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  • April 2020
  • Article

Designs for Estimating the Treatment Effect in Networks with Interference

By: Ravi Jagadeesan, Natesh S. Pillai and Alexander Volfovsky
In this paper, we introduce new, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies, we introduce the notion of considering a treatment... View Details
Keywords: Experimental Design; Network Inference; Neyman Estimator; Symmetric Interference Model; Homophily
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  • 31 May 2020
  • Working Paper Summaries

Demystifying the Math of the Coronavirus

Keywords: by Elon Kohlberg and Abraham Neyman; Health
  • 2020
  • Working Paper

Demystifying the Math of the Coronavirus

By: Elon Kohlberg and Abraham Neyman
We provide an elementary mathematical description of the spread of the coronavirus. We explain two fundamental relationships: How the rate of growth in new infections is determined by the “effective reproductive number” and how the effective reproductive number is... View Details
Keywords: Coronavirus; Health Pandemics; Mathematical Methods
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  • 03 Oct 2017
  • First Look

First Look at Research and Ideas, October 3, 2017

results are consistent with the key predictions of the rational addiction model, expanding its relevance to settings beyond what are usually considered “addictive” behaviors. Games of Threats By: Kohlberg, Elon, and Abraham Neyman... View Details
Keywords: by Sean Silverthorne
  • 21 Feb 2017
  • First Look

First Look at New Research: February 21

single year. This paper first documents that moves between paid work and self-employment are common and consistent with experimentation to learn about earnings. This pattern motivates estimating the expected returns to entrepreneurship... View Details
Keywords: Carmen Nobel