mode_choice: Intercity travel mode choice

In choicer: Discrete Choice Models for Economic Applications

Intercity travel mode choice

Description

Stated choices of intercity travel mode for 210 travellers, each choosing among the same four modes: air, train, bus and car. This is the classic Greene & Hensher (1997) data set, reshaped into choicer's long layout (one row per traveller-by-alternative). It is a convenient, recognizable example for multinomial and nested logit models and the demand/welfare toolkit (elasticities, diversion ratios, willingness-to-pay, counterfactuals).

Usage

mode_choice

Format

A data frame with 840 rows (210 travellers x 4 modes) and 9 columns:

id

Integer traveller (choice situation) identifier, 1-210.

mode

Factor giving the travel mode: "air", "train", "bus" or "car". Use as the alternative column.

choice

Integer indicator, 1 for the chosen mode and 0 otherwise. Exactly one mode is chosen per traveller.

wait

Terminal waiting time in minutes (0 for car).

travel

In-vehicle travel time in minutes.

vcost

In-vehicle cost component, in currency units.

gcost

Generalized cost measure, in currency units.

income

Household income (traveller level, in thousands).

size

Size of the travelling party (traveller level).

Details

wait, travel, vcost and gcost vary across modes within a traveller, while income and size are traveller-level attributes that are constant across modes. A standard specification regresses the choice on wait, travel and vcost with alternative-specific constants; vcost then plays the role of price for willingness-to-pay and consumer-surplus calculations.

The sample is choice-based: the survey over-sampled the less popular modes (air, train, bus) and under-sampled car, so sample choice shares do not estimate population mode shares. With a full set of alternative-specific constants the slope coefficients remain consistently estimated under this design (Manski and Lerman, 1977), and willingness-to-pay ratios are unaffected; the constants, and any shares, elasticities or surplus levels computed from fitted probabilities, inherit the sampling design. To target population quantities, attach WESML weights with wesml_weights using external population shares; see vignette("wesml", package = "choicer").

Source

Greene, W. H. and Hensher, D. A. (1997). Reshaped from the TravelMode data distributed with the AER package (https://CRAN.R-project.org/package=AER). The same data appear in Greene's Econometric Analysis and in several other choice-modelling packages.

References

Manski, C. F. and Lerman, S. R. (1977). The estimation of choice probabilities from choice based samples. Econometrica, 45(8), 1977-1988.

Examples

data(mode_choice)
head(mode_choice)
table(mode_choice$mode[mode_choice$choice == 1L])

choicer documentation built on Sept. 5, 2026, 1:07 a.m.