_as_pdf
  • Lall, Ranjit (2017). Beyond institutional design: explaining the performance of international organizations. International Organization, 71(2), 245 - 280. https://doi.org/10.1017/S0020818317000066 picture_as_pdf
  • Lall, Ranjit (2016). How multiple imputation makes a difference. Political Analysis, 24(4), 414 - 433. https://doi.org/10.1093/pan/mpw020 picture_as_pdf
  • Lall, Ranjit (2015). Timing as a source of regulatory influence: a technical elite network analysis of global finance. Regulation and Governance, 9(2), 125-143. https://doi.org/10.1111/rego.12050
    • Dataset
  • Lall, Ranjit (2022). Replication Data for: The Financial Consequences of Rating International Institutions: Competition, Collaboration, and the Politics of Assessment. [Dataset]. Harvard Dataverse. https://doi.org/10.7910/dvn/3ffvi5
  • Lall, Ranjit, Honig, Dan, Parks, Bradley (2021). Replication Data for: When Does Transparency Improve Institutional Performance? Evidence from 20,000 Projects in 183 Countries. [Dataset]. Harvard Dataverse. https://doi.org/10.7910/dvn/jqglhx