Dealing with endogeneity in a time‐varying parameter model: joint estimation and two‐step estimation procedures

DOI10.1111/j.1368-423X.2011.00353.xzbMath1284.62537OpenAlexW2101617965MaRDI QIDQ4913920

Chang-Jin Kim, Yunmi Kim

Publication date: 17 April 2013

Published in: The Econometrics Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1368-423x.2011.00353.x

zbMATH Keywords

endogeneitygenerated regressorscontrol function approachtwo-step estimation proceduretime-varying parameter modeljoint estimation procedure

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Non-Markovian processes: estimation (62M09) Non-Markovian processes: hypothesis testing (62M07)

Related Items

A constrained state space approach for estimating firm efficiency ⋮ Battese-Coelli estimator with endogenous regressors ⋮ Regime-dependent fiscal multipliers in the United States ⋮ An extensive study on Markov switching models with endogenous regressors ⋮ Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing ⋮ Dealing with endogeneity in a time‐varying parameter model: joint estimation and two‐step estimation procedures ⋮ Estimation of market power in the presence of firm level inefficiencies

Uses Software

• bvarsv

Cites Work

• Some identification and estimation results for regression models with stochastically varying coefficients
• Consumption and the credit market
• Time-varying parameter models with endogenous regressors
• Econometric Issues in the Analysis of Regressions with Generated Regressors
• Estimation in the Presence of Stochastic Parameter Variation
• Dealing with endogeneity in a time‐varying parameter model: joint estimation and two‐step estimation procedures
• Time Varying Structural Vector Autoregressions and Monetary Policy