We present a method for searching in an image database using a query image that is similar to the intended target. The query image may be a hand-drawn sketch or a (potentially low-quality) scan of the image to be retrieved. Our searching algorithm makes use of multiresolution wavelet decompositions of the query and database images. The coefficients of these decompositions are distilled into small "signatures" for each image. We introduce an "image querying metric" that operates on these signatures. This metric essentially compares how many significant wavelet coefficients the query has in common with potential targets. The metric includes parameters that can be tuned, using a statistical analysis, to accommodate the kinds of image distortions found in different types of image queries. The resulting algorithm is simple, requires very little storage overhead for the database of signatures, and is fast enough to be performed on a database of 20,000 images at interactive rates (on standard...

A great deal of controversy exists about the impact of information technology on firm performance. While some authors have reported positive impacts, others have found negative or no impacts. This study focuses on Electronic Data Interchange (EDI) technology. Many of the problems in this line of research are overcome in this study by conducting a careful analysis of the performance data of the past decade gathered from the assembly centers of Chrysler Corporation. This study estimates the dollar benefits of improved information exchanges between Chrysler and its suppliers that result from using EDI. After controlling for variations in operational complexity arising from mix, volume, parts complexity, model, and engineering changes, the savings per vehicle that result from improved information exchanges are estimated to be about $60. Including the additional savings from electronic document preparation and transmission, the total benefits of EDI per vehicle amount to over $100. System wide, this translates to annual savings of $220 million for the company.

411 144 ecb d All rights reserved. Photocopying for educational and non-commercial purposes permitted provided that the source is acknowledged. ISSN 1607-1484Table of contents Abstract 5 1 Introduction: general aspects of the reference value for monetary growth in the context of the ECB’s monetary policy strategy 7 2 A first look at the data 10 2.1 The concept of M3 income velocity and its behaviour in the euro area 10 2.2 Data and aggregation issues 12

The method of instrumental variables is a signature technique in the econometrics toolkit. The canonical example, and earliest applications, of instrumental variables involved attempts to estimate demand and supply curves. 1 Economists such as P.G. Wright, Henry Schultz, Elmer Working and Ragnar Frisch were interested in estimating the elasticities of demand and supply for products ranging from herring to butter, usually with time series data. If the demand and supply curves shift over time, the observed data on quantities and prices reflect a set of equilibrium points on both curves. Consequently, an ordinary least squares regression of quantities on prices fails to identify—that is, trace out—either the supply or demand relationship. P.G. Wright (1928) confronted this issue in the seminal application of instrumental variables: estimating the elasticities of supply and demand for flaxseed, the source of linseed oil. 2 Wright noted the difficulty of obtaining estimates of the elasticities of supply and demand from the relationship between price and quantity 1

I review empirical research on the relation between capital markets and financial statements.The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the political process.The capital markets research topics of current interest to researchers include tests of market efficiency with respect to accounting information, fundamental analysis, and value relevance of financial reporting.Evidence from research on these topics is likely to be helpful in capital market investment decisions, accounting standard setting, and corporate financial

research associate of the NBER. Susan Houseman is a senior economist at the W. E. Upjohn

This study compares eight international failure prediction models on one data set of Belgian company accounts, using performance indicators based on the inequality principle and performance measures based on a classification rule. After a brief theoretical review of the two basic modelling techniques in failure prediction research and the performance measures used to evaluate them, we report type I and type II error rates corresponding with the original cut-off point and calculate new optimal cut-off points, as well as Gini-coefficients. A wide range of performances was observed for the different models. However the models estimated on a sample of Continental European companies are found to be better performing when validated on a sample of Continental European, i.e. Belgian companies, than the Anglo-Saxon models. A remarkable finding is also that the Greek Gloubos-Grammaticos models show better predictive ability when validated on samples of Belgian failing and non-failing companies than on their own (Greek) validation samples. Another important finding is the robustness of the older discriminant models and the models that were estimated on bigger companies. The validation shows that very simple models can have great predictive ability. 2

Faced with the question whether the Belgian failure prediction models by Ooghe, Joos and De Vos (1991) can be easily applied in all industries and for all sizeclasses, this study compares the performance of the OJD models across 18 different industries and different sizeclasses. After a brief theoretical review of the logistic regression modelling technique, which was used to design the OJD 1991 models, and the performance measures that are used to evaluate these models, we report type I and type II error rates corresponding with the original cut-off points of the models. Furthermore, we calculate new optimal cut-off points, as well as Ginicoefficients. Finally we report the reductions in unweighted error rates when using the new cut-off points instead of the original ones, and the graphs of the trade-off functions. As can be concluded from the performance results and the trade-off functions, there’s a wide range of performances for the different industries. However, we notice that the OJD 1991 models perform best for classical manufacturing industries- such as chemicals, paper and printing, textiles and apparel, paper and printing and metal- and financial services., while the models show the worst performance for service industries- such as real estate, hotel,

This paper presents analytical, Monte Carlo, and empirical evidence on models for event count data. Event counts are dependent variables that measure the number of times some event occurs. Counts of international events are probably the most common, but numerous examples exist in every empirical field of the discipline. The results of the analysis below strongly suggest that the way event counts have been analyzed in hundreds of important political science studies have produced statistically and substantively unreliable results. Misspecification, inefficiency, bias, inconsistency, insufficiency, and other problems result from the unknowing application of two common methods that are without theoretical justification or empirical utility in this type of data. I show that the exponential Poisson regression (EPR) model provides analytically, in large samples, and empirically, in small, finite samples, a far superior model and optimal estimator. I also demonstrate the advantage of this methodology in an application to nineteenth-century party switching in the U.S. Congress. Its use by political scientists is strongly encouraged. 1.

We are grateful for research assistance from Witold Czubala, Gergana Danailova-Trainor, and Migiwa Tanaka, and for suggestions from Andrew Feltenstein, Mark Gertler, and participants at the NBER Inflation Targeting Conference, January 2003. The views presented are those of the authors and do not necessarily