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Empirical economists are often deterred from the application of fixed effects binary choice models mainly for two reasons: the incidental parameter problem and the computational challenge even in moderately large panels. Using the example…

Econometrics · Economics 2020-10-27 Daniel Czarnowske , Amrei Stammann

We use the jackknife to bias correct the log-periodogram regression(LPR) estimator of the fractional parameter in a stationary fractionally integrated model. The weights for the jackknife estimator are chosen in such a way that bias…

Methodology · Statistics 2020-10-19 Kanchana Nadarajah , Gael M Martin , Donald S Poskitt

In many applications, parameters of interest are estimated by solving some non-smooth estimating equations with $U$-statistic structure. Jackknife empirical likelihood (JEL) approach can solve this problem efficiently by reducing the…

Methodology · Statistics 2019-06-18 Yongli Sang , Xin Dang , Yichuan Zhao

Jackknife empirical likelihood (JEL) is an effective modified version of empirical likelihood method (EL). Through the construction of the jackknife pseudo-values, JEL overcomes the computational difficulty of EL method when its constraints…

Methodology · Statistics 2016-03-15 Ying-Ju Chen , Wei Ning

We derive fixed effects estimators of parameters and average partial effects in (possibly dynamic) nonlinear panel data models with individual and time effects. They cover logit, probit, ordered probit, Poisson and Tobit models that are…

Methodology · Statistics 2018-12-19 Ivan Fernandez-Val , Martin Weidner

Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias correction method has no effect on the higher-order variance of semiparametrically efficient parametric estimators, so long as…

Econometrics · Economics 2024-01-29 Jinyong Hahn , David W. Hughes , Guido Kuersteiner , Whitney K. Newey

This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where…

Econometrics · Economics 2018-03-29 Iván Fernández-Val , Martin Weidner

Inference for fixed effects estimators is often unreliable due to Nickell- and incidental parameter biases. While these issues are well understood for classical two-dimensional panels, little is known about three-dimensional panel…

Econometrics · Economics 2026-05-05 Daniel Czarnowske , Amrei Stammann

We present the Stata commands probitfe and logitfe, which estimate probit and logit panel data models with individual and/or time unobserved effects. Fixed effect panel data methods that estimate the unobserved effects can be severely…

Methodology · Statistics 2018-01-16 Mario Cruz-Gonzalez , Ivan Fernandez-Val , Martin Weidner

In panel predictive regressions with persistent covariates, coexistence of the Nickell bias and the Stambaugh bias imposes challenges for estimation and hypothesis testing. This paper introduces an innovative estimator, the Double IVX…

Econometrics · Economics 2026-05-26 Chengwang Liao , Ziwei Mei , Zhentao Shi

This paper identifies an important bias - termed dynamic bias - in fixed effects panel estimators that arises when dynamic feedback is ignored in the estimating equation. Dynamic feedback occurs if past outcomes impact current outcomes, a…

Econometrics · Economics 2024-10-22 Sylvia Klosin

Jackknife instrumental variable estimation (JIVE) is a classic method to leverage many weak instrumental variables (IVs) to estimate linear structural models, overcoming the bias of standard methods like two-stage least squares. In this…

Statistics Theory · Mathematics 2024-10-08 Aurélien Bibaut , Nathan Kallus , Apoorva Lal

Small area estimation has received enormous attention in recent years due to its wide range of application, particularly in policy making decisions. The variance based on direct sample size of small area estimator is unduly large and there…

Statistics Theory · Mathematics 2007-06-13 Soumendra N. Lahiri , Tapabrata Maiti

In this paper, we study the asymptotic bias of the factor-augmented regression estimator and its reduction, which is augmented by the $r$ factors extracted from a large number of $N$ variables with $T$ observations. In particular, we…

Methodology · Statistics 2025-10-02 Peiyun Jiang , Yoshimasa Uematsu , Takashi Yamagata

Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands dependence function. Some estimators for…

Statistics Theory · Mathematics 2013-03-21 Liang Peng , Linyi Qian , Jingping Yang

This paper considers fixed effects (FE) estimation for linear panel data models under possible model misspecification when both the number of individuals, $n$, and the number of time periods, $T$, are large. We first clarify the probability…

Statistics Theory · Mathematics 2014-03-12 Antonio F. Galvao , Kengo Kato

In the present article, we discuss jackknife empirical likelihood (JEL) and adjusted jackknife empirical likelihood (AJEL) based inference for finding confidence intervals for probability weighted moment (PWM). We obtain the asymptotic…

Methodology · Statistics 2018-07-13 Deepesh Bhati , Sudheesh K Kattumannil , N Sreelakshmi

I introduce a new method for bias correction of dyadic models with agent-specific fixed effects, including the dyadic link formation model with homophily and degree heterogeneity. The proposed approach uses a jackknife procedure to deal…

Econometrics · Economics 2025-11-18 David W. Hughes

Interactive fixed effects are routinely controlled for in linear panel models. While an analogous fixed effects (FE) estimator for nonlinear models has been available in the literature (Chen, Fernandez-Val and Weidner, 2021), it sees much…

Econometrics · Economics 2026-03-25 Andrei Zeleneev , Weisheng Zhang

Local projections (LPs) are widely used in empirical macroeconomics to estimate impulse responses to policy interventions. Yet, in many ways, they are black boxes. It is often unclear what mechanism or historical episodes drive a particular…

Econometrics · Economics 2025-07-30 Philippe Goulet Coulombe , Karin Klieber
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