Category: Data Source

Why Don’t We Know More About the Subway Cost Disease?

Alon Levy has a good deck based on data he collected covering 205 projects in 40 countries on why subway costs are so expensive in the United States compared to much of the rest of the world.

One of the points he makes is that a significant fraction of cost varies across countries which means “the explanation should be institutional and not geologic or geographic. This is difficult and requires qualitative research, since N is about 40.”

Costs are lower in poorer countries but Levy argues that GDP per capita is not a big factor once differences in type of subways are accounted for, I find that surprising and somewhat difficult to believe.

Levy’s major factor is simply that Americans and New Yorkers in particular don’t know much about how things are done elsewhere. In Europe, when a city builds a subway it can look to ten or twelve examples in three to four nearby countries for best practices. New Yorker’s don’t look anywhere else and say things like “New York has a more built-out commuter rail network than London,” as MTA chair Pat Foye recently claimed. In one way, this is good news because Levy argues that if Americans adopted European practices such as separating design from construction and simplifying station construction they could cut costs significantly.

Levy is to be lauded for his pioneering work on this issue yet isn’t it weird that a Patreon supported blogger has done the best work on comparative construction costs mostly using data from newspapers and trade publications? New York plans to spend billions on railway and subway expansion. If better research could cut construction costs by 1%, it would be worth spending tens of millions on that research. So why doesn’t the MTA embed accountants with every major project in the world and get to the bottom of this cost disease? (See previous point). Perhaps the greatest value of Levy’s work is in drawing attention to the issue so that the public gets mad enough about excess costs to get politicians to put pressure on agencies like the MTA.

Is the inequality of intelligence increasing?

“The inequality that matters,” as they used to say:

In a large US-representative adolescent sample, a Flynn Effect was found for IQs ≥ 130, and a negative effect for IQs ≤ 70

IQ changes also differed substantially by age group

A negative Flynn Effect for those with low intellectual ability suggests widening disparities in cognitive ability

Findings challenge the practice of generalizing IQ trends based on data from non-representative samples

So maybe yes — beware!

Here is the paper, via the excellent Kevin Lewis.

Are we undermeasuring productivity gains from the internet? part I

From my new paper with Ben Southwood on whether the rate of scientific progress is slowing down:

Third, we shouldn’t expect mismeasured GDP simply from the fact that the internet makes many goods and services cheaper. Spotify provides access to a huge range of music, and very cheaply, such that consumers can listen in a year to albums that would have cost them tens of thousands of dollars in the CD or vinyl eras. Yet this won’t lead to mismeasured GDP. For one thing, the gdp deflator already tries to capture these effects. But even if those efforts are imperfect, consider the broader economic interrelations. To the extent consumers save money on music, they have more to spend or invest elsewhere, and those alternative choices will indeed be captured by GDP. Another alternative (which does not seem to hold for music) is that the lower prices will increase the total amount of money spent on recorded music, which would mean a boost in recorded GDP for the music sector alone. Yet another alternative, more plausible, is that many artists give away their music on Spotify and YouTube to boost the demand for their live performances, and the increase in GDP  shows up there. No matter how you slice the cake, cheaper goods and services should not in general lower measured GDP in a way that will generate significant mismeasurement. 

Moving to the more formal studies, the Federal Reserve’s David Byrne, with Fed & IMF colleagues, finds a productivity adjustment worth only a few basis points when attempting to account for the gains from cheaper internet age and internet-enabled products. Work by Erik Brynjolfsson and Joo Hee Oh studies the allocation of time, and finds that people are valuing free Internet services at about $106 billion a year. That’s well under one percent of GDP, and it is not nearly large enough to close the measured productivity gap. A study by Nakamura, Samuels, and Soloveichik measures the value of free media on the internet, and concludes it is a small fraction of GDP, for instance 0.005% of measured nominal GDP growth between 1998 and 2012. 

Economist Chad Syverson probably has done the most to deflate the idea of major unmeasured productivity gains through internet technologies. For instance, countries with much smaller tech sectors than the United States usually have had comparably sized productivity slowdowns. That suggests the problem is quite general, and not belied by unmeasured productivity gains. Furthermore, and perhaps more importantly, the productivity slowdown is quite large in scale, compared to the size of the tech sector. Using a conservative estimate, the productivity slowdown implies a cumulative loss of $2.7 trillion in  GDP since the end of 2004; in other words, output would have been that much higher had the earlier rate of productivity growth been maintained. If unmeasured gains are to make up for that difference, that would have to be very large. For instance, consumer surplus would have to be five times higher in IT-related sectors than elsewhere in the economy, which seems implausibly large.

You can find footnotes and references in the original.  Here is my earlier post on the paper.

Superstar firms and market concentration

A new paper by Autor, Dorn, Katz, Patterson and Van Reenen (some real heavyweights) rebuts the notion that market concentration is rising because of inadequate antitrust concentration:

The fall of labor’s share of GDP in the United States and many other countries in recent decades is we ll documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value-added. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

Here is coverage from Peter Orszag.  As I’ve said before, people are opting for Philippon’s Great Reversal story because of ideology and convenience and mood affiliation, but it is not supported by the facts.

Nigeria and other Japan-Congo facts of the day

In 2018, the Nigerian government spent more on subsidies for petrol than on health, education, or defence.

And:

CD sales still make up 78% of music revenue in Japan (compared with less than 30% in the UK).

And:

80% of prisoners released late 2018 in a presidential pardon have opted to return to Kinshasa’s infamous Makala jail due to lack of means to live.

And:

Some blind people can understand speech that is almost three times faster than the fastest speech sighted people can understand. They can use speech synthesisers set at at 800 words per minute (conversational speech is 120–150 wpm). Research suggests that a section of the brain that normally responds to light is re-mapped in blind people to process sound.

That is all from 52 things Tom Whitwell learned this year.  Hat tip goes to The Browser — do subscribe!

Saudi facts of the day

Consanguineous marriage is preferred in many countries, especially by Muslims. Despite the increasing education rate in Saudi Arabia, the prevalence of consanguineous marriage does not seem to be decreasing as quickly as expected. The present study aimed to investigate the current prevalence of consanguineous marriage among educated married adults in Riyadh and to determine the factors favouring it. The cross-sectional study was conducted in 2017–18 using an online questionnaire. A total of 550 questionnaires were sent to married adults of both sexes and 417 responded, giving a response rate of 75.8%. The questionnaire consisted of two parts: the first section asked for demographic data such as age, sex, educational level, residential area and family size. The second part was about consanguineous marriage and its degree if present, family history of consanguineous marriage and level of awareness of its potential negative impact on offspring. It was found that the prevalence of consanguineous marriage among the participating educated adults was 39.8% and most of these were married to a first cousin. Neither level of education nor age affected the likelihood of consanguineous marriage, but predictors for the practice among the educated participating adults were having a family history of consanguineous marriage, having consanguineous parents and having a personal preference for consanguineous marriage.

That is from a new paper by Mahboub, Alsaqabi, Allwimi, and Aleissa.  Via the excellent Kevin Lewis.

Streets Vs Avenues Where to go to dinner in Manhattan model this

Abstract

Yelp data and statistical sampling was used to determine that the average restaurant is better on Manhattan streets than avenues, with an average rating of 3.62 on streets vs 3.49 on avenues. The difference was statistically significant. In addition, you are almost 50% more likely to find an outstanding restaurant while on a street compared to when you are on an avenue. 18% of restaurants on the streets had a score of 4.5 or higher, compared to 13% of restaurants on avenues.

Download Paper

or

SSRN

From the apparently awesome Alex Bell.

Nonbank lending

We provide novel systematic evidence on the extent and terms of direct lending by nonbank financial institutions, and explore whether banks are still special in lending to informationally opaque firms. Analyzing hand-collected data for a random sample of publicly-traded middle-market firms during the 2010-2015 period, we show that nonbank lending is widespread, with 32% of all loans being extended by nonbanks. Nonbank borrowers are less profitable, more levered, and more volatile than bank borrowers. Firms with a small negative EBITDA are 34% more likely to borrow from a nonbank than firms with a small positive EBITDA. While nonbank lenders are less likely to monitor by including financial covenants, they are more likely to align incentives through the use of warrants. Controlling for firm and loan characteristics, nonbank loans carry 190 basis points higher interest rates. Overall, our results provide evidence of market segmentation in the commercial loan market, where bank and nonbank lenders utilize different lending techniques and cater to different types of borrowers.

That is from a new NBER working paper by Sergey Chernenko, Isil Erel, and Robert Prilmeier.

The one-child policy and Chinese child trafficking

In the past 40 years, a large number of children have been abandoned by their families or have been abducted in China. We argue that the implementation of the one-child policy has significantly increased both child abandonment and child abduction and that, furthermore, the cultural preference for sons in China has shaped unique gender-based patterns whereby a majority of the children who are abandoned are girls and a majority of the children who are abducted are boys. We provide empirical evidence for the following findings: (1) Stricter one-child policy implementation leads to more child abandonment locally and more child abduction in neighboring regions; (2) A stronger son-preference bias in a given region intensifies both the local effects and spatial spillover effects of the region’s one-child policy on child abandonment and abduction; and (3) With the gradual relaxation of the one-child policy after 2002, both child abandonment and child abduction have dropped significantly. This paper is the first to provide empirical evidence on the unintended consequences of the one-child policy in terms of child trafficking in China.

That is the abstract of a new paper by Xiaojia Bao, Sebastian Galiani, Kai Li, and Cheryl Xiaoning Long.

Conscientiousness vs. working hard

South Korea ranks second to last in terms of conscientiousness but also ranks first in the number of hours worked.  South Korea is not an anomaly.  Country-level reports of Big Five conscientiousness are unrelated to the number of hours worked.  The rank correlation between hours worked and conscientiousness across countries is negative, though statistically insignificant.

That is from “Some Contributions of Economics to the Study of Personality,” a new working paper by James J. Heckman, Tomas Jagelka, and Timothy D. Kautz.  How do you interpret these numbers?  That the notion of conscientiousness is poorly measured?  Or that “susceptibility to manipulation by incentives” is a separate quality, highly valued in a workforce, but not well correlated with “conscientiousness as we know it”?

Why is labor mobility slowing in America?

There is a new and quite interesting paper on this topic, by Kyle Mangum and Patrick Coate:

This paper offers an explanation for declining internal migration in the United States motivated by a new empirical fact: the mobility decline is driven by locations with typically high rates of population turnover. These “fast” locations were the Sunbelt centers of population growth during the twentieth century. The paper presents evidence that as spatial population growth converged, residents of fast locations were subject to rising levels of preference for home. Using a novel measure of home attachment, the paper develops and estimates a structural model of migration that distinguishes moving frictions from home utility. Simulations quantify the role of multiple explanations of the mobility decline. Rising home attachment accounts for nearly half of the decline, roughly as large as the effect of an aging population, and is consistent with the spatial pattern. The implication is recent declining migration is a long run result of population shifts of the twentieth century.

For the pointer I thank the excellent Tyler Ransom.

Do social media drive the rise in right-wing populism?

Abstract: Many observers are concerned that echo chamber effects in digital media are contributing to the polarization of publics and in some places to the rise of right-wing populism. This study employs survey data collected in France, the United Kingdom, and United States (1500 respondents in each country) from April to May 2017. Overall, we do not find evidence that online/social media explain support for right-wing populist candidates and parties. Instead, in the USA, use of online media decreases support for right-wing populism. Looking specifically at echo chambers measures, we find offline discussion with those who are similar in race, ethnicity, and class positively correlates with support for populist candidates and parties in the UK and France. The findings challenge claims about the role of social media and the rise of populism.

That is from a new paper by Shelley Boulianne, Karolina Koc-Michalska, and Bruce Bimber, via somebody on Twitter.

China fact of the day

China is set to add new coal-fired power plants equivalent to the EU’s entire capacity, as the world’s biggest energy consumer ignores global pressure to rein in carbon emissions in its bid to boost a slowing economy.

Across the country, 148GW of coal-fired plants are either being built or are about to begin construction, according to a report from Global Energy Monitor, a non-profit group that monitors coal stations. The current capacity of the entire EU coal fleet is 149GW.

While the rest of the world has been largely reducing coal-powered capacity over the past two years, China is building so much coal power that it more than offsets the decline elsewhere.

Here is more from Leslie Hook at the FT.

Is the rate of scientific progress slowing down?

That is the title of my new paper with Ben Southwood, here is one segment from the introduction:

Our task is simple: we will consider whether the rate of scientific progress has slowed down, and more generally what we know about the rate of scientific progress, based on these literatures and other metrics we have been investigating. This investigation will take the form of a conceptual survey of the available data. We will consider which measures are out there, what they show, and how we should best interpret them, to attempt to create the most comprehensive and wide-ranging survey of metrics for the progress of science.  In particular, we integrate a number of strands in the productivity growth literature, the “science of science” literature, and various historical literatures on the nature of human progress. In our view, however, a mere reporting of different metrics does not suffice to answer the cluster of questions surrounding scientific progress. It is also necessary to ask some difficult questions about what science means, what progress means, and how the literatures on economic productivity and “science on its own terms” might connect with each other.

Mostly we think scientific progress is indeed slowing down, and this is supported by a wide variety of metrics, surveyed in the paper.  The gleam of optimism comes from this:

And to the extent that progress in science has not been slowing down, which is indeed the case under some of our metrics, that may give us new insight into where the strengths of modern and contemporary science truly lie. For instance, our analysis stresses the distinction between per capita progress and progress in the aggregate. As we will see later, a wide variety of “per capita” measures do indeed suggest that various metrics for growth, progress and productivity are slowing down. On the other side of that coin, a no less strong variety of metrics show that measures of total, aggregate progress are usually doing quite well. So the final answer to the progress question likely depends on how we weight per capita rates of progress vs. measures of total progress in the aggregate.

What do the data on productivity not tell us about scientific progress?  By how much is the contribution of the internet undervalued?  What can we learn from data on crop yields, life expectancy, and Moore’s Law?  Might the social sciences count as an example of progress in the sciences not slowing down?  Is the Solow model distinction between “once and for all changes” and “ongoing increases in the rate of innovation” sound?  And much more.

Your comments on this paper would be very much welcome, either on MR or through email.  I will be blogging some particular ideas from the paper over the next week or two.

And here is Ben on Twitter.

The future of higher education?

Two public four-year institutions, Maine Maritime Academy and the U.S. Merchant Marine Academy, rank in the top 10 colleges with the best long-term returns, while two four-year private colleges, St. Louis College of Pharmacy and Albany College of Pharmacy and Health Sciences, made the top 10 for short-term and long-term returns.

The report ranks 4,526 colleges and universities by return on investment.

Here is one article, with a graphic for the top ten, you will note that Harvard, Stanford, and MIT still do fine.  Babson is underrated, as it does much better over longer stretches of time.  Here is the Georgetown report.