Feedback Economics

This book approaches economic problems from a systems thinking and feedback perspective. By introducing system dynamics methods (including qualitative and quantitative techniques) and computer simulation models, the respective contributions apply feedback analysis and dynamic simulation modeling to important local, national, and global economics issues and concerns. Topics covered include: an introduction to macro modeling using a system dynamics framework; a system dynamics translation of the Phillips machine; a re-examination of classical economic theories from a feedback perspective; analyses of important social, ecological, and resource issues; the development of a biophysical economics module for global modelling; contributions to monetary and financial economics; analyses of macroeconomic growth, income distribution and alternative theories of well-being; and a re-examination of scenario macro modeling. The contributions also examine the philosophical differences between the economics and system dynamics communities in an effort to bridge existing gaps and compare methods. Many models and other supporting information are provided as online supplementary files. Consequently, the book appeals to students and scholars in economics, as well as to practitioners and policy analysts interested in using systems thinking and system dynamics modeling to understand and improve economic systems around the world. "Clearly, there is much space for more collaboration between the advocates of post-Keynesian economics and system dynamics! More generally, I would like to recommend this book to all scholars and practitioners interested in exploring the interface and synergies between economics, system dynamics, and feedback thinking." Comments in the Foreword by Marc Lavoie, Emeritus Professor, University of Ottawa and University of Sorbonne Paris Nord

This book investigates why economics makes less visible progress over time than scientific fields with a strong practical component, where interactions with physical technologies play a key role. The thesis of the book is that the main impediment to progress in economics is "false feedback", which it defines as the false result of an empirical study, such as empirical evidence produced by a statistical model that violates some of its assumptions. In contrast to scientific fields that work with physical technologies, false feedback is hard to recognize in economics. Economists thus have difficulties knowing where they stand in their inquiries, and false feedback will regularly lead them in the wrong directions. The book searches for the reasons behind the emergence of false feedback. It thereby contributes to a wider discussion in the field of metascience about the practices of researchers when pursuing their daily business. The book thus offers a case study of metascience for the field of empirical economics. The main strength of the book are the numerous smaller insights it provides throughout. The book delves into deep discussions of various theoretical issues, which it illustrates by many applied examples and a wide array of references, especially to philosophy of science. The book puts flesh on complicated and often abstract subjects, particularly when it comes to controversial topics such as p-hacking. The reader gains an understanding of the main challenges present in empirical economic research and also the possible solutions. The main audience of the book are all applied researchers working with data and, in particular, those who have found certain aspects of their research practice problematic.

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

A new era calls for new economics. This book offers a new paradigm of economics with a new perspective and a new fundamental logic system in this new century. The new paradigm originates from a fundamental fact: The main behavioral subjects of socio-economic activities are not individuals, but social organizations composed of individuals, such as families, enterprises, schools, research institutes, government branches, charity organizations and so on. So this book replaces the controversial assumption of "economic man" with the model of "the minimum economic system" abstracted from reality and establishes a new logic analysis framework of "economic unit (the minimum economic system) -- economic flow (the input and output between economic units) -- economic field (the space-time distribution of economic units and their movement)" which is totally different from all existing economics theories. As a result, this book reconstructs economics on a foundation of natural science and systems science and can explain the secret of China's rapid economic growth and other economic puzzles at the level of fundamental logic. This book replaces neoclassical and modern orthodox economics with a new economics meta-theory, making it a fascinating read and providing a valuable reference for researchers, teachers and students majoring in economics.

This book is devoted to establishing a completely new concept within economics referred to as "trading economics" which is a reconstructed economic system in theory that seeks perfect harmony between micro and macro elements in a structured way, hence making the economic theory a rigorous system supported by internal logical continuity. Representing a revolution of the existing theoretical framework, trading economics has changed the logic of mainstream economics. Specifically, it deduces the "macro whole" from the "micro individuals", and it introduces a systematic and comprehensive analysis approach. It stresses that within an interconnected world, the interaction between trading agents is the fundamental driving force behind the operation, development and evolution of the economic system.

Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors: Daron Acemoglu, Massachusetts Institute of Technology Philippe Aghion, Collège de France Ajay Agrawal, University of Toronto Susan Athey, Stanford University James Bessen, Boston University School of Law Erik Brynjolfsson, MIT Sloan School of Management Colin F. Camerer, California Institute of Technology Judith Chevalier, Yale School of Management Iain M. Cockburn, Boston University Tyler Cowen, George Mason University Jason Furman, Harvard Kennedy School Patrick Francois, University of British Columbia Alberto Galasso, University of Toronto Joshua Gans, University of Toronto Avi Goldfarb, University of Toronto Austan Goolsbee, University of Chicago Booth School of Business Rebecca Henderson, Harvard Business School Ginger Zhe Jin, University of Maryland Benjamin F. Jones, Northwestern University Charles I. Jones, Stanford University Daniel Kahneman, Princeton University Anton Korinek, Johns Hopkins University Mara Lederman, University of Toronto Hong Luo, Harvard Business School John McHale, National University of Ireland Paul R. Milgrom, Stanford University Matthew Mitchell, University of Toronto Alexander Oettl, Georgia Institute of Technology Andrea Prat, Columbia Business School Manav Raj, New York University Pascual Restrepo, Boston University Daniel Rock, MIT Sloan School of Management Jeffrey D. Sachs, Columbia University Robert Seamans, New York University Scott Stern, MIT Sloan School of Management Betsey Stevenson, University of Michigan Joseph E. Stiglitz. Columbia University Chad Syverson, University of Chicago Booth School of Business Matt Taddy, University of Chicago Booth School of Business Steven Tadelis, University of California, Berkeley Manuel Trajtenberg, Tel Aviv University Daniel Trefler, University of Toronto Catherine Tucker, MIT Sloan School of Management Hal Varian, University of California, Berkeley

In the past fifteen years a new field of research has emerged in economics: the application of control theory methods to macroeconomics and to microeconomics. The papers and books which have resulted from this research are important to the development of theoretical and applied economics. However, they are inaccessible to many with interest in economics because of the technical nature of the discussion. This book attempts to make the macro economic portion of this literature more accessible by providing a discussion of the key issues using words and figures rather than mathematical symbols. I would like to thank my mentors and colleagues in control theory and economics for their help over the years: Masanao Aoki, Michael Athans, Yaakov Bar-Shalom, Jeremy Bray, Arthur Bryson, Gregory Chow, Ray Fair, Laurie Henrikson, David Livesey, Raman Mehra, Alfred Norman, Robert Pindyck, Franklin Shupp, John Taylor, Lance Taylor, Peter Tinsley, Edison Tse, and Stephen Turnovsky.

Recently economists have more and more focussed on scenarios in which agents' views of the world may be erroneous. These notes introduce the concept of perfect forecasting rules which provide best least-squares predictions along the evolution of an economic system. The framework for nonparametric adaptive learning schemes is developed and it is argued that plausible learning schemes should aim at estimating a perfect forecasting rule taking into account the correct feedback structure of an economy. A link is provided between the traditional rational-expectations view and recent behavioristic approaches.