Identification, Estimation and Inference Based on Constructed Instruments

Chaohua Dong, Jiti Gao, Oliver Linton and Bin Peng

Papers from arXiv.org

Abstract: We propose a structural projection (SP) method for identifying and estimating structural parameters in regression models associated with endogenous regressors. The method projects the structural error onto the sigma-field generated by the regressors, decomposing it into a conditional mean component and an orthogonal residual. This decomposition yields an internally constructed instrument that is valid whenever the conditional mean lies in a known subspace, avoiding the need for external instruments. We establish identification conditions, derive consistency and asymptotic normality for the resulting estimator, and propose a LASSO-based selection procedure for choosing the subspace when no natural candidate is available. The SP method applies to a broad class of linear, nonlinear, and non-separable models. Simulations show that SP substantially outperforms least-squares-based benchmarks under endogeneity while remaining competitive when it is absent, and we illustrate the method using data on the returns to schooling.

Date: 2026-07, Revised 2026-10
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://arxiv.org/pdf/2607.05699 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2607.05699

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().