Compare methods

	Gabor-Granger Pricing	Discrete Choice Experiment
Field	Marketing Research	Marketing Research
Family	Process / pipeline	Regression model
Year of origin	1966	1983
Originator	André Gabor & Clive W. J. Granger	Jordan J. Louviere & George Woodworth; Daniel McFadden (random utility theory)
Type	Direct purchase-intent pricing survey yielding a demand curve	Stated-preference experiment for estimating preferences and willingness to pay
Seminal source	Gabor, A., & Granger, C. W. J. (1966). Price as an Indicator of Quality: Report on an Enquiry. Economica, 33(129), 43-70.	Louviere, J. J., & Woodworth, G. (1983). Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data. Journal of Marketing Research, 20(4), 350-367.
Aliases	Gabor-Granger, Gabor-Granger Technique, Direct Price-Response Method, Purchase-Intent Pricing	DCE, Stated Choice Experiment, Stated-Preference Choice Experiment, Choice Experiment
Related	4	4
Summary	The Gabor-Granger method is a direct pricing-research technique that estimates a product's demand curve by asking respondents whether they would buy it at each of several price points. Developed by economists André Gabor and Clive Granger in the 1960s through surveys of how consumers perceive and react to prices, it asks a simple question, would you purchase at this price?, across a ladder of prices, usually presented in random order. Aggregating the share of people willing to buy at each price traces a stated demand curve, from which the analyst computes expected revenue at every price and identifies the price that maximizes it. Because it focuses on a single product rather than competitive trade-offs, Gabor-Granger is fast, intuitive, and well suited to setting or testing a price for an existing or clearly defined offering. It also yields a straightforward estimate of price elasticity. Its directness is both its appeal and its main weakness, since asking about price in isolation can prime respondents and overstate price sensitivity.	A discrete choice experiment (DCE) is a stated-preference method in which respondents repeatedly choose their preferred option from sets of alternatives described by systematically varied attributes, allowing the analyst to estimate how each attribute drives choice. Grounded in McFadden's random utility theory and operationalized for designed experiments by Louviere and Woodworth in 1983, the DCE treats each choice as the selection of the alternative with the highest latent utility and recovers the utility coefficients from observed choices. Because attributes are varied independently by experimental design, the method isolates the marginal effect of each attribute, including price, and yields marginal rates of substitution such as willingness to pay. DCEs are analyzed with multinomial (conditional) logit and, increasingly, with mixed and nested logit models that relax restrictive assumptions and capture preference heterogeneity. The approach is essentially the same machinery as choice-based conjoint but is the standard term in transport, health, and environmental economics, where it is used to value non-market goods. Its rigor and flexibility have made it a dominant stated-preference technique across the social sciences.