A quantitative urban model for transport appraisal: Model estimation

Abstract

Quantitative spatial models (QSM) are a specialised type of spatial computable general equilibrium (SCGE) models that enable the causal estimation of key parameters. By ensuring causality, a QSM can isolate the effects of policy interventions on land use and economic outcomes, such as the spatial distribution of wages and house prices, from confounding factors like exogenous shocks (e.g., pandemics). This paper summarises the core empirical tasks in ; the first QSM framework designed to align with current transport appraisal practices. We address three key empirical challenges: the estimation of the gravity equation, which underpins location choices; the quantification of local geographical characteristics, including local amenities and firm productivity determinants, through model inversion; and the estimation of the relationship between accessibility and productivity. Through a better understunding of these empirical tasks, the study illustrates how QSMs can provide robust insights into the economic and spatial consequences of transport policy interventions.