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You searched for: Source 2017 v.200 no.2 Remove constraint Source: 2017 v.200 no.2 Subject economic analysis Remove constraint Subject: economic analysis Subject algorithms Remove constraint Subject: algorithms Subject economic theory Remove constraint Subject: economic theory
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1. Bayesian moment-based inference in a regression model with misclassification error

Author:
Bollinger, Christopher R.; van Hasselt, Martijn
Source:
Journal of econometrics 2017 v.200 no.2 pp. 282-294
ISSN:
0304-4076
Subject:
Bayesian theory; algorithms; data collection; econometric models; economic analysis; economic theory; pain; probability; regression analysis
Abstract:
... We present a Bayesian analysis of a regression model with a binary covariate that may have classification (measurement) error. Prior research demonstrates that the regression coefficient is only partially identified. We take a Bayesian approach which adds assumptions in the form of priors on the unknown misclassification probabilities. The approach is intermediate between the frequentist bounds of ...
DOI:
10.1016/j.jeconom.2017.06.011

2. Simulated minimum distance estimation of dynamic models with errors-in-variables

Author:
Gospodinov, Nikolay; Komunjer, Ivana; Ng, Serena
Source:
Journal of econometrics 2017 v.200 no.2 pp. 181-193
ISSN:
0304-4076
Subject:
algorithms; dynamic models; econometric models; economic analysis; economic theory; empirical research; least squares; risk
Abstract:
... Empirical analysis often involves using inexact measures of the predictors suggested by economic theory. The bias created by the correlation between the mismeasured regressors and the error term motivates the need for instrumental variable estimation. This paper considers a class of estimators that can be used in dynamic models with measurement errors when external instruments may not be available ...
DOI:
10.1016/j.jeconom.2017.06.004