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Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models

Cizek, Pavel - EconWPA - 2002

Classical parametric estimation methods applied to nonlinear regression and limited-dependent-variable models are very sensitive to misspecification and data errors. This sensitivity is addressed by the theory of robust statistics which builds upon parametric specification, but provides...

Persistent link: https://www.econbiz.de/10005556311

Instrumental Variable Estimation for Duration Data: A Reappraisal of the Illinois Reemployment Bonus Experiment

Bijwaard, G.E. - EconWPA - 2002

We propose an Instrumental Variable method for Generalised Accelerated Failure Time (GAFT) models that adjust for possible endogeneity of the intervention of interest, without suffering the problems of the intention-to-treat method. We develop an estimatiom procedure that collapses to the linear...

Persistent link: https://www.econbiz.de/10005062568

Nonparametric Estimation of a Survivor Function with Across- Interval-Censored Data

An, Mark Yuying; Ayala, Roberto - EconWPA - 1996

Persistent link: https://www.econbiz.de/10005556346

Plug-in bandwidth selection for kernel density estimation with discrete data

Chu, Chi-Yang; Henderson, Daniel J.; Parmeter, … - In: Econometrics 3 (2015) 2, pp. 199-214

This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, in non-uniform designs. We further find that...

Persistent link: https://www.econbiz.de/10011755277

Nonparametric Slope Estimators for Fixed-Effect Panel Data

Mundra, Kusum - EconWPA - 2005

heterogeneity. This paper proposes two nonparametric slope estimation where the unobserved effect is treated as fixed across cross … variable. Simulation results suggest that the new nonparametric estimators perform better than the parametric counterparts. We …. In this paper we estimate nonparametric slope of age and tenure on earnings using NLSY data and compare it to the …

Persistent link: https://www.econbiz.de/10005119099

Top incomes, heavy tails, and rank-size regressions

Schluter, Christian - In: Econometrics 6 (2018) 1, pp. 1-16

In economics, rank-size regressions provide popular estimators of tail exponents of heavy-tailed distributions. We discuss the properties of this approach when the tail of the distribution is regularly varying rather than strictly Pareto. The estimator then over-estimates the true value in the...

Persistent link: https://www.econbiz.de/10011995211

An overview of modified semiparametric memory estimation methods

Busch, Marie; Sibbertsen, Philipp - In: Econometrics 6 (2018) 1, pp. 1-21

performance of nine semiparametric estimation methods. Among them are two standard methods, four modified approaches to account …

Persistent link: https://www.econbiz.de/10011995214

Nonparametric regression estimation for multivariate null recurrent processes

Cai, Biqing; Tjøstheim, Dag - In: Econometrics 3 (2015) 2, pp. 265-288

This paper discusses nonparametric kernel regression with the regressor being a d-dimensional ß-null recurrent process …-of-sample performance of the nonparametric model is far better than the linear model. …

Persistent link: https://www.econbiz.de/10011755281

Strategic interaction model with censored strategies

Jenish, Nazgul - In: Econometrics 3 (2015) 2, pp. 412-442

In this paper, we develop a new model of a static game of incomplete information with a large number of players. The model has two key distinguishing features. First, the strategies are subject to threshold effects, and can be interpreted as dependent censored random variables. Second, in...

Persistent link: https://www.econbiz.de/10011755287

Efficient estimation in heteroscedastic varying coefficient models

Wei, Chuanhua; Wan, Lijie - In: Econometrics 3 (2015) 3, pp. 525-531

This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct...

Persistent link: https://www.econbiz.de/10011755291