Shana Scogin. (Forthcoming) “Is Male Out-Migration Associated with Women’s Participation in Post-Disaster Rebuilding? Evidence from Post-Earthquake Nepal.” Accepted for publication at Disasters. https://doi.org/10.1111/disa.12596
How does male out-migration impact women’s experience during post-disaster reconstruction? This paper employs survey data collected by Nepal’s Housing Recovery Reconstruction Platform in 2018 to establish robust associations between male out-migration and three indicators of women’s participation in rebuilding their private houses after the 2015 Gorkha earthquake: 1.) knowing where to consult for information, 2.) visiting a local government official by oneself, and 3.) signing a rebuilding agreement with the local government. Twenty-six semi-structured interviews collected in 2022 further revealed that women whose husbands were abroad undertook roles that they would not have taken had their husbands been present, including in management and decision-making. However, the interviews also highlighted challenges that women had to overcome, like a lack of knowledge about procuring materials and difficulties leading the process as a woman. This study advances the literature by establishing a relationship between male out-migration and variation in women’s post-earthquake rebuilding experiences.
Angela Chesler, Debra Javeline, Kimberly Peh, and Shana Scogin. (2023) “Is Democracy the Answer to Intractable Climate Change?” Global Environmental Politics. 1-16. https://doi.org/10.1162/glep_a_00710 (names in alphabetical order)
Climate change is the greatest governance challenge humanity has ever faced. Understanding why some governments successfully reduce greenhouse gas emissions and others fail is thus imperative. While regime type is often hypothesized to be a source of variation in greenhouse gas emissions, empirical findings about the effects of democracy and autocracy on climate action are contradictory. This research note reconciles these inconsistencies and adopts a quasi-experimental approach to investigate the relationship between democratization and greenhouse gas emissions. A fixed effects model with a synthetic control estimator is used to construct appropriate counterfactuals and evaluate the effect of regime type on emissions with data from the World Bank and Varieties of Democracy Project. The analysis shows that movement toward democracy does not have a significant effect on emissions, suggesting that research on the politics of emissions reduction should focus on factors other than regime type.
Selected Working Papers:
- “Public Opinion, Governance, and Disaster Management in Urban Nepal”
- “Model Robustness in Political Science”
- “Democratic Citizenship and the Provision of Electricity in Rural Nepal,” with Suraj Parajuli
- “Hydropower and Post-earthquake Reconstruction in Nepal,” with Arpan Pandit and Suraj Parajuli
- “Attribution and Statistical Software in Political Science,” with Jennifer Forestal
- “Ward-level Gender Quotas in the Kathmandu Valley,” with Benjamin Francis and Rabina Shrestha
- “Earthquake Early Warning System Preferences in the Kathmandu Valley,” with Sagar Khanal, Festus Amadu, and Rachael Lau
- “The Political Theory of Peacebuilding: Lederach and Adam Smith,” with Benjamin Francis
Shana Scogin, Johannes Karreth, Andreas Beger, and Jay Rob Williams. (2019). “BayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimation.” Journal of Open Source Software, 4(42), 1722. https://doi.org/10.21105/joss.01722. Visit the website here.
BayesPostEst is an R (R Core Team, 2019) package with convenience functions to generate and present quantities of interest after estimating Bayesian regression models fit using MCMC via JAGS (Plummer, 2017), Stan (Stan Development Team, 2019), MCMCpack (Martin, Quinn, & Park, 2011), or other MCMC samplers. Quantities of interest include predicted probabilities and changes in probabilities in generalized linear models and analyses of model fit using ROC curves and precision-recall curves. The package also contains two functions to create publication-ready tables summarizing model results with an assessment of substantively meaningful effect sizes.
Shana Scogin, Sarah Petersen, Jeff Harden, and Bruce Desmarais. (2019). “modeLLtest: An R Package for Unbiased Model Comparison using Cross Validation.” Journal of Open Source Software, 4(41), 1542. https://doi.org/10.21105/joss.01542
Selection among statistical models describing the same process is a crucial methodological step in quantitative research. Because different estimators for the same process are commonly available, researchers have developed tests for selecting among models. The R package modeLLtest implements a variety of such tests using leave-one-out cross-validation (LOOCV) to adjudicate among estimation methods. LOOCV accounts for outliers in data by comparing results across samples in which one observation has been left out (Diebold & Mariano, 2002).
The R package modeLLtest has three main functionalities. It implements an unbiased comparison of two linear parametric, non-nested models (Desmarais & Harden, 2014; Harden & Desmarais, 2011), a test comparing two estimations of the Cox proportional hazards model – the conventional partial likelihood maximization (PLM) and the iteratively reweighted robust model (IRR) (Desmarais & Harden, 2012), and a set of more general functions for comparison of arbitrary models.
Professional and Policy-Oriented Publications:
- Susan Ostermann and Shana Scogin, 2020 BTI Country Report: Nepal.