• ## Lee Kuan Yew—Deity or dude?

Why was Singapore’s development so easy? Here, I harry Lee Kuan Yew and suggest that Singapore’s success isn’t attributable to his putatively singular perspicacity.

### Intro

In a previous post, I presented a puzzle: Lee Kuan Yew’s The Singapore Story (Yew 2012) makes the incredible success of Singapore sound easy, but everything else I know suggests that growth and governance are far from easy. How do we explain the discrepancy?

One explanation that I think some people advance is that these problems are genuinely difficult, but they crumble before the searing brilliance of LKY (Lee Kuan Yew). I’ll confess that I had thought this might be the case before reading. Based on the memoir, I’m come to believe that LKY is closer to competent than Promethean.

### He put his pants on one leg at a time

First, we’ll start with some trifling excerpts which suggest that, indeed, LKY is an ordinary mortal:

• Eating and talking through the meal while conserving energy and not letting myself go and drink in case I lose my sharp cutting edge is quite a strain. It is part of the price to promote American investments.
• [H]owever hard and hectic the day had been, I would take two hours off in the late afternoon to go on the practice tee to hit 50–100 balls and play nine holes with one or two friends.

### Facile solutions to complex problems

He also sometimes responds to problems with solutions that seem like they can’t possibly be sufficient:

• Visiting CEOs used to call on me before making investment decisions. I thought the best way to convince them was to ensure that the roads from the airport to their hotel and to my office were neat and spruce, lined with shrubs and trees. When they drove into the Istana domain, they would see right in the heart of the city a green oasis, 90 acres of immaculate rolling lawns and woodland, and nestling between them a nine-hole golf course.

• The most effective [anti-corruption] change we made in 1960 was to allow the courts to treat proof that an accused was living beyond his means or had property his income could not explain as corroborating evidence that the accused had accepted or obtained a bribe[^corruption]. With a keen nose to the ground and the power to investigate every officer and every minister, the director of the CPIB, working from the Prime Minister’s Office, developed a justly formidable reputation for sniffing out those betraying the public trust.

It’s my understanding that anti-corruption measures are often a double-edge sword; they’re just as ably used by ruthless politicians to eliminate competition. In fact, LKY alludes to this very behavior elsewhere:

[D]uring the height of the Cultural Revolution, 1966–76, the system broke down. […] The whole society was degraded as opportunists masqueraded as revolutionaries and achieved “helicopter promotions” by betraying and persecuting their peers or superiors.

• […] Singapore should not have a central bank which could issue currency and create money. We were determined not to allow our currency to lose its value against the strong currencies of the big nations, especially the United States. So we retained our currency board which issued Singapore dollars only when backed by its equivalent value in foreign exchange.

Monetary policy has real value and it’s far from obvious that the winning move is not to play.

• [On limiting social programs:] We have arranged help but in such a way that only those who have no other choice will seek it. This is the opposite of attitudes in the West, where liberals actively encourage people to demand their entitlements with no sense of shame, causing an explosion of welfare costs.

An alternative consequence is those with the most acute sense of social responsibility will forgo entitlements and the most shameless will avail themselves of entitlements.

• Soon afterwards we also phased out protection for the assembly of refrigerators, air-conditioners, television sets, radios and other consumer electrical and electronic products.

Economic theory both recommends free trade for its positive impact on aggregate productivity and warns of its distributional consequences. I saw no engagement with the latter concern in the memoirs.

• […] I wanted: good health services, with waste and costs kept in check by requiring co-payments from the user. Subsidies for health care were necessary, but could be extremely wasteful and ruinous for the budget.

Requiring co-payments doesn’t solve moral hazard—it only mitigates. There are no easy solutions that eliminate moral hazard and retain subsidies.

To be clear, I’m not suggesting that these are easy problems or that I know the answer. In fact, that’s precisely my complaint—it seems LKY is suggesting they are problems with simple answers. One might respond that LKY had to make choices and didn’t have the luxury of indecision. I grant that, but think his presentation of these problems is less ‘forced to make the least bad choice when confronted with unsolved dilemmas’ and more ‘plucked out an answer to a trivialized problem’.

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• ## Exemplar's curse—Now with 80% more math!

We recently described the exemplar’s curse in words. Now we describe it with math and an interactive calculator. We also rebut one possible retort: exemplar’s curse scenarios don’t just mean we were too optimistic; they also lead us to picking the wrong exemplar.

Edit: (Marks 2008) covers essentially the same ground. But there’s no interactive calculator!

### Intro

Last time, I outlined the exemplar’s curse in the context of Singapore with a parable and an informal description. Rest easy; I’ve heard your needful clamoring—I’ll now describe the curse more precisely with math.

### The exemplar’s curse

Restating the core idea in words: The exemplar’s curse occurs when we select an exemplar from a set of outcomes which resulted from both stochastic and deterministic factors. If many outcomes have similarly compelling deterministic factors, the chosen winner is probably unusually lucky. Math then suggests that the chosen winner will disappoint when the deterministic factors are replicated.

#### Model

We can model this with the use of random variables. We’ll say that there’s a bundle of deterministic factors which we’ll represent as having a cumulative value (on some presently ill-defined scale of quality) ranging uniformly from $$0$$ to $$D$$ where $$D$$ is finite. Our bundle of stochastic factors range uniformly in value from from $$0$$ to $$S$$ where $$S$$ is finite. Since we observe only visible outcomes rather than underlying causal factors, we see $$O = D + S$$. The exemplar’s curse is then about the inferrable properties of the causal factors corresponding to the selected maximum $$O$$ from a set of outcomes $$\mathbb{O}$$. In other words, if we have a set of observable outcomes $$\mathbb{O}$$ and select the best outcome $$O$$ from that set, what can we infer about the underlying structure of $$O$$—how big are that $$O$$’s $$D$$ and $$S$$?

### False exemplars

In the last post, we only went so far as to claim that we should expect replicating causal factors to produce disappointing outcomes due to a sort of reversion to the mean. That is, the stochastic factors $$\mathcal{S}_1$$ for the maximum outcome $$O_1 = \max \mathbb{O}$$ are likely better than average ($$\frac{S}{2}$$). If we generate a new outcome $$O_2$$ using the same deterministic factors $$\mathcal{D}$$ that served us well in $$O_1$$, we should expect our new stochastic factors to be worse $$S_2 < S_1$$ and so we should expect $$O_2 < O_1$$.

This leaves a open a compelling retort. One could say, “Even though I’m too optimistic about the eventual outcome, in selecting the exemplar, I’m still selecting the best deterministic factors. That means I’m still making the best choice I can, so no harm done.”

Alas, this is not true. Depending on the parameters, there could be only a vanishingly small chance that the bundle of deterministic factors corresponding to the best outcome (the sum of the deterministic and stochastic factors) is also the best bundle of deterministic factors when looking only at the deterministic factors. In symbols, supposing we have a projection function $$p_\mathcal{D} : \mathbb{O} \rightarrow \mathbb{D}$$ which finds the $$D$$ used in outcome $$O$$, we’re interested in $$P(\max \mathbb{D} = p_\mathcal{D}(\max \mathbb{O}))$$.

For example, if we choose the max from 1000 outcomes and the value of stochastic factors ranges from 0 to 100 while the value of deterministic factors ranges from 0 to 1, we should be quite surprised if our best outcome actually has the best deterministic factors.

### Calculator

We can help build up an intuition around this math using the calculator below. The calculator uses Monte Carlo methods to estimate the probability that the maximum outcome corresponds to the maximum bundle of deterministic factors.

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• ## The Exemplar's Curse and Singapore

Like the optimizer’s curse, if we try to make policy decisions based on exemplars, we may systematically mislead ourselves by picking the luckiest polities rather than the wisest. If we try to replicate the policies of these lucky polities, regression toward the mean suggests we’ll meet with disappointment. This theory might apply to Singapore.

### The exemplar’s curse

#### A parable

Suppose you walk into the nearest WalMart, get on the PA, and ask everyone to congregate in the attached warehouse. Once the congregation has settled, you reveal a ream of printer paper, ask everyone to fold their best paper airplane, and finally ask everyone to toss their planes as far as they can. Once everyone’s tossed, you pull out your handy-dandy tape measure and determine which plane flew the farthest.

So far, so good. However, if you then proceed to marvel at the winning plane and attribute its long flight to the artful pattern of creases, you’re likely to err. Because, of course, there’s a substantial element of luck (meant in a casual sense; let’s not careen off on a tangent about determinism) in the outcome of the contest—it’s not a pure contest of skill. And in choosing the extreme value (the winner), we’ve positively selected for luck. This means our winner will likely have better than average luck. This result—in contests where many contestants are skilled, the outcome is often determined by luck—goes by the name the paradox of skill.

The unfortunate conclusion to this parable is that we should expect planes modeled after our winner to do worse than the original. Because the winner was unusually lucky, subsequent flights will experience reversion to the mean and perform worse.

Or, another route to this intuition: Even if you ran the contest again with the exact same planes, a different pattern of air drafts, a different incidental flick of the wrist might well result in a different victor. It’s only after we’ve run many trials and looked at the pattern of results for each plane that we can bring the risk of a false victor down to acceptable levels. If luck is a significant factor and there are many contestants, chances are that this true, final victor is not the same as the plane that happened to win the first trial. This is why sporting events often have multiple matches in a series—to diminish the impact of luck and suss out skill.

#### Abstracted

Summarizing, the exemplar’s curse occurs when you’re selecting an exemplar from a set of outcomes which resulted from both stochastic and deterministic factors. If many outcomes have similarly compelling deterministic factors1, the chosen winner is probably unusually lucky. Regression to the mean then suggests that the chosen winner will disappoint when the deterministic factors are replicated.

#### Optimizer’s curse

The following is offered as an extra in case it helps. If it doesn’t, dismiss it with prejudice:

The perspicacious reader will have noticed that this is just the optimizer’s curse dressed up in causal clothes (Smith and Winkler 2006). The paradigmatic optimizer’s curse warns about the difficulty of selecting actions based on the predicted value of the action. In such circumstances, naive optimizer’s will likely be disappointed because they will systematically pick actions based on overoptimistic predictions. (If this explanation doesn’t do it for you, you can just read the beginning of the linked paper; it’s not bad.) Our exemplar’s curse is structurally similar—we just have uncertain causal inference about the past instead of uncertain predictions about the future.

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• ## Is development easy? The Singapore Story

Lee Kuan Yew’s memoir, The Singapore Story, makes economic development sound easy. It’s probably not. How do we explain the discrepancy?

### Singapore’s economy grew. A lot.

It’s pretty hard to argue with the claim that Singapore’s post-independence economic development is an astounding success. Per capita GDP in the country grew from $6,506 (inflation-adjusted 2010 USD) in 1970 (57th among all countries) to$46,569 in 2010 (18th among all countries) (“Constant GDP Per Capita for Singapore”) (“List of Countries by Past and Projected GDP (Nominal) Per Capita” 2018). This represents an average annual real growth rate of 5.04% . For comparison, the real growth rates of China and the US over the same period of time were 7.78%1 and 1.84% respectively (“Constant GDP Per Capita for China”) (“Constant GDP Per Capita for the United States”).

Alas, broader measures of progress over that time period aren’t readily available. The UN’s Human Development Index, for example, only goes back to 1990. Thus, for want of a better measure, we’ll have to rely on GDP to support our claim that things really did change radically in Singapore after independence.

### What’s so hard about growth? Just stop making bad decisions and start making good ones.

A book club I recently attended read Lee Kuan Yew’s (the prime minister of Singapore from independence in 1965 to 1990) memoir, The Singapore Story (Yew 2012). My friend’s first reaction to the book was, “He makes it sound so easy!”, and I can’t disagree. My overwhelming impression of the book is that of proficient nonchalance.

Some examples from the text which I hope convey that feeling:

• I had many pressing concerns: first, to get international recognition for Singapore’s independence, including our membership of the United Nations. I chose Sinnathamby Rajaratnam (affectionately called Raja by all of us) as foreign minister. […] He was to be much liked and respected by all those he worked with at home and abroad. As messages of recognition flowed in, Toh Chin Chye, the deputy prime minister, and Raja as foreign minister set off to New York to take our seat at the UN that September of 1965.
• Mordecai Kidron, the Israeli ambassador in Bangkok […] had approached me several times in 1962–63 to ask for an Israeli consulate in Singapore. […] I replied that it … [might] create an issue that would excite the Malay Muslim grassroots and upset my plans […].

[…]

[N]ow that the Israeli presence in Singapore was well-known, we allowed them a diplomatic mission. They wanted an embassy. We decided to allow them a trade representative office first, in October 1968. The following May, after Malay Muslims in Singapore and the region had become accustomed to an Israeli presence, we allowed them to upgrade it to an embassy.
• Seah Mui Kok, a union leader and PAP MP, another old friend from my time with the unions, objected to the wide latitude given to employers to hire and fire, but accepted the need for unions to be less confrontational to create a better climate for foreign investments. I included safeguards against misuse of these powers.
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1. The surprising creativity of digital evolution

when you give a computer system a goal, and freedom in how it achieves that goal, then be prepared for surprises in the strategies it comes up with! Some surprises are pleasant (as in ‘oh that’s clever’), but some surprises show the system going outside the bounds of what you intended (but forgot to specify, because you never realised this could be a possibility…) using any means at its disposal to maximise the given objective.

The analogy to human systems is left to the imagination of the reader.

2. Empiricism is standpoint epistemology

Feminist standpoint theorists make three principal claims: (1) Knowledge is socially situated. (2) Marginalized groups are socially situated in ways that make it more possible for them to be aware of things and ask questions than it is for the non-marginalized. (3) Research, particularly that focused on power relations, should begin with the lives of the marginalized.

I have a definite soft spot for efforts to translate claims from one paradigm to another.

3. Statistically Controlling for Confounding Constructs Is Harder than You Think

Suppose we are given city statistics covering a four-month summer period, and observe that swimming pool deaths tend to increase on days when more ice cream is sold. As astute analysts, we immediately identify average daily temperature as a confound: on hotter days, people are more likely to both buy ice cream and visit swimming pools. Using multiple regression, we can statistically control for this confound, thereby eliminating the direct relationship between ice cream sales and swimming pool deaths.

Now consider the following twist. Rather than directly observing recorded daily temperatures, suppose we obtain self-reported Likert ratings of subjectively perceived heat levels. […] Fig 2 illustrates what happens when the error-laden subjective heat ratings are used in place of the more precisely recorded daily temperatures. […] When controlling for the subjective heat ratings (Fig 2B), the partial correlation between ice cream sales and swimming pool deaths is smaller, but remains positive and statistically significant, r(118) = .33, p < .001. Is the conclusion warranted that ice cream sales are a useful predictor of swimming pool deaths, over and above daily temperature? Obviously not. The problem is that subjective heat ratings are a noisy proxy for physical temperature, so controlling for the former does not equate observations on the latter.

4. The Psychology of Speciesism: How We Privilege Certain Animals Over Others

The post title oversells it a bit IMO, but still interesting preliminary findings:

[W]e developed a Speciesism Scale: a standardised, validated, and reliable measurement instrument that can assess the extent to which a person has speciesist views.

Speciesism correlates positively with racism, sexism, and homophobia, and seems to be underpinned by the same socio-ideological beliefs. Similar to racism and sexism, speciesism appears to be an expression of Social Dominance Orientation: the ideological belief that inequality can be justified and that weaker groups should be dominated by stronger groups […]. In addition, speciesism correlates negatively with both empathy and actively open-minded thinking. Men are more likely to be speciesists than women. Yet, there are no correlations with age or education.

5. Agnotology

Agnotology is the study of culturally induced ignorance or doubt. The tobacco industry is an easy example. “Doubt is our product”, says one industry memo.

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