Old and new liberals (and conservatives)

 Today surveys routinely ask people if they are liberal, moderate, or conservative.  This wasn't the case until about 1970--there are questions going back to the late 1930s, but they are not common.  I was looking at a Gallup survey from 1950 which asked "do you consider yourself to be a conservative or a liberal in your political views?"  26% said conservative, 30% said liberal, 14% said neither, 23% no opinion, and 8% "no code or no data."  I treated "no code or no data" as missing.  There is a question of how to interpret "neither" and "no opinion".  People in those categories might have been unable to choose because they saw themselves as in between, or because they weren't interested in politics or had no idea what the terms meant.  I looked at the relationship between self-rated ideology and vote in 1948:

                                      Dewey (R)      Truman (D)       Didn't vote

Conservative                       54%              27%                   11%

Liberal                                24%              54%                    11%

Neither                               31%              43%                    18%

No opinion                        24%              38%                     29%

So in terms of party support, both "neither" and "no opinion" were in between liberals and conservatives; both are also somewhat less likely to vote.  In both of these respects, they are like people who choose "moderate" in contemporary surveys.  So I treated them as a middle groups and "no code or no data" as missing.

The GSS has a question asking people to put themselves on a 7-point scale from very liberal to very conservative, with moderate in the middle.  I collapse that two three categories (liberal side, moderate, conservative side) in order to compare contemporary (2010-18) patterns with those from 1950.  Political ideology is more strongly connected to vote today--92% of liberals and only 26% of conservatives reported voting for Obama in 2012  (among people who voted).  This is not surprising--there used to be liberal Republicans (Dewey was sometimes regarded as one) and conservative Democrats (especially in the South).

 Next, I'll give the percent liberal minus the percent conservative for several demographic groups:  gender, race, education, and size of place, in 1950 and recent years.

                           1950      2010-18

Men                        +6            -9

Women                   +2            -4

A small gender gap, which reversed direction. 

Black                        +17           +8

White                         +4            -11

Blacks more liberal at both times.

no diploma                +3               -6

HS                               0              -10*

Some college            +13          

College grad               +7            +1

 More educated people a bit more liberal at both times.

less than 3,000           -10            -16

3,000-10,000              -6             -15

10,000-100,000          -2              -6

100,000-500,000        +9             +3

500,000+                    +30            +7

A big difference at both times, maybe larger in 1950.

Age also made a difference at both times, with older people more conservative.  The correlations were of similar size (-.11 recently and -.14 in 1950).

The two most noteworthy points are (1) educational differences in ideology haven't changed much, even though educational differences in party support have changed a lot (2) the urban/rural difference in ideology was at least as large in 1950 as in recent years, although the urban/rural difference in party support seems to have grown. 

The 1950 survey also contained a number of questions about political issues; I'll discuss the connection of ideology to these in my next post.

 *includes people with some college

 [Data from the Roper Center for Public Opinion Research]

In GDP we trust

 A paper published in the Lancet recently considered a large number of variables and found that only a few of them helped to predict national differences in Covid rates.  One of those was interpersonal trust, as measured by a question asking which statement you agree with:   "most people can be trusted" or "you can't be too careful in dealing with people."  This is a plausible finding, since the average level of trust, as measured by this question, is correlated with lots of good things at the national level.  Ezra Klein, discussing this study in the New York Times, suggests that low levels of trust explain why the United States has had higher Covid rates than many other nations:  "Now that we know the truth about ourselves, and the havoc our divisions will wreak on any pandemic response, the problem we need to solve becomes clearer.  What does good pandemic policy look like for a low-trust, high-dysfunction society?"  

My initial intention was just to point out that the United States isn't really a low-trust society by international standards--it ranks 17th out of the 80 nations for which data are available in the source used by the paper (the World Values Survey).*  But it occurred to me that trust tends to increase with GDP, so I should consider the level of trust relative to GDP. Here is a plot of the relationship:

 The United States is a little below the level of trust that one would expect from our GDP, but not really unusual.  There are some economically developed democracies with lower levels of trust than the US--I indicate three, France, Italy, and Taiwan.  I also indicate three affluent nations with relatively high levels of trust--Finland, Denmark, and Norway.  Sweden and Iceland are also high, so there's a clear pattern here.  I also mark two real outliers--China, with much higher levels of trust than predicted from GDP, and Singapore, with much lower levels.  

The Lancet paper began by regressing rates on "some key known drivers of infection," one of which was GDP.  The next stage used the "adjusted" values--basically the residuals from the regression of infection rates on the "known drivers"--as dependent variables and regressed them on trust.  Of course, this isn't how it should be done--you should regress infection rates on trust and GDP together, so I did that analysis.*

The estimated effects of trust (and per-capita GDP) on infection rates:

                   (1)                  (2)                 (3)             (4)

 GDP                              -.0068           -.0080        -.0091

                                        (.0017)        (.0018)        (.0021)

 Trust         -7.94            -4.68              -3.15          -2.31

                   (1.55)           (1.85)             (1.99)        (2.18)

The first column is a regression of adjusted infection rates on trust.  The estimates I get seem to match those in the Lancet paper (I can't say for sure, since they showed them in a figure rather than giving the numbers).  That way, it seems that trust definitely makes a difference (a t-ratio of about 5).  The second is a regression of the unadjusted infection rates on GDP and trust.  The estimated effect of trust is smaller and the t-ratio is about 2.5.   It seems that the Lancet paper didn't adequately control for GDP--I believe that they used the log of GDP, and the relationship is closer to linear.   

The third column is the same model as column 2, but omits China, which reports very low levels of Covid and high levels of trust.  Some observers have already questioned their Covid figures.  As far as trust, there's a question of whether people believe that their answers will really remain secret.  The Chinese authorities don't have much tolerance for dissent, and seem quite efficient in keeping track of people.  Thus, I suspect that many respondents are giving the answers that they think they "should" give.   Without China, the estimated effect of trust is smaller and not statistically significant at conventional levels.  

Finally, column 4 omits China and also Singapore, where the GDP per capita is much higher than in any other nation ($98,000--Switzerland is second with $71,000).  Although Singapore is certainly an affluent nation, the GDP figures for small nations can be distorted.  Also, the relationship between GDP and infection has to be non-linear (otherwise there will be negative predicted values) but given the gap between Singapore all other nations in the data we can't really estimate the nature of the non-linearity.  Now the estimate for trust is even smaller and the t-ratio is just a bit over one.

So although it's plausible that trust makes a difference, the evidence isn't very strong.  What clearly does make a difference is general affluence, as seen in this figure. 

 

 

 Returning to Klein's issue, the United States has had higher rates of Covid than expected given our economic level, and we have certainly been a "high dysfunction" society in terms of the politics of the issue.  The question is whether those politics reflect a general social problem of low trust (or low solidarity).  I don't think they do.

 

*The paper didn't give any information about the distribution of trust (or other predictor variables), so it's understandable that Klein didn't realize this.

**Ideally, I would have included the other "known drivers," but the paper didn't provide those data.  It gave Covid rates, and I got trust from the WVS (their source) and GDP from the World Bank (they weren't clear on what their source was). 

Don't look down

 One of the questions that I keep returning to is how people at different educational levels view each other.  One view, held by many critics of "meritocracy," is that educated people increasingly feel disdain for less educated people, and less educated people sense that and resent it.  My view is that there's increasing social egalitarianism on the part of educated people--they don't want to be thought of as snobs or elitists--and not much change among less educated people--they just go about their lives and don't pay much attention to the fine points of social status.  I keep an eye out for questions that bear on the issue, and I ran across another one recently.  An Axios/IPSOS poll from last August asked what people thought about the statement "People without college degrees are looked down on in our society."  

Critics of meritocracy hold that educated people don't openly announce their prejudices, but reveal them by behavior or off-the-cuff remarks (like the famous "basket of deplorables").  Thus, there should be substantial differences in agreement by educational level--more educated people will deny that people without college degrees are looked down on, while less educated people will agree that they are.  The means by education (1=strongly agree, 2=somewhat agree, 3=neither agree nor disagree.... 5=strongly disagree).

No HS diploma        2.47 

HS                            2.67

Some college            2.57

Bachelor's                 2.57

Master's                    2.68

There's no pattern, and the p-value for differences between groups is 0.162.   I looked for other demographic differences and found a couple of moderate size--blacks and younger people are more likely to agree.  

 Turning to politics, Democrats were most likely to agree (2.45) and Republicans most likely to disagree (2.82), with independents and "something else" in the middle.  These differences were statistically significant.  This seems reasonable, since generally Republicans are less likely to see injustices in American society.  

But there is evidence of an interaction between party and education:

There are differences by educational level among Republicans, but no evidence of differences among Democrats and independents.  If there is a causal association, it could go in either direction--beliefs could affect partisanship or partisanship could affect beliefs.  That is, beliefs could have different effects at different educational levels.  But another way the interaction could arise is if more educated people are more aware of and influenced by what their party elites say.   With clearly partisan issues like abortion, you usually find bigger partisan differences among more educated people.  But this isn't a clearly partisan issue--Republican elites often say that Democrats look down on less educated people, but it's not clear how that would translate to views of "our society."

The survey also asked about where people got most of their news, and gave a list to choose from.  I show them from most to least agreement.  Although the numbers in most categories are small, there seems to be a pattern.

MSNBC                        2.30

NY Times/Wash Post    2.40

Public TV/radio             2.44

Online news                   2.46

CNN                               2.48

Social media                   2.49

ABC/CBS/NBC              2.64

Other                               2.76

None of them                  2.81

Fox News                        2.82

local newspaper              2.87

The ones with the strongest agreement tend to have liberal readers, and also more educated readers.  Unfortunately, they didn't include the Wall Street Journal, which has a relatively conservative and well educated readership.  But these results suggest that the belief that people without college degrees are looked down on is common among politically aware liberals.

[Data from the Roper Center for Public Opinion Research]