The paper develops a non-parametric, non-stationary framework for business-cycle dating based on an innovative statistical methodology known as Adaptive Weights Smoothing (AWS). The methodology is used both for the study of the individual macroeconomic time series relevant to the dating of the...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

This dissertation presents a detailed study of geostatistics. Included in this workare details of the development of geostatistics and its usefulness both in andoutside of the mining industry, a comprehensive presentation of the theory ofgeostatistics, and a discussion of the application of this...

This paper conducts Granger-causality tests on real per capita GDP and four types of air emissions (CO2, CO, SO2 and NOx) by using Norwegian data covering the period 1973-2003. The test results indicate that only unidirectional causal relationships exist between GDP and air emissions. For CO2...