The autoregressive distributed lag model

Anyu Liu; Xinyang Liu

doi:10.4324/9781003269366

The autoregressive distributed lag model

Anyu Liu, Xinyang Liu

Research output: Chapter in book / Conference proceeding › Chapter in an edited book (as author) › Academic research

Abstract

This chapter introduces the autoregressive distributed lag model (ADLM). The ADLM is incorporated with the general-to-specific (GETS) approach for model specification, estimation, and selection to capture the relationship between tourism demand and its determinants. The model is applied to analyse and forecast inbound tourism demand for Thailand from selected source markets. Following a discussion of the forecasting performance of the ADLM, future research directions are proposed.

Original language	English
Title of host publication	Econometric Modelling and Forecasting of Tourism Demand: Methods and Applications
Editors	Doris Chenguang Wu, Gang Li, Haiyan Song
Place of Publication	London
Publisher	Taylor & Francis
Chapter	3
Pages	53-75
Edition	1st
ISBN (Electronic)	9781003269366
DOIs	https://doi.org/10.4324/9781003269366
Publication status	Published - Oct 2022

More information

10.4324/9781003269366

http://hdl.handle.net/10397/99572

Cite this

@inbook{777d87d2c5b844d3bca2c92608db47ec,

title = "The autoregressive distributed lag model",

abstract = "This chapter introduces the autoregressive distributed lag model (ADLM). The ADLM is incorporated with the general-to-specific (GETS) approach for model specification, estimation, and selection to capture the relationship between tourism demand and its determinants. The model is applied to analyse and forecast inbound tourism demand for Thailand from selected source markets. Following a discussion of the forecasting performance of the ADLM, future research directions are proposed.",

author = "Anyu Liu and Xinyang Liu",

note = "Publisher Copyright: {\textcopyright} 2022 Informa UK Limited, trading as Taylor & Francis Group.",

year = "2022",

month = oct,

doi = "10.4324/9781003269366",

language = "English",

pages = "53--75",

editor = "Wu, {Doris Chenguang} and Gang Li and Haiyan Song",

booktitle = "Econometric Modelling and Forecasting of Tourism Demand: Methods and Applications",

publisher = "Taylor & Francis",

edition = "1st",

}

The autoregressive distributed lag model. / Liu, Anyu; Liu, Xinyang.
Econometric Modelling and Forecasting of Tourism Demand: Methods and Applications. ed. / Doris Chenguang Wu; Gang Li; Haiyan Song. 1st. ed. London: Taylor & Francis, 2022. p. 53-75.

Research output: Chapter in book / Conference proceeding › Chapter in an edited book (as author) › Academic research

TY - CHAP

T1 - The autoregressive distributed lag model

AU - Liu, Anyu

AU - Liu, Xinyang

PY - 2022/10

Y1 - 2022/10

N2 - This chapter introduces the autoregressive distributed lag model (ADLM). The ADLM is incorporated with the general-to-specific (GETS) approach for model specification, estimation, and selection to capture the relationship between tourism demand and its determinants. The model is applied to analyse and forecast inbound tourism demand for Thailand from selected source markets. Following a discussion of the forecasting performance of the ADLM, future research directions are proposed.

AB - This chapter introduces the autoregressive distributed lag model (ADLM). The ADLM is incorporated with the general-to-specific (GETS) approach for model specification, estimation, and selection to capture the relationship between tourism demand and its determinants. The model is applied to analyse and forecast inbound tourism demand for Thailand from selected source markets. Following a discussion of the forecasting performance of the ADLM, future research directions are proposed.

U2 - 10.4324/9781003269366

DO - 10.4324/9781003269366

M3 - Chapter in an edited book (as author)

SP - 53

EP - 75

BT - Econometric Modelling and Forecasting of Tourism Demand: Methods and Applications

A2 - Wu, Doris Chenguang

A2 - Li, Gang

A2 - Song, Haiyan

PB - Taylor & Francis

CY - London

ER -

The autoregressive distributed lag model

Abstract

More information

Fingerprint

Cite this