David,
 
Other options:
 
(1) bivariate probit (two equations, one for Prop 8, one for Prop 13), which allows correlated errors between the two equations (see Andrew Martin and Christina Wolbrecht. 2000. ``Partisanship and Pre-Floor Behavior: The Equal Rights and School Prayer Amendments.'' Political Research Quarterly) 
(2) multinomial logit with separate categories for YY, YN, NY, NN (vote on Prop 8, Prop 3).  Multinomial probit may be better in this case to allow for correlated errors across the choices.  
 
Errors in these equations may be correlated due to strategic voting or to nonseparable preferences, among other things.  (See Dean Lacy and Emerson Niou. 1998. A Problem with Referendums.  Journal of Theoretical Politics)
 
Either approach, particularly #2, would allow you to calculate predicted utilities for each pair of votes for each voter.  You could then calculate cut-points between support for 13 only, 8 only, both, neither.  You could also calculate how vote shares for 8 and 13 would have changed if the other proposition had not been on the ballot.  
 
Dean Lacy

________________________________

From: Political Methodology Society on behalf of David Hugh-Jones
Sent: Mon 3/6/2006 6:33 AM
To: [log in to unmask]
Subject: [POLMETH] strategy for pairs of votes



Hi guys

I am examining pairs of initiative votes, such as votes on
California's Propositions 13 and 8 (8 was a counter-initiative placed
on the ballot by the legislature). My basic hypothesis looks like
this:



                                          [=== Yes on 13 ==========...
                           [===== Yes on 8 ====]
<------------------------------------------------------------------------------------>
underlying policy preference


I.e. moderates vote yes on 8, and there is some overlap where people
vote yes on both.

As I don't have a nice linear measure of policy preference, my idea
was to (logit) regress support for Proposition 13 against my
independent variables (which are almost all categorical), then to use
each individual's predicted logged
odds for support of 13 as a measure of underlying policy preference. I
could then put this predicted value into a logit on support for
Proposition 8, either interacted with actual support for 13, or in two
separate regressions for supporters and opponents of 13. The
expectation would be that the policy variable would be significant but
with opposite signs for yes and no voters on 13.

However, I am worried about endogeneity: if the votes are
interrelated, is using the Yhats for one vote in a regression on the
other acceptable?

Any thoughts would be welcome.

Cheers
David Hugh-Jones
PhD student
Essex Dept of Govt

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