Large time-varying parameter VARs

Koop, Gary; Korobilis, Dimitris

doi:10.1016/j.jeconom.2013.04.007

Cited by 374 publications

(420 citation statements)

References 28 publications

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“…In the following empirical study, consistent with previous tourism demand studies, constants are included in the specified model and deterministic trends are excluded. ii For a single country see Kadiyala and Carlsson (1997, 101) and Koop and Korobilis (2013).…”

Section: Resultsmentioning

confidence: 99%

Modeling and Forecasting Regional Tourism Demand Using the Bayesian Global Vector Autoregressive (BGVAR) Model

Assaf

Song

et al. 2018

Journal of Travel Research

118

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Increasing levels of global and regional integration have led to tourist flows between countries becoming closely linked. These links should be considered when modeling and forecasting international tourism demand within a region. This study introduces a comprehensive and accurate systematic approach to tourism demand analysis, based on a Bayesian global vector autoregressive (BGVAR) model. An empirical study of international tourist flows in nine countries in Southeast Asia demonstrates the ability of the BGVAR model to capture the spillover effects of international tourism demand in this region. The study provides clear evidence that the BGVAR model consistently outperforms three other alternative VAR model versions throughout one-to four-quarters-ahead forecasting horizons. The potential of the BGVAR model in future applications is demonstrated by its superiority in both modeling and forecasting tourism demand.

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Section: Resultsmentioning

confidence: 99%

Modeling and Forecasting Regional Tourism Demand Using the Bayesian Global Vector Autoregressive (BGVAR) Model

Assaf

Song

et al. 2018

Journal of Travel Research

118

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“…2 In this paper, we use fast, approximate, estimation methods which vastly reduce the computational burden. Similar to the approximate methods for TVP-VARs used in Koop and Korobilis (2013), we estimate all TVP-FAVAR coe¢ cients using fast updating schemes based on one-sided exponentially weighted moving average (EWMA) …lters combined with Kalman …lter recursions. Complete details are provided in the Technical Appendix.…”

Section: Introductionmentioning

confidence: 99%

A New Index of Financial Conditions

2013

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We use factor augmented vector autoregressive models with time-varying coe¢ cients to construct a …nancial conditions index. The time-variation in the parameters allows for the weights attached to each …nancial variable in the index to evolve over time. Furthermore, we develop methods for dynamic model averaging or selection which allow the …nancial variables entering into the FCI to change over time. We discuss why such extensions of the existing literature are important and show them to be so in an empirical application involving a wide range of …nancial variables.

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“…Then challenges are the computational burden and the use of approximate methods, such as forgetting factor in the Kalman filter, see, e.g. , Koop and Korobillis [2012] and Koop and Korobilis [2012]. Parallelization techniques using, for instance, Graphical Processing Units, are promising avenues for research.…”

Section: Resultsmentioning

confidence: 99%