Measurement systems

Arbeitspapier

Economic models often depend on quantities that are unobservable, either for privacy reasons or because they are difficult to measure. Examples of such variables include human capital (or ability), personal income, unobserved heterogeneity (such as consumer "types"), etc. This situation has historically been handled either by simply using observable imperfect proxies for each the unobservables, or by assuming that such unobservables satisfy convenient conditional mean or independence assumptions that enable their elimination from the estimation problem. However, thanks to tremendous increases in both the amount of data available and computing power, it has become possible to take full advantage of recent formal methods to infer the statistical properties of unobservable variables from multiple imperfect measurements of them. The general framework used is the concept of measurement systems in which a vector of observed variables is expressed as a (possibly nonlinear or nonparametric) function of a vector of all unobserved variables (including unobserved error terms or "disturbances" that may have non additively separable affects). The framework emphasizes important connections with related fields, such as nonlinear panel data, limited dependent variables, game theoretic models, dynamic models and set-identification. This review reports the progress made towards the central question of whether there exist plausible assumptions under which one can identify the joint distribution of the unobservables from the knowledge of the joint distribution of the observables. It also overviews empirical efforts aimed at exploiting such identification results to deliver novel findings that formally account for the unavoidable presence of unobservables.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: cemmap working paper ; No. CWP12/21

Klassifikation und Themen

• Klassifikation: Wirtschaft
• Thema: Messung ; Statistischer Fehler ; Schätztheorie ; Item-Response-Theorie ; Methodologie

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Schennach, Susanne M.
• Ereignis: Veröffentlichung
• (wer): Centre for Microdata Methods and Practice (cemmap)
• (wo): London
• (wann): 2021

Weitere Informationen

• DOI: doi:10.47004/wp.cem.2021.1221
• Handle: http://hdl.handle.net/10419/241948
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ