Likelihood analysis of the binary instrumental variable model

By Roland R. Ramsahai, Steffen L. Lauritzen. 2011

26 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Statistics and Probability, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Robin J. Evans
2. Ricardo M. A. Silva
3. Roland R. Ramsahai

In Statistics and Probability

1. Ricardo M. A. Silva
2. Robin J. Evans
3. Roland R. Ramsahai

In Signal Processing

1. Robin J. Evans
2. Ricardo M. A. Silva
3. Roland R. Ramsahai

Citations in the corpus

• Causal Inference through a Witness Protection Program (2014, methodology): “For the standard IV model, [17] discuss a proper way of testing such models in a frequentist sense.”
• Causal Bounds and Observable Constraints for Non-deterministic Models (2012, methodology): “Sampling uncertainty is ignored here but can be proprly considered using techniques described in Ramsahai and Lauritzen (2011).”
• Instrumental Variables: An Econometrician's Perspective (2014, unknown): “ most controversial assumption underlying instrumental variables methods. First of all, it has some testable implications; see Balke and Pearl (1997) and the recent discussions in Kitagawa (2009) and Ramsahai and Lauritzen (2011). This testable restriction can be seen most easily in a binary outcome”