Data/hora: 05/06/2024 00:50:13

Provedor de dados: | 31
País: | United States
Título: | Jackknife instrumental variables estimation in Stata
Autores: | Poi,   Brian P.
Data: | 2011-11-04
Ano: | 2006
Palavras-chave: | Jive; 2SLS; LIML; JIVE; Instrumental variables; Endogeneity; Weak instruments; Research Methods/ Statistical Methods.
Resumo: | The two-stage least-squares (2SLS) instrumental variables estimator is commonly used to address endogeneity. However, the estimator suffers from bias that is exacerbated when the instruments are only weakly correlated with the endogenous variables and when many instruments are used. In this article, I discuss jackknife instrumental variables estimation as an alternative to 2SLS. Monte Carlo simulations comparing the jackknife instrument variables estimators to 2SLS and limited information maximum likelihood (LIML) show that two of the four variants perform remarkably well even when 2SLS does not. In a weak-instrument experiment, the two best performing jackknife estimators also outperform LIML.
Tipo: | Journal Article
Idioma: | Inglês

Identificador:

st0108

http://purl.umn.edu/117586

Relação: | Stata Journal&gt;Volume 6, Number 3, 3rd Quarter 2006
Formato: | 13