ESTIMATION OF DISAGGREGATE REGRESSION MODELS OF PERSON TRIP GENERATION WITH MULTIDAY DATA

Abstract

Theoretical discussions of travel behavior recognize the day to day variability of such behavior and provide a rationale for such variability. However, this variability is commonly ignored in the process of data collection and model estimation. This paper examines the estimation of disaggregate least squares regression models of person trip generation with multiday data. The estimation properties of a variety of models are formulated, including multiday models which take account of correlated errors within individuals, averaged multiday models, and single day models. All three types of models yield unbiased estimators. However, the estimators of both types of multiday models are more efficient than those of the single day model. These analytic results are verified empirically and the magnitude of the efficiency gain is estimated using a five day data set collected in Reading, England. (Author/TRRL)

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