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Semiparametric Bayesian Modeling of Income Volatility Heterogeneity
hierarchical Dirichlet process income volatility state-space models
2016/3/18
Research on income risk typically treats its proxy—income volatility, the expected magnitude of income changes—as if it were unchanged for an individual over time, the same for everyone at a point in ...
A Bayesian semiparametric multilevel survival modelling of age at first birth in Nigeria
childbearing age fertility first birth geo-additive models Nigeria prior and posterior distributions spatial analysis
2014/11/24
Background: The age at which childbearing begins influences the total number of children a woman bears throughout her reproductive period, in the absence of any active fertility control. For countries...
Semiparametric Selection Models with Binary Outcomes
sample selection binary outcomes marginal effects semiparametric
2012/10/23
This paper addresses the estimation of a semiparametric sample selection index model where both the selection rule and the outcome variable are binary. Since the marginal effects are often of primary ...
Semiparametric Estimation with Generated Covariates
semiparametric estimation generated covariates profiling propensity score
2012/10/22
In this paper, we study a general class of semiparametric optimization estimators of a vector-valued parameter. The criterion function depends on two types of infinite-dimensional nuisance parameters:...
Sexual Bias and Household Consumption: A Semiparametric Analysis of Engel Curves in Rural China
Household economics consumption bias gender differences Engel curve
2013/10/17
We analyze Engel curves for nuclear households in rural China. The sample includes more than 5000 nuclear families covering nineteen out of thirty Chinese provinces. We consider expenditures on food, ...
Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables
Immigrants speaking fluency misclassification error
2013/10/17
We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-r...