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Giffen Goods and the Law of Demand

Journal of Political Economy 1982 90(4), 809-815
The paradoxical aspect of the Giffen Paradox is the inability of demand theory to explain why Giffen goods are apparently so rare. The resolution of the paradox arises from the distinction between the shape of market demand curves and the sequence of equilibrium prices that will be observed in markets in which quantity supplied changes. The sense in which the Giffen case is "unlikely" to occur is that the probability of identifying a Giffen good is less than the probability that such a good exists.

Giffen Goods and the Law of Demand

Journal of Political Economy 1982 90(4), 809-815
The paradoxical aspect of the Giffen Paradox is the inability of demand theory to explain why Giffen goods are apparently so rare. The resolution of the paradox arises from the distinction between the shape of market demand curves and the sequence of equilibrium prices that will be observed in markets in which quantity supplied changes. The sense in which the Giffen case is "unlikely" to occur is that the probability of identifying a Giffen good is less than the probability that such a good exists.

Conjoint Measurement and the Analysis of Noisy Data: A Comment

Journal of Accounting Research 1982 20(2), 450
In a previous study reported here Moriarity and Barron [1976] used conjoint measurement to model the materiality judgment process of audit partners. They did so following the approach suggested by Krantz and Tversky [1971] in which axiomatic conjoint measurement (ACM) is used to identify the functional form of the decision maker's judgment model, and then numerical conjoint measurement (NCM) is applied to find the best-fitting scale values (part-worth functions).' Shortly thereafter, the American Accounting Association's Committee on Human Information Processing (AAA [1978]) suggested that conjoint measurement would be useful in the study of certain aspects of human information processing in accounting research, particularly for testing alternative composition rules which uses only ordinal properties of the data [1978, p. 32]. Composition rules refer to the functional forms (e.g., additive, multiplicative, etc.) of decision makers' judgment models.2 In a later paper, Moriarity and Barron [1979] examined the preaudit materiality judgments of audit partners, in which they assumed an additive model and used a holistic orthogonal parameter estimation procedure (Barron and Person, [1979]). Swieringa [1979] criticized this