A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Inflation is regarded by the many as a menace that damages business and can only make life worse for households. Keeping it low depends critically on ensuring that firms and workers expect it to be low. So expectations of inflation are a key influence on national economic welfare. This collection pulls together a galaxy of world experts (including Roy Batchelor, Richard Curtin and Staffan Linden) on inflation expectations to debate different aspects of the issues involved. The main focus of the volume is on likely inflation developments. A number of factors have led practitioners and academic observers of monetary policy to place increasing emphasis recently on inflation expectations. One is the spread of inflation targeting, invented in New Zealand over 15 years ago, but now encompassing many important economies including Brazil, Canada, Israel and Great Britain. Even more significantly, the European Central Bank, the Bank of Japan and the United States Federal Bank are the leading members of another group of monetary institutions all considering or implementing moves in the same direction. A second is the large reduction in actual inflation that has been observed in most countries over the past decade or so. These considerations underscore the critical – and largely underrecognized - importance of inflation expectations. They emphasize the importance of the issues, and the great need for a volume that offers a clear, systematic treatment of them. This book, under the steely editorship of Peter Sinclair, should prove very important for policy makers and monetary economists alike.
A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike
The lasting turmoil associated with the unprecedented pandemic, triggered by the novel corona virus COVID-19, has dragged the world into a mud of uncertainty. Fiscal stimulation, interest rate cuts, global supply-chain redeployment, "pandemic bond" and circuit breakers kicked in and the world is responding to this great challenge. But how can finance and economic research help the world under such circumstances? This book dwells on this new area of research and tries to understand how pandemics impact the economic and financial ecosystem of both emerging and advanced economies. Lessons learnt from the experience of previous pandemics maybe presented and discussed through drawing on policy lessons to date. By gathering research on political economy, geopolitical issues, behavioral finance, international institutional responses and medical and health issues resulting from pandemics, the chapters in this edited volume help in expanding the knowledge of social and economic consequences of the pandemic as well as set the foundation for future research. This book would benefit scholars, policy makers and entrepreneurs worldwide as a valuable archive of research on pandemics. The chapters in this book were originally published as a special issue of Emerging Markets Finance and Trade.
The recent global financial crisis exposed the serious limitations of existing economic and financial models. Not only did macro models fail to predict the crisis, they seemed incapable of explaining what was happening to the economy. Policymakers felt abandoned by the conventional tools of the now obsolete Washington consensus and the World Trade Organization’s oversimplified faith in free markets.The traditional models for agricultural commodities have so far failed to take into account the uncertain character of the global agricultural economy and its ferocious consequences in food price volatility, the worst in 300 years, yielding hunger riots throughout the world. This book explores the elements which could help to close this fundamental modeling gap. To what extent should traditional models be questioned regarding agricultural commodities? Are prices on these markets foreseeable? Can their evolution be either predicted or convincingly simulated, and if so, by which methods and models? Presenting contributions from acknowledged experts from several countries and backgrounds – professors at major international universities or researchers within specialized international organizations – the book concentrates on four issues: the role of expectations and capacity of prediction; policy issues related to development strategies and food security; the role of hoarding and speculation and finally, global modeling methods. The book offers a renewed wisdom on some of the core issues in the world economy today and puts forward important innovations in analyzing these core issues, among which the modular modeling design, the Momagri model being a seminal example of it. Reading this book should inspire fruitful revisions in policy-making to improve the welfare of populations worldwide.
Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
Joseph Stiglitz examines the theory behind the economic downturns that have plagued our world in recent times. This fascinating three-part lecture acknowledges the failure of economic models to successfully predict the 2008 crisis and explores alternative models which, if adopted, could potentially restore a stable and prosperous economy.
We develop new economic policy uncertainty (EPU) indices for Japan from January 1987 onwards building on the approach of Baker, Bloom and Davis (2016). Each index reflects the frequency of newspaper articles that contain certain terms pertaining to the economy, policy matters and uncertainty. Our overall EPU index co-varies positively with implied volatilities for Japanese equities, exchange rates and interest rates and with a survey-based measure of political uncertainty. The EPU index rises around contested national elections and major leadership transitions in Japan, during the Asian Financial Crisis and in reaction to the Lehman Brothers failure, U.S. debt downgrade in 2011, Brexit referendum, and Japan’s recent decision to defer a consumption tax hike. Our uncertainty indices for fiscal, monetary, trade and exchange rate policy co-vary positively but also display distinct dynamics. VAR models imply that upward EPU innovations foreshadow deteriorations in Japan’s macroeconomic performance, as reflected by impulse response functions for investment, employment and output. Our study adds to evidence that credible policy plans and strong policy frameworks can favorably influence macroeconomic performance by, in part, reducing policy uncertainty.
