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Expend, a Gauss programme for non-linear GMM estimation of exponential models with endogenous regressors for cross section and panel data

Windmeijer, Frank - 2002

endogenous regressors for cross section and panel data. The estimators included in this package are simple Poisson pseudo ML; GMM … Poisson for panel data; GMM estimation using quasi-differenced moment conditions eliminating unobserved heterogeneity and …

Persistent link: https://www.econbiz.de/10010318531

Identification in a binary choice panel data model with a predetermined covariate

Bonhomme, Stéphane; Dano, Kevin; Graham, Bryan S. - 2023

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a …

Persistent link: https://www.econbiz.de/10014480540

Perception and retrospection: The dynamic consistency of responses to survey questions on wellbeing

Pudney, Stephen - 2010

a vector ARMA model for panel data, with dependent variables observed ordinally and find that current perceptions …

Persistent link: https://www.econbiz.de/10010288374

Estimation of dynamic linear models in short panels with ordinal observation

Pudney, Stephen E. - 2005

We develop a simulated ML method for short-panel estimation of one or more dynamic linear equations, where the …

Persistent link: https://www.econbiz.de/10010318504

The weak instrument problem of the system GMM estimator in dynamic panel data models

Bun, Maurice; Windmeijer, Frank - 2007

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences … model in terms of bias and root mean squared error. However, we show in this paper that in the covariance stationary panel … results are shown in a Monte Carlo study to extend to the panel data system GMM estimator. …

Persistent link: https://www.econbiz.de/10010318586

Inverse probability weighted estimation for general missing data problems

Wooldridge, Jeffrey M. - 2004

I study inverse probability weighted M-estimation under a general missing data scheme. The cases covered that do not previously appear in the literature include M-estimation with missing data due to a censored survival time, propensity score estimation of the average treatment effect for linear...

Persistent link: https://www.econbiz.de/10010318477

Nonparametric identification and estimation with non-classical errors-in-variables

Evdokimov, Kirill S.; Zeleneev, Andrei - 2024

This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and...

Persistent link: https://www.econbiz.de/10014581847

Estimating average marginal effects in nonseparable structural systems

Schennach, Susanne; White, Halbert; Chalak, Karim - 2007

We provide nonparametric estimators of derivative ratio-based average marginal effects of an endogenous cause, X, on a response of interest, Y , for a system of recursive structural equations. The system need not exhibit linearity, separability, or monotonicity. Our estimators are local indirect...

Persistent link: https://www.econbiz.de/10010318554

Generalized empirical likelihood estimamtors and tests under partial, weaks and strong identification

Guggenberger, Patrik; Smith, Richard J. - 2003

The principal purpose of this paper is to describe the performance of generalized empirical likelihood (GEL) methods for time series instrumental variable models specified by nonlinear moment restrictions when identification may be weak. The paper makes two main contributions. Firstly, we show...

Persistent link: https://www.econbiz.de/10010318480

Generalized empirical likelihood tests in time models with potential identification failure

Guggenberger, Patrik; Smith, Richard J. - 2005

We introduce test statistics based on generalized empirical likelihood methods that can be used to test simple hypotheses involving the unknown parameter vector in moment condition time series models. The test statistics generalize those in Guggenberger and Smith (2005) from the i.i.d. to the...

Persistent link: https://www.econbiz.de/10010318483

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