Choice Model Simulation - Defining Choice Probabilities

Defining Choice Probabilities

Once the consumer utilities have been specified, the researcher can derive choice probabilities. Namely, the probability of the student choosing the Irish pub over the American pub is

\begin{align} P_i & = \Pr(U_i > U_a) = \Pr( \alpha P_i + \beta D_i + \varepsilon_i > \alpha P_a + \beta D_a + \varepsilon_a ) \\ & = \Pr( \varepsilon_i - \varepsilon_a > \alpha P_a + \beta D_a - \alpha P_i - \beta D_i ) \end{align}

Denoting the observed portion of the utility function as V,

(3)

In the end, discrete choice modeling comes down to specifying the distribution of (or ) and solving the integral over the range of to calculate . Extending this to more general situations with

  1. N consumers (n = 1, 2, …, N),
  2. J choices of consumption (j = 1, 2, …, J),

The choice probability of consumer n choosing j can be written as

(4)

for all i other than j

Read more about this topic:  Choice Model Simulation

Famous quotes containing the words defining and/or choice:

    “The industrial world would be a more peaceful place if workers were called in as collaborators in the process of establishing standards and defining shop practices, matters which surely affect their interests and well-being fully as much as they affect those of employers and consumers.”
    —Mary Barnett Gilson (1877–?)

    “... the black girls didn’t get these pills because their black ministers were up on the pulpit saying that birth control pills were black genocide. What I’m saying is that black men have exploited black women.... They didn’t want them to have any choice about their reproductive health. And if you can’t control your reproduction, you can’t control your life.”
    —Joycelyn Elders (b. 1933)