Analysis of private transfers with panel fixed-effect censored model estimator
نویسندگان
چکیده
منابع مشابه
First-difference estimator for panel censored-selection models
We propose a semiparametric first-difference estimator for panel censored-selection models where the selection equation is of tobit type. The estimator allows the unit-specific term to be arbitrarily related to regressors. The estimator minimizes a convex function and does not require any smoothing. A simulation study is provided comparing our proposal with the estimators of Wooldridge (Journal...
متن کاملLinear Regression for Dependently Censored Panel Duration Models with Nonadditive Fixed Effects
This paper proposes estimators for a class of panel duration models with induced dependent censoring and fixed effects which may appear nonadditively in the model. No parametric assumptions are made about the distribution of the random error. The dependent censoring implies that the usual differencing approach common in fixed-effects models will lead to disproportionate weighting of the errors,...
متن کاملEstimation of a Censored Dynamic Panel Data Model
This paper proposes a method for estimating a censored panel data model with a lagged latent dependent variable and individual-specific fixed effects. The main insight is to trim observations in such a way that a certain symmetry, which was destroyed by censoring, is restored. Based on the restored symmetry, orthogonality conditions are constructed and GMM estimation is implemented. Valid asymp...
متن کاملEmpirical likelihood analysis of the rank estimator for the censored accelerated failure time model
We use the empirical likelihood method to derive a test and thus a confidence interval based on the rank estimators of the regression coefficient in the accelerated failure time model. Standard chi-squared distributions are used to calculate the p-value and to construct the confidence interval. Simulations and examples show that the chi-squared approximation to the distribution of the log empir...
متن کاملKernel Ridge Estimator for the Partially Linear Model under Right-Censored Data
Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Economics Letters
سال: 2003
ISSN: 0165-1765
DOI: 10.1016/s0165-1765(03)00083-1