Discrete choice

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In economics, "discrete choice" problems involve choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be continuously variable. In the continuous case, calculus methods can be used to determine the theoretical optimum, and demand can be modelled using regression analysis.

Modelling discrete choice is commonly undertaken using logit and probit models. Daniel McFadden won the Nobel Prize in 2000 for his pioneering work in developing the theoretical basis for discrete choice.

Discrete choice empirical work often quantifies, through the use of statistical models, the impact of variations in the "attributes" of the choice. Data for creating the models comes from the experiments, surveys, and/or structural estimation price and quantity information. Prior to discrete choice modeling, most choice modeling depended upon characteristics of the decision maker, such as income, age, etc., not characteristics of the attributes of the choice.

[edit] Application Areas

• Next product to buy models: These models predict which product to purchase, which travel mode (bus, plane, train, etc.)to select and which hotel to choose.

[edit] References

G.S. Maddala, Limited-dependent and Qualitative Variables in Econometrics, New York : Cambridge University Press, 1983.

Moshe Ben-Akiva and Steven Lerman, "Discrete Choice Analysis: Theory and Application to Travel Demand (Transportation Studies)", Massachusetts: MIT Press, 1985.

David A. Hensher, John M. Rose and William H. Greene "Applied Choice Analysis: A Primer", Massachusetts: Cambridge University Press, 2005.

Kenneth E. Train, " Discrete Choice Methods with Simulation", Massachusetts: Cambridge University Press, 2003.

[edit] External links

• Nobel Prize
• Discrete choice in consumer decision-making