This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of...

Introduction -- ARMA models -- Forecasting stationary processes -- Estimation of Mean and Autocovariance Function -- Estimation of ARMA Models -- Spectral Analysis and Linear Filters -- Integrated Processes -- Models of Volatility -- Multivariate Time series -- Estimation of Covariance Function...

In evaluating prediction models, many researchers flank comparative ex-ante prediction experiments by significance tests on accuracy improvement, such as the Diebold-Mariano test. We argue that basing the choice of prediction models on such significance tests is problematic, as this practice may...

The selection problem among models for the seasonal behavior in time series is considered. The central decision of interest is between models with seasonal unit roots and with deterministic cycles. In multivariate models, also the number of stochastic seasonal factors is a discrete parameter of...