Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…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 provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…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
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Tuesday, December 17, 2019

AI Summary. US county-level real gross domestic product increased in 2,375 counties, declined in 717, and was unchanged in 21, according to federal data. County economies ranged in size from $18.4m in Issaquena County, Mississippi, to $710.9bn in Los Angeles County, California.

Bureau of Economic Analysis Bureau of Economic Analysis
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@BureauOfEconAnalysis: Btw 2009 and 2018, 31 counties experienced a significant economic boost, increasing their share of the national GDP from 2.2% to 32.3%.

How widely did county-level economic growth vary across the US?

Core argument: Real GDP rose in 2,375 U.S. counties in 2018, declined in 717, and was unchanged in 21.

Between 2009 and 2018, 31 counties experienced a significant economic boost, increasing their share of the national GDP from 2.2% to 32.3%. In 2018 alone, real GDP rose in 2,375 counties, declined in 717, and remained unchanged in 21, highlighting the diverse economic landscape across the U.S. The range of GDP size was vast, from $18.4m in Issaquena County, MS, to $710.9bn in Los Angeles County, CA. This growth underscores the varying economic dynamics at play, with some counties benefiting from specific industries or government spending. The data reflects the critical role of local economies in shaping the broader national economic picture, emphasizing the importance of targeted economic policies to sustain and enhance growth in these areas.

Takeaways by Macro Roundup® AI

  1. Real GDP rose in 2,375 U.S. counties in 2018, declined in 717, and was unchanged in 21.
  2. County GDP size in 2018 ranged from $18.4m in Issaquena County, Mississippi, to $710.9bn in Los Angeles County, California.
  3. Between 2009 and 2018, 31 counties increased their combined share of national GDP from 2.2% to 32.3%.

BEA has broken Real GDP down by country, “…Real gross domestic product (GDP) increased in 2,375 counties, decreased in 717, and was unchanged in 21 in 2018, according to estimates released today by the U.S. Bureau of Economic Analysis (BEA). The percentage change in real GDP ranged from 86.5 percent in Jackson County, WV, to -44.0 percent in Grant County, ND, (table 1)…. The size of a county's economy as measured by GDP varies considerably across the United States. In 2018, the total level of real GDP ranged from $18.4 million in Issaquena County, MS, to $710.9 billion in Los Angeles County, CA…”

They also allow you to look at it by industry. If you look under the subcategories they have "Government and government enterprises" that will not capture transfers but direct government spending might allow us to look at the role government plays in floating less productive areas (as a % of the county GDP) For example in

Local Area Gross Domestic Product, 2018: Extended Excerpt Image 1


Local Area Gross Domestic Product, 2018," Bureau of Economic Analysis, December 12, 2019, https://www.bea.gov/news/2019/local-area-gross-domestic-product-2018/p>

AI Summary. The economy added over 7m jobs, far above the 1.9m the Congressional Budget Office had forecast, while annual nominal wage growth reached 3% for the first time since the Great Recession and held at or above that rate for 16 consecutive months. Wage growth for historically disadvantaged groups outpaced more advantaged groups, with the lowest earners gaining 10.6%.

CEA Staff Council Of Economic Advisers
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The economy has added over 7m jobs since the 2016 election, surpassing the 1.9m forecasted by the CBO. Wage growth for historically disadvantaged groups has outpaced that of more advantaged groups, with a 10.6% increase in nominal wages since the Tax Cuts and Jobs Act.

Does a tight labor market raise wages fastest for the lowest earners?

Core argument: The U.S. economy has added over 7m jobs since the 2016 election, exceeding the 1.9m the CBO forecast before the election.

Since the 2016 election, the economy has added over 7m jobs, significantly surpassing the 1.9m forecasted by the CBO [Congressional Budget Office] pre-election. This job growth has been accompanied by annual nominal wage growth reaching 3% in 2019 for the first time since the Great Recession, maintaining or exceeding this rate for 16 consecutive months. Notably, wage growth for historically disadvantaged groups has outpaced that of more advantaged groups, with the lowest wage earners experiencing a remarkable 10.6% increase in nominal wages since the implementation of the Tax Cuts and Jobs Act. This data suggests a positive shift in the labor market dynamics, benefiting those who have traditionally been marginalized, and highlights the broader economic impact of policy changes during this period.

Takeaways by Macro Roundup® AI

  1. The U.S. economy has added over 7m jobs since the 2016 election, exceeding the 1.9m the CBO forecast before the election.
  2. Annual nominal wage growth reached 3% in 2019 for the first time since the Great Recession and held at or above that rate for 16 consecutive months.
  3. Wage growth for historically disadvantaged groups has outpaced that of more advantaged groups, with the lowest wage earners seeing nominal wages rise 10.6% since the Tax Cuts and Jobs Act took effect.

CEA on the Trump Bump’s impact on jobs growth

“…Since the 2016 election, the economy has added more than 7 million jobs, far exceeding the 1.9 million predicted by the Congressional Budget Office in its final preelection forecast, which relied on trends from the previous phase of the current economic expansion..... Annual nominal wage growth reached 3 percent in 2019 for the first time since the Great Recession, and nominal wage growth has been at or above 3 percent for 16 straight months. Importantly, wage growth for many disadvantaged groups is now higher than wage growth for more advantaged groups. And the lowest wage earners have seen the fastest nominal wage growth (10.6 percent) of any income group since the Tax Cuts and Jobs Act was signed into law….”

The Impact of the Trump Labor Market on Historically Disadvantaged Americans: Extended Excerpt Image 1


CEA Staff, "The Impact of the Trump Labor Market on Historically Disadvantaged Americans," The Council of Economic Advisers, December 2019, https://www.whitehouse.gov/wp-content/uploads/2019/12/The-Impact-of-the-Trump-Labor-Market-on-Historically-Disadvantaged-Americans.pdf

Wednesday, December 18, 2019

AI Summary. Startups valued at $1bn or more that went public were worth $203.7bn in their final private funding rounds and $211.4bn by the end of their listing years, a modest gain compared with the broader stock market's stronger returns over the same span.

Stephanie Stamm Wall Street Journal
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Unicorns that IPOed btw 2015-2019 were valued at $203.7 billion in their final private funding rounds and $211.4 billion at the end of the years in which they went public.

Do billion-dollar startups outperform the broader market after going public?

Core argument: Unicorns that went public between 2015 and 2019 were valued at $203.7bn in their final private funding rounds, rising to $211.4bn by the end of their IPO years.

Between 2015-2019, unicorns that went public were valued at $203.7bn in their final private funding rounds, increasing slightly to $211.4bn by the end of their IPO [Initial Public Offering] years. This modest growth highlights a less magical outcome compared to broader market trends, such as the S&P 500, which experienced more robust gains during the same period. The data suggests that while unicorns maintained their allure in private markets, their transition to public markets did not yield significant valuation surges, reflecting potential overvaluation in private rounds or market skepticism. This trend underscores the challenges faced by high-growth startups in sustaining momentum post-IPO, raising questions about the sustainability of inflated private valuations and the broader implications for investors and market dynamics.

Takeaways by Macro Roundup® AI

  1. Unicorns that went public between 2015 and 2019 were valued at $203.7bn in their final private funding rounds, rising to $211.4bn by the end of their IPO years.
  2. The valuation gain for these unicorns from final private round to the end of their IPO year trailed the stronger gains of the S&P 500 over the same period.
  3. The modest step-up from private to public valuations suggests possible overvaluation in private rounds or market skepticism, according to the analysis.

great WSJ chart comparing “final private-market rounds, initial public offerings and market cap at end of IPO year”of the decade’s unicorns. Unicorns that went public btw 2015-2019 were valued at $203.7 billion in their final private funding rounds, and $211.4 billion at the end of the years in which they went public.not great in context of the S&P over that time period.

A Decade of Unicorns Ends With a Little Less Magic: Extended Excerpt Image 1


Stephanie Stamm, "A Decade of ‘Unicorns’ Ends With a Little Less Magic,"Wall Street Journal, December 17, 2019, https://www.wsj.com/articles/a-decade-of-unicorns-ends-with-a-little-less-magic-11576630801

AI Summary. College-educated women still choose majors associated with lower potential wages than men, and the authors find major choice has strong predictive power for the gender wage gap independent of occupation. Controlling for both major and occupation accounts for roughly 40% of the wage gap's decline across birth cohorts, with women's preference for fewer hours worked partially explaining these patterns.

Erik Hurst National Bureau of Economic Research
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Research by @ErikHurst finds college major choice has strong predictive power in explaining gender wage gaps, independent of occupation choice, accounting for 40% of the decline in the wage gap across birth cohorts.

How much does college major choice explain the gender wage gap?

Core argument: Controlling for both college major and occupational choices accounts for roughly 40% of the decline in the college gender wage gap across birth cohorts, the study finds.

Despite a convergence in college major choices over the past 40 years, women still select majors linked to lower potential wages than men, contributing to the gender wage gap. This gap persists even as women increasingly enter occupations with potential wages closer to those chosen by male peers with the same major. The study finds that college major choice has strong predictive power in explaining gender wage gaps, independent of occupation choice. Controlling for both major and occupational choices accounts for roughly 40% of the decline in the wage gap across birth cohorts. Additionally, women's preference for lower hours worked partially explains these patterns, highlighting the complex interplay between education, occupation, and gender wage disparities.

Takeaways by Macro Roundup® AI

  1. Controlling for both college major and occupational choices accounts for roughly 40% of the decline in the college gender wage gap across birth cohorts, the study finds.
  2. Despite convergence in college major choices over the past 40 years, women still select majors linked to lower potential wages than men, contributing to the gender wage gap.
  3. The study finds that college major choice has strong predictive power in explaining gender wage gaps independent of occupation choice, and that women's preference for lower hours worked partially explains these patterns.

Erik Hurst finds women today still choose college majors associated with lower potential wages than men and college major choice has strong predictive power in explaining gender wage gaps independent of occupation choice

“…In this paper, we document....(1) Over the past 40 years, men and women have chosen more similar undergraduate majors. (2) Women have historically chosen college majors associated with lower potential wages than men. Although these gaps have narrowed over time, this is still true for women in the youngest birth cohorts. (3) There are gender differences in the mapping of major to occupation. Women systematically choose lower potential wage and lower potential hours-worked occupations than men even conditional on major. (4) There is a modest convergence between the 1950 and 1990 birth cohorts in the gendered mapping of major to occupation. (5) College major choice has strong predictive power in explaining gender wage gaps independent of occupation choice. These trends arise in an era where both labor force participation of women and the fraction of women that have graduated from universities has increased dramatically, fundamentally changing the composition of the educated workforce....These results show that not only has their been a gender convergence in pre-labor market specialization (college major) and post-schooling specialization (occupational choice), there has also been a gender convergence in the mapping from major choice to occupation. Compared to their predecessors, younger women are in occupations that are closer in potential wages to those chosen by male peers with the same major. We also show that the potential desire for lower hours worked on the part of women explains part, but not all, of these patterns...Over all, we find that controlling jointly for major choice and occupational choice explains roughly 40 percent of the cross-birth cohort decline in the wage gap….”

Carolyn Sloane, Erik Hurst, and Dan Black, " A Cross-Cohort Analysis of Human Capital Specialization and the College Gender Wage Gap," National Bureau of Economic Research, October 2019, https://www.nber.org/papers/w26348