R: Marginal effects of the covariates

effects.mlogit {mlogit} | R Documentation

## Marginal effects of the covariates

### Description

The `effects` method for `mlogit` objects computes the marginal effects of the selected covariate on the probabilities of choosing the alternatives

### Usage

    ## S3 method for class 'mlogit'
    effects(object, covariate = NULL,
                            type = c("aa", "ar", "rr", "ra"), data = NULL, ...)

### Arguments

`object` | a `mlogit` object,
`covariate` | the name of the covariate for which the effect should be computed,
`type` | the effect is a ratio of two marginal variations of the probability and of the covariate ; these variations can be absolute `"a"` or relative `"r"`. This argument is a string that contains two letters, the first refers to the probability, the second to the covariate,
`data` | a data.frame containing the values for which the effects should be calculated. The number of lines of this data.frame should be equal to the number of alternatives,
`...` | further arguments.

### Value

If the covariate is alternative specific, a $J$ times $J$ matrix is returned, $J$ being the number of alternatives. Each line contains the marginal effects of the covariate of one alternative on the probability to choose any alternative. If the covariate is individual specific, a vector of length $J$ is returned.

### Author(s)

Yves Croissant

### See Also

`mlogit` for the estimation of multinomial logit models.

### Examples

    data("Fishing", package = "mlogit")
    Fish <- mlogit.data(Fishing, varying = c(2:9), shape = "wide", choice = "mode")
    m <- mlogit(mode ~ price | income | catch, data = Fish)
    # compute a data.frame containing the mean value of the covariates in
    # the sample
    z <- with(Fish, data.frame(price = tapply(price, index(m)$alt, mean),
                               catch = tapply(catch, index(m)$alt, mean),
                               income = mean(income)))
    # compute the marginal effects (the second one is an elasticity
    effects(m, covariate = "income", data = z)
    effects(m, covariate = "price", type = "rr", data = z)
    effects(m, covariate = "catch", type = "ar", data = z)

[Package mlogit version 0.3-0 Index]