Cointegration analysis is used to estimate the long-run equilibrium relations between several time series. The coefficients of these long-run equilibrium relations are the cointegrating vectors. In this paper, we provide a sparse estimator of the cointegrating vectors. The estimation technique...

The customer lifetime value combines into one construct the transaction timing, spending and dropout processes that characterize the purchase behavior of customers. Recently, the potential relationship between these processes, either at the individual customer level (i.e. intra-customer...

Retailers use the Vector AutoRegressive (VAR) model as a standard tool to estimate the effects of prices, promotions and sales in one product category on the sales of another product category. Besides, these price, promotion and sales data are available for not just one store, but a whole chain...

This paper compares the importance of different sovereign credit rating determinants over time, using a sample of 90 countries for the years 2002-2015. Applying the composite marginal likelihood approach, we estimate a multi-year ordered probit model for each of the three major credit rating...

The correct understanding of commodity price dynamics can bring relevant improvements in terms of policy formulation both for developing and developed countries. Agricultural, metal and energy commodity prices might depend on each other: although we expect few important effects among the total...

This paper analyzes impulse response functions of vector autoregression models for variables that are linearly transformed. These impulse responses are equal to the linear transformation of the original impulse responses only if the shocks are equal to the linear transformation of the original...

This paper compares Bayesian estimators with different prior choices for the time variation of the coefficients of Time Varying Parameter Vector Autoregression models using Monte Carlo Simulations. Since the commonly used prior choice only allows for a tiny amount of time variation, less...

Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR)...

We provide a framework for robust exponential smoothing. For a class of exponential smoothing variants, we present a robust alternative. The class includes models with a damped trend and/or seasonal components. We provide robust forecasting equations, robust starting values, robust smoothing...

The model parameters of linear state space models are typically estimated with maximum likelihood estimation, where the likelihood is computed analytically with the Kalman filter. Outliers can deteriorate the estimation. Therefore we propose an alternative estimation method. The Kalman filter is...