Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…
Robert Barro

Robert Barro

· Paul M. Warburg Professor of Economics

Harvard University · Economics

Active 1970–2024

h-index5
Citations55
Papers42
Funding
See your match with Robert Barro — sign in to PhdFit.Sign in

About

Robert J. Barro is the Paul M. Warburg Professor of Economics at Harvard University. His professional contact information includes his office at Littauer Center 218, email rbarro@harvard.edu, and phone number 617-495-3203. Additional support staff contact is Emily Sall at Littauer Center 327, esall@fas.harvard.edu, phone 617-496-0399. The webpage provides links to his biography, CV, classes, data sets, publications, popular writings, speaking topics, and working papers. No further biographical details, research focus, background, or key contributions are provided in the text.

Research topics

  • Business
  • Economics
  • Psychology
  • Computer science
  • Political science

Selected publications

  • Markups and Entry in a Circular Hotelling Model

    National Bureau of Economic Research · 2024-07-01 · 5 citations

    reportOpen access1st authorCorresponding

    The circular version of Hotelling’s locational model is extended by incorporating a continuum of consumers with constant-elasticity demand functions along with stores that have constant marginal costs of production. The stores are evenly spaced in equilibrium. The model implies that the markup of price over marginal cost depends on the spacing between stores and a transportation-cost parameter but is, as an approximation, independent of the elasticity of demand. This result reflects pricing decisions by stores that factor in the threat of losing business entirely at the borders with neighboring stores. This model provides a theory of price markups that substitutes for, or at least supplements, the familiar Lerner approach, which puts all the weight on the elasticity of demand. Moreover, the pricing results apply even when the magnitude of the elasticity of demand is less than one. The price markups determine the extent of entry into the market and, thereby, the efficiency of market outcomes. Entry is excessive when the approximate markup formula is accurate.

  • r Minus g

    National Bureau of Economic Research · 2020-10-01 · 11 citations

    report1st authorCorresponding

    Long-term data show that the dynamic efficiency condition r>g holds when g is represented by the average growth rate of real GDP if r is the average real rate of return on equity, E(re), but not if r is the risk-free rate, rf. This pattern accords with a simple disaster-risk model calibrated to fit observed equity premia. If Ponzi (chain-letter) finance by private agents and the government are precluded, the equilibrium can feature rf≤E(g), a result that does not signal dynamic inefficiency. In contrast, E(re)>E(g) is required for dynamic efficiency, implied by the model, and consistent with the data. The model satisfies Ricardian Equivalence because, without Ponzi finance by the government, a rise in safe assets from increased public debt is matched by an increase in the safe (that is, certain) present value of liabilities associated with net taxes.

  • Comments and Discussion

    Brookings Papers on Economic Activity · 2017-01-01 · 9 citations

    article1st authorCorresponding
  • Introduction

    Oxford University Press eBooks · 2015-08-01

    book-chapter1st authorCorresponding

    Abstract This chapter describes how the book is organized and presents a brief overview of educational expansion over the past two centuries. Education, considered as the preserve of privileged classes until the 19th century, began to grow in advanced countries, and it then spread to developing countries. The expansion of primary education, which has become almost universal in most countries in recent periods, occurred in the 19th and early 20th centuries, due to government policies, demographic changes, and rising GDP per capita. It was followed by the expansion of secondary and tertiary education. Additionally, there has been steady progress toward gender equality in educational opportunities.

  • Conclusions

    Oxford University Press eBooks · 2015-08-01

    book-chapter1st authorCorresponding

    Abstract This chapter summarizes the main findings and arguments presented in the previous chapters, and it discusses challenges related to education and human development. Many countries achieved economic development along with democratization in the 20th century. The remaining challenges to current and future educational development include removing disparities in opportunities for education, improving quality of education, and enhancing technical and vocational training. Education has major consequences not only for economic growth but also for the distribution of income. The chapter argues that technological progress implies that education, interacting with technologies, will continue to play an important role in economic growth and income differences across countries. Further movements toward educational equality will moderate income differences across countries and promote further modernization, including a greater prevalence of democracy.

  • Projection of Educational Attainment for 2015–2040

    Oxford University Press eBooks · 2015-08-01

    book-chapter1st authorCorresponding
  • Safe Assets

    SSRN Electronic Journal · 2014-01-01

    articleOpen access1st authorCorresponding
  • Gold Returns

    National Bureau of Economic Research · 2013-02-01 · 8 citations

    reportOpen access1st authorCorresponding

    From 1836 to 2011, the average real rate of price change for gold in the United States is 1.1% per year and the standard deviation is 13.1%, implying a one-standard-deviation confidence band for the mean of (0.1%, 2.1%). The covariances of gold's real rate of price change with consumption and GDP growth rates are small and statistically insignificantly different from zero. These negligible covariances suggest that gold's expected real rate of return-which includes an unobserved dividend yield-would be close to the risk-free rate, estimated to be around 1%. We study these properties within an asset-pricing model in which ordinary consumption and gold services are imperfect substitutes for the representative household. Disaster and other shocks impinge directly on consumption and GDP but not on stocks of gold. With a high elasticity of substitution between gold services and ordinary consumption, the model can generate a mean real rate of price change within the (0.1%, 2.1%) confidence band along with a small risk premium for gold. In this scenario, the bulk of gold's expected return corresponds to the unobserved dividend yield (the implicit rental income from holding gold) and only a small part comprises expected real price appreciation. Nevertheless, the uncertainty in gold returns is concentrated in the price-change component. The model can explain the time-varying volatility of real gold prices if preference shocks for gold services are small under the classical gold standard but large in other periods particularly because of shifting monetary roles for gold.

  • How to Get That AAA Rating Back

    ˜The œWall Street journal (Eastern ed. : Online)/˜The œWall Street journal. Eastern edition · 2011-01-01

    article1st authorCorresponding
  • Thoughts on QE2

    Economist on CD-ROM/Economist · 2010-01-01 · 1 citations

    article1st authorCorresponding

Frequent coauthors

  • Jong‐Wha Lee

    Korea University

    3 shared
  • James Tobin

    1 shared
  • Lucrezia Reichlin

    Centre for Economic Policy Research

    1 shared
  • David M. Cutler

    1 shared
  • William P. Schaefer

    The University of Texas at San Antonio

    1 shared
  • R. Dornbusch

    1 shared
  • M. Simonsen

    1 shared
  • R.E. Marsh

    1 shared
  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Robert Barro

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup