Showing 1 - 8 of 8
The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the "treatment") on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing...
Persistent link: https://www.econbiz.de/10009739427
The paper reconsiders existing estimators for the panel data fixed effects ordered logit model, including one that has not been used in econometric studies before, and studies the small sample properties of these estimators in a series of Monte Carlo simulations. There are two main findings....
Persistent link: https://www.econbiz.de/10009748954
The paper re-examines existing estimators for the panel data fixed effects ordered logit model, proposes a new one, and studies the sampling properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the...
Persistent link: https://www.econbiz.de/10009738616
In this paper, we test how reporting behaviors (response time, cognitive effort, questionnaire order) affect reported happiness in a large Dutch internet panel survey. We find that slower responses and higher cognitive effort reduce reported happiness. Moreover, in multivariate happiness...
Persistent link: https://www.econbiz.de/10009742624
The paper re-examines existing estimators for the panel data fixed effects ordered logit model, proposes a new one, and studies the sampling properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the...
Persistent link: https://www.econbiz.de/10009125046
The maximum likelihood estimator for the regression coefficients, β, in a panel binary response model with fixed effects can be severely biased if N is large and T is small, a consequence of the incidental parameters problem. This has led to the development of conditional maximum likelihood...
Persistent link: https://www.econbiz.de/10011764680
The paper introduces two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regressions with averaged data, meta regressions and the linear probability model. While one estimator builds...
Persistent link: https://www.econbiz.de/10014551389
The paper considers two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regression with averaged data, meta regression and the linear probability model. While one estimator builds on...
Persistent link: https://www.econbiz.de/10015062188