Evaluating Time Series Models in Short and Long-Term Forecasting of Canadian Air Passenger Data

This paper uses six time series models to forecast seasonally unadjusted monthly data of Canadian enplaned/deplaned air passengers, for the domestic, transborder and international sectors. We find that forecasting performance of the models varies widely across series and forecast horizons. Our forecasting results are compared with forecasts published by Transport Canada’s Aviation Forecasting Division.

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Year of publication:	2003
Authors:	Emiray, Emir ; Rodriguez, Gabriel
Institutions:	Département d'Économie / Department of Economics, Université d'Ottawa / University of Ottawa
Subject:	Forecasts \| Seasonal Unit Roots \| ARIMA Models \| Periodic Autoregressive Models \| Structural Time Series Model

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Extent:	application/pdf
Series:	Working Papers.
Type of publication:	Book / Working Paper
Notes:	Number 0306E 46 pages
Classification:	C2 - Econometric Methods: Single Equation Models ; C5 - Econometric Modeling
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008491484