Exploring causality in trade and air passenger travel relationships: the case of Asia-Pacific, 1980–2010

Air Passenger Transport and Regional Development: Cause and Effect in Europe

“…air passenger transport) is said to 'Granger cause' a variable Y (e.g employment), if taking into account past values of X enables better predictions of Y than based exclusively on past values of Y. Variable X does not literally 'cause' Y, but rather helps to forecast it which is then taken to be a sign of explanatory power [26].…”

“…The latter refers to the time difference which offers the maximum level of 'causality' [54]. The assumption underlying this extension is that the autoregressive coefficient is constant for all cross-sections, while the regression coefficient is constant for all time periods but can vary across the cross-sections, which enables the causal heterogeneity [26].…”

“…The heterogeneous TSCS-causality testing procedure consists of three consecutive steps, which have been extensively described in Hurlin and Venet [54], Hood III et al [56], Tranos [27] and Van De Vijver et al [26]. The procedure is tested separately for the three relationships (i) passenger volume versus total employment, (ii) passenger volume versus employment in the services sector, and (iii) passenger volume versus employment in the manufacturing sector.…”

“…Multiple case studies have examined the catalytic impacts of European airports on the regional economy (for instance Heuer and Klophaus [23] for Frankfurt-Hahn Airport, and Abraham et al [24] for Lü-beck Airport). These case studies generally emphasise that European airports are vital for the international competitiveness of their wider surrounding region by providing improved accessibility, attracting inward investment, and facilitating trade and tourism [24,25,26], and can as such be seen as regional economic motors [21]. However, air passenger transport is endogenous to economic development, as economic development influences air passenger transport in its own right.…”

Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling

“…First, even though it is airlines that realize the opening or closure of routes, their decisions regarding the anticipated profitability are influenced by the socio-economic context (e.g., the economic power measured by GDP, population and other indicators) of the cities or catchment areas in which airports are located. And second, only in relatively liberalized markets carriers can freely choose to open or close a route: when shaping (de)regulation policies, government and airport operators consider the overall geographies of air transport aggregated by airports (Van De Vijver et al, 2014), and these geographies are not solely or always directly shaped by individual carriers. From this perspective, airports implicitly co-determine the opening or closure of routes.…”