Working Paper: NBER ID: w31814
Authors: John Mullahy
Abstract: This paper presents and assesses analytical strategies that respect the bounded count structures of outcomes that are encountered often in health and other applications. The paper's main motivation is that the applied econometrics literature lacks a comprehensive discussion and critique of strategies for analyzing and understand such data. The paper's goal is to provide a treatment of prominent issues arising in such analyses, with particular focus on evaluations in which bounded count outcomes are of interest, and on econometric modeling of their probability and moment structures. Hopefully the paper will provide a toolkit for researchers so they may better appreciate the range of questions that might be asked of such data and the merits and limitations of the analytical methods they might contemplate to study them. It will be seen that the choice of analytical method is often consequential: questions of interest may be unanswerable when some familiar analytical methods are deployed in some circumstances.
Keywords: No keywords provided
JEL Codes: I1; I10
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| analytical method (C60) | ability to answer research questions (C90) |
| bounded nature of count data (C25) | specific analytical considerations (C38) |