My co-authors and I finally have a working paper based on our 2008 survey of the general public and political scientists. Many thanks to all the EconLog readers who helpedalong the way.
Here's the basic idea from the intro. Corrections and suggestions in the comments will be much appreciated.
Voters are not merely ignorant;
their beliefs about policy-relevant subjects are often systematically
overestimate the fraction of the federal budget spent on foreign aid and
welfare, and underestimate the fraction spent on Social Security and health.
(Kaiser Family Foundation and Harvard University 1995)Less-informed voters favor systematically
different policies than otherwise identical more-informed voters. (Althaus
2003, 1998, 1996)Laymen's beliefs about
economics, the causes of cancer, and toxicology systematically diverge from the
beliefs of experts, even when matched on traits like income, employment sector,
job security, demographics, party identification, and ideology. (Caplan and
Miller 2010; Caplan 2007, 2002; Lichter and Rothman 1999; Kraus, Malmfors, and
Slovic 1992) Voters also tend to discount
evidence in conflict with their pre-existing beliefs. (Taber and Lodge 2006;
Bullock 2006; Nyhan and Reifler 2010) Taken
together, the evidence raises a troubling question: If politicians cater to the
policy preferences of the median voter, won't inefficient and
counter-productive policies win by popular demand?
The strongest reply to this concern
is that citizens vote for results, not policies...One simple heuristic - reward
success, punish failure - seems to allow voters with little, zero, or even
negative knowledge about policy to extract socially desirable behavior from their leaders.
Unfortunately for democracy, this
heuristic is not as foolproof as it seems.In order to reward success and punish failure, voters need to know which
government actors - if any - are able to influence the various outcomes voters
care about. (Arceneaux 2006; Anderson 2006; Cutler 2008, 2004; Rudolph and Grant 2002; Somin
1998; Lewis-Beck 1997; Leyden and Borrelli 1995; Kerr 1975)
danger to democracy comes from systematically
biased beliefs about political influence. (Caplan 2007; Rabin 1998; Thaler
1992; Gilovich 1991)Just as the market
for automobile repair will work poorly if the average customer blames his
grocer for engine trouble, local elections will work poorly if the average
voter blames the president for the quality of public schools.
To test the American public's
beliefs about political influence for systematic bias, we designed a new
survey, and administered it to two distinct groups: (1) a nationally
representative sample of Americans, and (2) members of the American Political
Science Association who specialize in American politics.One of the main ways that scholars have tested
for the presence of systematic bias on other topics is to see whether average
beliefs of laymen and experts diverge. (Caplan 2007; Lichter and Rothman 1999; Kraus,
Malmfors, and Slovic 1992)...If
laymen and experts' average beliefs differ, our defeasible presumption is that
experts are right and laymen are wrong.
Systematically biased attributional beliefs
turn out to be common and large.Fully
14 out of 16 survey questions exhibit statistically significant biases.Compared to experts in American politics, the
public greatly overestimates the influence of state and local governments on
the economy, the president and Congress on the quality of public education, the
Federal Reserve on the budget, Congress on the Iraq War, and the Supreme Court
on crime rates.The public also
moderately underestimates the influence
of the Federal Reserve on the economy, state and local governments on public
education, and the president and Congress on the budget.While we are open to the possibility that non-cognitive
factors explain observed belief gaps, controlling for demographics and various
measures of self-serving and ideological bias does little to alter our
results.A full set of controls reduces
the absolute magnitude of the raw belief gaps by less than 13% - and leaves the
number of statistically significant lay-expert differences unchanged.