ARE INSTRUMENTAL VARIABLES REALLY THAT INSTRUMENTAL? ENDOGENEITY RESOLUTION IN REGRESSION MODELS FOR COMPARATIVE STUDIES
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 645-651 |
| Journal / Publication | Statistica Sinica |
| Volume | 32 |
| Issue number | Online Special Issue |
| Publication status | Published - 2022 |
Link(s)
| DOI | DOI |
|---|---|
| Attachment(s) | Documents
Publisher's Copyright Statement
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| Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85170058453&origin=recordpage |
| Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(46f90ab9-9d93-4214-ae7e-f4ad0da208b4).html |
Abstract
We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable method. We show that when performing any comparative study, it is possible to measure the true change in the coefficients under a broad set of conditions. Our results hold, as long as the product of the covariance structure between the explanatory variables and the covariance between the error term and the explanatory variables are equal, within the same system at different time periods or across multiple systems at the same point in time.
Research Area(s)
- Bias, coefficients, comparative, econometric, endogeneity, experimental design, instrumental variable, regression model, time series analysis, quantitative methodology
Bibliographic Note
Full text of this publication does not contain sufficient affiliation information. The Research Unit(s) information for this record is based on the then academic department affiliation of the author(s).
Citation Format(s)
ARE INSTRUMENTAL VARIABLES REALLY THAT INSTRUMENTAL? ENDOGENEITY RESOLUTION IN REGRESSION MODELS FOR COMPARATIVE STUDIES. / Kashyap, Ravi.
In: Statistica Sinica, Vol. 32, No. Online Special Issue, 2022, p. 645-651.
In: Statistica Sinica, Vol. 32, No. Online Special Issue, 2022, p. 645-651.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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