Econometric and fuzzy models for the forecast of demand in the airport of Rhodes

Profillidis, Vassilios

doi:10.1016/s0969-6997(99)00026-5

Cited by 59 publications

(26 citation statements)

References 2 publications

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“…A significant number of the demand models in Table 1 do not explicitly treat the time dimension of the data, despite the underlying data being time series in nature (6,(8)(9)(10)(11)(12) The number of studies using time series data for modeling air cargo transport demand is small compared to air passenger demand (20-23). This reflects the importance of air passenger demand with respect to cargo demand in most of the airports in the world.…”

Section: Literature On Air Passenger and Cargo Demandmentioning

confidence: 99%

Simultaneous Modeling of Passenger and Cargo Demand at an Airport

Wadud

2013

Transportation Research Record

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Forecasts for future passenger and cargo demands are important parameters for airport planners. While there are a number of studies for passenger demand in an airport, the number of studies for air cargo is much smaller. Also, these two entities are often separately dealt with in the literature. However, there can be advantages in modeling them both simultaneously, especially when time-series data is used for the estimation of the demand models. We follow a Seemingly Unrelated Regression (SUR) framework to jointly model passenger and cargo demand at the Shahjalal International Airport at Dhaka, Bangladesh. Allowing for contemporaneous correlation among the air passenger and air cargo demand models in the SUR approach allows a more efficient and reliable estimate than OLS and individual cointegration methods. We use the results of our simultaneous demand modeling to forecast passenger and cargo demand at the airport up to 2030.

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Section: Literature On Air Passenger and Cargo Demandmentioning

confidence: 99%

Simultaneous Modeling of Passenger and Cargo Demand at an Airport

Wadud

2013

Transportation Research Record

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“…Because of this importance of demand forecasts, there is a substantial literature on air transport demand modeling (e.g. Profillidis 2000, Lim et al 2008, Tsekeris 2009, Department for Transport 2009, Wadud 2011 and, like most other demand models, all of these are based on the assumption of a perfectly reversible and symmetric relationship between demand and its drivers. However, such an assumption has been challenged in other economic relationships in the area of transport and energy, such as those between oil price and energy demand (e.g.…”

Section: Introductionmentioning

confidence: 99%

The asymmetric effects of income and fuel price on air transport demand

Wadud

2014

Transportation Research Part A: Policy and Practice

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Article:Wadud, Z (2014) The asymmetric effects of income and fuel price on air transport demand. ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Note: There will still be some minor changes made to this manuscript prior to final publication. AbstractForecasts of passenger demand are an important parameter for aviation planners. Air transport demand models typically assume a perfectly reversible impact of the demand drivers. However, there are reasons to believe that the impacts of some of the demand drivers such as fuel price or income on air transport demand may not be perfectly reversible. Two types of imperfect reversibility, namely asymmetry and hysteresis, are possible. Asymmetry refers to the differences in the demand impacts of a rising price or income from that of a falling price or income. Hysteresis refers to the dependence of the impacts of changing price or income on previous history, especially on previous maximum price or income. We use US time series data and decompose each of fuel price and income into three component series to develop an econometric model for air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find statistical evidence of asymmetry and hysteresis for both, prices and income in air transport demand. Implications for policy and practice are then discussed.

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“…In general, it is acknowledged that the air transport demand is closely related to GDP (Profillidis, 2000). Figure 1 shows the positive correlation between GDP and air travel for each country.…”

Section: Movementsmentioning

confidence: 94%

“…This study analyzes the relation of economic variables and the air traffic demand by using historical air traffic data and GDP. The hardest part of econometric forecasting is a specified type of functional relationship between the dependent and the independent variables to be considered in the forecasting (Profillidis, 2000). The prediction of the future development of the independent variable is important (Profillidis, 1994 …”

Section: Introductionmentioning

confidence: 99%