Edward Conard

Top Ten New York Times Bestselling Author

  • “…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 must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…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
  • “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
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Monday, February 24, 2014

AI Summary. The authors estimate that the spread of performance-based pay such as bonuses and commissions accounts for 24% of the growth in male wage variance and nearly all top-end wage dispersion growth for the top fifth of earners. Performance-pay jobs, which expanded from 30% to over 40% of jobs, show returns to education and experience 40–60% higher than other jobs.

Lemieux, Thomas, MacLeod, W Bentley, and Daniel Parent National Bureau of Economic Research
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Performance pay has significantly contributed to wage inequality, explaining 24% of male wage variance growth from the late 1970s to early 1990s. @LemieuxThomas @MacLeodW @DanielParent

How much of wage inequality growth does performance pay explain?

Core argument: Performance-based pay, including bonuses and commissions, explains 24% of the growth in male wage variance from the late 1970s to the early 1990s and nearly all top-end wage dispersion growth for the top quintile.

The rise of performance-based pay, including bonuses and commissions, has significantly contributed to wage inequality, explaining 24% of the growth in male wage variance from the late 1970s to early 1990s and nearly all top-end wage dispersion growth for the top quintile. Wage inequality is greater and has risen faster in performance-pay jobs compared to others during the 1980s. The adoption of performance pay expanded from 30% of jobs in the late 1970s to over 40% by the 1990s, rewarding positive worker characteristics with returns on education and experience exceeding those in non-performance-pay jobs by 40-60%. Advances in compensation technology have enhanced worker-firm matches and productivity, with performance pay aligning wages more closely with workers' marginal products than non-performance pay systems.

Takeaways by Macro Roundup® AI

  1. Performance-based pay, including bonuses and commissions, explains 24% of the growth in male wage variance from the late 1970s to the early 1990s and nearly all top-end wage dispersion growth for the top quintile.
  2. Performance pay spread from 30% of jobs in the late 1970s to over 40% by the 1990s, with returns to education and experience in those jobs exceeding non-performance-pay jobs by 40–60%.
  3. Wage inequality is greater and rose faster in performance-pay jobs than in other jobs during the 1980s, and performance pay aligns wages more closely with workers' marginal products than non-performance-pay systems.

Lemieux, Thomas, MacLeod, W Bentley, and Daniel Parent, “Performance Pay and Wage Inequality” NBER Working Paper No. 13128. May 2007. Available at:http://www.nber.org/papers/w13128 According to the paper the rise of performance based pay (bonuses, commissions, and price-rates) can explain 24 percent of the growth in the variance of male wages between the late 1970s and the early 1990s, and accounts for nearly all of the top-end growth in wage dispersion for the top quintile.

Wage inequality is generally greater in performance-pay jobs than in other jobs, and that inequality has risen faster in performance-pay jobs than in other jobs during the 1980’s

Adaptation of performance pay has been widespread, growing from 30 percent of jobs in the late 1970 to more than 40 percent by the 1990s.

This has had the effect of rewarding positive worker characteristics - the return to education and experience in performance-pay jobs has exceeded that of the return on non-performance-pay jobs by factor in the 40-60 percent range.

The rise in “technology of compensation” such as effective measurement systems and new payment schemes has allowed firms to improve the quality of a “worker-firm match” and as well as employee productivity. Performance pay is an indicator that firms pay wages that are closer to the marginal product of workers than firms that do not use performance pay.

Monday, March 24, 2014

AI Summary. Economic models of "uncertainty traps" show feedback loops in which firms invest less when they perceive high uncertainty, while low investment limits the flow of information and sustains that uncertainty. The authors argue this can produce multiple stable regimes, so short-lived shocks generate prolonged downturns even with strong fundamentals.

Fajgelbaum, Pablo, Edouard Schael and Mathieu Taschereau-Dumouchel National Bureau of Economic Research
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Uncertainty Traps by @FajgelbaumPablo @EdouardSchael @MathieuTD, @nberpub: Feedback loops in economic systems can amplify uncertainty, leading to prolonged recessions even when fundamentals are strong.

Can brief shocks cause long downturns when fundamentals stay strong?

Core argument: The uncertainty trap model holds that feedback loops amplify uncertainty, so short-lived shocks can generate prolonged recessions even when economic fundamentals are strong.

The concept of uncertainty traps highlights how feedback loops in economic systems can amplify uncertainty, leading to prolonged recessions even when fundamentals are strong. This model suggests that short-lived shocks can have long-lasting effects, explaining phenomena like the slow recovery of U.S. output post-recession despite rapid productivity gains. The economy may settle into a high-activity regime with low uncertainty or a low-activity regime with high uncertainty, depending on initial conditions. Firms are more likely to invest when they perceive lower uncertainty, but low investment rates can increase uncertainty by limiting information flow. This dynamic creates multiple stationary points in economic activity, where only significant positive shocks can shift the economy from a low to a high-activity regime.

Takeaways by Macro Roundup® AI

  1. The uncertainty trap model holds that feedback loops amplify uncertainty, so short-lived shocks can generate prolonged recessions even when economic fundamentals are strong.
  2. In the model, firms invest more when they perceive lower uncertainty, while low investment rates raise uncertainty by limiting information flow, producing multiple stationary points in economic activity.
  3. In the uncertainty trap model, the economy settles into either a high-activity, low-uncertainty regime or a low-activity, high-uncertainty regime depending on initial conditions, with only significant positive shocks shifting it from low to high activity.

Uncertainty Trapspresents a new model that suggest and attempts to quantify uncertainty as a dynamic factor that generates feedback loops that can amplify its own impact. The authors explain this relationship on a firm level:

Fajgelbaum, Pablo, Edouard Schael and Mathieu Taschereau-Dumouchel, Uncertainty Traps, NBER March 5, 2014. Available at:http://www.parisschoolofeconomics.eu/IMG/pdf/uncertainty_traps.pdf

Because these relationships are driven by feedback loops they are highly non-linear.

Short-lived shocks can generate long lasting recessions, and low activity may persist even under good fundamentals. Thus, the theory rationalizes salient features of U.S. macroeconomic activity that are not easily explained by standard business cycle models, such as the slow recovery of output after recessions despite typically faster improvements in measured productivity.

The authors believe this premise explains American macroeconomic activity better than standard business cycle models as it combines two forces, “higher uncertainty about economic fundamentals deters investment, and uncertainty evolves endogenously because agents learn from the actions of others” Due to their self-reinforcing nature episodes:

The economy will converge to either a good regime (with low uncertainty and high economic activity) if the current level of uncertainty is sufficiently low or to a bad regime (with high uncertainty and low activity) if the current level of uncertainty is sufficiently high. As a result of this multiplicity, the economy exhibits strong nonlinearities in its response to shocks. The economy quickly recovers after small temporary shocks, but it may shift into low-activity regime after a large temporary shock. Once it has fallen in the low regime, only a large enough positive shock can but the economy back into the high-activity regime.

The basic thesis is the relationship between information and investment can create feedback loops - uncertainty traps - in the papers parlance “the coexistence of multiple stationary points in the dynamics of uncertainty and economic activity.” Thus:

Firms are more likely to invest if their beliefs about the fundamentals have higher mean, but also if they have smaller variance (lower uncertainty). At the same time, the laws of motion for the mean and variance of beliefs depend on the investment rate. When few firms invest, little information is released, so uncertainty rises.