Forecasting jobs location choices by Discrete Choice Models: A sensitivity analysis to scale and implications for LUTI models

Jones, Jonathan; Thomas, Isabelle; Peeters, Dominique

doi:10.18335/region.v2i1.63

Cited by 7 publications

(10 citation statements)

References 43 publications

(66 reference statements)

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“…Let us now consider a lived research experience based on a participation to a EU project where researchers from several disciplines (including economists) aimed at applying the UrbanSim Land Use and Transport Interaction (LUTI) model to three European cities (Paris, Brussels and Zurich) (see Bierlaire et al, 2015). Jonathan Jones further developed this topic in his PhD dissertation and in the consequent scientific papers (see Jones et al 2015aJones et al and 2015bJones et al , 2017Thomas et al, 2018); these publications will be the main source of inspiration of this section and have the advantage of opening the debate to other disciplines than economics. We knew from the very beginning of the research project that LUTI models were data intensive and hence often leading to data crunching rather than modelling; as expected, we drowned into data problems among which the delineation of the cities and the choice of the basic spatial units.…”

Section: Butterflies Lions and Other Felinesmentioning

confidence: 99%

“…Thomas et al 2018 The simulations reported confirm that the absence of control on city delineation strongly weakens the LUTI result, impacting in particular commuting times. The delineation of the city area plays a major role as well as the size of the spatial units (Jones, 2015b and2017) in transport modelling results and the consequences for not controlling these effects are clearly underestimated in the transport literature.…”

Section: Butterflies Lions and Other Felinesmentioning

confidence: 99%

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On the Survival of Butterflies in the Jungle of Urban Systems

Sanders¹,

Thomas

Vacchiani-Marcuzzo

2020

Lecture Notes in Morphogenesis

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In 2005 Gilles Duranton and Andrés Rodriguez-Pose signed a paper entitled « When economists and geographers collide, or the tale of the lions and the butterflies ». Let's briefly recall the demonstration of the two authors, one being a geographical economist, the other an economic geographer. Through analyses of cross citations and behaviors at conferences, they conclude to a relation of "mutual ignorance, rather than outright discord" between the researchers of these two communities. Looking at their scientific approaches, they underline two radically different ways of proceeding: the lions "improving and expanding their tricks", laboring "the same core questions over and over again", and the butterflies "freely flying the fields of knowledge with the aim of tasting the best from every flower they visit". The two authors note that both communities are in fact interested in the same questions (among others, the geography of cities), but that there is very little scientific cross-fertilization At the same period (2007), a similar debate took place in the French scientific journal L'Espace Géographique: Denise Pumain, Jacques-François Thisse, Isabelle Thomas and Bernard Walliser tried to explore the relationship between New Economic Geography and Geography. Jacques-François Thisse conceded at this occasion that "En ce qui concerne les échelles spatiales, il est exact que la plupart des économistes n'ont pas compris grand-chose à cette question 1 ». One specific point in this debate deserves to be focused on, that of spatial scales, that is maybe a major point of discrepancy between lions and butterflies. Indeed, initially (and very broadly said), economists (the lions) were myopic, considering a city as a point on a line (1D), and hence over simplifying urban realities for the sake of rigorous economic theory. At the same time, geographers (the butterflies), more aware of the crucial role of scale, were

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Section: Butterflies Lions and Other Felinesmentioning

confidence: 99%

Section: Butterflies Lions and Other Felinesmentioning

confidence: 99%

On the Survival of Butterflies in the Jungle of Urban Systems

Sanders¹,

Thomas

Vacchiani-Marcuzzo

2020

Lecture Notes in Morphogenesis

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“…The study area used in the SustainCity project (or "SustainCity Area") raises several concerns (see Thomas et al, 2015a;Jones et al, 2015a), since it encompasses municipalities having few relationships with the CBD and/or that belong to the catchment area of another city (Figure 1b). Previous works (Jones et al, 2015b;Thomas et al, 2015a) have demonstrated that the extent and composition of the study area may influence the parameter estimates of the location choice's sub models within UrbanSim and the outcomes from the model.…”

Section: Datamentioning

confidence: 99%

“…The variations of parameter estimates will, however, not be further discussed since we focus here on changes in the outputs of UrbanSim. We refer to Fotheringham and Wong (1991), Arauzo-Carod and Manjon-Antolin (2004), and Jones et al (2015b) for work dedicated to the MAUP.…”

Section: Econometric Sub Modelsmentioning

confidence: 99%

Scale effect in a LUTI model of Brussels: challenges for policy evaluation

Jones,

Peeters,

Thomas

2017

European Journal of Transport and Infrastructure Research

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The aim of this paper is to assess the reliability of policy evaluation based on Land Use and Transport Interactions models, relative to the choice of the Basic Spatial Units. An UrbanSim (+ MATsim) model applied to Brussels (Belgium) is used as the case study. The evolution of the study area over twenty years is forecasted for four levels of Basic Spatial Units and five scenarios (businessas-usual and four alternatives). Results show larger variations between Basic Spatial Units levels than across scenarios. These findings are valid for various sustainability indicators and for a simple cost-benefit analysis aiming at ranking the scenarios. The direction of the variations resulting from the implementation of the scenarios remains, however, the same for all Basic Spatial Units levels. Hence, the influence of the scale on policy evaluation based on Land Use and Transport Interactions models appears limited when it is only intended to compare scenarios, but it will have a crucial role when evaluations are based on absolute variations or threshold values.

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“…Two exceptions are worth mentioning. The first is Jones et al, which studies the effect of aggregation of alternatives on forecasting error for location choice models ( 17 ). In that study, the authors explicitly describe why variation in parameter estimates cannot reliably measure predictive performance in the forecasting phase.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Error From Sampling of Alternatives in Logit-Based Demand Forecasting Models with Massive Choice Sets

Gardner,

Waddell

2023

Transportation Research Record: Journal of the Transportation R

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Use of the multinomial logit (MNL) functional form is widespread in transportation and land use demand modeling. As the state-of-the-art evolves away from aggregate forecasting and toward activity-based models and microsimulation, MNL models are being asked to accommodate increasingly large choice sets. Different strategies exist to address the challenge of estimating models with very large choice sets, but perhaps none is as commonly employed as sampling of alternatives. The effect of sampling of alternatives on parameter estimation has received considerable attention in the scientific literature. Yet comparatively little quantitative research exists that examines the issues that arise when the same sampling strategies are applied in the context of forecasting. In this study we conducted an analysis of the effect of sampling of alternatives in discrete choice models for disaggregate location choice forecasting. First, a novel measure of forecast error was defined and then used to quantify the extent of the problem as a function of sample rate, model error, and size of the universe of alternatives. Finally, we explored the potential for strategic sampling techniques to reduce the error observed under simple random sampling. In general, we found that the proportion of aggregate demand that was misallocated owing to sampling of alternatives was actually reduced as the size of the universe of alternatives increased. Additionally, simple random sampling was shown to outperform importance sampling in most scenarios. These findings suggest that error resulting from random sampling of alternatives is less of a problem for logit-based microsimulation models than previously assumed.

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Forecasting jobs location choices by Discrete Choice Models: A sensitivity analysis to scale and implications for LUTI models

Cited by 7 publications

References 43 publications

On the Survival of Butterflies in the Jungle of Urban Systems

On the Survival of Butterflies in the Jungle of Urban Systems

Scale effect in a LUTI model of Brussels: challenges for policy evaluation

Numerical Analysis of Error From Sampling of Alternatives in Logit-Based Demand Forecasting Models with Massive Choice Sets

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