Estimation of random-effects dynamic probit models for panel data entailsthe so-called “initial conditions problem”. We argue that the relative finite-sample performance of the two main competing solutions is driven by themagnitude of the individual unobserved heterogeneity and/or of the statedependence in the data. We investigate our conjecture by means of a com-prehensive Monte Carlo experiment and offer useful indications for the practitioner
Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental para...
Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specifi...
A novel for multivariate dynamic panel data analysis with correlated random effects is proposed when...
Estimation of random-effects dynamic probit models for panel data entailsthe so-called “initial cond...
Estimation of random-effects dynamic probit models for panel data entails the so-called ``initial co...
For discrete panel data, the dynamic relationship between successive observations is often of intere...
We present a method to estimate and predict fixed effects in a panel probit model when N is large an...
In this paper, new estimating methods proposed for dynamic and static probit models with panel data....
This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynam...
For discrete panel data, the dynamic relationship between successive observations is often of intere...
This paper presents the gretl function package DPB for estimating dynamic binary models with panel d...
This paper presents the gretl function package DPB for estimating dynamic binary models with panel d...
In this paper, we analyze a dynamic panel probit model with two flexible latent effects: first, unob...
We propose four different GMM estimators that allow almost consistent estimation of the structural p...
Panel data models are widely used in empirical analysis because they allow researchers to control fo...
Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental para...
Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specifi...
A novel for multivariate dynamic panel data analysis with correlated random effects is proposed when...
Estimation of random-effects dynamic probit models for panel data entailsthe so-called “initial cond...
Estimation of random-effects dynamic probit models for panel data entails the so-called ``initial co...
For discrete panel data, the dynamic relationship between successive observations is often of intere...
We present a method to estimate and predict fixed effects in a panel probit model when N is large an...
In this paper, new estimating methods proposed for dynamic and static probit models with panel data....
This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynam...
For discrete panel data, the dynamic relationship between successive observations is often of intere...
This paper presents the gretl function package DPB for estimating dynamic binary models with panel d...
This paper presents the gretl function package DPB for estimating dynamic binary models with panel d...
In this paper, we analyze a dynamic panel probit model with two flexible latent effects: first, unob...
We propose four different GMM estimators that allow almost consistent estimation of the structural p...
Panel data models are widely used in empirical analysis because they allow researchers to control fo...
Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental para...
Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specifi...
A novel for multivariate dynamic panel data analysis with correlated random effects is proposed when...
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