Robert Kubinec

Assistant Professor of Political Science

New York University Abu Dhabi

Biography

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.

Interests

Political Economy
Middle East and North Africa
Applied Bayesian Methods (Stan)

Education

PhD, 2018

University of Virginia

Recent Posts

Why You Should Be Careful About the MaterniT 21 Test

My wife and I have been faced with a decision in our pregnancies that has always caused me some consternation: should we take the MaterniT 21 test to see if our baby might have Down’s syndrome (trisomy 21) or other genetic abnormalities?

Sep 13, 2020 13 min read

What Panel Data Is Really All About

We’ve all been in that seminar where the author puts up a slide containing regression coefficients, and buried in the bottom line of the table we can see little Ys and Ns indicating the kind of panel data model employed.

Apr 22, 2020 29 min read

A Proposed Model for Partial Identification of SARS-CoV2 Infection Rates Given Observed Tests and Cases

Introduction In recent days as more and more data is available on observed case counts of the SARS-CoV2 coronavirus there are also increasing attempts to infer infection rates from these case counts.

Mar 28, 2020 30 min read

Simulating Conjoint Survey Experiments

Background Conjoint survey experiments have become more popular in political science since the publication of Hainmueller, Hopkins and Yamamoto (2014). However, analysis of the statistical of power of conjoint experiments is difficult using standard parametric techniques because of the use of multiple treatments, interaction effects and paired vignettes.

Feb 11, 2019 12 min read

idealstan: an R Package for Ideal Point Modeling with Stan

This is a paper that was presented at the StanCon2018 conference on Bayesian inference with the Stan Hamiltonian Markov Chain Monte Carlo (MCMC) method. Video of my talk is available here.

Mar 14, 2018 29 min read