Several Bayesian and classical models are used to forecast house prices in 20 states in
the United States. There are two approaches: extracting common factors (principle
components) in a factor-augmented vector autoregressive or factor-augmented Bayesian
vector autoregressive models or Bayesian shrinkage in a large-scale Bayesian vector
autoregressive models. The study compares the forecast performance of the 1976:Q1 to
1994:Q4 in-sample period to the out-of-sample horizon 1995:Q1 to 2009:Q1 period. The
findings provide mixed evidence on the role of macroeconomic fundamentals in
improving the forecasting performance of time-series models. For 13 states, models that
include the information of macroeconomic fundamentals improve the forecasting
performance, while for seven states they do not.
Since the emergence of systematic science it has been recognized that a natural phenomenon can be described
by different models that vary in their complexity and their ability to capture the details of the features
Olivier, Laurentz Eugene; Craig, Ian K.(Elsevier, 2013-02)
The performance of a model predictive controller depends on the quality of
the plant model that is available. Often parameters in a run-of-mine (ROM)
ore milling circuit are uncertain and inaccurate parameter estimation ...
Sekgota, Mpolaeng Gilbert(University of Pretoria, 2013-05-27)
The Sustainable Restitution Support – South Africa (SRS-SA) program aimed at the development of a post-settlement support model that could be used to support beneficiaries of land reform in South Africa, especially those ...