This paper analyzes the nonlinear relationship between monetary policy and financial stress and its effects on the transmission of shocks to output. Results from a Bayesian Threshold Vector Autoregression (TVAR) model show that the effects of monetary policy shocks on output growth are stronger during normal times than during times of financial stress. Monetary policy shocks are effective to ease stressed financial conditions, but have limited ability to fully contain the buildup of vulnerabilities. These results have important policy implications for central banks’ countercyclical policies under different financial conditions and for “lean against the wind” policies to address financial vulnerabilities.
This dissertation examines the interaction between macroeconomic aggregates and financial markets in two different essays. The expansion of derivatives markets has prompted interest in estimating options-implied measures to analyze market participants’ beliefs about future movements in the prices of these derivatives’ underlying assets and the probability these participants assign to unlikely events (see Datta et al., 2014). In this spirit, analyzing oil market is important for two main reasons. First, among all commodities, crude oil futures and derivatives are the most traded and liquid asset in the whole commodity market. Second, the informational content of oil derivatives can be indicative of shifts in global economic expectations which may be of interests to producers, investors and policy makers. Because the risk neutral density (RND, hereafter) consists of information from various option series that have a wide range of strike prices and maturities, we can conjecture more detailed effects of news announcements on market sentiment by investigating the changes in the RND. Chapter 1 links the crude oil market to macroeconomic risk by studying the RND around the U.S. macroeconomic news announcements. I use a non-parametric method to recover the RND and conduct regression analysis using daily data. The analysis provides several noteworthy results. First, I find that the RND is systematically affected by certain macroeconomic news announcements. Second, after controlling for the content of the news, my results indicate that good news tend to make the distribution less negatively skewed, whereas bad news have an opposite effect. However, I do not find any systematic pattern between the content (bad/good) of the news and the implied volatility or kurtosis. Hence, my results show that better/worse-than-expected news in macroeconomic announcements may both increase and decrease implied volatility and kurtosis of the option implied distribution. Finally my estimates obtained from nonlinear regressions display that the magnitude of the surprise may play into this effect; for example worse-than-expected news in Housing Starts announcement decrease the implied volatility and increase the implied kurtosis only when the size of surprise is not too large. How should a central bank conduct monetary policy in the presence of financial shocks? In Chapter 2, I use different nonlinear policy rules and address this question. Most empirical work on monetary policy relies on simple linear policy rules, however it is not clear whether such a rule can be an adequate representation of a process as complex as that of monetary policy. I first estimate Markov Switching Taylor rules with constant transition probabilities to allow for state-contingent policy making during 1987.3-2008.4. As a proxy for financial stress, I use the Adjusted National Financial Conditions Index constructed by the Chicago Fed. Then, I allow transition probabilities driving the monetary policy stance to vary over time and be a function of economic and financial indicators. The paper provides clear-cut evidence that, during the Greenspan-Bernanke tenure, the U.S. monetary policy can be characterized falling into two distinct regimes; a conventional regime where the Fed puts a greater emphasis on targeting inflation while stabilizing the economic outlook and a distressed regime where the Fed responds aggressively to output gaps and is less concerned with inflation. The distressed regime is closely correlated with times of financial imbalances. The empirical results show that nonlinear models outperform the simple linear specification in terms of model fit and the ability to track the actual interest rate. Also, the economic and financial indicators are found to be informative in dating the evolution of the state of the monetary policy stance. The results have implications for nonlinear rules to be a useful guideline for forecasting and policy analysis.
This book by a leading authority on monetary policy offers a unique view of the subject from the perspectives of both scholar and practitioner. Frederic Mishkin is not only an academic expert in the field but also a high-level policymaker. He is especially well positioned to discuss the changes in the conduct of monetary policy in recent years, in particular the turn to inflation targeting. Monetary Policy Strategydescribes his work over the last ten years, offering published papers, new introductory material, and a summing up, "Everything You Wanted to Know about Monetary Policy Strategy, But Were Afraid to Ask," which reflects on what we have learned about monetary policy over the last thirty years. Mishkin blends theory, econometric evidence, and extensive case studies of monetary policy in advanced and emerging market and transition economies. Throughout, his focus is on these key areas: the importance of price stability and a nominal anch fiscal and financial preconditions for achieving price stability; central bank independence as an additional precondition; central bank accountability; the rationale for inflation targeting; the optimal inflation target; central bank transparency and communication; and the role of asset prices in monetary policy.
This paper explains specifics of stress testing at the IMF. After a brief section on the evolution of stress tests at the IMF, the paper presents the key steps of an IMF staff stress test. They are followed by a discussion on how IMF staff uses stress tests results for policy advice. The paper concludes by identifying remaining challenges to make stress tests more useful for the monitoring of financial stability and an overview of IMF staff work program in that direction. Stress tests help assess the resilience of financial systems in IMF member countries and underpin policy advice to preserve or restore financial stability. This assessment and advice are mainly provided through the Financial Sector Assessment Program (FSAP). IMF staff also provide technical assistance in stress testing to many its member countries. An IMF macroprudential stress test is a methodology to assess financial vulnerabilities that can trigger systemic risk and the need of systemwide mitigating measures. The definition of systemic risk as used by the IMF is relevant to understanding the role of its stress tests as tools for financial surveillance and the IMF’s current work program. IMF stress tests primarily apply to depository intermediaries, and, systemically important banks.
In central banking, the need for effective governance and policy transformations has never been more pressing. Central banks serve as the bedrock of a nation's financial stability, and yet, they face an array of complex challenges in the modern era. The delicate balance between autonomy from government influence and the necessity of adapting to external economic forces has become increasingly elusive. As the world grapples with the aftermath of a global pandemic and persistent economic turbulence, the demand for innovative strategies to safeguard economic and financial stability has reached a crescendo. Central bankers, economists, and policy experts are left grappling with the daunting task of navigating these treacherous waters, in dire need of a compass to guide them toward a resilient future. Governance and Policy Transformations in Central Banking is a groundbreaking book that transcends traditional boundaries to offer a comprehensive solution to the complex challenges faced by central banks worldwide. This book not only diagnoses problems, it also presents a meticulously curated collection of new empirical and theoretical chapters that illuminate the path forward. It is an invaluable resource that empowers central banks with the knowledge and tools necessary for development, governance, and policy transformation.
The Fall 2017 IMF Research Bulletin includes a Q&A article covering "Seven Questions on the Globalization of Farmland" by Christian Bogmans. The first research summary, by Manmohan Singh and Haobing Wang is "Central Bank Balance Sheet Policies: Some Policy Implications." The second research summary is "Leaning Against the Windy Bank Lending" by Giovanni Melina and Stefania Villa. A listing of new IMF Working Papers and Staff Discussion Notes is featured, as well as new titles from IMF Publications. Information on IMF Economic Review is also included.
This paper reviews empirical and theoretical work on the links between banks and their governments (the bank-sovereign nexus). How significant is this nexus? What do we know about it? To what extent is it a source of concern? What is the role of policy intervention? The paper concludes with a review of recent policy proposals.
This book describes various approaches in modelling financial risks and compiling ratings. Focusing on emerging markets, it illustrates how risk assessment is performed and analyses the use of machine learning methods for financial risk assessment and measurement. It not only offers readers insights into the differences between emerging and developed markets, but also helps them understand the development of risk management approaches for banks. Highlighting current problems connected with the evaluation and modelling of financial risks in the banking sector of emerging markets, the book presents the methodologies applied to credit and market financial risks and integrated and payment risks, and discusses the outcomes. In addition it explores the systemic risks and innovations in banking and risk management by analyzing the features of risk measurement in emerging countries. Lastly, it demonstrates the aggregation of approaches to financial risk for emerging financial markets, comparing the experiences of various countries, including Russia, Belarus, China and Brazil.
Central banks in emerging and developing economies (EMDEs) have been modernizing their monetary policy frameworks, often moving toward inflation targeting (IT). However, questions regarding the strength of monetary policy transmission from interest rates to inflation and output have often stalled progress. We conduct a novel empirical analysis using Jordà’s (2005) approach for 40 EMDEs to shed a light on monetary transmission in these countries. We find that interest rate hikes reduce output growth and inflation, once we explicitly account for the behavior of the exchange rate. Having a modern monetary policy framework—adopting IT and independent and transparent central banks—matters more for monetary transmission than financial development.
Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
