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This handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

Regulatory Restructuring

United States. Congress. House. Committee on Financial Services. Subcommittee on Domestic Monetary Policy and Technology

Published: 2009

Total Pages: 256


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Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.
Financial crises are recurring phenomena that can cause significant economic and societal loss. This book is therefore vitally important as it analyzes why and how financial crises occur, the extent of their impact, and what can be done to prevent their recurrence or reduce the damage they cause. Comprising original and never-before-published papers by distinguished economists, this book offers insights about lessons that were or should have been learned from recent outbreaks of such crises in East Asia and elsewhere. Recent Financial Crises also presents a set of econometric studies of issues such as labor market behavior, investment and productivity, and exchange rate adjustments. Although China did not have a crisis, its economic behavior was closely monitored in order to see if that had any effect on the crisis conditions. In this respect, the book contains an estimation of China s core inflation rate, as well as its true cost of living index, over a 20-year period spanning the Asian financial crisis. In general, collectively, the studies point to a need for ongoing structural reforms to minimize vulnerability to crises or soften their impact. The necessity for resorting to viable safety nets is also stressed. Policymakers and central bankers will find this book of great value, as will scholars and researchers at many levels of academe, involved in financial, business, and international economics.
In this paper we show that, in the aftermath of a currency crisis, a government that adjusts the nominal interest rate in response to domestic currency depreciation can induce aggregate instability in the economy by generating self-fulfilling endogenous cycles. We find that, if a government raises the interest rate proportionally more than an increase in currency depreciation, then it induces self-fulfilling cycles that, driven by people's expectations about depreciation, replicate several of the salient stylized facts of the "Sudden Stop" phenomenon. These facts include a decline in domestic production and aggregate demand, a collapse in asset prices, a sharp correction in the price of traded goods relative to non-traded goods, an improvement in the current account deficit, a moderately higher CPI-inflation, more rapid currency depreciation, and higher nominal interest rates. In this sense, an interest rate policy that responds to depreciation may have contributed to generating the dynamic cycles experienced by some economies in the aftermath of a currency crisis.
This paper uses an open economy DSGE model to explore how trade openness affects the transmission of domestic shocks. For some calibrations, closed and open economies appear dramatically different, reminiscent of the implications of Mundell-Fleming style models. However, we argue such stark differences hinge on calibrations that impose an implausibly high trade price elasticity and Frisch elasticity of labor supply. Overall, our results suggest that the main effects of openness are on the composition of expenditure, and on the wedge between consumer and domestic prices, rather than on the response of aggregate output and domestic prices.
Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using volatility signature plots and a recently-proposed formal decision rule to select the sampling frequency, we find that one can sample FX returns as frequently as once every 15 to 20 seconds without contaminating volatility estimates; bond returns may be sampled as frequently as once every 2 to 3 minutes on days without U.S. macroeconomic announcements, and as frequently as once every 40 seconds on announcement days. With a simple realized kernel estimator, the sampling frequencies can be increased to once every 2 to 5 seconds for FX returns and to about once every 30 to 40 seconds for bond returns. These sampling frequencies, especially in the case of FX returns, are much higher than those often recommended in the empirical literature on realized volatility in equity markets. We suggest that the generally superior depth and liquidity of trading in FX and government bond markets contributes importantly to this difference.