African Air Transport Management by Eyden Samunderu

Author:Eyden Samunderu
Language: eng
Format: epub
ISBN: 9783031293245
Publisher: Springer International Publishing

Spatial Econometrics

Spatial econometrics is a cross-disciplinary field of study that crosses into statistics, economics, regional science and econometrics. The field originally evolved out of econometrics, which mixes statistics and math with economics. The spatial aspect of econometrics leads to a study of how spatial relationships, or geography, affects the study of analysis of statistical data, providing a geographically centred interpretation of a set of data which can either be route level or airport level data that can be constructed from the industry.

The attempt to identify air service market demand is not new. An interest in modelling demand for air transportation began to appear in the literature during the early 1950s, when the effort primarily focussed on forecasting travel propensity between two points (Harvey, 1951; Richmond, 1951). Alongside qualitative techniques used to predict air travel demand, a number of quantitative techniques have been used over time. These mathematical techniques primarily rely on time series and causal methods (Button & Hensher, 2000). Within time series models, demand forecasts are based on a series of past observations, assuming that the factors that influenced the past performance will continue (Doganis, 2010). The suitability of using trend analysis, however, depends merely on the stability in historic developments and the certainty that the assumptions of continuing trends are appropriate also in the particular operating environment under study (Zheng, 2013).

Causal models use mathematical techniques to postulate precise, deterministic relationships, where regressors and regress are identified, a functional form is specified and a qualitative statement is made about the effects that occur when independent variables in the model change (Greene, 2002). In air travel demand, causal methods attempt to relate changes in traffic levels to changes in selected socio-economic variables. Dependent variables in the estimation of traffic demand are, in general, historical traffic data measured in terms of passenger volumes or tonnes of cargo. The explanatory variables are those variables that are known to have an influence on the demand for air travel.

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