Recent work by Hamilton, Waggoner and Zha (2002) has demonstrated the importance of identification and nomalization in econometric models. In this paper, we use the popular class of two-state Markov switching models to illustrate the consequences of alternative identification schemes for empirical analysis of business cycles. A defining feature of (classical) recessions is that economic activit...

Traffic modeling is a fertile research area. This paper proposes a packet-level traffic model of traffic sources based on Hidden Markov Model. It has been developed by using real network traffic and estimating in a combined fashion Packet Size and Inter Packet Time. The effectiveness of the proposed model is evaluated by studying several traffic types with strong differences in terms of both ap...

With competition playing a critical role in market-based strategic planning and implementation, identifying and understanding competiton and competitive dynamics has become critical. In this vein, the strategic groups perspective has emerged as a powerful means to understand such competitive phenomena. Empirical approaches to model competitive dynamics within the strategic groups framework, how...

Markov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogen...

The objective of this paper is to evaluate the effectiveness of using Markov switching models to measure the strength of synchronization between business cycles. Synchronization is defined by the fraction of time in which two country’s business cycles are in the same state (concordance) and by the degree to which turning points cluster together (correlation). We use a Bayesian, Gibbs sampling a...

In this study, two-state Markov switching multinomial logit models are proposed for statistical modeling of accident-injury severities. These models assume Markov switching over time between two unobserved states of roadway safety as a means of accounting for potential unobserved heterogeneity. The states are distinct in the sense that in different states accident-severity outcomes are generate...

We use high-frequency intra-day realized volatility to evaluate the relative forecasting performance of several models for the volatility of crude oil daily spot returns. Our objective is to evaluate the predictive ability of time-invariant and Markov switching GARCH models over different horizons. Using Carasco, Hu and Ploberger (2014) test for regime switching in the mean and variance of the ...

The goal of this study is to investigate the performance Markov regime switching autoregressive (MRS-AR) model estimate and forecast gold prices in Pakistan. Initial analysis data covering from January 1995 2019 reveals existence nonstationarity, heteroscedasticity, structural changes. dynamics are studied two distinct regimes. empirical provides evidence that shifts mattered MRS-AR found be su...