ScholarGate
Assistent
Regression modelQuasi-experimental / causal inference

Robust Instrumental Variables Estimation

Robust Instrumental Variables estimation udvider standard IV og to-trins mindste kvadraters metode (2SLS) ved at beskytte mod svag-instrument bias og ikke-standard inferens. Metoder som Anderson-Rubin-testen, Limited Information Maximum Likelihood (LIML) og Conditional Likelihood Ratio-testen giver gyldige konfidensintervaller og hypotesetest, selv når instrumenterne er svage eller kun delvist identificerede, hvilket gør IV-inferens pålidelig i situationer, hvor standard 2SLS bryder sammen.

Åbn i MethodMindSnartVideoSnartDownload slides

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Method map

The neighbourhood of related methods — select a node to explore.

Kilder

  1. Stock, J. H., Wright, J. H., & Yogo, M. (2002). A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics, 20(4), 518-529. DOI: 10.1198/073500102288618658
  2. Andrews, I., Stock, J. H., & Sun, L. (2019). Weak instruments in instrumental variables regression: Theory and practice. Annual Review of Economics, 11, 727-753. DOI: 10.1146/annurev-economics-080218-025643

Sådan citerer du denne side

ScholarGate. (2026, June 3). Robust Instrumental Variables Estimation. ScholarGate. https://scholargate.app/da/causal-inference/robust-instrumental-variables

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateRobust Instrumental Variables (Robust Instrumental Variables Estimation). Hentet 2026-06-15 fra https://scholargate.app/da/causal-inference/robust-instrumental-variables · Datasæt: https://doi.org/10.5281/zenodo.20539026