Multivariate control charts based on Bayesian state space models

This paper develops a new multivariate control charting method for vector autocorrelated and serially correlated processes. The main idea is to propose a Bayesian multivariate local level model, which is a generalization of the Shewhart-Deming model for autocorrelated processes, in order to provide the predictive error distribution of the process and then to apply a univariate modified EWMA control chart to the logarithm of the Bayes' factors of the predictive error density versus the target error density. The resulting chart is proposed as capable to deal with both the non-normality and the autocorrelation structure of the log Bayes' factors. The new control charting scheme is general in application and it has the advantage to control simultaneously not only the process mean vector and the dispersion covariance matrix, but also the entire target distribution of the process. Two examples of London metal exchange data and of production time series data illustrate the capabilities of the new control chart.Comment: 19 pages, 6 figure

An Examination of the Robustness to Non Normality of the EWMA Control Charts for the Dispersion

The EWMA control chart is used to detect small shifts in a process. It has been shown that, for certain values of the smoothing parameter, the EWMA chart for the mean is robust to non normality. In this article, we examine the case of non normality in the EWMA charts for the dispersion. It is shown that we can have an EWMA chart for dispersion robust to non normality when non normality is not extreme.Average run length, Control charts, Exponntially weighted moving average control chart, Median run length, Non normality, Statistical process control

Multivariate Statistical Process Control Charts: An Overview

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.quality control, process control, multivariate statistical process control, Hotelling's T-square, CUSUM, EWMA, PCA, PLS

Stress testing banks' profitability: the case of French banks

We build a stress testing framework to evaluate the sensitivity of banks’ profitability to plausible but severe adverse macroeconomic shocks. Specifically, we test the resilience of French banks using supervisory data over the period 1993-2009. First, we identify the macroeconomic and financial variables (GDP growth, interest rate maturity spread, stock market’s volatility) and bank-specific variables (size, capital ratio, ratio of non interest income to assets) that significantly affect French banks’ profitability. Second, our macroeconomic stress testing exercises based on a simulation of macroeconomic variables show that French banks’ profitability is resilient to major adverse macroeconomic scenarios. Specifically, our findings highlight that even severe recessions would leave the French banking system profitable.bank profitability, dynamic panel estimation, stress test.

Sectorial Border Effects in the European Single Market: an Explanation through Industrial Concentration

The purpose of this paper is to explain the relation between the Border Effect and industrial concentration. This is achieved by founding this relation on the Home Market Effect and testing the robustness of this foundation through an application to the European Single Market. A sectorial Gravity Equation is estimated using different econometric estimators, in particular we discuss a recently suggested technique for the estimation of log-linear CES models. Overall, our findings suggest a steady relation between the Border Effect and industrial concentration. Besides, the analysis of industrial concentration through a synthetic index provides us with valuable insights into the structure of the European industry. JEL Classification: F10, F12, F15.Border Effect, European Single Market, Home Market Effect, Industrial Concentration, Trade

Modelling Underlying Energy Demand Trends and Stochastic Seasonality: An Econometric Analysis of Transport Oil Demand in the UK and Japan

This paper demonstrates the importance of adequately modelling the Underlying Energy Demand Trend (UEDT) and seasonality when estimating transportation oil demand for the UK and Japan. The structural time series model is therefore employed to allow for a stochastic underlying trend and stochastic seasonals using quarterly data from the early 1970s, for both the UK and Japan. It is found that the stochastic seasonals are preferred to the conventional deterministic dummies and, more importantly, the UEDT is found to be highly nonlinear for both countries, with periods where it is both upward and downward sloping.energy demand, stochastic trend model, unobservable underling trend, seasonality.

Exchange Rate Pass-Through and Irish Import Prices

This study assesses the extent to which exchange rate changes affect Irish import prices (i.e. the extent of exchange rate pass-through, PT) by analysing data from the 1963 to 1995 period. The paper fills two important gaps in the literature: i) by making due allowance for the time series properties of the data and ii) by concentrating on the case of a small open economy. The majority of international empirical studies in the area do not provide support for full, or close to full, PT. Reasons put forward for this finding include the "menu" costs associated with altering prices, hedging techniques, intra-firm pricing by multinationals, the existence of non-tariff barriers, and the entry/exit of firms associated with exchange rate induced price changes. If the proposition of monetary neutrality is accepted, however, full PT would be expected to hold over the medium to long run. Many previous studies assess the degree of PT by relating import prices to the exchange rate, foreign costs and domestic competing prices. The usual approach involves estimating a single equation and using the estimated coefficients to assess the degree of PT. It is argued in this paper, however, that such single equation estimation will lead to estimates of the degree of PT which appear too low because the strong relationship between import and domestic-competing prices will not be properly taken into account using such a technique. This study makes use of the so-called Johansen technique to allow for this problem and uncovers two long-run relationships among the data, i.e. one between import unit values, the exchange rate and foreign costs and another between domestic competing prices and the same two variables. In so doing, it confirms the existence of very close to full PT in the case of both Irish import prices and domestic competing prices. Many of the previous results in the literature demonstrating substantially less than full PT may be due to the failure to make proper allowance for the time series properties of the data or for the strong relationship which exists between import and domestic competing prices. Finally, it is found that the speed of adjustment to the long-run relationships appears to be quite low, thus supporting the existence of incomplete PT in the short run.

Discussion paper. Conditional growth charts

Growth charts are often more informative when they are customized per subject, taking into account prior measurements and possibly other covariates of the subject. We study a global semiparametric quantile regression model that has the ability to estimate conditional quantiles without the usual distributional assumptions. The model can be estimated from longitudinal reference data with irregular measurement times and with some level of robustness against outliers, and it is also flexible for including covariate information. We propose a rank score test for large sample inference on covariates, and develop a new model assessment tool for longitudinal growth data. Our research indicates that the global model has the potential to be a very useful tool in conditional growth chart analysis.Comment: This paper discussed in: [math/0702636], [math/0702640], [math/0702641], [math/0702642]. Rejoinder in [math.ST/0702643]. Published at http://dx.doi.org/10.1214/009053606000000623 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Monetary Policy and Data Uncertainty: A Case Study of Distribution, Hotels and Catering Growth

This paper is a case study of the real world monetary policy data uncertainty problem. The initial and the latest release for growth rates of the distribution, hotels and catering sector are combined with official data on household income and two surveys in a state-space model. Though important to the UK economy, the distribution, hotels and catering sector is apparently difficult to measure. One finding is that the initial release data is not important in predicting the latest release. It could be that the statistical office develop the initial release as a building block towards the final release rather than an estimate of it. Indeed, there is multicollinearity between the initial release and the retail sales survey, which would then contain the same early available information. A second finding is that the estimate of the later release is sensitive to the estimate of the average historical growth rate. This means that establishing priors for this parameter and testing for shift structural breaks should be very important.Data Uncertainty; Distribution Sector; Kalman Filter; Monetary Policy