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.

This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N. The proposed tests are based on average of pair-wise correlation coefficients of the OLS residuals from the individual regressions in the panel, and can be used to test for cross section dependence of any fixed order p, as well as the case where no aprioriordering of the cross section units is assumed, referred to as CD(p) and CD tests, respectively. Asymptotic distribution of these tests are derived and their power function analyzed under different alternatives. It is shown that these tests are correctly centred for fixed N and T, and are robust to single or multiple breaks in the slope coefficients and/or error variances. The small sample properties of the tests are investigated and compared to the Lagrange multiplier test of Breusch and Pagan using Monte Carlo experiments. It is shown that the tests have the correct size in very small samples and satisfactory power, and as predicted by the theory, quite robust to the presence of unit roots and structural breaks. The use of the CD test is illustrated by applying it to study the degree of dependence in per capita output innovations acrosscountrieswithinagivenregionandacrosscountriesindifferent regions. The results show significant evidence of cross dependence in output innovations across many countries and regions in the World.

Statistical inference in long-horizon event studies has been hampered by the fact that abnormal returns are neither normally distributed nor independent. This study presents a new approach to inference that overcomes these difficulties and dominates other popular testing methods. I illustrate the use of the methodology by examining the long-horizon returns of initial public offerings ~IPOs!. I find that the Fama and French ~1993! three-factor model is inconsistent with the observed long-horizon price performance of these IPOs, whereas a characteristic-based model cannot be rejected. RECENT EMPIRICAL STUDIES IN FINANCE document systematic long-run abnormal price reactions subsequent to numerous corporate activities. 1 Since these results imply that stock prices react with a long delay to publicly available information, they appear to be at odds with the Efficient Markets Hypothesis ~EMH!. Long-run event studies, however, are subject to serious statistical difficulties

Seemingly unrelated regression (SUR) models traditionally appear in econometrics but recently also emerged in likelihood factorizations of Gaussian graphical models. The literature on maximum likelihood estimation in SUR seems not to mention the possibility of a multimodal likelihood.

Estimates of standard performance measures can be improved by using returns on assets not used to dene those measures. Alpha, the intercept in a regression of a fund's return on passive benchmark returns, can be estimated more precisely by using information in returns on non-benchmark passive assets, whether or not one believes those assets are priced by the benchmarks. A fund's Sharpe ratio can be estimated more precisely by using returns on other assets as well as the fund. New estimates of these performance measures for a large universe of equity mutual funds exhibit substantial differences from the usual estimates.

Abstract not found

We present an empirical analysis of the determinants of labour cost in OECD countries, with particular reference to the impact of labour market institutions from 1960 to 1994. The main contribution of the paper is to show that labour market regulations can explain a large part of labour cost rise in OECD countries in the last decades once we control for productivity. These results are consistent with the findings of a companion paper (Nickell et al., 2001) where the effects of institutions on unemployment are examined. The model controls for macroeconomic shocks, and include the possibility of interactions among institutions. We present also a discussion of the potential problems encountered when estimating a macro pooled model like ours. We focus, among other things, on the hypothesis of poolability and on the cointegration properties of the model, suggesting a two way fixed effects specification in GLS form that corrects for heteroskedasticity and serial correlation. The explanatory power of the model is finally tested by means of a series of by country dynamic simulations.

We develop a Bayesian “sum-of-trees ” model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms in particular, BART is defined by a statistical model: a prior and a likelihood. This approach enables full posterior inference including point and interval estimates of the unknown regression function as well as the marginal effects of potential predictors. By keeping track of predictor inclusion frequencies, BART can also be used for model free variable selection. BART’s many features are illustrated with a bake-off against competing methods on 42 different data sets, with a simulation experiment and on a drug discovery classification problem.

Abstract not found

“Financial Systems and Institutions in the Third Millenium ” conference (Jerusalem), and the “Emerging Markets Finance ” conference (London Business School) for very helpful comments and suggestions. Several individuals assisted us with data collection, especially Chanhi Park with the Korean data, Liat Sack with the Israeli data, and Hideaki Miyajima with the pre-war Japanese data. William Simpson contributed his invaluable econometric expertise, and Eli Enoch, Kathleen Ryan, James Schorr and Zamir Sivan assisted in assembling the database. Khanna thanks the Division of Research at HBS for financial support. All errors remain our own. Business Groups and Risk Sharing around the World Researchers commonly assume that business groups, a ubiquitous organizational form in emerging markets, permit affiliated firms to share risk by smoothing income flows and by reallocating money from one affiliate to another in times of distress. This view has received support in the literature on Japanese keiretsu. To examine the generality of these findings worldwide, we amass a new data set on business groups in 15 emerging markets, and couple this with historical and modern data from Japan. Our results, using multiple estimation techniques, corroborate the existing evidence on risk sharing within the Japanese keiretsu. In addition, in