Reconstruction of Macroeconomics: Methods of Statistical Physics, and Keynes' Principle of Effective Demand

Download or read book Reconstruction of Macroeconomics: Methods of Statistical Physics, and Keynes' Principle of Effective Demand written by Hiroshi Yoshikawa and published by Springer Nature. This book was released on 2022-10-29 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how standard micro-founded macroeconomics is misguided and proposes an alternative method based on statistical physics. The Great Recession following the bankruptcy of Lehman Brothers in September 2015 amply demonstrated that mainstream micro-founded macroeconomics was in trouble. The new approach advanced in this book reasonably explains important macro-problems such as employment, business cycles, growth, and inflation/deflation. The key concept is demand failures, which modern micro-founded macroeconomics has ignored. “It (Chapter 3) captures analytically a good part of the intuition that underlies the Keynesian economics of people like Tobin and me.” Robert Solow, Emeritus Institute Professor of Economics, Massachusetts Institute of Technology, Nobel Laureate in Economics, 1987 “Professor Hiroshi Yoshikawa provides a unique synthesis of statistical physics and macro-economic theory in order to confront the dismal failure in economics and in finance to understand how an economy or a financial market works, given the heterogeneous decision making of many different individual interacting actors. Economics has failed in this regard with the naive and often misleading concept of “representative agents.” The author presents many insights on the historical development, concepts, and errors made by the most illustrious economists in the past. This book should be essential readings for any economics students as well as academic researchers and policy makers, who should learn to bring back good-sense thinking in their impactful decisions.” Didier Sornette, Professor on the Chair of Entrepreneurial Risks at the Swiss Federal Institute of Technology Zurich (ETH Zurich)