We are modelling the effect of the number of ballot propositions on voter turnout. Scholars of ballot propositions have traditionally used OLS models to estimate this effect, but this seems implausible. It seems likely that there will be diminishing returns (a/k/a "voter fatigue"), so that the model should not be linear. For instance, the difference in turnout for 3 ballot propositions vs. 0 ballot propositions is probably not equal to the difference in turnout for 6 ballot propositions vs. 3 ballot propositions. How can we estimate these threshholds, or effectly model this nonlinearly? I recognize this is a problem of estimating threshholds for an ordered categorical variable, but I am not sure how to approach it because the categorical variable at issue is our *explanatory* variable, not our dependent variable. Any suggestions? Thanks, Anna _______________________________________________ gov2001-l mailing list gov2001-l(a)fas.harvard.edu http://www.fas.harvard.edu/mailman/listinfo/gov2001-l

We are modelling the effect of the number of ballot propositions on voter turnout. Scholars of ballot propositions have traditionally used OLS models to estimate this effect, but this seems implausible. It seems likely that there will be diminishing returns (a/k/a "voter fatigue"), so that the model should not be linear. For instance, the difference in turnout for 3 ballot propositions vs. 0 ballot propositions is probably not equal to the difference in turnout for 6 ballot propositions vs. 3 ballot propositions. How can we estimate these threshholds, or effectly model this nonlinearly? I recognize this is a problem of estimating threshholds for an ordered categorical variable, but I am not sure how to approach it because the categorical variable at issue is our *explanatory* variable, not our dependent variable. Any suggestions? Thanks, Anna _______________________________________________ gov2001-l mailing list gov2001-l(a)fas.harvard.edu http://www.fas.harvard.edu/mailman/listinfo/gov2001-l