Readers of this blog will know I’ve been interested in the divergence of voting and food shopping behavior for some time (e.g., see here, here, or here). Much of this interested was prompted by the stark example provided by Proposition 2 in California back in 2008, when about 64% of Californian’s went to the polls and outlawed the production of a good they routinely bought (caged eggs) resulting in a so-called vote-buy gap. I think it was Glynn Tonsor who I first heard refer to the outcome as an unfunded mandate: voters required producers to adopt costlier production practices for which shoppers had already revealed they were unwilling to provide sufficient compensation in the marketplace.
While we know this phenomenon exists, it isn’t clear why. Along with Glynn Tonsor, Bailey Norwood, and Andrew Paul, we set out to tackle this question by conducting some real-food, real-money experiments. The resulting paper is now forthcoming in the Journal of Behavioral and Experimental Economics.
What did we do? We recruited people to participate in a series of decision making exercise, where they first made a shopping choice. The shopping choice options were: A) a more expensive cookie made with cage free eggs, B) a less extensive cookie made with conventional eggs, C) a snack without animal products, or D) refrain from buying anything. Then, in a second step, people were placed into groups (of small or large size), where they voted on whether to ban option B (the cookie made from conventional eggs) for the people in their group. Finally, if the vote passed, people re-chose from the constrained set of options. This basic set-up was repeated in several conditions that varied information, group size, and more to test different reasons for vote-buy gap.
The first result is that we can replicate the vote-buy gap in our experimental setting. We note:
approximately 80% of the individuals who chose snacks with caged eggs when shopping subsequently voted to ban snacks with caged eggs. The finding rules out the suggestion that the vote-buy gap is an illusion or statistical artifact, as it can be re-created in an experimental lab setting at an individual level.
As the above results suggests, we are immediately able to rule out one explanation for the vote-buy gap - something we call the non-buyer hypothesis. The non-buyer hypothesis suggests the vote-buy gap is something of an illusion because, proverbially speaking, apples (voters) are being compared to oranges (shoppers). In the “real world”, many consumers of eggs are voters; however, not all voters are egg consumers. For example, individuals who are vegan do not buy eggs, but they may vote in favor of initiatives similar to that of Proposition 2. But, in our study we can compare each individual’s shopping choice to their own vote, and as the foregoing quote indicates, 80% of people switch.
We find a bit of support for the following, which is tested by giving one group more salient information about which options used cage and which used cage free eggs:
Knowledge Hypothesis: The vote-buy gap is caused by the fact that consumers themselves believe, or perceive that other consumers believe, that they are buying cage-free eggs when in fact they are buying cage eggs; better, more salient information about housing practices when shopping will reduce the vote-buy gap.
But, even in the condition where clear-transparent information was given about the types of eggs used to make each cookie, the share of people who voted to ban cage eggs was 15 to 20 percentage points higher than was the market share of purchased snacks made with cage free eggs.
I was personally most excited to test two hypotheses that related to group size (people voted in groups of roughly five or fifty). Here were those hypotheses, both of which suggest greater likelihood of voting “yes” to ban snacks with cage eggs in larger groups as compared to smaller groups.
Public Good Hypothesis: The vote-buy gap is caused by the fact that more animals and people are impacted by a ban than the impact of a single shopping choice for cage-free eggs; as the size of the group affected by a vote increases, individuals are more likely to vote in favor of the initiative if it has a desirable public good component, thereby increasing the vote-buy gap.
Expressive Voter Hypothesis: The vote-buy gap is caused by the fact that in large groups, an individual’s vote is unlikely to be a deciding factor, privileging expressive preferences over instrumental preferences; as a group size increases, and the likelihood that an individual’s vote is consequential and decisive falls, individuals are more likely to vote in favor of the initiative, thereby increasing the vote-buy gap.
Both hypotheses conjecture that the vote-buy gap will be larger in large groups than small groups. However, our data shows that when moving from small to large groups, the vote-buy gap is actually larger in the small groups than the large group, exactly the opposite of what is predicted.
In the end, we can be fairly confident the vote-buy gap is real and replicatable, but alas we still don’t have a good answer as for why. Here’s how we leave it in the paper:
A residual hypothesis that remains if all others fail to explain the gap is inconsistent preferences. That is, people may have different preferences when shopping as compared to voting. This sort of preference inconsistency is at the heart of the so-called consumer vs. citizen phenomenon. The thought is that people adopt more public-minded preferences when in the voting booth but rely on more selfish motives when shopping privately. ... While this explanation is perhaps not intellectually satisfying, it is perhaps consistent with one long strain of economic thought, De gustibus non est disputandum, while contradicting another, fixed and stable preferences.
But, make no mistake: just because we don’t know the answer to the “why” doesn’t imply the vote-buy gap is inconsequential. Recall the unfunded mandate? Here’s what happened in our experiment.
many individuals who originally chose to purchase a cookie decided, after the ban, to select “none” in their second selection when only higher-priced cookies were available. Depending on the treatment, anywhere from 21.74% to 43.38% of consumers who purchased cookies prior to the ban no longer did so after the ban. These lost purchases are precisely the worry of egg producers.