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The professor called the shot

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It has been clear for a while that, unless the home price bubble were to miraculously stabilize in mid collapse, the US government itself would have to socialize the entire problem in order to solve it.

It looks like Ben Bernanke (AB Harvard, PhD MIT, Professor at Princeton) made the call. Paulson is no slouch (AB Dartmouth, MBA Harvard, CEO and Chairman of Goldman Sachs), but when the biggest financial decision of our generation was made, the geeky PhD told the Harvard MBA what to do.

NYTimes: The ad hoc approach Mr. Bernanke and Mr. Paulson had been trying was no longer enough.

Talking into the speaker phone on a coffee table in his office, Mr. Bernanke told Mr. Paulson that it was time to stop treating the symptoms by bailing out distressed companies and instead start attacking the root problem with a comprehensive strategy.

Congress would have to sign off, and it would fall to Mr. Paulson, as the envoy of the executive branch, to take the lead.

Mr. Paulson understood.

…“Going back a long time, maybe a year ago, Ben, as a world-class economist, said to me, when you look at the housing bubble and the correction, if the price decline was significant enough,” the only solution might be a large-scale government intervention, Mr. Paulson said. “He talked about what had happened when there had been other situations historically. And basically he said in his view the time might ultimately come when something like this was necessary.

Mr. Paulson said he agreed but hoped it would not come to that. “I knew he was right theoretically,” he said. “But I also had, and we both did, some hope that, with all the liquidity out there from investors, that after a certain decline that we would reach a bottom.”

Written by infoproc

September 20, 2008 at 7:10 pm

Hank in charge

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This Times article details who is running the show when it comes to the Fannie and Freddie bailout.

NYTimes: …“Bush was in charge when it was cut taxes, deregulate, have free trade, etc.,” said Representative Barney Frank, the Massachusetts Democrat and chairman of the House Financial Services Committee. “But then the old paradigm broke down, and it fell, frankly, to more serious thinkers to figure out how to cope with the current reality.”

…Mr. Paulson, a former chairman of Goldman Sachs, joined the White House in July 2006 after an intense courtship by Mr. Bush’s chief of staff, Joshua B. Bolten. He demanded clout and got it, in part because “Paulson did not need the job; the administration needed Paulson,” said Vincent R. Reinhart, a monetary economist at the American Enterprise Institute in Washington.

Mr. Reinhart says Mr. Paulson, like Mr. Bush, would ordinarily resist government intervention. “I think the economy is taking Bush and Paulson to a place where they wouldn’t go on their own,” he said. “In a crisis, you start bending principles, and Paulson bent principles.”

By relying so heavily on Mr. Paulson, Mr. Bush is doing more than bend conservative principles. He is taking himself out of public view in the one area of policy making that matters most to Americans: the economy. Mr. Wehner, Mr. Bush’s former adviser, does not see that as a problem so long as the markets stabilize. And Mr. Frank, the Democratic congressman, said Mr. Bush’s reliance on the Treasury secretary is “one of those things that, historically, will be to his credit.”

Do the people who think Sarah Palin is up to the job of President of the United States think she could have been CEO of Goldman Sachs as Paulson was? (“After all, Alaska is a lot bigger than Goldman Sachs! And, it’s closer to Russia! How much oil does Goldman have, anyway? Hey, she does have a journalism degree from U Idaho!”) Anti-elitism can only go so far…

Who has more responsibility, the President or CEO of Goldman?

Written by infoproc

September 9, 2008 at 5:16 pm

Annals of psychometry: IQs of eminent scientists

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I recently came across a 1950s study of eminent scientists by Harvard psychologist Anne Roe (The Making of a Scientist, published in 1952). Her study is by far the most systematic and sophisticated that I am aware of. She selected 64 eminent scientists — well known, but not quite at the Nobel level — in a more or less random fashion, using, e.g., membership lists of scholarly organizations and expert evaluators in the particular subfields. Roughly speaking, there were three groups: physicists (divided into experimental and theoretical subgroups), biologists (including biochemists and geneticists) and social scientists (psychologists, anthropologists).

Roe devised her own high-end intelligence tests as follows: she obtained difficult problems in verbal, spatial and mathematical reasoning from the Educational Testing Service, which administers the SAT, but also performs bespoke testing research for, e.g., the US military. Using these problems, she created three tests (V, S and M), which were administered to the 64 scientists, and also to a cohort of PhD students at Columbia Teacher’s College. The PhD students also took standard IQ tests and the results were used to norm the high-end VSM tests using an SD = 15. Most IQ tests are not good indicators of true high level ability (e.g., beyond +3 SD or so).

Average ages of subjects: mid-40s for physicists, somewhat older for other scientists

Overall normed scores:

Test (Low / Median / High)

V 121 / 166 / 177

S 123 / 137 / 164

M 128 / 154 / 194

Roe comments: (1) V test was too easy for some takers, so top score no ceiling. (2) S scores tend to decrease with age (correlation .4). Peak (younger) performance would have been higher. (3) M test was found to be too easy for the physicists; only administered to other groups.

It is unlikely that any single individual obtained all of the low scores, so each of the 64 would have been strongly superior in at least one or more areas.

Median scores (raw) by group:

group (V / S / M)

Biologists 56.6 / 9.4 / 16.8
Exp. Physics 46.6 / 11.7 / *
Theo. Physics 64.2 / 13.8 / *
Psychologists 57.7 / 11.3 / 15.6
Anthropologists 61.1 / 8.2 / 9.2

The lowest score in each category among the 12 theoretical physicists would have been roughly V 160 (!) S 130 M >> 150. (Ranges for all groups are given, but I’m too lazy to reproduce them all here.) It is hard to estimate the M scores of the physicists since when Roe tried the test on a few of them they more or less solved every problem modulo some careless mistakes. Note the top raw scores (27 out of 30 problems solved) among the non-physicists (obtained by 2 geneticists and a psychologist), are quite high but short of a full score. The corresponding normed score is 194!

The lowest V scores in the 120-range were only obtained by 2 experimental physicists, all other scientists scored well above this level — note the mean is 166.

My comments:

The data strongly suggests that high IQ provides a significant advantage in science. Some have claimed that IQ is irrelevant beyond some threshold: more precisely, that the advantage conferred by IQ above some threshold (e.g., 120) decreases significantly as other factors like drive or creativity take precedence. But, if that were the case it would be unlikely to have found such high scores in this group. The average IQ of a science PhD is probably in the 130 range, and individuals with IQs in the range described above constitute a tiny fraction of the overall population of scientists. If IQ were irrelevant above 130 we would expect the most eminent group to have a similar average.

Conversely, I think one should be impressed that a simple test which can be administered in a short period of time (e.g., 30 minutes for Roe’s high-end exams) offers significant predictive power. While it is not true that anyone with a high IQ can or will become a great scientist (certainly other factors like drive, luck, creativity play a role), one can nevertheless easily identify the 99 percent (even 99.9 percent) of the population for which success in science is highly improbable. Psychometrics works!

The scores for theoretical physicists confirm an estimate made to me by a famous colleague many years ago, that only 1 in 100,000 people could do high level theoretical physics.

Feynman’s 124: in this context one often hears of Feynman’s modest grade school IQ score of 124. To understand this score we have to remember that typical IQ tests (e.g., administered to public school children) tend to have low ceilings. They are not of the kind that Roe used in her study. One can imagine that the ceiling on Feynman’s exam was roughly 135 (say, 99th percentile). If Feynman received the highest score on the mathematical portion, and a modest score of 115 on the verbal, we can easily understand the resulting average of 124. However, it is well known that Feynman was extremely strong mathematically. He was asked on short notice to take the Putnam exam for MIT as a senior, and received the top score in the country that year! On Roe’s test Feynman’s math score would presumably have been > 190, with a correspondingly higher composite IQ.

I thought I should put this post up now, as the new book by Malcolm Gladwell, Outliers: Why Some People Succeed and Some Don’t is out soon and will surely handicap the discourse on this subject for years to come 🙂

Written by infoproc

July 7, 2008 at 4:02 pm

Higher education and human capital II

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I thought I’d also link to some interesting data from a paper by UT Austin economist Daniel Hamermesh, discussed here on the NYTimes Freakonomics blog.

Their survey covered UT Austin alumni between the ages of 23 and 43, revealing enormous variations in average earnings between different majors. Not surprisingly, the business majors and engineers tend to be high earners. However, the highest earners of all are the Plan II (honors college) alumni, who have by far the highest average SAT scores (1364). Note the huge variance within each major (SD = number in parentheses below the mean value), in particular for business, natural sciences and Plan II. For these majors the standard deviation is larger than the mean, suggesting, perhaps, that a few millionaires (startup founders, entrepreneurs?) are skewing the results.

The effect of college curriculum on earnings: …Clearly, there are large differences across major in average earnings, with the highest-earning majors (Honors Plan II, and “Hard” Business) having averages almost three times that of the lowest (Education). Much of the differences across majors must be due to differences in what the students bring to and do at the University. Students in the higher-earning majors generally have higher SAT totals upon entry, and the fractions of students taking upper-division math and science courses and doing well in them are greater too. The differences are also consistent with the results of differential effort in the labor market and male-female differences in earnings. Thus respondents in the higher-earning majors tend to state that they work longer hours than those in lower-earning majors; and except for the Honors Plan II major, the fraction of women in the higher-earning majors is lower. On the other hand, advanced degrees are more prevalent among those graduates who have majored in subjects that eventually generate lower earnings. Family incomes in the areas where the students attended high school do not differ across majors …

…Even within major, taking more upper-division science or math courses and doing better in them raise eventual earnings. While the effects are not highly significant statistically, the t-statistics generally exceed 1.28. A student who takes 15 credits of upper-division science and math courses and obtains a B average in them will earn about 10 percent more than an otherwise identical student in the same major … who takes no upper-division classes in these areas. There is clearly a return to taking these difficult courses. This holds true even after we have adjusted for differences in mathematical ability by using the total SAT score … . The importance of access to this information should not be underestimated. Estimated earnings differences across majors are substantially higher (e.g., the premium for “hard” business rises to 64 log points, that for engineering to 50 log points) when the information on science and math courses is excluded from the equation in Column (1).

Click on the figure below for a larger, more readable version.


Written by infoproc

June 29, 2008 at 8:15 pm

Higher education and human capital

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What good is higher education? The conventional view is that, in addition to producing a well-informed citizenry, it builds important human capital and raises national productivity. But what is the evidence for these assertions? In policy debates we are typically presented with faulty logic: workers in desirable, high value-added jobs (e.g., at Google or Biogen) tend to have lots of education. Therefore, if we want Americans to have such jobs we had better expand access to higher education. The counter argument, that returns to society as a whole from education diminish as access increases beyond the cognitive elite, is given below by a well-known curmudgeon and psychometric realist:

Brutal, just brutal: …There is no magic point at which a genuine college-level education becomes an option, but anything below an IQ of 110 is problematic. If you want to do well, you should have an IQ of 115 or higher. Put another way, it makes sense for only about 15% of the population, 25% if one stretches it, to get a college education. And yet more than 45% of recent high school graduates enroll in four-year colleges. Adjust that percentage to account for high-school dropouts, and more than 40% of all persons in their late teens are trying to go to a four-year college–enough people to absorb everyone down through an IQ of 104.

Note the claim is not that benefits from higher education are zero for the average student, but merely that they diminish significantly as we expand access. At some point we need to consider whether the marginal cost exceeds the marginal benefit. No amount of schooling will turn an average student into a materials engineer, tax lawyer or derivatives trader.

I’m afraid these kinds of thoughts lurk in the minds of most professors these days — I’ve heard them discussed many times. Why can’t my students write? Why can’t my students do simple math? Does the bottom half of the class really absorb anything from my lectures? Is science just too difficult for some people? If I showed you some of the emails I receive from students in my physics 101 course, you would cry at the lack of mastery of grammar and spelling, let alone physics.

Below I excerpt some depressing results from researchers at Stanford and Yale, which support the sorting and signalling model of higher ed, rather than the human capital building model.

Education and Verbal Ability over Time: Evidence from Three Multi-Time Sources

Nie, Golde and Butler

Abstract: During the 20th century, there was an unprecedented expansion in the level of educational attainment in America. Using three separate measures, this paper investigates whether there was a concurrent increase in verbal ability and skills. Changes in verbal ability in the general population as well as changes in the verbal ability of graduates of different levels of education are investigated. An additional investigation of how changes in the differences between males’ and females’ educational attainment are associated with changes in differences between their respective verbal abilities follows. The main finding is that there is little evidence that the large increase in educational attainment has resulted in an increase in any of the measures of verbal abilities and skills.

From the paper:

The results from using these three different measures of verbal ability and skills all show the same striking patterns: (1) there is no increase in scores in the overall population over time; (2) as the number of people obtaining a certain level of education increased, the verbal ability of those terminating with that degree has decreased. …

Comment for the psychometric cognoscenti: where is the Flynn effect here? I see no overall increase in verbal IQ.

See also this less technical exposition:

Nie and Golde: …Our initial hypothesis was that if amount of schooling causally affects any outcome, it would be verbal ability. The vast expansion of the American education system over the course of the 20th century served as our test bed. We expected that the huge increase in educational attainment in the U.S. across the decades would be accompanied by a substantial improvement in verbal abilities. To our initial amazement, we found no evidence for such improvement.

We started our investigation by showing that there is, indeed, a strong correlation between education and verbal ability. The data on which our analyses are based came from the General Social Survey, a program of in-person interviews that has been conducted regularly since 1972 by the National Opinion Research Center at the University of Chicago. While the samples were nationally representative, to avoid complications caused by changing demographics and questions about the validity of such tests with minority and immigrant populations, we included only the native-born, white American population 30 to 65 years of age, using information collected over the last 35 years of parallel surveys. (We used only those 30 years or older to ensure that we were dealing only with people who had completed their education; we stopped at age 65, lest we contaminate the analysis by differential mortality rates.)

Education levels and scores on a vocabulary test given to subjects are indeed correlated (see Figure 1). Over the three-plus decades studied, those with more education got better vocabulary scores, and vice versa.

Those results, however, do not necessarily imply that education causes increased verbal ability. If education did increase verbal ability, we would expect increasing levels of education over time to bring about measurably higher levels of verbal ability. During the 20th century, there was an unprecedented expansion in the levels of educational attainment in the U.S. The average American born between 1910 and 1914 received a bit more than 10 years of education. The average American born between 1970 and 1974 received 14 years of education. In 60 years, the “average American” went from being a high school dropout to having two years of college — a remarkable increase. The increase in education is across the board. A person born between 1910 and 1914 who obtained some postgraduate education was in the top 6 percent of his or her cohort in terms of education. By the 1970s, nearly 16 percent of the birth cohort had some postgraduate education. The percentage of college graduates or beyond has almost quadrupled over the same period, from just over 10 percent to almost 40 percent.

But, as Figure 2 shows, even though education has increased considerably through the decades, and even though education is correlated with verbal ability, verbal ability has stayed practically constant over time. The lack of change in the average vocabulary score of Americans, despite the large increase in the population’s average years of schooling, is an intriguing finding. …

Written by infoproc

June 28, 2008 at 2:51 pm

Asian-White IQ variance from PISA results

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The vexing question of average differences between groups of humans has been the subject of scrutiny for a very long time. Differences in variance or standard deviation (SD) are less well understood, but have important implications as well. This point was emphasized during the Larry Summers debacle, in which he posited that the variance in male intelligence might be larger than for women, even though the averages are similar (more very dumb and very bright men than women). Summers argued that this effect might explain the preponderance of males in science and engineering, even for a very small difference in SD.

Summers NBER speech:
…If one supposes, as I think is reasonable, that if one is talking about physicists at a top twenty-five research university, one is not talking about people who are two standard deviations above the mean. And perhaps it’s not even talking about somebody who is three standard deviations above the mean. But it’s talking about people who are three and a half, four standard deviations above the mean in the one in 5,000, one in 10,000 class. Even small differences in the standard deviation will translate into very large differences in the available pool substantially out [on the tail].

I did a very crude calculation, which I’m sure was wrong and certainly was unsubtle, twenty different ways. I looked at the Xie and Shauman paper-looked at the book, rather-looked at the evidence on the sex ratios in the top 5% of twelfth graders. If you look at those-they’re all over the map, depends on which test, whether it’s math, or science, and so forth-but 50% women, one woman for every two men, would be a high-end estimate from their estimates. From that, you can back out a difference in the implied standard deviations that works out to be about 20%. And from that, you can work out the difference out several standard deviations. If you do that calculation-and I have no reason to think that it couldn’t be refined in a hundred ways-you get five to one, at the high end.

I’ve occasionally heard a variant of the Summers argument applied to Europeans vs Asians (specifically, NE Asians such as Japanese, Koreans and Chinese): although NE Asians exhibit higher averages than whites in psychometric tests (SAT, IQ, etc.), some suspect a smaller variance, leading to fewer “geniuses” per capita, despite the higher mean. See, e.g., this article in National Review:

…The two populations also differ in the variability of their scores. A representative sample of Americans or Europeans will show more variability than will an East Asian sample. In the familiar bell-shaped distribution curve, the bell is much narrower for the Japanese–which is what you would expect from such a homogeneous population.

This difference is a major matter, and it is worth focusing hard on the data. Just about all Western populations report a standard deviation of 15 IQ points. (The SD, a basic measure of variability, quantifies the extent to which a series of figures deviates from its mean.) But the SD for the Japanese and other East Asian populations appears to be a shade under 13 IQ points. That difference does not sound like a big deal, and, in fact, it does not change things much in the center of the distribution. …

…but it does make a big difference at the high end, and it affects estimates of elite human capital availability in different countries.

I’ve never seen any data to back up the smaller NE Asian SD claim. Looking at SAT data shows a larger variance for the Asian-Pacific Islander category, but that is not surprising since it’s a catch-all category that includes S. Asians, SE Asians, NE Asians and Pacific Islanders. I’ve found very little analysis specific to NE Asians, so I decided to produce some myself. I took the 2006 PISA (OECD Program for International Student Assessment) data, which is painstakingly assembled every 3 years by a huge team of psychologists and educators (400k students from 57 countries tested). The samples are supposed to be statistically representative of the various countries, and the tests are carefully translated into different languages. Most studies of national IQ are quite crude, and subject to numerous methodological uncertainties, although the overall results tend to correlate with PISA results.

Below is what I obtained from the 2006 PISA mathematics exam data (overall rankings by average score here). To get the data, scroll down this page and download the chapter 6 data in .xls spreadsheet format. Level 6 is the highest achievement category listed in the data. For most OECD countries, e.g., France, Germany, UK, only a few percent of students attained this level of performance. In NE Asian countries as many as 11% of students performed at this level. Using these percentages and the country averages, one can extract the SD. (Level 6 = raw score 669, or +1.88SD for OECD, +1.28SD for NE Asians.)

OECD AVG=500 SD=90

NE Asia (HK, Korea, Taiwan) AVG=548 SD=95

The NE Asians performed about .5 SD better on average (consistent with IQ test results), and exhibited similar (somewhat higher) variance. (After doing my calculations I realized that there is actually a table of means and SDs in the spreadsheet, that more or less agree with my results. The standard error for the given SDs is only 1-2 points, so I guess a gap of 5 or 10 points is statistically significant.)

Interestingly, the Finns performed quite well on the exam, posting a very high average, but their SD is smaller. The usual arguments about a (slightly) “narrow bell curve” might apply to the Finns, but apparently not to the NE Asians.

Finland AVG=548 SD=80

Returning to Summers’ calculation, and boldly extrapolating the normal distribution to the far tail (not necessarily reliable, but let’s follow Larry a bit further), the fraction of NE Asians at +4SD (relative to the OECD avg) is about 1 in 4k, whereas the fraction of Europeans at +4SD is 1 in 33k. So the relative representation is about 8 to 1. (This assumed the same SD=90 for both populations. The Finnish numbers might be similar, although it depends crucially on whether you use the smaller SD=80.) Are these results plausible? Have a look at the pictures here of the last dozen or so US Mathematical Olympiad teams (the US Asian population percentage is about 3 percent; the most recent team seems to be about half Asians). The IMO results from 2007 are here. Of the top 15 countries, half are East Asian (including tiny Hong Kong, which outperformed Germany, India and the UK).

Incidentally, again assuming a normal distribution, there are only about 10k people in the US who perform at +4SD (and a similar number in Europe), so this is quite a select population (roughly, the top few hundred high school seniors each year in the US). If you extrapolate the NE Asian numbers to the 1.3 billion population of China you get something like 300k individuals at this level, which is pretty overwhelming.

Although it’s all there in the data set, I didn’t have time to examine the male-female variances in mathematical ability (and don’t want to deal with the abuse that might be heaped on me based on what I might find), but I encourage any interested readers to have a look. The authors of the PISA report wisely only reported that male-female averages are similar 😉

Note: as often happens with this kind of topic, a related discussion has broken out at GNXP.

Written by infoproc

June 18, 2008 at 1:08 am

IIT uber alles?

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I recently came across this interesting web site maintained by Kamal Sinha, an IIT (Indian Institute of Technology) Bombay alum who has worked at Mitsubishi in Japan and in Silicon Valley.

It has been widely claimed (e.g., CBS Sixty Minutes) that IITs are the most selective universities in the world — each year about 300k applicants compete for about 4000 spots. To enter the most competitive (e.g., EECS) departments, applicants must score amongst the top few hundred! I know several theoretical physicists in the US who were “toppers” on the IIT-JEE (Joint Entrance Exam), including one who placed first in all of India his year (“first ranker”)! Perhaps ironically, the first ranker didn’t attend IIT — he chose Caltech instead.

Despite the hype (see below) Sinha seems to think IIT is roughly comparable to other elite national universities like University of Tokyo, Seoul National University or Taiwan National University. Note he estimates the effective population base (the number of people who have access to first world educational resources in K-12) of India as only comparable to that of Japan (about 125 million; see here for a similar estimate by a well-known physicist). The estimates that lead to the conclusion that IIT is the most competitive in the world usually normalize to the entire Indian population of nearly 1 billion. I would say that China’s effective population (in this sense) is around 200-300 million people (and growing rapidly), so perhaps Beida (Beijing University) and Tsinghua are the most competitive universities in the world.

I’d be interested in the opinions of other IIT graduates! Here is some detailed discussion of the JEE exam by an IIT-Kanpur professor (link provided by a commenter). The professor suggests that the test is too hard: beyond the first few hundred or thousand rankers, noise dominates signal (i.e., even many admitted students have very low absolute scores, in which luck may have played a role).

Hype:

“This is IIT Bombay. Put Harvard, MIT and Princeton together, and you begin to get an idea of the status of this school in India.” (Lesley Stahl, co-anchor on CBS 60 Minutes)

“And it’s hard to think of anything like IIT anywhere in the world. It is a very unique institution.” (Bill Gates, Microsoft)

“Per capita, IIT has produced more millionaires than any other undergraduate institution.” (Salon Magazine)

Sinha on IIT acceptance rate:

Admission to IITs is extremely difficult. Only the top 2 percent of the applicants are admitted and to get into a decent department, about half a percent is a reasonable corresponding figure. Here I will explore whether IITs are the hardest school to get into and later I will check if high selectivity results in higher quality. “Hard” facts will be supplied when they become available.

Extremely low Acceptance Rate?

Having results of a single entrance examination determine whether one would be accepted or not is a common feature among the educational institutions in East Asian countries. I worked in Japan for six years and therefore being somewhat familiar with them will compare Japanese figures with that of IITs. All figures ae based on certain assumptions.

Selective Admissions in Japan

While it might not make the CBS news, Tokyo University, or Todai, an abbreviated form of Tokyo Daigaku is the place Japanese moms start thinking of to send their children for undergraduate studies before they are even born. There are 8 national universities like the Tokyo university, Todai being the most coveted one, and a few prestigious private schools like the Keio and Waseda, and these are the schools where almost every graduating school senior hopes to get into. Among technical schools Tokyo Institute of Technology (part of those 8 national universities) leads the pack. Each year news of a few students committing suicide on failing to secure admission into one of these schools is not uncommon.

Tokyo University admits fewer than 1500. My guess is that all the top private universities and the eight national universities combined admit fewer than 15000 applicants. How many students applied for these seats? About one and a half million which is about the total number of graduating seniors. Means about one percent!

Applicant Pool Size

‘Wait a minute’ I can hear you saying. Unlike in Japan where almost everyone takes the test to get into an an university, in India not everybody applies to IITs. Most of the applicants who take the JEE are quite good, there being a self-selection process. In response I will point out that if we compare the potential applicant pools, the following factors stand out:

IIT JEE is taken mostly by middle class applicants from urban areas with total population about 125 million. Japan has about same population with lower percentage of test-takers compared to that of India because of lower birth rates. There almost all eligible seniors take the test to get into these prestigious universities, meaning the potential applicant pools are almost equal.

Engineering schools like Tokyo Institute of Technlogy and various engineering departments in other universities are more selective than the average department. Assume those to be twice as selective.

IITs accept about 3500 of applicants. Given the above assumptions it is about (15000/2)/3500 = two times more selective than the average engineering department in these Japanese universities.

Take Tokyo University for comparision. An overwhelming majority of the grduating seniors choose Todai as their first choice. This means that Tokyo University is about twice (3500/1500) as selective as the IITs and more likely at least four times as selective than the IITs when engineering departments are compared.

Quality of Potential Applicant Pools

Japanese seniors in schools perform near the top in international tests in sciences and mathematics. (Seniors from Korea, Hong Kong and Singapore perform equally well.) Indians are not included in most comparison studies but there seems to be some evidence that the average Indian students would have performed near the average, probably somewhat below it. Moreover, after graduation many Japanese students take time off to study for the entrance exam and their dedication has to be seen to be believed. It leads me to believe that their potential applicant pool of of higher quality.

Other Asian Countries like Korea, Singapore, Hongkong, China?

It may be assumed that the student quality and the selection rates are similar to that in Japan, if not better. Means it appears that IITs, however difficult they are to get into, could be overshadowed by institutions in neighboring countries with more difficult admission standards.

There is a difference though. While graduates of universities like Tokyo are quietly working hard to bring their countries up to top and compete with the West, India with its population of a billion or so, through its IIT and other engineering college graduates, seems destined to become a country where the developed world can chooose its low-cost subcontractors to do the jobs they don’t want to do or have a shortage of workers.

Admissions in the USA

While it seems true that admission rate at IITs is less than even the most selective US school like the CalTech, it does not mean IIT recruits students of higher caliber. In a country like the USA, educational resources were well developed and the enrollment capacity for engineering majors is kept about the same as the number of seniors intending to enter those programs, if not more. It means less desparation. Moreover, there are lot of top-notch schools schools of about equal caliber which decreases their selectivity figures. My guess is that the top 50 engineering schools in the USA exceed IITs in almost all respect and another 100 or so other schools are not far behind.

Written by infoproc

June 3, 2008 at 2:00 am