A framework for estimating dynamic, unobserved effects panel data models with possible feedback to future explanatory variables

DOI10.1016/S0165-1765(00)00230-5zbMath1026.91525MaRDI QIDQ1606444

Jeffrey M. Wooldridge

Publication date: 1 September 2002

Published in: Economics Letters (Search for Journal in Brave)

zbMATH Keywords

maximum likelihood estimatorlikelihood functioninitial conditions problem

Mathematics Subject Classification ID

Statistical methods; economic indices and measures (91B82)

Related Items (9)

Birth-spacing, fertility and neonatal mortality in India: dynamics, frailty, and fecundity ⋮ Non-causality in bivariate binary time series ⋮ Two tests for strict exogeneity in a correlated random effects panel data Tobit model ⋮ Estimating willingness to pay for Medicare using a dynamic life-cycle model of demand for health insurance ⋮ Correlated random effects models with unbalanced panels ⋮ Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data ⋮ Fixed effects estimation of structural parameters and marginal effects in panel probit models ⋮ Bias corrections for two-step fixed effects panel data estimators ⋮ A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressorsa

Cites Work

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• Semi-Nonparametric Maximum Likelihood Estimation
• Estimating Vector Autoregressions with Panel Data
• Efficient estimation of models for dynamic panel data
• Two-step estimation of panel data models with censored endogenous variables and selection bias
• The Effect of Sample Selection and Initial Conditions in Duration Models: Evidence from Experimental Data on Training
• Econometrics

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