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Efficiency of average treatment effect estimation when the true propensity is parametric

Kim, Kyoo Il - In: Econometrics : open access journal 7 (2019) 2/25, pp. 1-13

It is well known that efficient estimation of average treatment effects can be obtained by the method of inverse propensity score weighting, using the estimated propensity score, even when the true one is known. When the true propensity score is unknown but parametric, it is conjectured from the...

Persistent link: https://www.econbiz.de/10012025779

Generalized information matrix tests for detecting model misspecification

Golden, Richard M.; Henley, Steven S.; White, Halbert; … - In: Econometrics : open access journal 4 (2016) 4, pp. 1-24

Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is developed for the purpose of identifying,...

Persistent link: https://www.econbiz.de/10011650480

Outliers in semi-parametric estimation of treatment effects

Canavire-Bacarreza, Gustavo; Castro, Luis; Ontiveros, … - In: Econometrics : open access journal 9 (2021) 2, pp. 1-32

Outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric estimates. In this … presence of outliers. Bad and good leverage point outliers are considered. Bias arises in the case of bad leverage points … correct for the effects of outliers following a reweighting strategy in the spirit of the Stahel-Donoho (SD) multivariate …

Persistent link: https://www.econbiz.de/10012547410

Testing for a set of linear restrictions in VARMA models using autoregressive metric : an application to Granger causality test

Di Iorio, Francesca; Triacca, Umberto - In: Econometrics : open access journal 2 (2014) 4, pp. 203-216

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Persistent link: https://www.econbiz.de/10010479050

Building a structural model : parameterization and structurality

Mouchart, Michel; Orsi, Renzo - In: Econometrics : open access journal 4 (2016) 2, pp. 1-16

A specific concept of structural model is used as a background for discussing the structurality of its parameterization. Conditions for a structural model to be also causal are examined. Difficulties and pitfalls arising from the parameterization are analyzed. In particular, pitfalls when...

Persistent link: https://www.econbiz.de/10011506231

The biggest myth in spatial econometrics

Lesage, James P.; Pace, R. Kelley - In: Econometrics : open access journal 2 (2014) 4, pp. 217-249

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

Persistent link: https://www.econbiz.de/10010479047

Interpretation and semiparametric efficiency in quantile regression under misspecification

Lee, Ying-ying - In: Econometrics : open access journal 4 (2016) 1, pp. 1-14

Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β ( τ ) in Koenker and Bassett (1978). The first result on interpretation shows that under a...

Persistent link: https://www.econbiz.de/10011411323

On the asymptotic distribution of ridge regression estimators using training and test samples

Sengupta, Nandana; Sowell, Fallaw - In: Econometrics : open access journal 8 (2020) 4/39, pp. 1-25

The asymptotic distribution of the linear instrumental variables (IV) estimator with empirically selected ridge regression penalty is characterized. The regularization tuning parameter is selected by splitting the observed data into training and test samples and becomes an estimated parameter...

Persistent link: https://www.econbiz.de/10012312086

The discovery of long-run causal order : a preliminary investigation

Hoover, Kevin D. - In: Econometrics : open access journal 8 (2020) 3/31, pp. 1-24

The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending...

Persistent link: https://www.econbiz.de/10012265689

Lasso maximum likelihood estimation of parametric models with singular information matrices

Jin, Fei; Lee, Lung-fei - In: Econometrics : open access journal 6 (2018) 1, pp. 1-24

An information matrix of a parametric model being singular at a certain true value of a parameter vector is irregular. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the √n-rate in a regular case. We propose to estimate such models by the...

Persistent link: https://www.econbiz.de/10011823268

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