Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/68527
Authors: 
Polasek, Wolfgang
Year of Publication: 
2011
Series/Report no.: 
Economics Series, Institute for Advanced Studies 275
Abstract: 
The extended Hodrick-Prescott (HP) method was developed by Polasek (2011) for a class of data smoother based on second order smoothness. This paper develops a new extended HP smoothing model that can be applied for spatial smoothing problems. In Bayesian smoothing we need a linear regression model with a strong prior based on differencing matrices for the smoothness parameter and a weak prior for the regression part. We define a Bayesian spatial smoothing model with neighbors for each observation and we define a smoothness prior similar to the HP filter in time series. This opens a new approach to model-based smoothers for time series and spatial models based on MCMC. We apply it to the NUTS-2 regions of the European Union for regional GDP and GDP per capita, where the fixed effects are removed by an extended HP smoothing model.
Subjects: 
Hodrick-Prescott (HP) smoothers
smoothed square loss function
spatial smoothing
smoothness prior
Bayesian econometrics
JEL: 
C11
C15
C52
E17
R12
Document Type: 
Working Paper

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