Book review: Bad Samaritans: The Myth of Free Trade and the Secret History of Capitalism by Ha-Joon Chang.
This book attacks orthodoxies of the World Bank, IMF, WTO, neo-liberal economists, free-market economists, and pundits such as Thomas Friedman. Chang often implies that they all share a common orthodoxy, but the ideas he attacks are usually questioned by some of those groups.
His criticisms of the World Bank, IMF, and WTO are often correct, but it shouldn’t be surprising that they serve goals that don’t coincide with needs of developing countries.
His most important argument is a defense of mercantilist protection of infant industries. He shows that the evidence on the effects of tariffs is sufficiently mixed that his selective use of examples can give the impression that he has shown tariffs promote economic growth in developing countries. He makes claims of the form “X would have failed without protection”, but doesn’t say why his ability to predict failure is more reliable than other alleged experts (e.g. MITI’s belief that Honda would fail in the auto business). This provoked me into searching for more complete tests of the effects of tariffs. The evidence I found confirms that his confidence that tariffs work is foolish, but I was surprised to find that the evidence is too unclear to provide a guide to policy decision.
Chang has a good argument that the common orthodoxy about comparative advantage is a less conclusive reason for removing tariffs than it appears. But his attempts to describe a mechanism by which tariffs can be beneficial are naive. He talks about government protecting infant industries the way a parent protects a child, without any analysis of the political forces which cause governments to protect entrenched declining industries at the expense of less politically powerful startups.
He gives only vague hints about how to distinguish the tariffs he thinks are good from bad tariffs. I’ll offer a suggestion: any tariff that is designed to meet his notion of a good tariff should be set by statute to decrease to zero over a period of about a decade and never be reinstated for an industry to which they’ve been applied under this statute.
His complaints about privatizing state-owned enterprises contain some valid points. I wish people didn’t assume government and stockholder control are the only available choices. Having governments spin off enterprises as nonprofits would sometimes (often?) be a better option.
His comments about how patents and copyright affect developing countries are mostly correct. But he underestimates our dependence on drug patents when he implies that the 57% of drug research funding that comes from not-for-profit sources means we could get 57% of the results without commercial funding. A drug startup that will go broke if it doesn’t produce something valuable does different work than someone whose success comes from publishing papers.
Chang’s modest suggestions for patent reform would provide much less improvement than ideas I’ve found by reading free-market economists (e.g. prizes instead of patents, or Kremer’s patent buyout proposal).
His comments about inflation assume that it produces some benefits, but he shows no awareness of the economic literature which disputes that assumption.
He has plausible hypotheses that increasing market forces might cause an increase in corruption in some countries. I see no easy way to estimate the size of these effects.
His arguments that cultures change in response to economic change more than most people realize are strong enough to lower my opinion of Fukuyama’s book Trust (Fukuyama seems unaware that the German current high-trust culture is very different from a century ago when they had a reputation for dishonesty). But Chang exaggerates a lot when he says immigrants from poor countries working much harder in rich countries proves that work habits result from economic conditions rather than culture – those immigrants are unlikely to be typical of the culture they came from.
Book Reviews
Book review: Counting Sheep: The Science and Pleasures of Sleep and Dreams by Paul Martin.
This book makes convincing claims that most people give too little thought to an activity that occupies a large fraction of our life.
It has lots of little pieces of information which can be read as independent essays. Here are some claims I found interesting:
- “sleepiness is responsible for far more deaths on the roads than alcohol or drugs”.
- Tired people rate their abilities higher than people who slept well do.
- Poor sleep contributes to poor health a good deal more than medical diagnoses suggest, but hospitals are designed in ways that hinder patients’ sleep.
- Idle time was apparently a status symbol up to a century ago, now being busy is a status symbol. This should have economic implications that someone ought to explore in depth.
- People in a vegetative state have REM sleep. This sounds like cause to re-evaluate the label we apply to that state.
While the book has many references, it doesn’t connect specific claims to references, and I’m sometimes left wondering why I should believe a claim. How can boredom be a modern concept? When he says “no person has ever gone completely without sleep for more than a few days”, how does he know he can dismiss people who claim to have not slept for years?
Book review: The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives by Stephen Ziliak and Deirdre McCloskey.
This book provides strong arguments that scientists often use tests of statistical significance as a ritual that substitutes for thought about how hypotheses should be tested.
Some of the practices they criticize are clearly foolish, such as treating data which fall slightly short of providing statistically significant evidence for a hypothesis as reason for concluding the hypothesis is false. But for other practices they attack, it’s unclear whether we can expect scientists to be reasonable enough to do better.
Much of the book is a history of how this situation arose. That might be valuable if it provided insights into what rules could have prevented the problems, but it is mainly devoted to identifying heroes and villains. It seems strange that economists would pay so little attention to incentives that might be responsible.
Instead of blaming the problems primarily on one influential man (R.A. Fisher), I’d suggest asking what distinguishes the areas of science where the problems are common from those where it is largely absent. It appears that the problems are worst in areas where acquiring additional data is hard and where powerful interest groups might benefit from false conclusions. Which leads me to wonder whether scientists are reacting to a risk that they’ll be perceived as agents of drug companies, political parties, etc.
The book sometimes mentions anti-commercial attitudes among the villains, but fails to ask whether that might be a symptom of a desire for “pure” science that is divorced from real world interests. Such a desire might cause many of the beliefs that the authors are fighting.
The book does not adequately address concerns that if scientists in those fields abandon easily applied rules, scientists are sufficiently vulnerable to corruption that we’d end up with less accurate conclusions.
The authors claim the problems have been getting worse, and show some measures by which that seems true. But I suspect their measures fail to capture some improvement that has been happening as the increasing pressure to follow the ritual has caused papers that would previously have been purely qualitative to use quantitative tests that reject the worst ideas.
The book seems somewhat sloppy in its analysis of specific examples. When interpreting data from a study where scientists decided there was no effect because the evidence fell somewhat short of statistical significance, it claims the data show “St. John’s-wort is on average twice as helpful as the placebo”. But the data would provide evidence for that only if there were data showing that the remission rate with no treatment was zero. It’s likely that some or all of the alleged placebo effect was due to effects that are unrelated to treatment. And their use of the word “show” suggests stronger evidence than is provided by the data.
I’ll close with two quotes that I liked from the book:
The goal of an empirical economist should not be to determine the truthfulness of a model but rather the domain of its usefulness – Edward E. Leamer
The probability that an experimental design will be replicated becomes very small once such an experiment appears in print. – Thomas D. Sterling
Predictocracy (part 2)
Book review: Predictocracy: Market Mechanisms for Public and Private Decision Making by Michael Abramowicz (continued from prior post).
I’m puzzled by his claim that it’s easier to determine a good subsidy for a PM that predicts what subsidy we should use for a basic PM than it is to determine the a good subsidy for the basic PM. My intuition tells me that at least until traders become experienced with predicting effects of subsidies, the markets that are farther removed from familiar questions will be less predictable. Even with experience, for many of the book’s PMs it’s hard to see what measurable criteria could tell us whether one subsidy level is better than another. There will be some criteria that indicate severely mistaken subsidy levels (zero trading, or enough trading to produce bubbles). But if we try something more sophisticated, such as measuring how accurately PMs with various subsidy levels predict the results of court cases, I predict that we will find some range of subsidies above which increased subsidy produces tiny increases in correlations between PMs and actual trials. Even if we knew that the increased subsidy was producing a more just result, how would we evaluate the tradeoff between justice and the cost of the subsidy? And how would we tell whether the increased subsidy is producing a more just result, or whether the PMs were predicting the actual court cases more accurately by observing effects of factors irrelevant to justice (e.g. the weather on the day the verdict is decided)?
His proposal for self-resolving prediction markets (i.e. markets that predict markets recursively with no grounding in observed results) is bizarre. His arguments about why some of the obvious problems aren’t serious would be fascinating if they didn’t seem pointless due to his failure to address the probably fatal flaw of susceptibility to manipulation.
His description of why short-term PMs may be more resistant to bubbles than stock markets was discredited just as it was being printed. His example of deluded Green Party voters pushing their candidate’s price too high is a near-perfect match for what happened with Ron Paul contracts on Intrade. What Abramowicz missed is that traders betting against Paul needed to tie up a lot more money than traders betting for Paul. High volume futures markets have sophisticated margin rules which mostly eliminate this problem. I expect that low-volume PMs can do the same, but it isn’t easy and companies such as Intrade have only weak motivation to do this.
He suggests that PMs be used to minimize the harm resulting from legislative budget deadlocks by providing tentative funding to projects that PMs predict will receive funding. But if the existence of funding biases legislatures to continue that funding (which appears to be a strong bias, judging by how rare it is for a legislature to stop funding projects), then this proposal would fund many projects that wouldn’t otherwise be funded.
His proposals to use PMs to respond to disasters such as Katrina are poorly thought out. He claims “not much advanced planning of the particular subjects that the markets should cover would be needed”. This appears to underestimate the difficulty of writing unambiguous claims, the time required for traders to understand them, the risks that the agencies creating the PMs will bias the claim wording to the agencies’ advantage, etc. I’d have a lot more confidence in a few preplanned PM claims such as the expected travel times on key sections of roads used in evacuations.
I expect to have additional comments on Predictocracy later this month; they may be technical enough that I will only post the on the futarchy_discuss mailing list.
Book review: Predictocracy: Market Mechanisms for Public and Private Decision Making by Michael Abramowicz.
This had the potential to be an unusually great book, which makes its shortcomings rather frustrating. It is loaded with good ideas, but it’s often hard to distinguish the good ideas from the bad ideas, and the arguments for the good ideas aren’t as convincing as I hoped.
The book’s first paragraph provides a frustratingly half-right model of why markets produce better predictions than alternative institutions, involving a correlation between confidence (or sincerity) and correctness. If trader confidence was the main mechanism by which markets produce accurate predictions, I’d be pretty reluctant to believe the evidence that Abramowicz presents of their success. Sincerity is hard to measure, so I don’t know what to think of its effects. A layman reading this book would have trouble figuring out that the main force for accurate predictions is that the incentives alter traders’ reasoning so that it becomes more accurate.
The book brings a fresh perspective to an area where there are few enough perspectives that any new perspective is valuable when it’s not clearly wrong. He is occasionally clearer than others. For instance, his figure 4.1 enabled me to compare three scoring rules in a few seconds (I’d previously been unwilling to do the equivalent by reading equations).
He advocates some very fine-grained uses of prediction markets (PMs), which is a sharp contrast to my expectation that they are mainly valuable for important issues. Abramowicz has a very different intuition than I do about how much it costs to run a prediction market for an issue that people normally don’t find interesting. For instance, he wants to partly replace small claims court cases with prediction markets for individual cases. I’m fairly sure that obvious ways to do that would require market subsidies much larger than current court costs. The only way I can imagine PMs becoming an affordable substitute for small claims courts would be if most of the decisions involved were done by software. Even then it’s not obvious why one or more PM per court case would be better than a few more careful evaluations of whether to turn those decisions over to software.
He goes even further when proposing PMs to assess niceness, claiming that “just a few dollars’ worth of subsidy per person” would be adequate to assess peoples’ niceness. Assuming the PM requires human traders, that cost estimate seems several orders of magnitude too low (not to mention the problems with judging such PMs).
His idea of “the market web” seems like a potentially valuable idea for a new way of coordinating diverse decisions.
He convinced me that Predictocracy will solve a larger fraction of democracy’s problems than I initially expected, but I see little reason to believe that it will work as well as Futarchy will. I see important classes of systematic biases (e.g. the desire of politicians and bureaucrats to acquire more power than the rest of us should want) that Futarchy would reduce but which Predictocracy doesn’t appear to alter.
Abramowicz provides reasons to hope that predictions of government decisions 10+ years in the future will help remove partisan components of decisions and quirks of particular decision makers because uncertainty over who will make decisions at that time will cause PMs to average forecasts over several possible decision makers.
He claims evaluations used to judge a PM are likely to be less politicized than evaluations that directly affect policy because the evaluations are made after the PM has determined the policy. Interest groups will sometimes get around this by making credible commitments (at the time PMs are influencing the policy) to influence whoever judges the PM, but the costs of keeping those commitments after the policy has been decided will reduce that influence. I’m not as optimistic about this as Abramowicz is. I expect the effect to be real in some cases, but in many cases the evaluator will effectively be part of the interest group in question.
Book review: The Birth of Plenty : How the Prosperity of the Modern World was Created by William Bernstein.
This book contains many ideas about the causes of economic growth that are approximately right, but rarely backs them up with good arguments.
He starts by saying four institutions are needed to escape from a Malthusian trap: property rights (rule of law), reason (scientific methods), capital markets, and fast transportation/communication. But later when discussing why some countries were slow to develop, he adds ad hoc explanations (e.g. “excessive military expenditure” “reliably derails great nations”).
The biggest shortcoming of the book is that it ignores evidence that China provides a counter-example to his main claims. He doesn’t acknowledge expert claims that parts of China around 1800 had a degree of property rights and rule of law that was comparable to England at that time, nor does he discuss the recent dramatic Chinese takeoff that happened with a mediocre degree of property rights and rule of law.
He gives many hints about why those four institutions are helpful, but provides little evidence that any one is essential. About the closest he comes to providing rigorous evidence is a graph indicating how much of economic growth appears to be explained by a Rule-of-Law indicator. He follows that with a similar graph of how government spending levels explain economic growth, and claims the negative effect of government spending would be invisible without the computed trend line, but the rule-of-law trend is more impressive. I see those graphs differently. The most obvious trend is that government spending over about 15 to 18% (of GDP?) reduces growth, with no obvious pattern for lower spending levels. The most obvious trend in the rule-of-law graph is that low values on the rule-of-law indicator are associated with larger variations in economic growth, which is somewhat contrary to his claim that such values reliably prevent growth.
The section I found most valuable was the one describing reasons for thinking that 16th century Holland created the beginnings of the industrial revolution.
There are enough misleading or false statements in the book to convince me not to trust him. For example, he refers to eclipse prediction around 1700 as a spectacular change to what was previously a mystery. He appears unaware that eclipses had been predicted more than a millennium earlier.
He often digresses into anecdotes that have no apparent relevance. For example, he claims “a healthy market for government debt is, in fact, essential for funding business”. After giving two implausible theoretical reasons for that claim, he says it was “vividly demonstrated in the U.S.” in 1862, but then gives a description of how government bonds were sold, without mentioning anything about the effect on business.
His discussion of the possible trade-offs between inflation and unemployment makes a claim that increased unemployment caused more unhappiness than “an identical rise in inflation”. But inflation is measured in different units that unemployment. If we happened to measure inflation in percent per presidential election, the naive comparison would work much differently. (He is subtly misinterpreting a serious paper that is hard to fully explain to laymen).
His advice to undeveloped nations includes “before a nation builds roads … it must first train lawyers”, which makes me doubt his understanding of what causes the rule of law.
Book review: The Age of Turbulence: Adventures in a New World by Alan Greenspan.
The first half of this book provides a decent history of the past 40 years, with a few special insights such as descriptions of how most presidents in that period worked (he’s one of the least partisan people to have worked with most of them). The second half is a discussion of economics of rather mixed quality (both in terms of wisdom and ability to put the reader to sleep).
He comes across as a rather ordinary person whose private thoughts are little more interesting that his congressional testimony.
One of the strangest sections describes the problems he worried would result from a projected paydown of all federal government debt. He does claim to have been careful not to forget the possibility those forecasts could be mistaken. But his failure to mention ways that forecasts of Social Security deficits could be way off suggests he hasn’t learned much from that mistake.
He mentions a “conundrum” of falling long-term interest rates in 2004-2005, when he had expected that rising short-term rates would push up long-term rates. I find his main explanation rather weak (it involves technology induced job insecurity leading to lower inflation expectations). But he then goes on to describe a better explanation (but is vague about whether he believes it explains the conundrum): the massive savings increase caused largely by rapid growth in China. I suspect this is a powerful enough force that Deng Xiaoping deserves more credit than Greenspan for the results that inspired the label Maestro.
The book is often more notable for what it evades than what it says. It says nothing about his inflationary policies in 2003-2004 or his favorable comments about ARMs and how they contributed to the housing bubble.
He gives a brief explanation of how Ayn Rand converted him to an Objectivist by pointing out a flaw in his existing worldview, but he is vague about his drift away from Objectivism. His description of the 1995 government “shutdown” as a crisis is fairly strong evidence of a non-Randian worldview, but mostly he tries to avoid controversies between libertarianism and the policies of politicians he likes.
He often praises markets’ abilities to signal valuable information, yet when claiming that the invasion of Iraq was “about oil”, he neglects to mention the relevant market prices. Those prices appear to discredit his position (see Leigh, Wolfers and Zitzewitz’ paper What do Financial Markets Think of War in Iraq?).
He argues against new hedge fund regulations on the grounds that hedge funds change their positions faster than regulators can react. He is right about the regulations that he imagines, but it’s unfortunate that he stops there. The biggest financial problems involve positions that can’t be liquidated in a few weeks. It seem like it ought to be possible for accounting standards to provide better ways for institutions to communicate to their investors how leveraged they are and how sensitive their equity is to changes in important economic variables.
He argues against using econometric models to set Fed policy, citing real problems with measuring things like NAIRU and GDP, but if he was really interested in scientifically optimizing Fed policy, why didn’t he try to create models based on more relevant and timelier data (such as from the ISM?) the way he did when he had a job that depended on providing business with useful measures? Maybe he couldn’t have become Fed chairman if he had that kind of desire.
I listened to the cd version of this book because I got it as a present and listening to it while driving had essentially no cost. I wouldn’t have bought it or read the dead tree version.
Book review: Seeing Red: A Study in Consciousness (Mind/Brain/Behavior Initiative) by Nicholas Humphrey,
This book provides a clear and simple description of phenomena that are often described as qualia, and a good guess about how and why they might have evolved as convenient ways for one part of a brain to get useful information from other parts. It uses examples of blindsight to clarify the difference between using sensory input and being aware of that input.
I liked the description of consciousness as being “temporally thick” rather than being about an instantaneous “now”, suggesting that it includes pieces of short-term memory and possibly predictions about the next few seconds.
The book won’t stop people from claiming that there’s still something mysterious about qualia, but it will make it hard for them to claim that they have a well-posed question that hasn’t been answered. It avoids most debates over meanings of words by usually sticking to simpler and less controversial words than qualia, and only using the word consciousness in ways that are relatively uncontroversial.
The book is short and readable, yet the important parts of it are concise enough that it could be adequately expressed in a shorter essay.
Book review: Poverty and Discrimination by Kevin Lang.
This book is designed to make you feel less sure of your knowledge, and it succeeds in that goal. That’s a worthy accomplishment, although it provides much less satisfaction than a book that provides a grand vision for solving problems would. At some abstract intellectual level I liked the book, but my gut feelings often told me that reading the book was unrewarding work that I shouldn’t do unless it was assigned reading for a course I needed.
The book will dissatisfy anyone who wants to view politics as a fight between good and evil. For many issues such as the minimum wage, he provides strong arguments that the effects are small enough that we should doubt whether the issue is worth fighting about.
He gives good explanations of why it’s hard to even have clear concepts of poverty and discrimination by providing examples of how seemingly trivial or unobservable differences can create results that our intuitions say are important to our moral rules.
He provides clear evidence that some discrimination still exists, and then thoroughly explains why there’s large uncertainty about how harmful it is. He presents one moderately unrealistic model in which discrimination is common but doesn’t affect wages. Then he presents a somewhat more realistic model in which a tiny bit of discrimination produces large wage differences. But those wage differences may overstate the harm done, because they’re partly due to minorities spending less on education and to women pursuing careers in lower risk occupations or careers which allow more flexibility to take time off.
There are only a handful of places where I doubted his objectivity.
He reports one study showing evidence of racial discrimination in home loans, but fails to mention any of the contrary evidence such as the Anderson and Vanderhoff paper showing higher marginal default rates for blacks.
The final few pages on policy implications seem poorly thought out compared to the rest of the book (he says that’s the least important chapter of the book). He claims that income taxes on the bottom quintile can be reduced to zero by a 10% increase on the top quintile, but that claim depends on assumptions about how reported income changes in response to tax increases. He doesn’t indicate what assumptions his claim depends on.
He claims “The high rate of incarceration in the United States and the high level of inequality are related.” He gives a plausible theory about why inequality causes the wealthy in some countries to spend a lot protecting their wealth from the poor, but provides no evidence connecting that theory to U.S. incarceration rates.
Book review: The First Word: The Search for the Origins of Language by Christine Kenneally
This book contains a few good ideas, but spends more time than I want discussing the personalities and politics that have been involved in the field.
It presents some good arguments against the “big bang” theory of the origin of human language (which suggests that one mutation may have created syntactic abilities that don’t correspond to anything in other species), mainly by presenting evidence that human language is not a monolithic feature, and that most aspects of it resemble features which can be seen in other species. For example, some of our syntactic ability involves reusing parts of the brain that provide motor control.
I’m uncertain whether the “big bang” theory she argues against is actually believed by any serious scholar, because those who may have advocated it haven’t articulated much of a theory (partly because they think there’s too little evidence to say much about the origin of language).
The most valuable idea I got from the book was the possibility that the development of human language may have been a byproduct of a sophisticated theory of mind. Other apes seem to get less benefit from communications because with only the limited theory of mind that a typical chimp has, there’s little that improved communication by one individual can do to increase cooperation between individuals.