Pushback against Nudges

A couple items recently came across my desk that were somewhat critical (at least in parts) of the use of behavioral economics in public policy making - in particular the idea that government can use insights from behavioral economists to nudge us into making the "right" decisions.

The first item is this new paper by Viscusi and Gayer for the Brookings Institute.  They reasonably ask why behavioral economists haven't spent nearly as much time studying the irrationality of bureaucrats, politicians, and policy makers as they have studying the irrationality of consumers.  Here's an extended quote (footnotes omitted) from their discussion on the propensity of government officials to suffer from a phenomenon called ambiguity aversion:

“Ambiguity aversion is a form of irrational behavior and should not be confused with risk aversion in which people are averse to the risk of incurring a large loss . . .

Government policies frequently reflect this ambiguity aversion with novel risks. For example, court rulings tend to demonstrate a bias against innovation and the attendant uncertainties
of novel drug products. In situations where there are adverse health effects from new drugs, the courts are more likely to levy sanctions against the producer. This bias on behalf of the public is also reflected in product liability case experiments using a sample of judges participating in a legal education program. The judges considered hypothetical cases involving novel drugs and their associated liability risks. When given a choice between a new drug posing an uncertain risk or another drug with a higher known risk, most of the judges recommend that the company market the latter drug.

Another instance of ambiguity aversion involves genetically modified organisms (GMOs) . . . GMOs have come under fire and are increasingly subject to potential regulation throughout the world. . . Critics have characterized GMO foods as being very risky products of biotechnology, labeling them “Frankenfoods.” The policy trade-off involved is that GMOs may pose uncertain risks that currently are believed to be low in magnitude, but they reduce the cost of producing agricultural products, which in turn lowers food prices and promotes better nutrition. ”

They go on to hint at the idea (though never come right out and say it) that the precautionary principle is a behavioral bias.  

The other item was an article in the The Guardian that asks whether all the cutesy messages by companies and governments encouraging us to "do the right thing" are really all that helpful or more effective than traditional policies.  The conclusion: 

“And another lesson, not mentioned by the team, but by other economists , is that it is very important to question whether the choices of the behaviourists, whether in government or in ad agencies where nudging opens up a yet more glorious prospect, are invariably wise and good. What, for instance, made the Highways Agency think that a made-up kiddie quote indebted to the Pret school of copywriting condescension (“a little girl asked us why we didn’t make gingerbread men”) might be preferable to speed cameras that build up points for offending drivers, as opposed to irritation in the law-abiding? Or preferable, indeed, to nothing? Maybe a little girl was involved.”

Behavioral Economics and Public Policy

David Just and Andrew Hanks have a new paper forthcoming in the American Journal of Agricultural Economics entitled: The Hidden Cost of Regulation (I noticed Marc Bellemare beat me to the punch in discussing his views on the paper).  

This is an important paper in many respects.  As I see it, one of the general problems with the behavioral economics literature is that the findings of behavioral biases (e.g., status quo bias, overweighting low probability risks, loss aversion, present, etc.) are almost always put forth as motivation for more government regulation.  Yet, it is easy to imagine many behavioral economic findings suggesting just the opposite - though that is rarely the conclusion drawn by the authors.

Here's an  example I used in the Food Police

“Here is the irony. The behavioral economists have told us for years that humans make mistakes by exaggerating the importance of low-probability risks. Yet, I have not seen a single behavioral economist use this insight to tell the food police to relax and put their fears over growth hormones, genetically modified food, or pesticides into perspective. Instead, we see the behavioral economists partner with the food police to advocate policies they want even if it means ignoring the implications of their own research. ”

Now, enter the paper by Just and Hanks.  They show that if consumers have a positive emotional attachment to a good that a government policy that attempts to restrict consumption of that good may cause a backlash by causing people to want it even more.

 Think of the Bloomberg large soda ban.  The very action of telling people "you can't have large sodas" makes them want large sodas even more, which makes banning large sodas even more costly in terms of foregone consumer welfare.  They argue that the reverse  may also be true: subsidizing something like healthy food that people feel like they should be consuming more of makes  them want it all the more.  

The general story here is that people's preferences (what they want) may not be independent of the policies government officials pursue.  It is an issue I've studied on a couple of occasions (here and here) with regard to the effects of mandatory labels on genetically engineered food. If people see a mandatory label as information about the risks of genetic engineering, the very presence of a label could make them even more averse to genetically engineered food.  

All this makes the normal sort of "welfare economics" we economists normally do a bit tricky.    Normally we look at the choices (and prices) before a policy is in place and the choices (and prices) after a policy is in place to determine whether consumers are better off with the policy or not.  How do we determine better off?  With a mathematical function derived from the choices people make.  Think of it like: happiness = f(prices, # of options).   But, if a policy changes preferences, then it is hard to know whether the consumer is happier or sadder because, in a sense, they're now a different person that has different tastes and wants.  Not only have prices and number of options changed but the function relating happiness to these factors has changed too.

While the Just and Hanks paper is largely a theoretical paper, I'm please to see a framework put forward for people to seriously evaluate public policies in a fully consistent behavioral economics framework rather than the ad hoc way it's normally done.  I also hinted as this sort of thing in a paper with Bailey Norwood and Stephan Marette where we ran some experiments where people could either choose for themselves or where other's made choices for them (we called the choosers the "paternalist" and the recipients of the choices (or children as Stephan calls them) the "paternalee)".  

“One interpretation of these results is that paternalees place an intrinsic value on freedom of choice. This does not necessarily imply that the paternalees’ choices are in any sense “optimal” or that, should paternalees suffer from time-inconsistent preferences, their long-term well-being couldn’t be enhanced by restricting current choices. Nevertheless, if this interpretation is correct, the results suggest that any long-term benefits that might arise from paternalism must be weighed against the loss of freedom of choice.”

Applying behavioral economics to politics

This is an interesting review paper on Behavioral Political Economy by Jan Schnellenbach and Christian Schubert.

One of the points they make is that researchers have not fully integrated the insights of behavioral economics into analyses of how politicians and bureaucrats behave.
 

A quote

“The case of Libertarian Paternalism therefore illustrates the difference between BPE [behavioral political economy] and behavioral welfare economics, which is very akin to the old conflict between Political Economy and traditional welfare economics. Behavioral welfare economists are currently at risk of repeating the mistake of neglecting the real-world political process with its many intricacies. Under these conditions, policy advice addressed to an imaginary social planner may not only be useless, but even dangerous, if it helps to promote policies that have unintended, negative consequences under real-world conditions. ”

Regulating your food choices vs. retailers' food choices

Suppose the government made it illegal for you to buy sugared soda.  What would be your reaction?  How would you feel?  

Now, suppose instead that the government made it illegal for grocery stores and other vendors to sell sugared soda.  Is your reaction to the second law less visceral than the first?  

I suspect so.  But, here's the key: both laws impose the same restriction on your freedom - the outcomes are precisely the same.

Writing at Forbes, John Goodman notes this dichotomy in the case of California eggs (HT David Henderson)

“California has a new law that requires all eggs sold in the state to come from chickens that are housed in roomier cages. Specifically, the hens “must be able to lie down, stand up and fully spread their wings.”

So how many Californians have been arrested for eating the wrong kind of egg? Zero. Not even one? Not one. Actually, the law doesn’t take effect until January, but even then egg eaters will have nothing to fear. The reason: the law doesn’t apply to people who eat eggs. It only applies to people who sell eggs.

When you stop to think about it, that’s not unusual. Almost all government restrictions on our freedom are indirect. They are imposed on us by way of some business. In fact, laws that directly restrict the freedom of the individual are rare and almost always controversial.”

After discussing various reasons for the differences in the way we respond to individual vs. business restrictions, Goodman concludes:

“Finally, the idea being proposed here seems consistent with history. Over the past two hundred years, we have had a steady migration of people from agriculture to the cities, where they became employees of firms. Over the same period of time we have had a parallel increase in the intrusiveness of government.

Bottom line: if there were no firms, taxes would be much lower, there would be far fewer regulations and government would be a much less important institution in our lives.”

What are the farm-level effects of GMOs?

A new study published in PLoS ONE by Wilhelm Klümper and Matin Qaim surveyed the literature on the farm-level effects of GMO adoption.  They conducted a Meta analysis - a type of quantitative literature review - covering 147 previous studies.

What did they find?

“On average, GM technology adoption has reduced chemical pesticide use by 37%, increased crop yields by 22%, and increased farmer profits by 68%. Yield gains and pesticide reductions are larger for insect-resistant crops than for herbicide-tolerant crops. Yield and profit gains are higher in developing countries than in developed countries.”

This is a a decent study which summarizes what most people who follow the literature already know.  There will, no doubt, be attempts by the anti-GMO crowd to discredit the study.  However, Qaim is a productive, well known agricultural economist.  He’s published in the best outlets in agricultural and development economics, and even in journals like Science and Nature Biotechnology.  

Like any Meta analysis, the study isn't perfect, and is only as good as the studies being reviewed.  A few criticisms.  The analysis didn't much differentiate between insecticides (the use of which has almost certainly fallen) and herbicides (total use is probably up, but because GM producers have switched to less toxic herbicides  the total toxicity is likely down).  Also, some of the underlying studies may not have done a good job separating yield gains from traditional hybrid breeding from gains conveyed by biotechnology per se, so the yield gains attributable to GM may be a bit overstated (e.g., see this study).  What I’m saying here is that corn/soybean yields probably would have increased regardless of whether GM was adopted, so you have to “back out” the increase attributable to GM; some studies do that well, others don’t.  Finally, as you can see in their figures, there is a lot of heterogeneity across studies; the mean effects for yields and profit are positive, but some studies show negative.  

In any event, this is a good study that re-confirms my own reading of the literature.