世界経済・社会統計 = World development indicators

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T2) for any number of breaks. Our method can be applied to both pure and partial structural change models. Second, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program. Copyright © 2002 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jae.659

Computation and analysis of multiple structural change models

This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.

Introductory Econometrics for Finance

Testing the hypothesis that international equity market correlation increases in volatile times is a difficult exercise and misleading results have often been reported in the past because of a spurious relationship between correlation and volatility. Using “extreme value theory” to model the multivariate distribution tails, we derive the distribution of extreme correlation for a wide class of return distributions. Empirically, we reject the null hypothesis of multivariate normality for the negative tail, but not for the positive tail. We also find that correlation is not related to market volatility per se but to the market trend. Correlation increases in bear markets, but not in bull markets. INTERNATIONAL EQUITY MARKET CORRELATION has been widely studied. Previous studies 1 suggest that correlation is larger when focusing on large absolutevalue returns, and that this seems more important in bear markets. The conclusion that international correlation is much higher in periods of volatile markets ~large absolute returns! has indeed become part of the accepted wisdom among practitioners and the financial press. However, one should exert great care in testing such a proposition. The usual approach is to condition the estimated correlation on the observed ~or ex post! realization of market returns. Unfortunately correlation is a complex function of returns and such tests can lead to wrong conclusions, unless the null hypothesis and

/pdf/extreme-correlation-of-international-equity-markets-20e1oippcd.pdf

Extreme Correlation of International Equity Markets

Financial returns are known to be nonnormal and tend to have fat-tailed distributions. This article presents a simple methodology that accurately estimates the degree of tail fatness, characterized by the tail index, in small samples. Our method is a weighted average of Hill estimators for different threshold values that corrects for the small-sample bias apparent in the latter. Using this estimator we produce tail-index estimates for returns on exchange rates that are close to nonbiased estimates obtained from extremely large datasets. The results indicate that many documented conclusions concerning the tail behavior of financial series are likely to have overestimated the tail fatness in small samples.

/pdf/tail-index-estimates-in-small-samples-3eo8m3rnp4.pdf

Tail Index Estimates in Small Samples

In this paper we focus on the assumption of a common efficient frontier when performing an efficiency study for the banking sector. The fact that environmental factors that are not appropriately controlled may easily bias efficiency estimates. First, we estimate a common cost and profit frontier. In this first stage, as an innovation to the literature, we use exogenously computed input prices rather than the normally used endogenous input prices. Second, we regress the estimated inefficiencies on a set of a bank.s strategic choices, local banking market variables, and local (regional) macro variables. For the analysis, we use a unique dataset of 401 largely independent cooperative local banks in the Netherlands for the years 1998 and 1999. Our results show that the use of exogenous input prices rather than endogenous input prices is particularly important for the cost frontier as the spread in cost inefficiencies becomes larger and more plausible. Our second stage results suggest that most of the estimated inefficiency indeed is managerial (X-) inefficiency. Environmental factors do play a role, but only to a limited extent.

Bank Efficiency the Role of Bank Strategy and Local Market Conditions

We present evidence from the United States and the United Kingdom that the persistence of price inflation is significantly higher under managed-exchange-rate regimes than under gold-based, fixed-exchange-rate regimes. These differences are also reflected in expectations-augmented Phillips curves. We use a two-country macro model, with forward-looking price setters, to demonstrate that higher monetary accommodation of inflation and exchange-rate accommodation of inflation differentials increase inflation persistence. The evidence does not contradict this hypothesis. It supports the hypothesis of forward-looking price setters and highlights the empirical significance of the Lucas critique. (JEL E31, E42, F33)

/pdf/the-phillips-curve-the-persistence-of-inflation-and-the-3ksi60esyt.pdf

The Phillips curve, the persistence of inflation, and the Lucas critique: evidence from exchange-rate regimes: comment

Most bank merger studies do not control for hidden bailouts, which may lead to biased results. In this study we employ a unique data set of approximately 1000 mergers to analyze the determinants of bank mergers. We use undisclosed information on banks' regulatory intervention history to distinguish between distressed and non-distressed mergers. Among merging banks, we find that improving financial profiles lower the likelihood of distressed mergers more than the likelihood of nondistressed mergers. The likelihood to acquire a bank is also reduced but less than the probability to be acquired. Both distressed and non-distressed mergers have worse CAMEL profiles than non-merging banks. Hence, non-distressed mergers may be motivated by the desire to forestall serious future financial distress and prevent regulatory intervention.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=811525

Accounting for Distress in Bank Mergers

In this paper we focus on the assumption of a common efficient frontier when performing an efficiency study for the banking sector. The fact that environmental factors that are not appropriately controlled may easily bias efficiency estimates. First, we estimate a common cost and profit frontier. In this first stage, as an innovation to the literature, we use exogenously computed input prices rather than the normally used endogenous input prices. Second, we regress the estimated inefficiencies on a set of a bank’s strategic choices, local banking market variables, and local (regional) macro variables. For the analysis, we use a unique dataset of 401 largely independent cooperative local banks in the Netherlands for the years 1998 and 1999. Our results show that the use of exogenous input prices rather than endogenous input prices is particularly important for the cost frontier as the spread in cost inefficiencies becomes larger and more plausible. Our second stage results suggest that most of the estimated inefficiency indeed is managerial (X-) inefficiency. Environmental factors do play a role, but only to a limited extent.

Clemens J.M. Kool

Papers

Tail Index Estimates in Small Samples

Bank Efficiency the Role of Bank Strategy and Local Market Conditions

The Phillips curve, the persistence of inflation, and the Lucas critique: evidence from exchange-rate regimes: comment

Accounting for Distress in Bank Mergers

Bank efficiency: The role of bank strategy and local market conditions