Robert Kubinec

Robert Kubinec

Assistant Professor of Political Science

New York University Abu Dhabi

About

This website serves mainly as a blog in which I present ideas on political-economic topics I study and issues related to data science with R/Rstudio and causal inference. My R-related posts are syndicated with RBloggers, a consortium of R bloggers.

My research centers on political-economic issues such as corruption, economic development, and business-state relations in developing countries, and in particular the Middle East and North Africa. I am also involved in the development of Bayesian statistical models with Stan for hard-to-study subjects like corruption, polarization, and other latent social constructs. To see a list of my current working papers and access the PDFs, see my Google Scholar page.

Recent Posts

How to Estimate Models with Measurement Error for our COVID-19 Indices

This tutorial gives an overview of the COVID-19 policy indexes just released by the CoronaNet project of which I am a part and the Oxford Government Response Tracker.

Tornadoes Have Side Effects: A Response to Victor Chernozhukov

Recently I had a spirited conversation with Victor Chernozhukov, a leading econometrician whose work spans both traditional subjects like panel data modeling and newer application of machine learning models to causal inference.

The Good, the Bad and the Ugly in the CDC's Face Mask Study

While perusing the news, I read eagerly about the CDC’s recent study examining associations between county-level mask mandates and COVID-19 growth rates. This study has already been the subject of angry retorts from the restaurant industry due to the CDC’s claim that restaurant closures reduced COVID-19 spread.

Why People Are Doubting the AstraZeneca Vaccine Report

In this blog post, I use Gelman and Loken’s garden of forking paths analysis to construct a simulation showing why skepticism of AstraZeneca’s vaccine results is warranted at this early stage.

A More Realistic P-Value for the Pfizer Vaccine Report

I start with Eric Novik’s excellent blog post on how to calculate the relevant statistics for the vaccine, i.e. vaccine efficacy (VE). This is defined as: \[ VE = 1 - \frac{p_t}{p_c} \]

Contact

  • Abu Dhabi,