Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice

Denis Bolduc, Richard Laferrière and Gino Santarossa
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Denis Bolduc: Université Laval
Richard Laferrière: Université de Montréal
Gino Santarossa: Université Laval

Chapter 4 in New Directions in Spatial Econometrics, 1995, pp 96-108 from Springer

Abstract: Abstract In this chapter we use empirical examples to demonstrate the usefulness of the generalized error component framework suggested in Bolduc et al. (1992) for dealing with the problem of correlation among the errors of a regression based on travel flow data. This methodology augments Standard error component decompositions with first-order spatial autoregressive processes, i.e., SAR(l), with the purpose of allowing for the different sources of misspecification generally associated with this type of model. The error component approach splits the error term into a sum of one component related to the zones in origin, one component associated with the zones in destination and a remainder. The interdependencies among the errors are modeled with the help of SAR(l) processes. This decompositional approach extends the previous works by Brandsma and Ketellapper (1979) and Bolduc et al. (1989) which also relied on spatial autoregressive processes to model the error correlation.

Keywords: Error Component; Nuisance Parameter; Weight Structure; Error Covariance Matrix; Network Variable (search for similar items in EconPapers)
Date: 1995
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DOI: 10.1007/978-3-642-79877-1_4

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