Market demand analysis and forecasting through applied econometrics: Empirical research in the public transit sector in the Toronto City Area (1969-2019)
Creators: name: Taty, Jeremy
Publisher: name: Zenodo
Year: 2023

description: Context: This working paper shall focus on sensitivity analysis, modelling, and forecasting of market demand to cope with uncertainty in the decision-making process. In addition, this paper also aims to provide the reader with an intuitive and practical experience of the optimisation tools of microeconomics, coupled with time series econometrics methods applied with R software. The strong interest in data from the public transit sector in this empirical research is linked to the fact that it is undoubtedly one of the sectors likely to play an important role in achieving the Sustainable Development Goals (SDGs) in future smart cities, which is all the more interesting as Toronto is Canada's largest municipality in terms of population. Indeed, public transit is a service that is beneficial to society for all its positive externalities. These benefits include accessibility and social equity in terms of fares and reduced road congestion, and, by extension, the fight against atmospheric pollution by reducing riders' CO2 emissions through public transport.

Findings. (i) We shall provide a price-demand sensitivity model (fare in C$) for ridership demand inside the Toronto city area from 1969 to 2019 as well as the derivation of short- and long-term elasticities. We shall also provide, through modelling and forecasting, insight into future demand trends considering pre- and post-pandemic scenarios. It is clear that one of the most remarkable points to emerge from the transit data in recent times is that the effects of the pandemic crisis have slowed ridership demand by almost half (225 million riders in 2020) compared to the previous trend (525.5 million riders in 2019) in the City of Toronto (TTC operating service area only), causing a structural break in the time series data, also observed in the TTC's latest report (only 197.8 million riders in 2021). This is not an isolated case for the city of Toronto, as Montreal (only 200 million users in 2020 compared to 426 million in 2019) and most of the major metropolitan cities in the world that were affected also experienced the same slowdown in demand due to reduced activity during the pandemic. (ii) Using our estimated market demand model for transit in the city of Toronto, we will attempt to estimate the optimal price and the price at which consumers are no longer willing to pay. And since this study concerns a public transit company in the form of a natural monopoly commonly referred to as a state monopoly, we shall draw on the seminal work and contributions of Frank Ramsey and Marcel Boiteux (Ramsey-Boiteux pricing rule) to understand the optimal pricing behaviour of this type of network infrastructure. The aim of this research will therefore also be to understand, beyond the elements of microeconomic optimization, that the nature of the company is at the center of its interests, which has a considerable influence on certain aspects that determine its business model and in particular its pricing behaviour (Baumol, 1959).

Keywords: market demand, sensitivity analysis, time series modeling and forecasting, pricing behaviour.

JEL Classification: C22; C63; C87; D12; D22; D42