Endogeneity

Version 1.1.0 (5 October 2026): corrected — see the Journal's errata page (journal.valuation-engineer.com/index.php/vej/errata). Condition is restated on the Journal's 0.00–10.00 condition score and a remodel as an event whose value is the condition and quality it produced; every number is unchanged. Pages 71-78 of Vol. 1 No. 2 (formerly 69-75).Endogeneity is the condition in which a regressor is correlated with a model's error term, so that its coefficient does not recover the causal effect of interest. This entry generalizes the omitted-variable case of entry 008, presenting omitted variables, simultaneity, selection, and measurement error as four mechanisms producing one condition, and distinguishing endogeneity from imprecision by the fact that additional observations do not reduce it. Appraisal encounters are developed for each mechanism: reverse causation between school quality and neighborhood price levels; renovation as an owner's choice conditioned on unobserved property qualities rather than as a randomly assigned treatment; selection in the comparable set, since sold properties are not a random sample of properties; and condition ratings assigned by an appraiser who already knows the transaction price. The central result is that measuring an omitted variable cures the omission without necessarily curing the endogeneity --- a remodel coefficient estimated from observational data conflates the value the work added with the value of the properties whose owners chose to do it, so an appraiser answering a renovation-payback question from such a coefficient will systematically overstate the return. Since no residual plot or test statistic detects endogeneity from data alone, the entry argues that the defensible response is an explicit argument about mechanism and direction, and that design choices in assembling a comparable set do more for defensibility than any estimator applied afterward.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-04
DOI
https://doi.org/10.5281/zenodo.23134752
Primary Topic
Advanced Causal Inference Techniques
Type
article
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article

Endogeneity

William Bert Craytor
Zenodo (CERN European Organization for Nuclear Research)
Advanced Causal Inference Techniques
article

Endogeneity

William Bert Craytor
article en

Abstract

Version 1.1.0 (5 October 2026): corrected — see the Journal's errata page (journal.valuation-engineer.com/index.php/vej/errata). Condition is restated on the Journal's 0.00–10.00 condition score and a remodel as an event whose value is the condition and quality it produced; every number is unchanged. Pages 71-78 of Vol. 1 No. 2 (formerly 69-75).Endogeneity is the condition in which a regressor is correlated with a model's error term, so that its coefficient does not recover the causal effect of interest. This entry generalizes the omitted-variable case of entry 008, presenting omitted variables, simultaneity, selection, and measurement error as four mechanisms producing one condition, and distinguishing endogeneity from imprecision by the fact that additional observations do not reduce it. Appraisal encounters are developed for each mechanism: reverse causation between school quality and neighborhood price levels; renovation as an owner's choice conditioned on unobserved property qualities rather than as a randomly assigned treatment; selection in the comparable set, since sold properties are not a random sample of properties; and condition ratings assigned by an appraiser who already knows the transaction price. The central result is that measuring an omitted variable cures the omission without necessarily curing the endogeneity --- a remodel coefficient estimated from observational data conflates the value the work added with the value of the properties whose owners chose to do it, so an appraiser answering a renovation-payback question from such a coefficient will systematically overstate the return. Since no residual plot or test statistic detects endogeneity from data alone, the entry argues that the defensible response is an explicit argument about mechanism and direction, and that design choices in assembling a comparable set do more for defensibility than any estimator applied afterward.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 11%
Advanced Causal Inference Techniques
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