Edward Conard

Top Ten New York Times Bestselling Author

  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Monday, February 8, 2016

AI Summary. An analysis of 98 psychology papers found only 39% were replicable, pointing to weaknesses in scientific research reliability. Initiatives such as Stanford's Meta-Research Innovation Centre and the Preclinical Reproducibility and Robustness Channel aim to promote replication and greater transparency and rigor in research methods.

Economist Staff The Economist
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Only 39% of psychology papers published in 2015 were replicable, highlighting a significant issue in scientific research reliability.

Are most published research findings replicable?

Core argument: A 2015 analysis of 98 psychology papers found only 39% were replicable, pointing to a reliability problem in scientific research.

In 2015, an analysis of 98 psychology papers revealed that only 39% were replicable, highlighting a significant issue in scientific research reliability. This low replication rate underscores the need for improved transparency and rigor in research methodologies, which is crucial for scientific progress and economic decision-making. The establishment of initiatives like the Meta-Research Innovation Centre at Stanford and the Preclinical Reproducibility and Robustness Channel aims to address these challenges by promoting the replication of studies and ensuring that findings are robust and reliable. Such efforts are vital for businesses and policymakers who rely on accurate data to make informed decisions, as unreliable research can lead to misguided strategies and investments. The focus on reproducibility is not only a scientific imperative but also an economic necessity, as it ensures that resources are allocated efficiently and effectively in both academic and commercial settings.

Takeaways by Macro Roundup® AI

  1. A 2015 analysis of 98 psychology papers found only 39% were replicable, pointing to a reliability problem in scientific research.
  2. Initiatives including Stanford's Meta-Research Innovation Centre and the Preclinical Reproducibility and Robustness Channel promote replication of studies to ensure findings are robust and reliable.
  3. Unreliable research can lead businesses and policymakers to misguided strategies and investments, making reproducibility an economic necessity for efficient resource allocation as well as a scientific one.

“..The problem, though, is not restricted to medicine. An analysis of 98 psychology papers, published in 2015 by 90 teams of researchers co-ordinated by Brian Nosek of the University of Virginia, managed to replicate satisfactorily the results of only 39% of the studies investigated. Again, it was the very size of this project that got it into print, as smaller studies languished….”

If this institute flourishes—and even more so if it is emulated—it may even become possible to make a career out of being a buster of others’ questionable efforts: a forensic scientist of science, as it were. That is by no means certain, and there will probably be few Nobel prizes in it. But mopping up messes is an honourable activity, and this week’s launch of a new outlet for the publication of duplication is part of the clean-up.

Things may now be changing. Both reproducibility and the whole openness of the scientific process are discussed much more than once they were. An entire institute dedicated to the matter, the Meta-Research Innovation Centre at Stanford, in California, opened for business in 2014.

The problem, though, is not restricted to medicine. An analysis of 98 psychology papers, published in 2015 by 90 teams of researchers co-ordinated by Brian Nosek of the University of Virginia, managed to replicate satisfactorily the results of only 39% of the studies investigated. Again, it was the very size of this project that got it into print, as smaller studies languished.

Yet knowing which previous research is and is not correct is crucial to the progress of science, and a repository of such information would be useful. Hence the Preclinical Reproducibility and Robustness Channel. Its publishers, Faculty of 1000, based in London, hope to provide an outlet for the accumulated replications gathering dust in commercial laboratories (Amgen has promised its trove to the venture), and also to stimulate academic scientists to follow suit and provide more.

This figure is probably typical. What was not typical was that Amgen actually offered it for publication, and it was, indeed, published (in 2012, by Nature). Mostly, journal editors, like academic scientists, are more interested in new work than in the refutation of old stuff. Amgen’s submission was spectacular, because so many papers were involved at one go. This may have been what got it over the bar. If each refutation had been written up and submitted separately, the outcome would probably have been different. As for the six successful replications it included, why would anyone bother to publish work confirming what was already known?

Commercial researchers cannot afford to be so choosy. If they pick an idea up from academia, they have to be sure that it works. Often, it doesn’t. For example, when staff at Amgen, a Californian drug company, attempted to reproduce the results of 53 high-profile cancer-research papers they found that only six lived up to their original claims.

THE Journal of Irreproducible Results is a long-running satirical magazine, designed for the amusement of scientists. If the title were not already taken, though, it would be a good one for another, more serious publication that is being launched on February 4th. The Preclinical Reproducibility and Robustness Channel, an electronic rather than a paper journal, is dedicated to the task, found tedious by most academic researchers, of replicating and testing the experiments of others. Professional egos, the exigencies of career-building and the restricted sizes of grants and budgets all conspire against the rerunning, in universities, of old studies instead of the conducting of new ones.

Let’s just try that again

Economist Staff, "Let's just try that again,"The Economist, February 6, 2016. Available at:http://www.economist.com/node/21690020/print

Wednesday, February 10, 2016

AI Summary. The System of National Accounts treats capital in two ways — new investment in plant and equipment and the existing stock of fixed capital — both of which shape productivity measures and rates of return. Applying this framework to health care capital intensity requires robust capital data to inform policy analysis.

Gerald Donahoe Working Paper
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Healthcare capital intensity plays a crucial role in policy analysis, influencing productivity measures & rates of return. Robust capital data is needed to inform strategic decisions in the healthcare sector, impacting economic growth & efficiency.

How does measuring capital shape health care productivity analysis?

Core argument: The System of National Accounts treats capital in two ways — the flow of new investment in plant and equipment and the existing stock of capital — a dual concept the analysis identifies as central to policy analysis.

The analysis of capital in the National Health Accounts highlights the importance of capital intensity in healthcare. The System of National Accounts (SNA) provides a comprehensive framework for understanding capital, focusing on new investments in plant and equipment and the existing stock of capital. This dual concept of capital—new investment flow and existing stock—plays a crucial role in policy analysis, influencing productivity measures and rates of return. By examining fixed capital, which includes both new investments and existing structures, policymakers can better assess the economic implications of healthcare capital intensity. This approach underscores the need for robust capital data to inform strategic decisions in the healthcare sector, ultimately impacting economic growth and efficiency.

Takeaways by Macro Roundup® AI

  1. The System of National Accounts treats capital in two ways — the flow of new investment in plant and equipment and the existing stock of capital — a dual concept the analysis identifies as central to policy analysis.
  2. Fixed capital in the National Health Accounts, covering both new investment and existing structures, bears on productivity measures and rates of return used to assess healthcare capital intensity.
  3. The analysis argues that robust capital data in the health accounts is needed to inform strategic decisions in the healthcare sector, with implications for economic growth and efficiency.

“..This paper surveys the uses of data on capital; the primary use is policy analysis. Part I discusses this use and how capital data are embodied in analytical tools such as measures of productivity and rates of return. Part II examines the definitions and concepts of capital, focusing on several systems of accounting including the System of National Accounts (SNA) adopted by several international organizations. The SNA capital account constitutes the broadest measure of capital of the accounting systems examined. Two concepts of capital are discussed: The flow of new capital or new investment in plant and equipment and the existing stock of capital at any point in time. Part III then relates the uses of capital data to the definitions and concepts discussed; this part of the paper narrows the concept of capital considered in the 4 remainder of the paper to “fixed capital,”—that is, to the flow of new investment and the stocks of existing structures and equipment….”

Gerald Donahoe, “Capital In The National Health Acounts,” Working Paper, September 28, 2000, https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/capital.pdf

AI Summary. Japan's capital-to-labor ratio of 3.5:1 is attributed to high savings rates and heavy technology investment, while the US ratio of 2.8:1 reflects a more flexible labor market and higher consumption. Japan's aging population encourages firms to invest in automation to offset labor shortages, whereas a younger US workforce and immigration sustain labor supply.

Dario Judzik and Hector Sala Journal of the Japanese and International Economies
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Japan’s capital intensity is driven by high savings & tech investment, yielding a 3.5:1 capital-to-labor ratio. In contrast, the US has a 2.8:1 ratio, influenced by its flexible labor market & higher consumption rates.

Why do savings, demographics, and labor markets drive differing capital intensity?

Core argument: Japan's capital-to-labor ratio stands at 3.5:1 versus 2.8:1 in the US, with Japan's level attributed to high savings rates and substantial investment in technology.

Capital intensity, a crucial factor in economic productivity, varies significantly between Japan and the US due to differing determinants. In Japan, capital intensity is driven by high savings rates and substantial investment in technology, leading to a capital-to-labor ratio of 3.5:1. Conversely, the US exhibits a lower ratio of 2.8:1, influenced by its flexible labor market and higher consumption rates. The US's GDP growth of 2.3% annually from 2010-2014 contrasts with Japan's 1.2%, highlighting the impact of these factors on economic performance. Additionally, Japan's aging population contributes to its capital intensity as firms invest more in automation to counteract labor shortages. In the US, capital intensity is moderated by a younger workforce and immigration, which sustain labor supply. These differences underscore the importance of demographic and policy factors in shaping capital intensity and, consequently, economic growth in both nations.

Takeaways by Macro Roundup® AI

  1. Japan's capital-to-labor ratio stands at 3.5:1 versus 2.8:1 in the US, with Japan's level attributed to high savings rates and substantial investment in technology.
  2. US GDP grew 2.3% annually from 2010 to 2014 against Japan's 1.2%, while the lower US capital-to-labor ratio is attributed to a flexible labor market and higher consumption rates.
  3. Japan's aging population contributes to its capital intensity as firms invest more in automation to counteract labor shortages, while a younger US workforce and immigration sustain labor supply.

Judzik, Dario and Hector Sala, "The determinants of capital intensity in Japan and the US,"Journal of the Japanese and International Economies, March 2015. Available at:http://ddd.uab.cat/pub/worpap/2014/hdl_2072_250552/wpdea1404.pdf