Tourism demand modelling and forecasting: modern econometric approaches
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Pergamon
2000
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Advances in tourism research series
|
| Schlagwörter: | |
| Links: | http://www.sciencedirect.com/science/book/9780080436739 http://www.sciencedirect.com/science/book/9780080436739 |
| Beschreibung: | The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions Includes bibliographical references (pages 167-71) "The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications." "The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data Finally, the book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions."--Jacket |
| Umfang: | viii, 178 pages |
| ISBN: | 9780080436739 0080436730 |
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| 490 | 0 | |a Advances in tourism research series | |
| 500 | |a The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions | ||
| 500 | |a Includes bibliographical references (pages 167-71) | ||
| 500 | |a "The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications." | ||
| 500 | |a "The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data | ||
| 500 | |a Finally, the book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions."--Jacket | ||
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| 650 | 7 | |a Tourism / Forecasting |2 fast | |
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Datensatz im Suchindex
| _version_ | 1818983331933454336 |
|---|---|
| any_adam_object | |
| author | Song, Haiyan |
| author_facet | Song, Haiyan |
| author_role | aut |
| author_sort | Song, Haiyan |
| author_variant | h s hs |
| building | Verbundindex |
| bvnumber | BV044379285 |
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| dewey-full | 338.4/791 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 338 - Production |
| dewey-raw | 338.4/791 |
| dewey-search | 338.4/791 |
| dewey-sort | 3338.4 3791 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
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| id | DE-604.BV044379285 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T18:01:25Z |
| institution | BVB |
| isbn | 9780080436739 0080436730 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029781507 |
| oclc_num | 474963358 |
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| owner_facet | DE-1046 |
| physical | viii, 178 pages |
| psigel | ZDB-33-ESD ZDB-33-ESD FAW_PDA_ESD |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Pergamon |
| record_format | marc |
| series2 | Advances in tourism research series |
| spelling | Song, Haiyan Verfasser aut Tourism demand modelling and forecasting modern econometric approaches Haiyan Song and Stephen F. Witt 1st ed New York Pergamon 2000 viii, 178 pages txt rdacontent c rdamedia cr rdacarrier Advances in tourism research series The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions Includes bibliographical references (pages 167-71) "The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications." "The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data Finally, the book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions."--Jacket Tourism / Econometric models fast Tourism / Forecasting fast Ökonometrisches Modell Tourism Econometric models Tourism Forecasting Nachfrage (DE-588)4041036-5 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Tourismus (DE-588)4018406-7 gnd rswk-swf Prognose (DE-588)4047390-9 gnd rswk-swf Tourismus (DE-588)4018406-7 s Nachfrage (DE-588)4041036-5 s Mathematisches Modell (DE-588)4114528-8 s 1\p DE-604 Prognose (DE-588)4047390-9 s 2\p DE-604 Witt, Stephen F. Sonstige oth http://www.sciencedirect.com/science/book/9780080436739 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Song, Haiyan Tourism demand modelling and forecasting modern econometric approaches Tourism / Econometric models fast Tourism / Forecasting fast Ökonometrisches Modell Tourism Econometric models Tourism Forecasting Nachfrage (DE-588)4041036-5 gnd Mathematisches Modell (DE-588)4114528-8 gnd Tourismus (DE-588)4018406-7 gnd Prognose (DE-588)4047390-9 gnd |
| subject_GND | (DE-588)4041036-5 (DE-588)4114528-8 (DE-588)4018406-7 (DE-588)4047390-9 |
| title | Tourism demand modelling and forecasting modern econometric approaches |
| title_auth | Tourism demand modelling and forecasting modern econometric approaches |
| title_exact_search | Tourism demand modelling and forecasting modern econometric approaches |
| title_full | Tourism demand modelling and forecasting modern econometric approaches Haiyan Song and Stephen F. Witt |
| title_fullStr | Tourism demand modelling and forecasting modern econometric approaches Haiyan Song and Stephen F. Witt |
| title_full_unstemmed | Tourism demand modelling and forecasting modern econometric approaches Haiyan Song and Stephen F. Witt |
| title_short | Tourism demand modelling and forecasting |
| title_sort | tourism demand modelling and forecasting modern econometric approaches |
| title_sub | modern econometric approaches |
| topic | Tourism / Econometric models fast Tourism / Forecasting fast Ökonometrisches Modell Tourism Econometric models Tourism Forecasting Nachfrage (DE-588)4041036-5 gnd Mathematisches Modell (DE-588)4114528-8 gnd Tourismus (DE-588)4018406-7 gnd Prognose (DE-588)4047390-9 gnd |
| topic_facet | Tourism / Econometric models Tourism / Forecasting Ökonometrisches Modell Tourism Econometric models Tourism Forecasting Nachfrage Mathematisches Modell Tourismus Prognose |
| url | http://www.sciencedirect.com/science/book/9780080436739 |
| work_keys_str_mv | AT songhaiyan tourismdemandmodellingandforecastingmoderneconometricapproaches AT wittstephenf tourismdemandmodellingandforecastingmoderneconometricapproaches |