RT - Journal Article
T1 - Bayesian Analysis of Regression Models Using Instrumental Variables: A Case Study (Iranian Rural Households Income and Expenditure Data)
JF - srtc-jsri
YR - 2017
JO - srtc-jsri
VO - 14
IS - 1
UR - http://jsri.srtc.ac.ir/article-1-254-en.html
SP - 53
EP - 75
K1 - Instrumental variable
K1 - endogenous (exogenous) variable
K1 - bayesian inference
K1 - skew-normal distribution
K1 - Markov chain Monte Carlo logarithm
AB - The instrumental variable (IV) regression is a common model in econometrics and other applied disciplines. This model is one of the proper candidate in dealing with endogeneity phenomenon which occurs in analyzing the multivariate regression when the errors are correlated with some covariates. One can consider IV regression as a special case of simultaneous equation models (SEM). There are some cases in which the normality assumption might not hold for the error term in these models and so the skew-normal distribution might be a suitable candidate. The present paper tackle the Bayesian inference based on Markov Chain Monte Carlo (MCMC) using this density for the error term while some instrumental variables are considered in the corresponding regression model. The proposed model is utilized to analysis the Iranian rural households income and expenditure collected in 2009.
LA eng
UL http://jsri.srtc.ac.ir/article-1-254-en.html
M3 10.18869/acadpub.jsri.14.1.53
ER -