The Limited Political Implications of Behavioral Economics

A recent post on Marginal Revolution contends that progressives use findings from behavioral economics to support the economic policies they favor, while ignoring the implications that support conservative policies. The short post, originally a comment by blogger and computational biologist Luis Pedro Coelho, is perhaps intentionally controversial, arguing that loss aversion is a case against redistributive policies and social mobility:

"Taking from the higher-incomes to give it to the lower incomes may be negative utility as the higher incomes are valuing their loss at an exaggerated rate (it’s a loss), while the lower income recipients under value it... 

...if your utility function is heavily rank-based (a standard left-wing view) and you accept loss-aversion from the behavioral literature, then social mobility is suspect from an utility point-of-view."

Tyler Cowen made a similar point a few years ago, arguing that "For a given level of income, if some are moving up others are moving down... More upward — and thus downward — relative mobility probably means less aggregate happiness, due to habit formation and frame of reference effects."

I don't think loss aversion, habit formation, and the like make a strong case against (or for) redistribution or social mobility, but I do think Coelho has a point that economists need to watch out for our own confirmation bias when we go pointing out other behavioral biases to support our favorite policies. Simply appealing to behavioral economics, in general, or to loss aversion or any number of documented decision-making biases, rarely makes a strong case for or against broad policy aims or strategies. The reason is best summarized by Wolfgang Pesendorfer in "Behavioral Economics Comes of Age":

Behavioral economics argues that economists ignore important variables that affect behavior. The new variables are typically shown to affect decisions in experimental settings. For economists, the difficulty is that these new variables may be unobservable or even difficult to define in economic settings with economic data. From the perspective of an economist, the unobservable variable amounts to a free parameter in the utility function. Having too many such parameters already, the economist finds it difficult to utilize the experimental finding.

All economic models require making drastic simplifications of reality. Whether they can say anything useful depends on how well they can capture those aspects of reality that are relevant to the question at hand and leave out those that aren't. Behavioral economics has done a good job of pointing out some aspects of reality that standard models leave out, but not always of telling us exactly when these are more relevant than dozens of other aspects of reality we also leave out without second thought. For example, "default bias" seems to be a hugely important factor in retirement savings, so it should definitely be a consideration in the design of very narrow policies regarding 401(K) plan participation, but that does not mean we need to also include it in every macroeconomic model.

Let's Not Give Up on Mobility

Gregory Clark, an economic historian at UC Davis, writes that "Social mobility barely exists but let’s not give up on equality." His research using rare surnames to track social mobility over several centuries finds that social mobility in England is still just as low in today's "modern noisy meritocracy" as it was in pre-industrial times. He concludes that "Lineage is destiny. At birth, most of your social outcome is predictable from your family history." He emphasizes that this is true not only in the UK, but also in Sweden, China, and the U.S.

The subtitle of Clark's article says that "Too much faith is placed in the idea of movement between the classes. Still, there are other ways to tackle the unfairness of society." He elaborates:

"Given that social mobility rates are immutable, it is better to reduce the gains people make from having high status, and the penalties from low status. The Swedish model of compressed inequality is a realistic option, the American dream of rapid mobility an illusion...While mobility seems governed by a social physics that defies easy intervention, the magnitude of social inequalities varies considerably across societies, and can be strongly influenced by social institutions. We cannot change the winners in the social lottery, but we can change the value of their prizes."

I agree that meritocracy alone does not guarantee high mobility, and therefore that making a society more meritocratic is not the silver bullet solution to inequality. But I wouldn't go so far as to say that social mobility rates are immutable. First, just because social mobility has not improved in the past doesn't mean that it's incapable of improving in the future. Second, the fact that social mobility varies across countries and even within countries implies that it should be possible to increase mobility.

Within the United States, there is substantial geographic variation in social mobility. Raj Chetty, Nathaniel Hendren, Patrick Kline, and Emmanuel Saez use administrative records on the incomes of 40 million children and their parents to study intergenerational mobility in 741 local areas. It turns out that the American dream is more viable in some places than in others. Chetty summarizes:

Looking at the probability that a child who grew up in a bottom-quintile income family reaches the top-quintile of the income distribution across areas of the U.S., we find substantial variation across regions. In some parts of the U.S. – such as the Southeast and the Rust Belt – children in the bottom quintile have less than a 5% chance of reaching the top quintile. In other areas, such as the Great Plains and the West Coast, children in the bottom quintile have more than a 15% chance of reaching the top quintile. 

There is substantial variation in upward mobility even among large cities that have comparable economies and demographics. Cities such as Salt Lake City and San Jose have rates of mobility comparable to Denmark and other countries with the highest rates of mobility in the world. Other cities – such as Charlotte and Milwaukee – offer children very limited prospects of escaping poverty. These cities have lower rates of mobility than any developed country for which data are currently available.

Not only does mobility vary across geographic regions, it varies in systematic ways. Chetty et al. find that proxies for the quality of the K-12 school system are positively correlated with mobility. So are social capital indices, which measure the strength of social networks and community involvement. For example, high upward mobility areas tend to have higher participation in local civic organizations and religious activity. Clark says that low social mobility is here to stay because of "strong transmission within families of the attributes that lead to social success." But certainly there are other methods of transmission, particularly in schools and communities, that could be developed or improved. 

Improving the living conditions of the poor is extremely important regardless of the level of mobility in a society. So I agree with Clark that we shouldn't give up on equality. But I think we shouldn't give up on mobility either. History tells us what has happened, not what can happen. We don't know what could happen under a sustained and ambitious effort to improve upward mobility.