Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
Publications
Publications
  • 2020
  • Working Paper
  • HBS Working Paper Series

A General Theory of Identification

By: Iavor Bojinov and Guillaume Basse
  • Format:Print
  • | Language:English
  • | Pages:27
ShareBar

Abstract

What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models — roughly, a parameter θ in a model P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective. This definition raises important questions: Are parameters the only quantities that can be identified? Is the concept of identification meaningful outside of parametric statistics? Does it even require the notion of a statistical model? Partial and idiosyncratic answers to these questions have been discussed in econometrics, biological modeling, and in some subfields of statistics like causal inference. This paper proposes a unifying theory of identification that incorporates existing definitions for parametric and nonparametric models and formalizes the process of identification analysis. The applicability of this framework is illustrated through a series of examples and two extended case studies.

Keywords

Identification; Econometric Models; Analytics and Data Science; Theory

Citation

Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
  • Read Now

About The Author

Iavor I. Bojinov

Technology and Operations Management
→More Publications

More from the Authors

    • 2022
    • Faculty Research

    Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

    By: Daniel Yue, Paul Hamilton and Iavor Bojinov
    • October 2022
    • Faculty Research

    On Ramp to Crypto

    By: Iavor Bojinov, Michael Parzen and Paul Hamilton
    • September 16, 2022
    • Science

    A Causal Test of the Strength of Weak Ties

    By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
More from the Authors
  • Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development By: Daniel Yue, Paul Hamilton and Iavor Bojinov
  • On Ramp to Crypto By: Iavor Bojinov, Michael Parzen and Paul Hamilton
  • A Causal Test of the Strength of Weak Ties By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
ǁ
Campus Map
Harvard Business School
Soldiers Field
Boston, MA 02163
→Map & Directions
→More Contact Information
  • Make a Gift
  • Site Map
  • Jobs
  • Harvard University
  • Trademarks
  • Policies
  • Accessibility
  • Digital Accessibility
Copyright © President & Fellows of Harvard College