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Closeness Counts Only in Horseshoes and Dancing

Published online by Cambridge University Press:  01 August 2014

John A. Ferejohn  and
Morris P. Fiorina
John A. Ferejohn
Affiliation:
California Institute of Technology
Morris P. Fiorina
Affiliation:
California Institute of Technology
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Extract

During the period in which our article (APSR vol. 68 [June 1974]) circulated in manuscript form it provoked an unusual amount of collegial reaction. Of course, we were quite prepared for a reaction from those who use decision-theoretic models in their research—they were our intended audience. More surprisingly, we also received comments from less directly involved bystanders—a medieval historian for example. All this correspondence indicates to us that nearly everyone has his own theory of how voters behave, and that most such theories do not agree with the one presented in our article. The comments of Professors Tullock, Beck, Mayer and Good, and Stephens further support this conclusion.

In an appendix to this note we have responded to the imaginative point raised by Tullock. As for the traditional questions raised by our other critics, however, we adopt a different line of rebuttal. Rather than conduct an unfruitful debate over the a priori plausibility of the minimax regret model we will do something that theorists too seldom do: examine some data. Before doing so we will make an important distinction between using a model prescriptively and using it descriptively. (Decision-theoretic types tend to move a bit too easily from one usage to the other.) Then, after reviewing the major point of our article we will turn to the data.

Type
Research Article
Information
American Political Science Review , Volume 69 , Issue 3 , September 1975 , pp. 920 - 925
Copyright
Copyright © American Political Science Association 1975

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References

1 Savage, Leonard J., The Foundations of Statistics, 2nd rev. ed. (New York: Dover, 1972), pp. 19–21, 59, passim Google Scholar.

2 Raiffa, Howard, Decision Analysis (Reading, Mass.: Addison-Wesley, 1968), p. x Google ScholarPubMed.

3 A number of recent experiments have cast serious doubt on the descriptive value of prevailing formulations of expected utility models. See, for example, two articles by Lichtenstein, Sarah and Slovic, Paul. “Reversals of Preference Between Bids and Choices in Gambling Decisions,” Journal of Experimental Psychology, 89 (07, 1971), 46–55 CrossRefGoogle Scholar. And “Relative Importance of Probabilities and Payoffs in Risk Taking,” Journal of Experimental Psychology Monograph, 78 (12, 1968), 1–18 CrossRefGoogle Scholar. Also, MacCrimmon, Kenneth R., “Descriptive and Normative Implications of the Decision Theory Postulates,” in Risk and Uncertainty, ed. Borch, Karl and Mossin, Jan (London: Macmillan, 1968), pp. 3–32 Google Scholar.

4 Plott, Charles and Levine, Michael, “On Using the Agenda to Influence Group Decisions: Theory, Experiments and an Application,” (mimeograph: California Institute of Technology, 1974)Google Scholar.

5 As we indicated earlier, examples such as crossing streets and driving on freeways are traditionally held up against minimax decision rules. For a discussion see Luce, R. Duncan and Raiffa, Howard, Games and Decisions (New York: Wiley, 1957), pp. 278–282 Google Scholar. Professors Beck and Stephens advance such criticisms as if we were unaware of them. Not so. We simply regard these criticisms as not telling when one works in the descriptive mode.

6 Riker, William and Ordeshook, Peter, “A Theory of the Calculus of Voting,” American Political Science Review, 62 (03, 1968), 25 CrossRefGoogle Scholar.

7 Indeed, Angus Campbell et al. claim that such an interaction occurs in 1956. See The American Voter (New York: Wiley, 1960), Table 5–3, p. 99 Google ScholarPubMed.

8 The data analyzed in the table were made available by the interuniversity consortium for political research. The data were originally collected by the SRC political behavior program. Neither the original collectors of the data nor the consortium bear any responsibility for our interpretation of the data. The 1968 survey is not used in the following analysis because of the three-candidate race. We do not possess the 1972 data.

9 Respondents' perceptions of closeness of the election are coded into four main categories ranging from landslide to tie. We have collapsed these categories into not close (win by landslide, or win by quite a lot) and close (win by a little, even). We assume that p tends to be lower for the first category of respondents.

10 In the analysis which follows the full range of the scale is not used. Respondents simply are dichotomized into zero scorers and everyone else.

11 These responses, too, were dichotomized. Those who responded “don't care,” or “care a little” were considered low party differential, “care,” and “care a lot” as high party differential.

12 Clausen, Aage, “Response Validity: Vote Report,” Public Opinion Quarterly, 32 (Winter, 1968–1969), 588–606 CrossRefGoogle Scholar.

13 In the remaining case (1960 postelection reports) neither hypothesis can be rejected. Thus although the general model is not rejected for this case, both particular models are.

14 At least if one considers the whole sample of registered voters. We might note that Fiorina has developed a “hybrid” expected utility model of voting behavior which produces the curious result that a subclass of the citizenry is less likely to vote the closer they perceive the election to be. Now, if the world were evenly divided between those whose turn-out was encouraged and those whose turnout was discouraged by a high p, one would expect no aggregate effect. Empirically, however, the unusual sub-class to which Fiorina's prediction applies typically appears to be small. See Fiorina, Morris, “The Voting Decision: Investment and Consumption Aspects,” (California Institute of Technology: Social Science Working Paper No. 46).Google Scholar