Robert G. King

About

Robert G. King is a Professor in the Department of Economics at Boston University. His academic background includes a PhD from Brown University. His research focuses on macroeconomics, monetary economics, and economic growth. He is associated with the Institute for Economic Development (IED) and is involved in various seminars, lectures, and research activities within the department. For more information or to contact him, his office is located in SSW 502, and he can be reached via email at rking@bu.edu or by phone at 617-353-5941. His professional profile and additional details are available through his website.

Research topics

• Political Science
• Keynesian economics
• Economics
• Physics
• Monetary economics
• Law

Selected publications

• Inflation Targeting in a St. Louis Model of the 21st Century

  2013-01-01 · 40 citations

  articleOpen access1st authorCorresponding

  Louis model of the early 1970s, as described by Its structure was sharply at variance with the framework of the major, larger scale macroeconometric models used for policy analysis by the Federal Reserve, both at the time of the inception of the St. Louis model and today.

  PublisherOA PDFDOI

• Optimal reputation building in the New Keynesian model

  Journal of Monetary Economics · 2016-11-06 · 15 citations

  article
  PublisherDOI

• Inflation and Real Activity with Firm-Level Productivity Shocks

  SSRN Electronic Journal · 2013-01-01 · 8 citations

  articleOpen access
  PublisherDOI

• The Rise, Fall and Stabilization of U.S. Inflation: Shifting Regimes and Evolving Reputation

  SSRN Electronic Journal · 2021 · 7 citations

  1st authorCorresponding
  PublisherDOI

• GLDEX: Fitting Single and Mixture of Generalised Lambda Distributions

  2022-05-12 · 5 citations

  datasetOpen access

  The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqp…

  PublisherOA PDFDOI

Frequent coauthors

• Alfred L. Copley

  77 shared

• Marvin Goodfriend

  Carnegie Mellon University

  57 shared

• Alexander L. Wolman

  45 shared

• Mark W. Watson

  34 shared

• Charles I. Plosser

  33 shared

• Michael Dotsey

  32 shared

• Yang Lu

  University of Houston

  29 shared

• Julia K. Thomas

  27 shared

Education

• Ph.D.

  Brown University

Similar researchers at Boston University

• Benjamin Marxh-90
• Laurence J. Kotlikoffh-72
• Pierre Perronh-72