Book review: Economics Rules

Economics and economists come in for a fair amount of criticism from those outside the discipline. Not all of that criticism is for good reason, but at least some of it is. And there is also a fair amount of criticism of economics and economists from within the discipline. Dani Rodrik's new book, Economics Rules, fits into the latter category. However, it isn't all negative. As Rodrik notes in the introduction, "this book both celebrates and critiques economics".

At the heart of economics lie models. Rodrik spends much of the early chapters describing what economic models are, and what makes them useful. The usefulness of models is that they capture aspects of reality. The multiplicity of different models in economics exist because they capture different aspects, relying on different simplifying assumptions to do so. However, this also causes a problem because:

...very few of the models that economists work with have ever been rejected so decisively that the profession discarded them as clearly false.

Despite this problem, Rodrik is clearly in favour of having diversity of models, and clearly advocates for this, with the caveat that economists need to recognise that each model is a model, not the model. This is fair criticism - too often economists rely on shoehorning reality into their preferred model, rather than recognising that in different situations or contexts, different models will be called for. This is something more akin to the approach of Nobel Prize winner Jean Tirole.

When economists confuse a model for the model, Rodrik explains that this leads to errors of omission (where economists fail to see troubles looming ahead, such as the Global Financial Crisis), and errors of commission (where economists become complicit in policies whose failure might have been predicted in advance, such as the Washington Consensus). He goes on to note that:

Because economists go through a similar training and share a common method of analysis, they act very much like a guild. The models themselves may be the product of analysis, reflection, and observation, but practitioners' views about the real world develop much more heuristically, as a by-product of informal conversations and socialization among themselves. This kind of echo chamber easily produces overconfidence...

Rodrik sees this as leading to two weaknesses in modern economics:

...the lack of attention to model selection and the excessive focus at times on some models at the expense of others.

Alluding back to his earlier book, The Globalization Paradox (which I reviewed here), he argues that economists need to be 'Foxes' (holding many different views about the world, based on different models), rather than 'Hedgehogs' (who are captivated by a single big ides, such as 'markets work best'). 

Overall, this book is a good read for both economists and non-economists alike. Economists who read the book with an open mind may be persuaded to be a little more open to alternative models, or at least they might apply themselves more thoughtfully to the task of model selection. Non-economists who read the book may gain a better appreciation for what underlies the perceived arrogance of economists in defending their policy prescriptions based on particular models. Recommended!

Crack cocaine and the gun violence equilibrium in the U.S.

In economics, we often recognise that there may be multiple equilibriums, and that even a relatively small shock may be enough to cause the economy to move from one equilibrium to another. Consider gun violence as an example. If gun violence is low, people feel safe and therefore don't feel the need to carry a gun for self-defence purposes. Therefore there exists a low gun violence equilibrium. [*] However, if some shock occurs, and gun violence increases, then people will feel less safe. They will be more likely to carry a gun for self-defence purposes, and therefore more likely to use a gun, perpetuating the level of gun violence. Therefore there also exists a high gun violence equilibrium. However, once a society is in a high gun violence equilibrium, it is going to be very difficult to reverse things.

What would cause society to move from a low gun violence equilibrium to a high gun violence equilibrium? A 2018 NBER Working Paper by William Evans (University of Notre Dame), Craig Garthwaite (Northwestern University), and Timothy Moore (Purdue University) provides evidence that the rise of the crack cocaine market in the U.S. in the 1990s caused a shift from a lower gun violence equilibrium to a higher gun violence equilibrium. Their argument is that:

...the daily experiences of young black males were fundamentally altered by the emergence of violent crack cocaine markets in the United States. We demonstrate that the diffusion of guns both as a part of, and in response to, these violent crack markets permanently changed the young black males’ rates of gun possession and their norms around carrying guns. The ramifications of these changes in the prevalence of gun possession among successive cohorts of young black males are felt to this day in the higher murder rates in this community.

They use city-level data from the largest 57 metropolitan areas (in 1980) on age-, sex- and race-specific murder rates, over the period:

...from eight years prior to the arrival of crack and 17 years after, for a total of 26 years for each city. As the earliest date of crack’s arrival is 1982 and the latest is 1994, our data set spans from 1974 through 2011.

Essentially, they use a difference-in-differences approach that compares the change in murder rate for young black males (aged 15-24 years) before and after the introduction of crack into their city, with the same change for black males aged 35 years and over. They find that:

...the emergence of crack cocaine markets is associated with an increase in the murder rate of young black males that peaks at 129 percent in the decade after these markets first emerge...

...17 years after crack markets arrived, the murder rates for young black males were 70 percent higher than they would have been had they followed the trends of older black males. 

They key figure from the paper is this one, which plots the change in murder rate for young black males:

The x-axis tracks years before (negative numbers) and after (positive numbers) the introduction of crack cocaine into the city. There is a clear and statistically significant increase in murders among young black males, compared with older black males. Evans et al. then go on to show that this likely arose from increases in gun violence, in three ways, by showing:

...in the six years after crack markets emerged, the share of all murders attributable to young black males increased by 75 percent. Seventeen years after crack markets emerged, young black males still accounted for a 45 percent greater share of all murders than they had in the years before the arrival of crack markets...

...these murders [between family members] increase markedly in the years after crack markets and remain elevated over the next sixteen years. This increase is driven entirely by murders involving guns, with no detectable change in the non-gun domestic violence murder rate over this time period...

...we further show that there is a strong correlation between ten-year changes in gun ownership and changes in the fraction of suicides involving guns among 15-19 year olds.

These results are all consistent with a story that the arrival of crack cocaine in a city increases murders primarily through an increase in gun-related violence. I liked this paper also because it gave a detailed account of the development of crack cocaine markets in the U.S. Here are the highlights:

In the early 1970s, much of the cocaine shipped to the U.S. originated in Chile. After the 1973 military coup by Augusto Pinochet in Chile that toppled the administration of Salvador Allende, Pinochet initiated a military crackdown on cocaine smuggling operations. Many smugglers moved to Colombia with the goal of using established marijuana smuggling routes as a way of getting cocaine to the United States...

As these organizations [the Colombian drug cartels] grew, an informal agreement was struck where the Medellin cartel would primarily control supply into Miami and Los Angeles, while Cali would concentrate its operations in New York...

The large-scale entrance of the Colombian cocaine cartels into Miami, New York and Los Angeles meant that by the early 1980s, these areas had relatively high cocaine supply leading to falling prices. Despite the downward pressure on prices, many low-income consumers remained priced out of the market...

Crack cocaine was an innovation that provided a safer way to smoke cocaine... This new product has two attractive properties. First, it produced an instant high, and its users could quickly become addicted. Second, an intense high could be produced with a minimal amount of cocaine, meaning that the profit-maximizing per-dose price was a fraction of the price per high for powder cocaine...

Crack was first introduced to the market by innovative retail organizations in New York, Miami and Los Angeles, which had a large supply of powder cocaine. It then spread from those cities...

The combination of a liquidity-constrained customer base and the short-lived high offered by the product meant many customers purchased multiple times a day... crack cocaine was sold in small doses, often in open-air drug markets where the dealer and the customer had no pre-existing contact to arrange that particular sale (though may have participated in a similarly anonymous sale at that location before)...

The lack of preexisting arrangements with buyers meant that geography was a key determinant of a crack dealer’s revenue...

The violence associated with establishing and defending a market from entry was a key reason for a substantial amount of drug-related violence.

If you need to fight a turf war to protect your market (or gain access to a market), guns are an efficient way to do so. Crack cocaine was a key driver that moved the U.S. from a lower gun violence equilibrium to a higher gun violence equilibrium.

[HT: Marginal Revolution, last year]

*****

[*] However, this equilibrium is very unstable. Readers who understand some game theory will probably recognise this as a form of the 'arms race' game, which is itself a type of prisoners' dilemma. Everyone would be safe(r) if no one carried a gun. However, if no one else carries a gun, you can be both safe and powerful by carrying a gun. So, there are incentives to carry a gun, regardless of whether everyone else is, or no one else is. The low gun violence 'equilibrium' is not actually a Nash equilibrium in this game. It is unstable, but may be kept in place by cultural norms against carrying guns, or high penalties for doing so.

Retractions hurt academic careers, and may be worst for senior researchers

In modern academic publishing, retractions (where a published article is removed from the academic record) have become a fairly regular occurrence (a quick read of Retraction Watch will show you just how often this occurs). Articles may be retracted for many reasons, from simple mistakes in analyses or contaminated lab samples, to fabrication of data and results. A reasonable question to ask, then, is to what extent a retraction impacts on an academic's career. Oftentimes, the retraction comes years after publication of the article, and in the meantime the author has used the article to contribution to their reputation. Is their reputation damaged by the retraction, and if so, by how much? And, does the type of retraction (simple mistake, or serious misconduct) matter?

A 2017 article by Pierre Azoulay, Alessandro Bonatti (both MIT), and Joshua Krieger (Harvard), published in the journal Research Policy (and not retracted, ungated earlier version here), provides some answers. First, they note that the number of retractions has increased over time, as shown in their Figure 1:

You can see that the problem is getting worse over time. Or at least, you can see that the number of retractions is increasing over time. Maybe we have become more vigilant at recognising mistakes and misconduct, and ensuring those articles are retracted? It is difficult to say.

In any case, Azoulay et al. then looked at data from 376 US-based biomedical researchers with at least one retracted article that was published between 1977 and 2007, and retracted before 2009. They compared those authors with a control group of 759 authors with no retractions, made up of authors who published the article that was immediately after the retracted one in the same journal. They focus on the impacts on citations of the authors' published articles that are unrelated to the retracted one, because a retraction might negatively impact the entire line of inquiry, in terms of citations. They find that:

...the rate of citation to retracted author's unrelated work published before the retraction drops by 10.7% relative to the citation trajectories of articles published by control authors.

Azoulay et al. also find evidence that the citation penalty increases over time. In the sample of retractions as a whole, they don't find differences between the impact on high status (those in the top quartile of researchers in terms of the number of citations to their previous research) researchers and low status researchers (those in the bottom three quartiles). However, when they look at different types of retraction, they find:

...a much stronger market response when misconduct or fraud are alleged (17.6% vs. 8.2% decrease).

You might wonder why a simple mistake would have a negative impact on researchers. This arises because no one can be certain of a researcher's quality, and if a researcher has made a mistake in a published article, then the perception of their quality are a researcher is reduced (and with it, citations of their other work).

When it comes to mistakes and misconduct, there are differences in their impact between high status and low status researchers. Retractions due to mistakes have a greater impact on low status researchers than high status researchers (about a 9.7% reduction in citations for low status researchers, but a 7.9% reduction for high status researchers). However, retractions due to misconduct have a much larger impact on high status researchers (19.1% reduction in citations) than on low status researchers (10% reduction).

Across all their results, the impacts on research funding follow a similar pattern. Junior researchers face greater career penalties for mistakes, but senior researchers face greater penalties for serious misconduct. However, since their sample was limited to researchers who were still employed after the retraction, their results may be biased if junior researchers are more likely to exit the profession than senior researchers, in response to a retraction (or before the retraction). Perhaps junior researchers whose careers would be most negatively affected are most likely to exit? Some additional work in this area is definitely warranted.

Despite that caveat, the overall story is somewhat comforting. The research community does punish researchers for their malpractices, and more severely than for genuine mistakes. However, in order for that process to be effective, the community needs to know the circumstances surrounding each retraction. Indeed, Azoulay et al. conclude that:

...the results highlight the importance of transparency in the retraction process itself. Retraction notices often obfuscate the difference between instances of “honest mistake” and scientific misconduct in order to avoid litigation risk or more rigorous fact-finding responsibilities. In spite of this garbled information, our study reveals that the content and context of retraction events influences their fallout.

Auckland as an internal migration donor to the rest of New Zealand is nothing new

Newsroom reported a couple of weeks ago:

A growing number of people are turning their back on Auckland for greener and cheaper pastures of the regions.

A study by independent economist Benje Patterson indicates 33,000 left the super city in the four years to 2017, when its overall population grew by nearly 200,000 to nearly 1.7 million.

Patterson's study is available here. He makes use of a cool new dataset from Statistics New Zealand on internal migration, based on linked administrative data from the Integrated Data Infrastructure (IDI). However, even though the data he uses are new, the story is not. Auckland has long been an internal migration donor to the rest of New Zealand. This is a point that Jacques Poot and I have made at numerous conferences and seminars over the years.

In each Census (until the 2018 Census), people were asked where they were living five years previously (including in the 2013 Census, even though it was seven years after the 2006 Census). We can use that data to construct a matrix of flows from each region or territorial authority (TA) to every other region or TA. This essentially captures the number of people who changed the region or TA they lived in over a five-year period. It is different from the annual change data that Patterson uses, and in comparison the annual flows should be larger (because a person who migrates from Auckland to somewhere else, and then back to Auckland, within the five-year period, would not count as a migrant in these data).

Now, even though (in the Newsroom article) Patterson describes the five-yearly Census as "clunky", it is this Census data that shows Auckland's net out-migration to the rest of New Zealand is not a new phenomenon, and has been ongoing since the mid-1990s. Here's the data for the last four Censuses we have data for (not the 2018 Census, as we are still waiting) [*]:

The blue bars are the number of in-migrants to Auckland (from elsewhere in New Zealand) over each five-year period based on the Census data. The orange bars are the number of out-migrants from Auckland (to other places in New Zealand) over the same period. The smaller grey bar is the net internal migration to or from Auckland. Notice that for the last three periods (1996-2001, 2001-2006, and 2008-2013), net migration is negative. That means more out-migrants from Auckland to the rest of New Zealand than in-migrants from the rest of New Zealand to Auckland.

In other words, the new Statistics New Zealand data are not showing a trend that is new at all. It's something that has been going on for a long time. Which also puts the shallowness of the analysis in Patterson's report into context, such as this:

Auckland’s regional migration losses to the rest of New Zealand are not surprising when one considers the deterioration to housing affordability in Auckland that occurred over the period. Data from interest.co.nz shows that in April 2017, the median Auckland house was estimated to cost about 9.5 times the median household income. By comparison this ratio was 6.2 nationally.

The largest net out-migration from Auckland was in the 2001-2006 period (-18,000; or 3600 per year). Was Auckland housing affordability declining the fastest during that period? The truth is, the data don't provide an answer as to why on net people are moving away from Auckland.

Even the locations where they are moving to are not new. Newsroom notes that:

The regions closest to Auckland attracted two thirds of the exodus, with Tauranga proving to be the most popular, attracting an average 1144 people a year.

Waikato District on the southern fringe of Auckland gained an average of 3381 Aucklanders over the period, while Hamilton gained just over 1500 residents from Auckland.

The data indicates nearly 6000 Aucklanders moved to Northland over the four years, with gains spread evenly across Whangarei District, Far North and Kaipara.

Looking at the Census data for 2001 (so, the 1996-2001 period), the regions that Auckland lost (on net) the largest number of migrants to were (in order, and to the nearest 10 people) Bay of Plenty (-2800), Waikato (-2340), and Northland (-1600).

So, really there is nothing new here, other than the (albeit very useful, and more timely than the Census) dataset.

*****

[*] I'm using inter-regional migration flows here, rather than inter-TA flows. However, the story is very similar if I use inter-TA flows, because the Auckland region is the Auckland TA.