Domestic and Global Determinants of Inflation: Evidence from Expectile Regression

Weighted expectile regression for right‐censored data

Statistics in Medicine ◽

10.1002/sim.9137 ◽

2021 ◽

Author(s):

Alexander Seipp ◽

Verena Uslar ◽

Dirk Weyhe ◽

Antje Timmer ◽

Fabian Otto‐Sobotka

Keyword(s):

Censored Data ◽

Right Censored Data ◽

Expectile Regression

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Generalized expectile regression with flexible response function

Biometrical Journal ◽

10.1002/bimj.202000203 ◽

2021 ◽

Author(s):

Elmar Spiegel ◽

Thomas Kneib ◽

Petra von Gablenz ◽

Fabian Otto‐Sobotka

Keyword(s):

Response Function ◽

Expectile Regression ◽

Flexible Response

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Spatio-temporal expectile regression models

Statistical Modelling ◽

10.1177/1471082x19829945 ◽

2019 ◽

Vol 20 (4) ◽

pp. 386-409

Author(s):

Elmar Spiegel ◽

Thomas Kneib ◽

Fabian Otto-Sobotka

Keyword(s):

Tensor Product ◽

Least Squares Regression ◽

Expectile Regression ◽

Specific Distribution ◽

Weighted Means ◽

Temporal Models ◽

Error Terms ◽

Spatio Temporal ◽

Set Up ◽

Main Effects

Spatio-temporal models are becoming increasingly popular in recent regression research. However, they usually rely on the assumption of a specific parametric distribution for the response and/or homoscedastic error terms. In this article, we propose to apply semiparametric expectile regression to model spatio-temporal effects beyond the mean. Besides the removal of the assumption of a specific distribution and homoscedasticity, with expectile regression the whole distribution of the response can be estimated. For the use of expectiles, we interpret them as weighted means and estimate them by established tools of (penalized) least squares regression. The spatio-temporal effect is set up as an interaction between time and space either based on trivariate tensor product P-splines or the tensor product of a Gaussian Markov random field and a univariate P-spline. Importantly, the model can easily be split up into main effects and interactions to facilitate interpretation. The method is presented along the analysis of spatio-temporal variation of temperatures in Germany from 1980 to 2014.

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