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A computationally practical simulation estimation algorithm for dynamic panel data models with unobserved endogenous state variables
Keane, Michael P.; Sauer, Robert M. - 2009
This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data …
Persistent link: https://www.econbiz.de/10010271244
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Inference for rank-rank regressions
Chetverikov, Denis N.; Wilhelm, Daniel - 2023
Slope coefficients in rank-rank regressions are popular measures of intergenerational mobility, for instance in regressions of a child's income rank on their parent's income rank. In this paper, we first point out that commonly used variance estimators such as the homoskedastic or robust...
Persistent link: https://www.econbiz.de/10014480485
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Identification and estimation of nonlinear dynamic panel data models with unobserved covariates
Shiu, Ji-Liang; Hu, Yingyao - 2010
This paper considers nonparametric identification of nonlinear dynamic models for panel data with unobserved voariates …. We also propose a sieve maximum likelihood estimator (MLE) and focus on two classes of nonlinear dynamic panel data … female labor force participation model is estimated as an empirical illustration using a sample from the Panel Study of …
Persistent link: https://www.econbiz.de/10010277530
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Sequential Matching Estimation of Dynamic Causal Models
Lechner, Michael - 2004
This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic causal effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...
Persistent link: https://www.econbiz.de/10010261808
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Simplified implementation of the Heckman estimator of the dynamic probit model and a comparison with alternative estimators
Arulampalam, Wiji; Stewart, Mark B. - 2007
This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynamic random effects probit model using standard software. It then compares the three estimators proposed by Heckman, Orme and Wooldridge based on three alternative approximations, first in an...
Persistent link: https://www.econbiz.de/10010268488
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Time-varying linear transformation models with fixed effects and endogeneity for short panels
Botosaru, Irene; Muris, Chris; Sokullu, Senay - 2022
This paper considers a class of fixed-T nonlinear panel models with timevarying link function, fixed effects, and …
Persistent link: https://www.econbiz.de/10013253005
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Semiparametric estimation with generated covariates
Mammen, Enno; Rothe, Christoph; Schienle, Melanie - 2011
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: a conditional expectation function that has been estimated nonparametrically using generated...
Persistent link: https://www.econbiz.de/10010281571
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The empirical relation between credit quality, recovery and correlation
Rösch, Daniel; Scheule, Harald - 2009
correlation. …
Persistent link: https://www.econbiz.de/10010276410
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Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance
Herwartz, Helmut; Golosnoy, Vasyl - 2007
We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data …. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily … correlation matrices and exogenous factors. The Fisher-z transformation guarantees robustness of correlation estimators under …
Persistent link: https://www.econbiz.de/10010296287
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Nonparametric Regression on Latent Covariates with an Application to Semiparametric GARCH-in-Mean Models
Conrad, Christian; Mammen, Enno - 2008
We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...
Persistent link: https://www.econbiz.de/10011422182