Earticle

초록

영어

Air travel demand estimation is vital for airlines and government authorities to make reasonable decisions. However, when estimating the demand, air passenger volume has been frequently employed as an instrumental variable, although there exists a big deviation between them. This inappropriate practice will lead to misleading conclusions and seri-ously perverse decisions. This paper, based on the partial adjustment theory, proposes a new method to distinguish and estimate air travel demand from air passenger volume. A multi-dimensional variable selection method is originally proposed and a new estimation method is advanced to solve the problem of endogeneity and serial correlation. The pro-posed model is finally applied to estimate and analyze the aggregate air travel demand in China, the results show that air travel demand in China is enjoying a big potential. The model may also be applied to study road, rail and ocean transportation demand.

목차

Abstract
 1. Introduction
 2. Relationship between Volume and Demand
 3. Explanatory Variable Selection and Model Construction
  3.1. Multidimensional Explanatory Variable Selection Method
  3.2. Finally Selected Explanatory Variables
  3.3. Model Specification
 4. Estimation Method
  4.1. Function Transformation
  4.2. Steps of the Estimation
  4.3. Detailed discussion on the estimation
 5. Empirical Study
  5.1. Data Description and Preparation
  5.2. Empirical Results
 6. Conclusion
 Acknowledgment
 Appendix
 References

키워드

저자

• Yingxiao Zhou [ School of Traffic and Transportation, Beijing Jiaotong University, China ]
• Peng Zhao [ School of Traffic and Transportation, Beijing Jiaotong University, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605