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feologit: a new command for fitting fixed-effects ordered logit models


Baetschmann, Gregori; Ballantyne, Alexander; Staub, Kevin E; Winkelmann, Rainer (2020). feologit: a new command for fitting fixed-effects ordered logit models. The Stata Journal, 20(2):253-275.

Abstract

In this article, we describe how to fit panel-data ordered logit models with fixed effects using the new community-contributed command feologit. Fixed-effects models are increasingly popular for estimating causal effects in the social sciences because they flexibly control for unobserved time-invariant heterogeneity. The ordered logit model is the standard model for ordered dependent variables, and this command is the first in Stata specifically for this model with fixed effects. The command includes a choice between two estimators, the blowup and cluster (BUC) estimator introduced in Baetschmann, Staub, and Winkelmann (2015, Journal of the Royal Statistical Society, Series A 178: 685–703) and the BUC-τ estimator in Baetschmann (2012, Economics Letters 115: 416-418). Baetschmann, Staub, and Winkelmann (2015) showed that the BUC estimator has good properties and is almost as efficient as more complex estimators such as generalized method-of-moments and empirical likelihood estimators. The command and model interpretations are illustrated with an analysis of the effect of parenthood on life satisfaction using data from the German Socio-Economic Panel.

Abstract

In this article, we describe how to fit panel-data ordered logit models with fixed effects using the new community-contributed command feologit. Fixed-effects models are increasingly popular for estimating causal effects in the social sciences because they flexibly control for unobserved time-invariant heterogeneity. The ordered logit model is the standard model for ordered dependent variables, and this command is the first in Stata specifically for this model with fixed effects. The command includes a choice between two estimators, the blowup and cluster (BUC) estimator introduced in Baetschmann, Staub, and Winkelmann (2015, Journal of the Royal Statistical Society, Series A 178: 685–703) and the BUC-τ estimator in Baetschmann (2012, Economics Letters 115: 416-418). Baetschmann, Staub, and Winkelmann (2015) showed that the BUC estimator has good properties and is almost as efficient as more complex estimators such as generalized method-of-moments and empirical likelihood estimators. The command and model interpretations are illustrated with an analysis of the effect of parenthood on life satisfaction using data from the German Socio-Economic Panel.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Mathematics (miscellaneous)
Uncontrolled Keywords:Mathematics (miscellaneous), feologit, panel data, ordered dependent variables, logistic models, fixed effects, blow-up and cluster estimator
Language:English
Date:1 June 2020
Deposited On:05 Feb 2021 10:34
Last Modified:06 Feb 2021 21:03
Publisher:Sage Publications
ISSN:1536-867X
OA Status:Closed
Publisher DOI:https://doi.org/10.1177/1536867x20930984

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