This book is a collection of state-of-the-art papers on the properties of business cycles and financial analysis. The individual contributions cover new advances in Markov-switching models with applications to business cycle research and finance. The introduction surveys the existing methods and new results of the last decade. Individual chapters study features of the U. S. and European business cycles with particular focus on the role of monetary policy, oil shocks and co movements among key variables. The short-run versus long-run consequences of an economic recession are also discussed. Another area that is featured is an extensive analysis of currency crises and the possibility of bubbles or fads in stock prices. A concluding chapter offers useful new results on testing for this kind of regime-switching behaviour. Overall, the book provides a state-of-the-art over view of new directions in methods and results for estimation and inference based on the use of Markov-switching time-series analysis. A special feature of the book is that it includes an illustration of a wide range of applications based on a common methodology. It is expected that the theme of the book will be of particular interest to the macroeconomics readers as well as econometrics professionals, scholars and graduate students. We wish to express our gratitude to the authors for their strong contributions and the reviewers for their assistance and careful attention to detail in their reports.

A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.

United States monetary policy has traditionally been modeled under the assumption that the domestic economy is immune to international factors and exogenous shocks. Such an assumption is increasingly unrealistic in the age of integrated capital markets, tightened links between national economies, and reduced trading costs. International Dimensions of Monetary Policy brings together fresh research to address the repercussions of the continuing evolution toward globalization for the conduct of monetary policy. In this comprehensive book, the authors examine the real and potential effects of increased openness and exposure to international economic dynamics from a variety of perspectives. Their findings reveal that central banks continue to influence decisively domestic economic outcomes—even inflation—suggesting that international factors may have a limited role in national performance. International Dimensions of Monetary Policy will lead the way in analyzing monetary policy measures in complex economies.

This paper examines the evidence on asymmetries in the effects of activity on inflation. Data for the G-7 countries are found to strongly support the view that the inflation-activity relationship is nonlinear, with high levels of activity raising inflation by more than low levels decrease it. In the face of such asymmetries, the average level of output in an economy subject to demand shocks will be below the level of output at which there is no tendency for inflation to rise or fall, contrary to the implications of linear models. One implication of these results is that policymakers can raise the average level of output over time by responding promptly to demand shocks, thus reducing the variance of output around trend.

Traditionally, economic growth and business cycles have been treated independently. However, the dependence of GDP levels on its history of shocks, what economists refer to as “hysteresis,” argues for unifying the analysis of growth and cycles. In this paper, we review the recent empirical and theoretical literature that motivate this paradigm shift. The renewed interest in hysteresis has been sparked by the persistence of the Global Financial Crisis and fears of a slow recovery from the Covid-19 crisis. The findings of the recent literature have far-reaching conceptual and policy implications. In recessions, monetary and fiscal policies need to be more active to avoid the permanent scars of a downturn. And in good times, running a high-pressure economy could have permanent positive effects.

Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.

This paper presents theory and evidence on the asymmetric effects of monetary policy on job creation and job destruction. First, it solves a dynamic matching model and it shows how interest rate changes result in an asymmetric response of job creation and destruction. Second, it looks at how changes in the federal fund rate affect gross job flows in the U.S. manufacturing industry, and it finds evidence of asymmetry. Tight policy increases job destruction and reduces net employment changes. Conversely, easy policy appears ineffective in stimulating job creation.