The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Data mining reconsidered: encompassing and the general‐to‐specific approach to specification search
Open accessAbstract
This paper examines the efficacy of the general‐to‐specific modeling approach associated with the LSE school of econometrics using a simulation framework. A mechanical algorithm is developed which mimics some aspects of the search procedures used by LSE practitioners. The algorithm is tested using 1000 replications of each of nine regression models and a data set patterned after Lovell’s (1983) study of data mining. The algorithm is assessed for its ability to recover the data‐generating process. Monte Carlo estimates of the size and power of exclusion tests based on t‐statistics for individual variables in the specification are also provided. The roles of alternative sizes for specification tests in the algorithm, the consequences of different signal‐to‐noise ratios, and strategies for reducing overparameterization are also investigated. The results are largely favorable to the general‐to‐specific approach. In particular, the size of exclusion tests remains close to the nominal size used in the algorithm despite extensive search.
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Cites
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The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics
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I Just Ran Two Million Regressions
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Let's Take the Con out of Econometrics
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Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots
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Cited by
A Reality Check for Data Snooping
White, H. (2000) · Econometrica · doi:10.1111/1468-0262.00152 · Cited by 1,851
Tests of Conditional Predictive Ability
Giacomini, R., & White, H. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00718.x · Cited by 1,646
Sovacool, B. K., Axsen, J., & Sorrell, S. (2018) · Energy Research & Social Science · doi:10.1016/j.erss.2018.07.007 · Cited by 1,092
Bekaert, G., Harvey, C. R., Lundblad, C. T., & Siegel, S. (2011) · Review of Financial Studies · doi:10.1093/rfs/hhr082 · Cited by 394
Miller, H. J., & Goodchild, M. F. (2015) · GeoJournal · doi:10.1007/s10708-014-9602-6 · Cited by 391
Metadata
- Authors
- Hoover, K. D., & Perez, S. J.
- Venue
- The Econometrics Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-12-01
- Volume
- 2
- Issue
- 2
- Pages
- 167-191
- ISSN
- 1368-4221 (ISSN-L)
- 1368-423X
- OpenAlex
- W2164821349
- Cited by
- 486
- References
- 29
- FWCI
- 24.47
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
