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Classical Discrete Choice Theory

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Usual regression model untenable if applied to discrete choices ... Each good might represent a type of car or a mode of transportation, for example. ... – PowerPoint PPT presentation

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Title: Classical Discrete Choice Theory


1
Classical Discrete Choice Theory
  • ECON 721
  • Petra Todd

2
  • Usual regression model untenable if applied to
    discrete choices
  • Need to think of the ingredients that give rise
    to choices.

3
The Forecast problem
  • Suppose we want to forecast demand for a new good
    and we observe consumption data on old goods,
    x1xI.
  • Each good might represent a type of car or a mode
    of transportation, for example.
  • McFadden wanted to forecast demand for San
    Fransisco BART subway
  • Need to find way of putting new good on a basis
    with the old

4
Two predominant modeling approaches
  • Luce (1953)-McFadden conditional logit model
  • Widely used in economics
  • Easy to compute
  • Identifiability of parameters well understood
  • Restrictive substitution possibilities among goods

5
  • Thurstone (1929) -Quandt multivariate probit
    model
  • Very general substitution possibilities
  • Allows for general forms of heterogeneity
  • More difficult to compute
  • Identifiability less easily established

6
Luce/McFadden Conditional Logit Model
  • References Manski and McFadden, Chapter 5
    Greene, Chapter 21 Amemiya, Chapter 9
  • Notation

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  • We might assume there is a distribution of choice
    rules, because
  • In observation we lost some information governing
    chocies
  • There can be random variaion in choices due to
    unmeasured psychological factors
  • Define the probability that an individual drawn
    randomly from the population with attributes x
    and alternatives set B chooses x
  • Luce Axioms maintain some restrictions on
    P(xs,B) and derive implications for functional
    form of P

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Can now derive multinomial logit (MNL) form
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Random Utility Models (RUMs)
  • First proposed by Thurstone (1920s,1930s). Link
    between Luce model and RUM established by Marshak
    (1959)

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Marshak (1959) result
  • Assuming weibull errors, get Luce logit model
    from RUM framework

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  • Weibull is sufficient, but not necessary
  • Yellot (1977) showed that if we require
    invariance of choice probabilities under uniform
    expansions of the choice set, then weibull is the
    only distribution that yields logistic form
  • coffee, tea, milk
  • coffee,tea,milk,coffee,tea,milk

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The forecast problem
  • Suppose want to forecast demand for a new good

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Debreu Red-Bus-Blue-Bus Critique
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Criteria for a good probability choice system
(PCS)
  • Flexible functional form
  • Computationally practical
  • Allows for flexibility in representing
    substitution patterns
  • Is consistent with a RUM

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How do you know if a PCS is consistent with a
RUM?
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Daly-Zachary-Williams Theorem
  • Provide a set of conditions that make it easier
    to derive a PCS from an RUM for a class of models
    called generalized extreme value models
  • McFadden shows that under certain assumptions
    about the form of V, the DZW result can be seen
    as a form of Roys identity

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Example Choice of Transportation mode
  • Neighborhood m, transportation mode t

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