Department of Government, Harvard University

Konstantin Kashin is a PhD Candidate in the Department of Government and an affiliate of the Institute for Quantitative Social Science at Harvard University. His primary research interests include quantitative political methodology, with a focus on causal inference and machine learning. He is interested in applying these methods to the study of business-state relations and interest group politics in the United States and Western Europe.

Recent Blog Posts
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- Network Visualization with D3.js | Tags: data visualization D3.js
- Scraping PDFs and Word Documents with Python | Tags: python bash
- Note on Bivariate Regression | Tags: regression
- Bootstrap Confidence Interval Methods in R | Tags: R bootstrapping
- Using ggplot2 to Plot Regression Coefficients with Confidence Intervals | Tags: R ggplot2 regression

Here is a visualization I constructed using D3.js based on a visualization for Harvard’s Stat 221 class of a network of individuals for whom HIV status is known (original visualization... »

This week I wanted to write a Python script that was able to extract text from both pdf files and Microsoft Word documents (both .doc and .docx formats). This actually... »

I’ve just updated and uploaded a note on bivariate regression from a sampling perspective (based on GOV 2000 material): Note on Bivariate Regression: Connecting Practice and Theory »

This post briefly sketches out the types of bootstrapped confidence intervals commonly used, along with code in R for how to calculate them from scratch. Specifically, I focus on nonparametric... »

A graphical approach to displaying regression coefficients / effect sizes across multiple specifications can often be significantly more powerful and intuitive than presenting a regression table. Moreover, we can easily... »