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Panel Data Econometrics: Modelling and Estimation
Hübler, Olaf - 2005
multilevel models with a new variant are discussed. Furthermore, non-linear, nonparametric and semiparametric models are analyzed …. In contrast to linear models there do not exist unified methods for nonlinear approaches. In this case FEM are dominated … simulated estimators exist. If the nonlinear function is not exactly known, nonparametric or semiparametric methods should be …
Persistent link: https://www.econbiz.de/10010262940
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Multilevel and nonlinear panel data models
Hübler, Olaf - In: AStA Advances in Statistical Analysis 90 (2006) 1, pp. 121-136
Persistent link: https://www.econbiz.de/10005155560
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Age-cohort-time effects in sickness absence : exploring a large data set by polynomial regression
Biørn, Erik - 2013
Identification of equations explaining a continuous variable, e.g., the length of sickness absence spells, by age, cohort and time (ACT), subject to their definitional identity is reconsidered. Various extensions of a linear equation to polynomials are explored. If no interactions between the...
Persistent link: https://www.econbiz.de/10009757087
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Identifying age-cohort-time effects, their curvature and interactions from polynomials : examples related to sickness absence
Biørn, Erik - 2013
In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including...
Persistent link: https://www.econbiz.de/10009723903
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Identifying Age-Cohort-Time Effects, Their Curvature and Interactions from Polynomials: Examples Related to Sickness Absence
Biørn, Erik - Økonomisk institutt, Universitetet i Oslo - 2013
In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including...
Persistent link: https://www.econbiz.de/10010785532
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Age-Cohort-Time Effects in Sickness Absence: Exploring a Large Data Set by Polynomial Regression
Biørn, Erik - Økonomisk institutt, Universitetet i Oslo - 2013
Identification of equations explaining a continuous variable, e.g., the length of sickness absence spells, by age, cohort and time (ACT), subject to their definitional identity is reconsidered. Various extensions of a linear equation to polynomials are explored. If no interactions between the...
Persistent link: https://www.econbiz.de/10010785538
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Identifying age-cohort-time effects, their curvature and interactions from polynomials: Examples related to sickness absence
Biørn, Erik - 2013
In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including...
Persistent link: https://www.econbiz.de/10010330247
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Age-cohort-time effects in sickness absence: Exploring a large data set by polynomial regression
Biørn, Erik - 2013
Identification of equations explaining a continuous variable, e.g., the length of sickness absence spells, by age, cohort and time (ACT), subject to their definitional identity is reconsidered. Various extensions of a linear equation to polynomials are explored. If no interactions between the...
Persistent link: https://www.econbiz.de/10010330256
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Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects
Mugnier, Martin; Wang, Ao - 2022
We study a nonlinear two-way fixed effects panel model that allows for unobserved individual heterogeneity in slopes …
Persistent link: https://www.econbiz.de/10014078902
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Treatment evaluation with multiple outcome periods under endogeneity and attrition
Frölich, Markus; Huber, Martin - 2014
This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...
Persistent link: https://www.econbiz.de/10010249397