We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...

This paper considers the maximum likelihood estimation of a stochastic frontier production function with an interval outcome. We derive an analytical formula for calculating the likelihood function of the interval stochastic frontier models. Monte Carlo experiments reveal that the finite sample...

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...

This research suggests an easy-to-implement forecast combination procedure to deal with the model uncertainty issues when evaluating the cartel damages. We combine the Mallows model averaging (MMA) method with both the dummy variable (DV) and forecasting approaches to investigate the famous...

This paper presents a generalized autoregressive distributed lag (GADL) model for conducting regression estimations that involve mixed-frequency data. As an example, we show that daily asset market information - currency and equity market movements - can produce forecasts of quarterly commodity...

The "home bias" phenomenon states that empirically, economic agents often under-utilize opportunities beyond their country borders, and it is well-documented in various international pricing and purchase patterns. This bias manifests in the forms of fewer exchanges of goods and net...