Our starting place is the first order seasonal autoregressive model. Its series are shown to have canonical model-based decompositions whose finite-sample estimates, filters, and error covariances have simple revealing formulas from basic linear regression.We obtain analogous formulas for...

Hybrid time series data often require special care in estimating seasonal factors. Series such as the state and metro area Current Employment Statistics produced by the Bureau of Labor Statistics (BLS) are composed of two different source series that often have two different seasonal patterns....

This methodological paper reviews different spectral techniques well suitable to the analysis of economic time series. While econometric time series analysis is generally yielded in the time domain, these techniques propose a complementary approach based on the frequency domain. Spectral...

timeseriesdb is an R package which suggests a PostgreSQL database structure to store time series alongside extensive multi-lingual meta information and provides an R database interface including a web based GUI. The timeseriesdb package was designed to handle time series in establishment...

Outlier detection refers to the identification of rare items that are deviant from the general data distribution. Existing approaches suffer from high computational complexity, low predictive capability, and limited interpretability. As a remedy, we present a novel outlier detection algorithm...

National economy and security are fully dependent on information technology and infrastructure. At the core of the information infrastructure society relies on, we have the Internet, a system designed initially as a scientists’ forum for unclassified research. The use of communication networks...

We document five novel empirical findings on the well-known potential ordering drawback associated with the time-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP-SV. First, the ordering does not affect point...

We extract tone-adjusted, time-varying and hierarchically ordered topics from a large corpus of Dutch financial news and investigate whether these topics are useful for monitoring the business cycle and nowcasting GDP growth in the Netherlands. The financial newspaper articles span the period...

A distance between pairs of sets of autoregressive moving average (ARMA) processes is proposed. Its main properties are discussed. The paper also shows how the proposed distance finds application in time series analysis. In particular it can be used to evaluate the distance between portfolios of...

It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that...