Nicolas Apfel, Frank Windmeijer
arXiv 9 Dec 2022 · Econometrics · 2 citations (OpenAlex)
arXiv:2212.04814 · PDF · DOI · OpenAlex · Extracted main text
Masten and Poirier (2021) introduced the falsification adaptive set (FAS) in linear models with a single endogenous variable estimated with multiple correlated instrumental variables (IVs). The FAS reflects the model uncertainty that arises from falsification of the baseline model. We show that it applies to cases where a conditional exogeneity assumption holds and invalid instruments violate the exclusion assumption only. We propose a generalized FAS that reflects the model uncertainty when some instruments violate the exclusion assumption and/or some instruments violate the conditional exogeneity assumption. Under the assumption that invalid instruments are not themselves endogenous explanatory variables, if there is at least one relevant instrument that satisfies both the exclusion and conditional exogeneity assumptions then this generalized FAS is guaranteed to contain the parameter of interest.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Duranton, G., P. M. Morrow, and M. A. Turner (2014) Roads and Trade: Evidence from the US | 0.874 | 6 | 2 | 100% |
| 2 | Masten, M. A. and A. Poirier (2021) Salvaging Falsified Instrumental Variable Models | 0.843 | 3 | 3 | 100% |
| 3 | Apfel, N. and F. Windmeijer (2022) The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exogeneity or Exclusion Restriction self | 0.644 | 2 | 2 | 100% |
| 4 | Guo, Z., H. Kang, T. T. Cai, and D. S. Small (2018) Confidence Intervals for Causal Effects with Invalid Instruments by Using Two-Stage Hard Thresholding with Voting | 0.405 | 1 | 1 | 100% |
| 5 | Hansen, L. P (1982) Large Sample Properties of Generalized Method of Moments Estimators | 0.405 | 1 | 1 | 100% |
| 6 | Heckman, J. and R. Pinto (2015) Causal Analysis After Haavelmo | 0.405 | 1 | 1 | 100% |
| 7 | Masten, M. A. and A. Poirier (2020) Salvaging Falsified Instrumental Variable Models | 0.405 | 1 | 1 | 100% |
| 8 | Sargan, J. D (1958) The Estimation of Economic Relationships using Instrumental Variables | 0.405 | 1 | 1 | 100% |
| 9 | Windmeijer, F., X. Liang, F. P. Hartwig, and J. Bowden (2021) The Confidence Interval Method for Selecting Valid Instrumental Variables self | 0.405 | 1 | 1 | 100% |
Showing the top 9 of 9 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | The Markup Falsification Adaptive Set | 0.405 | 1 | 1 |