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Vector Autoregressive Models with Multivariate Time Series: Spillovers of International Tourist Arrivals on a Local Economy

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Quantitative Tourism Research in Asia

Part of the book series: Perspectives on Asian Tourism ((PAT))

Abstract

The chapter demonstrates an application of vector autoregressive models with time series in tourism research. The chapter describes how to apply vector autoregression with time series in a multivariate setting to estimate the short-run and long-run effects of international tourist arrivals on a local economy and associated economic spillovers in the local economy in Asia. The study employs unit root tests (i.e., the augmented Dickey and Fuller test, the Phillips and Perron test, the Ng and Perron test, and the Kwiatkowski et al. test), cointegration test (i.e., the Johansen cointegration test), and vector autoregressive models with multivariate time series (i.e., vector autoregression analysis, model diagnostic tests, residual diagnostic tests, and impulse response tests) using quarterly time series data, which are available from the first quarter of 1970 to the third quarter of 2012 (172 observations) retrieved from the Bank of Korea.

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Authors and Affiliations

  1. Administrative Sciences Department, Metropolitan College, Boston University, Boston, MA, USA

    Jung Wan Lee

  2. School of Hospitality Administration, Boston University, Boston, MA, USA

    Michael Kwag

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  1. Jung Wan Lee
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  2. Michael Kwag
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Correspondence to Jung Wan Lee .

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Editors and Affiliations

  1. University of Hamburg, Hamburg, Germany

    Sajad Rezaei

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Lee, J.W., Kwag, M. (2019). Vector Autoregressive Models with Multivariate Time Series: Spillovers of International Tourist Arrivals on a Local Economy. In: Rezaei, S. (eds) Quantitative Tourism Research in Asia. Perspectives on Asian Tourism. Springer, Singapore. https://doi.org/10.1007/978-981-13-2463-5_13

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