Edward Conard

Top Ten New York Times Bestselling Author

  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “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
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “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 very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “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
  • “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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Thursday, June 11, 2020

AI Summary. Wage gaps between poorer and richer U.S. cities narrowed at about 1.4% a year between 1940 and 1980, but this regional convergence then stopped. Using a dynamic spatial equilibrium model that matches observed wage, skill-ratio, and migration patterns, the authors attribute much of the change in cross-city wage differences to skill-biased technical change and agglomeration economies.

Elisa Giannone University of Chicago
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Prior to 1980, US wage gaps btw poorer & richer cities were shrinking at 1.4% annual rate. Post-1980, regional convergence ceased due to skill-biased technical change & agglomeration economies.

Why did wage convergence between poorer and richer U.S. cities stop?

Core argument: The wage gap between poorer and richer U.S. cities narrowed at roughly 1.4% a year between 1940 and 1980, but regional convergence ceased after 1980, attributed largely to skill-biased technical change and agglomeration economies.

Between 1940 and 1980, the wage gap between poorer and richer U.S. cities was shrinking at an annual rate of ~1.4%. However, post-1980, regional convergence ceased, largely due to skill-biased technical change (SBTC) and agglomeration economies. A dynamic spatial equilibrium model was developed to analyze these shifts, successfully matching the quantitative features of U.S. regional wage convergence and reproducing changes in skill ratios and migration patterns across cities. The model's counterfactual analysis indicates that SBTC significantly contributed to the change in cross-city wage differentials, highlighting its role in halting the convergence trend.

Takeaways by Macro Roundup® AI

  1. The wage gap between poorer and richer U.S. cities narrowed at roughly 1.4% a year between 1940 and 1980, but regional convergence ceased after 1980, attributed largely to skill-biased technical change and agglomeration economies.
  2. A dynamic spatial equilibrium model matches the quantitative features of U.S. regional wage convergence and reproduces observed changes in skill ratios and migration patterns across cities.
  3. Counterfactual analysis of the spatial equilibrium model indicates that skill-biased technical change contributed substantially to the change in cross-city wage differentials and to the halt in regional convergence.

“…. Between 1940 and 1980 the wage gap between poorer U.S. cities and richer ones was shrinking at an annual rate of roughly 1.4%. After 1980, however, there was no further regional convergence overall. This paper quantifies the contributions of skill-biased technical change (SBTC) and agglomeration economies to the end of cross-city wage convergence within the U.S. between 1980 and 2010. I develop and estimate a dynamic spatial equilibrium model that looks at the causes of regional convergence and divergence. The model choice is motivated by novel empirical regularities regarding the evolution of the skill premium and migration patterns over time and across space. The model successfully matches the quantitative features of the U.S. regional wage convergence. Moreover, the model also reproduces changes in the skill ratio across U.S. cities, as well as, migration patterns after 1980. Finally, the counterfactual analysis suggests that SBTC explains much of change in cross-city wage differentials….”

Giannone, Elisa. January 4, 2017. “Skilled-Biased Technical Change and Regional Convergence.” University of Chicago.https://home.uchicago.edu/~elisagiannone/files/JMP_ElisaG.pdf

AI Summary. The US has seen a decline in business startups and employment dynamism, with the share of employment at young firms falling by nearly 30% over 30 years. The authors argue this indicates weakened incentives to start new firms and supports policies that encourage entrepreneurship.

Ryan Decker, John Haltiwanger, Ron Jarmin, and Javier Miranda Journal of Economic Perspectives
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US business startups and employment dynamism have declined, with the share of employment by young firms decreasing by nearly 30% over the last 30 years

Has US startup activity and employment at young firms declined?

Core argument: The share of US employment at young firms has fallen by nearly 30% over the past 30 years, indicating a reduced role for dynamic young businesses in the economy.

The US has experienced a notable decline in business startups and employment dynamism, with the trend accelerating post-2000. Over the last 30 years, the share of employment by young firms has decreased by nearly 30%, indicating a reduced role for dynamic young businesses in the economy. This decline suggests that incentives for entrepreneurs to start new firms have diminished, impacting economic growth and productivity. While the optimal pace of business dynamics is complex to define, the evidence points to a need for policies that encourage entrepreneurship to revitalize job creation and economic dynamism.

Takeaways by Macro Roundup® AI

  1. The share of US employment at young firms has fallen by nearly 30% over the past 30 years, indicating a reduced role for dynamic young businesses in the economy.
  2. US business startups and employment dynamism have declined, with the trend accelerating after 2000, suggesting that incentives for entrepreneurs to found new firms have diminished.
  3. Although the optimal pace of business dynamics is difficult to define, the evidence points to a need for policies encouraging entrepreneurship to revitalize job creation and economic dynamism.

“…An optimal pace of business dynamics—encompassing the processes of entry, exit, expansion, and contraction—would balance the benefits of productivity and economic growth against the costs to firms and workers associated with reallocation of productive resources. It is difficult to prescribe what the optimal pace should be, but evidence accumulating from multiple datasets and methodologies suggests that the rate of business startups and the pace of employment dynamism in the US economy has fallen over recent decades and that this downward trend accelerated after 2000. A critical factor in accounting for the decline in business dynamics is a lower rate of business startups and the related decreasing role of dynamic young businesses in the economy. For example, the share of US employment accounted for by young firms has declined by almost 30 percent over the last 30 years.These trends suggest that incentives for entrepreneurs to start new firms in the United States have diminished over time. We do not identify all the factors underlying these trends in this paper but offer some clues based on the empirical patterns for specific sectors and geographic regions….”

Decker, Ryan, John Haltiwanger, Ron Jarmin, and Javier Miranda. Summer 2014. “The Role of Entrepreneurship in US Job Creation and Economic Dynamism.”Journal of Economic Perspectives.https://www.aeaweb.org/articles

Friday, June 12, 2020

AI Summary. Households between the 80th and 99th percentiles saw their share of pretax income rise from 29% to 31%, while the top 1% share rose from 9% to 16% and the bottom 20% share fell from 7% to 5%.

CBO Staff Congressional Budget Office
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The share of pretax income for households in the 80th to 99th % increased modestly from 29% to 31% btw 1979 and 2016, @USCBOOffice reports.

How has the share of pretax income shifted across households?

Core argument: The top 1% of households saw their share of pretax income rise from 9% to 16% between 1979 and 2016.

Between 1979 and 2016, the share of pretax income for households in the 80th to 99th % increased modestly, reflecting a shift in income distribution. This group saw their share rise from 29% to 31%, indicating a gradual concentration of income among higher earners. In contrast, the bottom 20% experienced a decline in their share from 7% to 5%, highlighting growing income inequality. The top 1% saw a more significant increase, with their share rising from 9% to 16%, underscoring the disproportionate gains at the very top. These changes suggest that while the middle-upper income brackets have seen some growth, the most substantial gains have been concentrated among the wealthiest, raising concerns about economic disparity and its implications for economic policy and social equity.

Takeaways by Macro Roundup® AI

  1. The top 1% of households saw their share of pretax income rise from 9% to 16% between 1979 and 2016.
  2. Households in the 80th to 99th percentiles increased their share of pretax income from 29% to 31% between 1979 and 2016.
  3. The bottom 20% of households saw their share of pretax income fall from 7% to 5% between 1979 and 2016.

Congressional Budget Office (CBO). July 9, 2019. “The Distribution of Household Income, 2016.”https://www.cbo.gov/publication/55413