Northwestern University

About: Northwestern University is a education organization based out in Evanston, Illinois, United States. It is known for research contribution in the topics: Population & Medicine. The organization has 75430 authors who have published 188857 publications receiving 9463252 citations. The organization is also known as: Northwestern & NU.

The relationship between memory and judgment depends on whether the judgment task is memory-based or on-line

Abstract: Five alternative information processing models that relate memory for evidence to judgments based on the evidence are identified in the current social cognition literature: independent processing, availability, biased retrieval, biased encoding, and incongruity-biased encoding. A distinction between two types of judgment tasks, memory-based versus on-line, is introduced and is related to the five process models. In memory-based tasks where the availability model describes subjects' thinking, direct correlations between memory and judgment measures are obtained. In on-line tasks where any of the remaining four process models may apply, prediction of the memory-judgment relationship is equivocal but usually follows the independence model prediction of zero correlation. There ought to be a relationship between memory and judgment. Our intuition tells us that we should be able to generate more arguments and information in support of a favored position than against it, that evaluations of people should be related to the amounts of good and bad information we have about them. When a person is able to remember many arguments against a belief, or to cite many good characteristics of an acquaintance, we are surprised if they endorse the belief or dislike the person. In support of intuitions like these, names have been given to the idea that memory and judgment have a simple direct relationship, including "availability," "dominance of the given," "salience effect," and so forth. However, empirical studies of the relationship between memory and judgment with subject matter as diverse as social impressions, personal attitudes, attributions of causes for behavior, evaluations of legal culpability, and a variety of probability and frequency estimates have not revealed simple relations between memory and judgment. Some relationships have been found, but strong empirical relations are rare and results are often contradictory. Some examples seem to support the expectation of a direct relationship between memory and judgment. Tversky and Kahneman (1973) demonstrated that many judgments of numerosity were directly correlated with the "ease with which instances or associations could be brought to mind" (p. 208). In an illustrative series of experiments, they showed that judgments of the frequency of words in English text were correlated with the ease of remembering the words. Beyth-Marom and Fischhoff(1977) provided more definite evidence on the strength of the mem

Finite sample properties of some alternative GMM estimators

Abstract: We investigate the small-sample properties of three alternative generalized method of moments (GMM) estimators of asset-pricing models. The estimators that we consider include ones in which the weighting matrix is iterated to convergence and ones in which the weighting matrix is changed with each choice of the parameters. Particular attention is devoted to assessing the performance of the asymptotic theory for making inferences based directly on the deterioration of GMM criterion functions.

Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement

Abstract: Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1989), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.