CBL - Campus del Baix Llobregat

Projecte llegit

Títol: Un modelo econométrico para la previsión de tráfico aéreo en aeropuertos.

Estudiants que han llegit aquest projecte:

Director/a: TRAPOTE BARREIRA, CÉSAR

Departament: FIS

Títol: Un modelo econométrico para la previsión de tráfico aéreo en aeropuertos.

Data inici oferta: 19-07-2022     Data finalització oferta: 19-03-2023


Estudis d'assignació del projecte:
    GR ENG SIST AEROESP
Tipus: Individual
 
Lloc de realització: EETAC
 
Paraules clau:
Aeropuertos, transporte áereo, econometría, previsión, tráfico
 
Descripció del contingut i pla d'activitats:
El trabajo tiene por objeto realizar un modelo econométrico para la previsión de tráfico
aéreo en aeropuertos.



La tareas son:

1. Estado del arte sobre modelos econométricos en prognósis de demanda en
aeropuertos.

2. Recogida de datos y análisis estadístico-descriptivo.

3. Modelización.

4. Análisis de escenarios.
 
Overview (resum en anglès):
This paper presents an econometric model designed for forecasting air traffic at airports, with a specific focus on Barcelona-El Prat Airport.

An exhaustive analysis is conducted on the evolution of global air connectivity and its economic and social impact, highlighting historical development and current trends in Europe and particularly in Barcelona. The study applies linear regression models to evaluate how variables such as the number of flights, airport capacity, and the air connectivity index influence regional GDP, employment, tourism, and foreign direct investment in Catalonia.

The results indicate that better air connectivity is positively correlated with economic growth and regional development, although simply increasing the number of flights can have negative effects due to airport congestion.

Finally, recommendations are proposed to improve airport infrastructure and optimize connectivity, emphasizing the importance of adopting advanced technologies and sustainable practices to ensure balanced and responsible growth of the aviation sector in Barcelona.

The study also identifies areas for improvement, including the need to extend the analysis period to capture long-term trends and mitigate the impact of exceptional events such as the COVID-19 pandemic. It is suggested to develop more comprehensive connectivity indices that consider the quality and efficiency of service.

Additionally, it is recommended to use advanced econometric models that can better capture the complexity of interactions between variables. Incorporating external factors such as changes in regulation could also provide a more accurate view of air connectivity and its economic impact.

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