Outputs (10)

Large sample properties of GMM estimators under second-order identification (2023)
Working Paper
Kruiniger, H. (2022). Large sample properties of GMM estimators under second-order identification

Dovonon and Hall (Journal of Econometrics, 2018) proposed a limiting distribution theory for GMM estimators for a p - dimensional globally identified parameter vector {\phi} when local identification conditions fail at first-order but hold at second-... Read More about Large sample properties of GMM estimators under second-order identification.

Further results on the estimation of dynamic panel logit models with fixed effects (2023)
Working Paper
Kruiniger, H. (2020). Further results on the estimation of dynamic panel logit models with fixed effects

Kitazawa (2013, 2016) showed that the common parameters in the panel logit AR(1) model with strictly exogenous covariates and fixed effects are estimable at the root-n rate using the Generalized Method of Moments. Honoré and Weidner (2020) extended h... Read More about Further results on the estimation of dynamic panel logit models with fixed effects.

Estimation of dynamic panel data models with a lot of heterogeneity (2021)
Journal Article
Kruiniger, H. (2022). Estimation of dynamic panel data models with a lot of heterogeneity. Econometric Reviews, 41(2), 117-146. https://doi.org/10.1080/07474938.2021.1899507

The commonly used 1-step and 2-step System GMM estimators for the panel AR(1) model are inconsistent under mean stationarity when the ratio of the variance of the individual e§ects to the variance of the idiosyncratic errors is unbounded when N ! 1.... Read More about Estimation of dynamic panel data models with a lot of heterogeneity.

Identification without assuming mean-stationarity: Quasi ML estimation of dynamic panel models with endogenous regressors (2020)
Journal Article
Kruiniger, H. (2021). Identification without assuming mean-stationarity: Quasi ML estimation of dynamic panel models with endogenous regressors. The Econometrics Journal, 24(3), 417-441. https://doi.org/10.1093/ectj/utaa036

Linear GMM estimators for dynamic panel models with predetermined or endogenous regressors suffer from a weak instruments problem when the data are highly persistent. In this paper we propose new random and fixed effects Limited Information Quasi ML... Read More about Identification without assuming mean-stationarity: Quasi ML estimation of dynamic panel models with endogenous regressors.

A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions (2018)
Working Paper
Kruiniger, H. (2018). A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions

In this paper we consider two kinds of generalizations of Lancaster's (Review of Economic Studies, 2002) Modified ML estimator (MMLE) for the panel AR(1) model with fixed effects and arbitrary initial conditions and possibly covariates when the time... Read More about A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions.

Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions (2013)
Journal Article
Kruiniger, H. (2013). Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions. Journal of Econometrics, 173(2), https://doi.org/10.1016/j.jeconom.2012.11.004

In this paper we show that the Quasi ML estimation method yields consistent Random and Fixed Effects estimators for the autoregression parameter ρ in the panel AR(1) model with arbitrary initial conditions and possibly time-series heteroskedasticity... Read More about Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions.

GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data. (2009)
Journal Article
Kruiniger, H. (2009). GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data. Econometric Theory, 25(5), 1348-1391. https://doi.org/10.1017/s0266466608090531

In this paper we consider generalized method of moments–based (GMM-based) estimation and inference for the panel AR(1) model when the data are persistent and the time dimension of the panel is fixed. We find that the nature of the weak instruments pr... Read More about GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data..

Maximum Likelihood Estimation and Inference Methods for the Covariance Stationary Panel AR(1)/Unit Root Model (2008)
Journal Article
Kruiniger, H. (2008). Maximum Likelihood Estimation and Inference Methods for the Covariance Stationary Panel AR(1)/Unit Root Model. Journal of Econometrics, 144(2), 447-464. https://doi.org/10.1016/j.jeconom.2008.03.001

This paper considers Maximum Likelihood (ML) based estimation and inference procedures for linear dynamic panel data models with fixed effects. The paper first studies the asymptotic properties of MaCurdy’s [MaCurdy, T., 1982. The use of time series... Read More about Maximum Likelihood Estimation and Inference Methods for the Covariance Stationary Panel AR(1)/Unit Root Model.

An efficient linear GMM estimator for the covariance stationary AR (1)/unit root model for panel data (2007)
Journal Article
Kruiniger, H. (2007). An efficient linear GMM estimator for the covariance stationary AR (1)/unit root model for panel data. Econometric Theory, 23(3), 519-535. https://doi.org/10.1017/s0266466607070235

This paper considers generalized method of moments (GMM) estimation of the inclusive panel AR(1) model that contains the covariance stationary panel AR(1) model and the panel AR(1) model with a unit root as special cases. The paper presents a two-ste... Read More about An efficient linear GMM estimator for the covariance stationary AR (1)/unit root model for panel data.

On the solution of the linear rational expectations model with multiple lags (1999)
Journal Article
Kruiniger, H. (2000). On the solution of the linear rational expectations model with multiple lags. Journal of Economic Dynamics and Control, 24(4), 535-559. https://doi.org/10.1016/S0165-1889%2899%2900006-8

In this paper the symmetric linear rational expectations model from Kollintzas (1985) is generalized by allowing for multiple lags. By using a convenient decomposition of the matrix lag polynomial of the Euler–Lagrange equations that encompasses that... Read More about On the solution of the linear rational expectations model with multiple lags.